Nanotechnology in Cancer Management: Precise Diagnostics toward Personalized Health Care 9780128181546

Table of contents :
Cover
Nanotechnology in Cancer Management
Copyright
Contents
List of contributors
1 Nanotechnology and its application: a review
1.1 Introduction
1.2 Application of nanotechnology
1.2.1 Nanotechnology in biomedical
1.2.1.1 Drug delivery
1.2.1.2 Bioimaging
1.2.1.3 Nanotechnology for diagnosis and treatment
1.2.1.4 Nanotechnology for treatment of cancer
1.2.1.5 Nanotechnology in genetic material sequencing
1.2.1.6 Nanotechnology in biosensors
1.2.1.7 Nanotechnology in controlled release
1.2.1.8 Nanotechnology in bioremediation
1.2.1.9 Nanotechnology in agriculture and environment
1.2.1.10 Nanotechnology in water treatment
1.2.1.11 Nanotechnology in food industry
1.2.1.11.1 Active packing and intelligent packaging
1.2.1.11.2 Nanomaterial as barrier
1.2.1.11.3 Nanosensors
1.3 Conclusion
1.4 Future and challenges
Acknowledgment
References
2 Exploring biomarkers and diagnostics system for cancer management
2.1 Introduction
2.2 Efficient and miniaturized diagnostics system
2.3 Conclusion
Acknowledgment
Conflict of interest
References
3 Electrochemical detection: Cyclic voltammetry/differential pulse voltammetry/impedance spectroscopy
3.1 Introduction
3.2 Matrix for immobilization of biorecognition molecule
3.3 Electrochemical transducers for cancer biomarker detection
3.3.1 Cyclic voltammetry based biosensor for cancer detection
3.3.2 Differential pulse voltammetry based biosensor for cancer detection
3.3.3 Electrochemical impedance based biosensor for cancer detection
3.4 Conclusions and outlooks
Acknowledgments
References
4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy
4.1 Introduction
4.2 Fluorescence spectroscopy
4.2.1 Development history
4.3 Fundamentals
4.3.1 Excitation and emission fundamentals
4.3.1.1 Kasha’s law, Stokes shift, and Franck–Condon principle
4.3.2 Quantum yield and lifetime of florescence marker
4.3.3 Florescence lifetime imaging
4.3.4 Förster resonance energy transfer
4.3.5 Quenching and photobleaching
4.4 Instrumentation
4.5 Fluorescence light sources
4.6 Nanoparticles and organic dyes for florescence sensors
4.7 Quantum dots for florescence imaging and cancer diagnostics
4.8 Cancer detection
4.9 Conclusion
Acknowledgment
Conflict of interest
References
5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics
5.1 Introduction
5.2 History and working principle
5.3 Application of Raman-active nanostructures
5.4 Surface-enhanced Raman spectroscopy platforms in cancer diagnostics
5.4.1 Cell analysis
5.4.2 DNA and RNA analysis
5.4.3 Protein analysis
5.4.4 Extracellular vesicles analysis
5.5 Other bioanalysis application: the notable application of Raman-based assays
5.5.1 Bioimaging
5.5.2 Drug delivery
5.5.3 Raman spectroscopy to evaluate drug binding and release
5.5.4 Raman to evaluate nanoparticle-bio interface
5.6 Future challenges and conclusions
Acknowledgment
Conflict of interest
References
6 Bioinformatics–computer programming
6.1 Introduction
6.1.1 Bioinformatics in cancer research
6.2 Biological data
6.3 Cancer nanomedicine
6.4 Large-scale approaches to the study of cancer
6.4.1 Genomics
6.4.2 Transcriptomics
6.4.3 Proteomics
6.4.4 Bioinformatics techniques
6.4.5 Bioinformatics tools: application in cancer therapy
6.5 Artificial intelligence
6.5.1 Artificial intelligence in cancer diagnosis
6.5.2 Solid tumor diagnosis
6.5.3 Nonsolid tumor diagnosis
6.5.4 Artificial intelligence in cancer treatment
6.5.5 Artificial intelligence-enabled nanomedicine
6.6 Programming language
6.6.1 Programming language in cancer diagnosis
6.6.2 Programming language in cancer treatment
6.7 Conclusion
Acknowledgment
Conflict of interest
References
7 Magnetic-based sensing
7.1 Introduction
7.2 Magnetic sensors
7.2.1 Magnetoresistive sensors
7.2.1.1 Giant magnetoresistance based sensors
7.2.1.2 Spin-valve sensors
7.2.1.3 Tunneling magnetoresistance-based sensors
7.2.2 Giant magnetoimpedance based sensors
7.2.3 Hall effect based sensors
7.3 Conclusions and outlook
References
8 Microfluidics for early-stage cancer detection
8.1 Introduction
8.2 Blood-based cancer biomarkers and challenges in analysis
8.3 Fabrication of microfluidic biosensors
8.4 Microfluidics for cancer diagnosis
8.4.1 Microfluidic biosensors for circulating tumor cell detection
8.4.1.1 Size-based separation of circulating tumor cells in microfluidics
8.4.1.2 Microfluidic immune-affinity separation of circulating tumor cells
8.4.2 Microfluidic biosensors for cancer protein detection
8.4.3 Microfluidic biosensors for cancer exosome detection
8.4.4 Microfluidic biosensors for cell-free DNA (cfDNA)
8.5 Conclusions
References
9 Scale-up of rapid diagnostics for clinical applications: device development for clinical applications (oral cancer)
9.1 Introduction
9.2 Nanotechnology in cancer diagnosis
9.2.1 Biomarkers
9.2.2 Nanomaterials
9.2.3 Nanoscale devices
9.3 Nanotechnology in cancer therapy
9.3.1 Nanocarriers
9.3.2 Drug targeting approaches for cancer therapy
9.3.2.1 Active target
9.3.2.2 Passive target
9.4 Oral cancer challenges, limitations, safety issues, and ethical issues
9.4.1 Oral cancer challenges/limitations
9.4.2 Safety issues
9.4.3 Ethical issue
9.5 Nanobiochip devices for clinical application
9.6 Future perspectives
9.7 Conclusions
Acknowledgment
Conflict of interest
References
10 Challenges and future prospects of nano-enabled cancer management
10.1 Introduction
10.2 Immunotherapy approach
10.3 Detection of circulating tumor DNA/RNA
10.4 Extracellular vesicle analysis
10.5 Viewpoint
Acknowledgment
Conflict of interest
References
Index

Citation preview

NANOTECHNOLOGY IN CANCER MANAGEMENT

NANOTECHNOLOGY IN CANCER MANAGEMENT Precise Diagnostics Toward Personalized Health Care Edited by

KAMIL REZA KHONDAKAR Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia

AJEET KUMAR KAUSHIK NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2021 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-818154-6 For Information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Susan Dennis Acquisitions Editor: Kostas Marinakis Editorial Project Manager: Liz Heijkoop Production Project Manager: Joy Christel Neumarin Honest Thangiah Cover Designer: Victoria Pearson Typeset by MPS Limited, Chennai, India

Contents

List of contributors .........................................................................................ix

1 Nanotechnology and its application: a review ............................................1 Parshant Kumar Sharma, Shraddha Dorlikar, Pooja Rawat, Vidhu Malik, Nishant Vats, Manu Sharma, Jong Soo Rhyee and Ajeet Kumar Kaushik 1.1 Introduction .......................................................................................... 1 1.2 Application of nanotechnology ........................................................... 3 1.3 Conclusion .......................................................................................... 25 1.4 Future and challenges........................................................................ 26 Acknowledgment ...................................................................................... 27 References ................................................................................................. 27

2 Exploring biomarkers and diagnostics system for cancer management.........................................................................................................35 Kamil Reza Khondakar, Ajeet Kumar Kaushik and K. Mohsin Reza 2.1 Introduction ........................................................................................ 35 2.2 Efficient and miniaturized diagnostics system ................................ 39 2.3 Conclusion .......................................................................................... 40 Acknowledgment ...................................................................................... 40 Conflict of interest .................................................................................... 40 References ................................................................................................. 40

3 Electrochemical detection: Cyclic voltammetry/differential pulse voltammetry/impedance spectroscopy .........................................................43 Saurabh Kumar and Ashish Kalkal 3.1 Introduction ........................................................................................ 43 3.2 Matrix for immobilization of biorecognition molecule ................... 47 3.3 Electrochemical transducers for cancer biomarker detection......... 51 3.4 Conclusions and outlooks ................................................................. 65 v

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Acknowledgments .................................................................................... 66 References ................................................................................................. 66

4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy.....................................................................73 Surendra K. Yadav 4.1 Introduction ........................................................................................ 73 4.2 Fluorescence spectroscopy ............................................................... 75 4.3 Fundamentals ..................................................................................... 76 4.4 Instrumentation .................................................................................. 86 4.5 Fluorescence light sources ................................................................ 88 4.6 Nanoparticles and organic dyes for florescence sensors ............... 90 4.7 Quantum dots for florescence imaging and cancer diagnostics ...................................................................... 92 4.8 Cancer detection................................................................................. 96 4.9 Conclusion .......................................................................................... 98 Acknowledgment .................................................................................... 100 Conflict of interest .................................................................................. 100 References ............................................................................................... 100

5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics...........................................................................................107 Kamil Reza Khondakar, Prasanta Kalita, Nicoleta Hickman and Ajeet Kumar Kaushik 5.1 Introduction ...................................................................................... 107 5.2 History and working principle ......................................................... 109 5.3 Application of Raman-active nanostructures ................................. 111 5.4 Surface-enhanced Raman spectroscopy platforms in cancer diagnostics............................................................................ 112 5.5 Other bioanalysis application: the notable application of Raman-based assays ................................................................... 116 5.6 Future challenges and conclusions................................................. 119 Acknowledgment .................................................................................... 121 Conflict of interest .................................................................................. 121 References ............................................................................................... 121

Contents

vii

6 Bioinformatics computer programming ....................................................125 Muhammad Sarmad Iftikhar, Ghulam Mohyuddin Talha, Muqadas Aleem and Amen Shamim 6.1 Introduction ...................................................................................... 125 6.2 Biological data .................................................................................. 128 6.3 Cancer nanomedicine ...................................................................... 129 6.4 Large-scale approaches to the study of cancer ............................. 130 6.5 Artificial intelligence ........................................................................ 134 6.6 Programming language ................................................................... 139 6.7 Conclusion ........................................................................................ 141 Acknowledgment .................................................................................... 141 Conflict of interest .................................................................................. 141 References ............................................................................................... 142

7 Magnetic-based sensing ................................................................................149 Appan Roychoudhury 7.1 Introduction ...................................................................................... 149 7.2 Magnetic sensors ............................................................................. 151 7.3 Conclusions and outlook ................................................................. 176 References ............................................................................................... 178

8 Microfluidics for early-stage cancer detection .......................................185 Shuvashis Dey 8.1 Introduction ...................................................................................... 185 8.2 Blood-based cancer biomarkers and challenges in analysis ......................................................................................... 187 8.3 Fabrication of microfluidic biosensors ........................................... 188 8.4 Microfluidics for cancer diagnosis .................................................. 190 8.5 Conclusions ...................................................................................... 205 References ............................................................................................... 206

9 Scale-up of rapid diagnostics for clinical applications: device development for clinical applications (oral cancer) ................211 K. Mohsin Reza and Ayub Khan 9.1 Introduction ...................................................................................... 211 9.2 Nanotechnology in cancer diagnosis ............................................. 213 9.3 Nanotechnology in cancer therapy................................................. 217

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9.4 Oral cancer challenges, limitations, safety issues, and ethical issues ........................................................................... 219 9.5 Nanobiochip devices for clinical application ............................... 222 9.6 Future perspectives ........................................................................ 223 9.7 Conclusions .................................................................................... 224 Acknowledgment .................................................................................. 224 Conflict of interest ................................................................................ 224 References ............................................................................................. 225

10 Challenges and future prospects of nano-enabled cancer management ......................................................................................229 Kamil Reza Khondakar and Ajeet Kumar Kaushik 10.1 Introduction ...................................................................................229 10.2 Immunotherapy approach ............................................................230 10.3 Detection of circulating tumor DNA/RNA....................................230 10.4 Extracellular vesicle analysis........................................................231 10.5 Viewpoint .......................................................................................232 Acknowledgment .................................................................................. 232 Conflict of interest ................................................................................ 232 References ............................................................................................. 232 Index ............................................................................................................. 235

List of contributors Muqadas Aleem Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan; National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, Jiangsu, China Shuvashis Dey Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, QLD, Australia Shraddha Dorlikar Department of Microbiology, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, India Nicoleta Hickman Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States Muhammad Sarmad Iftikhar School of Agriculture and Food Sciences, The University of Queensland, St Lucia, QLD, Australia; Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan Prasanta Kalita Terrablue XT, New Delhi, India Ashish Kalkal Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, India Ajeet Kumar Kaushik NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States Ayub Khan Department of Orthodontics, AME Dental College, Raichur, India

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x

List of contributors

Kamil Reza Khondakar Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia Saurabh Kumar Centre for Nano Science and Engineering (CeNSE), Indian Institute of Science, Bengaluru, India Vidhu Malik Department of Chemistry, DCRUST Murthal, Sonipat, India Pooja Rawat Department of Applied Physics and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Republic of Korea K. Mohsin Reza Department of Conservative Dentistry Navodaya Dental College, Raichur, India

and

Endodontics,

Jong Soo Rhyee Department of Applied Physics and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Republic of Korea Appan Roychoudhury Centre for Biomedical Engineering, Indian Technology Delhi, Hauz Khas, New Delhi, India

Institute

of

Amen Shamim Department of Molecular Cell Biology, School of Medicine, Samsung Medical Center, Sungkyunkwan University, Suwon, Korea; Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan Manu Sharma Department of Biosciences, Shri Ram College Muzaffarnagar, India Parshant Kumar Sharma Department of Biotechnology, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India Ghulam Mohyuddin Talha Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan Nishant Vats Department Production Planning and Control, Varroc Polymers Pvt. Ltd., Greater Noida, India Surendra K. Yadav Department of Chemistry, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

Nanotechnology and its application: a review

1

Parshant Kumar Sharma1, Shraddha Dorlikar2, Pooja Rawat3, Vidhu Malik4, Nishant Vats5, Manu Sharma6, Jong Soo Rhyee3 and Ajeet Kumar Kaushik7 1

Department of Biotechnology, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India 2Department of Microbiology, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, India 3Department of Applied Physics and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Republic of Korea 4Department of Chemistry, DCRUST Murthal, Sonipat, India 5 Department Production Planning and Control, Varroc Polymers Pvt. Ltd., Greater Noida, India 6Department of Biosciences, Shri Ram College Muzaffarnagar, India 7NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States

1.1

Introduction

Nanotechnology (“nano,” the Greek word for “dwarf”) is the science and engineering associated with creation, formation, characterization, and application of materials and devices whose smallest functional unit in at least one dimension is on the nanometer scale [1 6]. A famous lecture of physics noble laureates R.P. Feynman at the meeting of the American Physics Society in December, 1959, entitled “There’s plenty of room at the bottom,” introduced the term nanotechnology [7]. After that, the Feynman idea of handling matter at the atomic scale was demonstrated by many ground-breaking developments in chemistry, physics, and biology. In 1974 Norio Taniguchi (a professor at the Tokyo University of Science) invented the term “nanotechnology” to describe extra-high precision and ultra-fine dimensions [8]. There are numerous definitions of nanotechnology, and according to the National Nanotechnology Initiative, nanotechnology is the field that includes the following characteristics: 1. Development of technology and research at the macromolecular, atomic, or molecular levels, in the scale of the approximately 1 100 nm range. Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00010-X © 2021 Elsevier Inc. All rights reserved.

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Chapter 1 Nanotechnology and its application: a review

2. Designing and using structures, equipment, and systems that have unique properties and function because of their tiny or intermediate size. 3. Ability to operate on the atomic scale. Nanotechnology means a process that involves the use of matter at the atomic and molecular level and exploitation of its unique capabilities and properties created at the atomic and molecular scale [9]. Nanotechnology has a broad range of applications, and its development brings rapid changes to research field and industries, detection and treatment of diseases and drug delivery, monitoring, environmental protection, food sector, agriculture, and building complex structure for electric circuit or airplanes [10 13]. Numerous research has been done in the field of nanotechnology, but there is less study in the field of nanobiotechnology. Nanobiotechnology is the field that applies the nanoscience to biosystems and uses biological principle and material to create a new device and system integrated from the nanoscale [14]. The application of devices like nanosensors, nanoparticles, and delivery system to agriculture and food has the most promising use [15 19]. Nanotechnology has made an important advance in biomedical and pharmacology application. The material and device are design with a high degree of functional specificity and allow interacting with cell and tissues at the molecular level [4,20]. These nanomaterials are designed in such a fashion that they interact with cells at the molecular level. These synthesized nanomaterials have properties such as being hard to break, have high electric and thermal conductivity, and are very reactive due to their small size. The effectiveness of nanomaterials can be increased by surface modification, changing shape and size and using different materials. Pesticides are used in agriculture to remove the pest, pathogens, and unwanted plant weeds, but these pesticides accumulate in the soil making the land non-fertile for agriculture [21 24]. Some pesticides remain in the soil without any degradation causing loss of soil diversity and these pesticides enter water bodies with surface water runoff affecting the marine aquatic biodiversity and can enter the body of marine animal causing mutation, loss of fertility, increases pH, and if these pollutants get access into drinking water reservoir can enter human causing cancer, protein damage, or damage to DNA [23]. Nanotechnology has potential to increase productivity of crop, genetic improvement in human, and liposome can be used for gene therapy as well as for drug delivery. Nanospheres, nanotubes, nanoparticles of metal and metal oxides, and nanoencapsules are synthesized from different sources

Chapter 1 Nanotechnology and its application: a review

and used against pathogens for bioremediation, removal of toxic metals, nanoencapsulation of fertilizer and biopesticides, nutrients, and growth hormones in the field are very useful and reduce the excess loss of agrochemicals. Application of nanotechnology to agriculture, medical, water treatment, and to various fields is less costly and economical over the conventional method. In this chapter, we describe the application of nanotechnology to a biological system and enable the development of a new class of bioactive systems.

1.2

Application of nanotechnology

Nanotechnology has various applications in different fields. Nanobiosensors, Nanotubes, Nanoparticles, nanosphere quantum dots, and different nanomaterials have a broad range of applications to biological systems used for numerous purposes in a different field. For instance, in medical fields it is used to study cancer cells and to improve drug delivery systems. In agriculture, it is used to improve crop productivity. Nanotechnology has great potential in water and wastewater treatment to improve treatment efficiency. Application of nanotechnology to biological system is discussed in the following sections.

1.2.1

Nanotechnology in biomedical

Nanotechnology has been discovered as a major breakthrough for medical fields [25 30]. Nanocapsules and nanotubes can be used as a drug delivery vehicle; nanoprobes are synthesized for cell imaging; and various nanoparticles are synthesized from bacteria, fungus, or plant for their antimicrobial activity against disease-causing multiple drug-resistant bacteria. Drug delivery using nanoparticles offer accurate, effective treatment against diseases. The application of nanotechnology in medical fields have helped in the diagnoses of various diseases.

1.2.1.1

Drug delivery

The major and most common application of nanotechnology in medical fields is for drug delivery [30 35]. Using nanotechnology, hydrophobic drugs could be delivered to the target site, and a lesser amount is required because the drug is delivered directly at the site of action; drug delivery using nanoparticles is very effective because it can cross the membrane, and the side effect of the harmful medication can also be avoided through capillary action and penetrated deep to the target site to show

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Chapter 1 Nanotechnology and its application: a review

its effect. Liposomes can be used for drug delivery inside the cell as they can pass through the lipid bilayer [36,37]. As liposomes cross the lipid bilayer they are also used for gene therapy. Drug or ligand covalents are bound to the nanoparticles and then bound to the target cell having a receptor for a ligand on their surface. Drug delivery using nanoparticles as a vector has the advantage that as the drug specifically kills the targeted cell, harm to normal surrounding cells reduced, which mainly happens due to the toxicity of the therapeutic. When the synthesized nanoparticles coated with poly ethyl-glycol (PEG), the PEG increases its accumulation and circulation time in the blood and also protects it from blood clearance and surface changes due to the action of protein or other enzymes [38,39]. Many researchers have been working to inhibit the replication of HIV from preventing AIDS; none of the treatment can cure HIV infection. Even highly active antiretroviral therapy, which consists of three antiretroviral drugs, failed the lead to viral resistance [40 42]. Lieven Baert et al. worked on development of long-acting injectable formulation with nanoparticles of rilpivirine (TMC278) for HIV treatment [41]. Nanosuspension of nonnucleoside reverse transcriptase inhibitor rilpivirine were prepared as base or HCl by wet milling in an aqueous carrier, and the particles size were 200 nm, 400 nm, and 800 nm. They found on single-dose administration, the plasma concentration showed the constant release of rilpivirine over 3 months in dogs and 3 weeks in mice. They compared subcutaneous and intramuscular injections of 5 mg/kg (200 nm) in dogs, and results showed that the subcutaneous route had the most stable plasma level while 200 nm nanosuspension had higher and less flexible plasma concentration as compared to 400 and 800 nm suspension. In mice, the pharmacokinetics of 20 mg/kg (200 nm) were similar to two different surfactants, that is, poloxamer 338 and Dalpha-tocopheryl polyethylene glycol 1000 succinate. From the following result they concluded that 200 nm sized rilpivirine nanosuspension could function as a long-acting injectable. Katherine A. Redmond et al. worked on all transretinoic acid nanodisk [43]. They synthesized the nanodisk of phospholipid bilayer associated with ATRA as a delivery agent on human hepatoma cell. ATRA is the derivative of vitamin A, which is waterinsoluble and controls the cell growth and apoptosis of a cell. In cancer cells there are defects in the mechanism of retinoic acid [44]. In their study they found that the nanodisk associated with ATRA inhibited the cell growth of human hepatoma cells and required fewer doses as these nanodisks injected intravenously.

Chapter 1 Nanotechnology and its application: a review

Whereas Lesego Tshweu worked on nanoencapsulation of the water-soluble drug, lamivudine, using a double emulsion spraydrying technique for improving HIV treatment [11]. Various secondary diseases caused by viruses due to lowered immunity of HIV patients. The antiretroviral drug may have side effects and toxicity as well. They developed biodegradable nanoparticles as a drug delivery system to overcome this problem associated with the use of the antiretroviral drug. Polyepsiloncaprolactone (PCL) nanoparticles were synthesized by double emulsion spraydrying method using solvent and excipient, loaded it with lamivudine [45]. Lamivudine is an anti-HIV hydrophilic drug having a plasma half-life of 5 6 h. Drug release rate increased for 4 days at pH 1.3, pH 4.5, and pH 6.8, which is very significant because the condition is similar to that within the gastrointestinal tract. This study shows the potential of PCL loaded with lamivudine for controlled release. Likewise, Lebogang Katata et al. also worked on the design and formulation of nanosized spray-dried efavirenz part I: influence of formulation parameters [46]. The produced nanoparticles were moral nanoencapsulation of efavirenz, which is water-insoluble nonnucleoside reverse transcriptase inhibitor used in HIV treatment. Researchers synthesized different nanoparticles to facilitate drug delivery. Dendrimers are also used for drug delivery [47,48]. They are having branch structure and their size is similar to protein (Fig. 1.1). As dendrimers with a large surface are different therapeutic or biologically active compounds are attached and delivered. Dendrimer can use for imaging also, also for the

Figure 1.1 Dendrimers showing the different groups and space for the drug delivery [48].

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identification of detected cell by attaching biomarker. Biosensors not only have applications in agriculture but can also have applications in the medical field. For example, they can be used to monitor blood glucose level in blood. Not only the glucose level but they are used to control the cholesterol, thyroid, and urea level. Nanobiosensors can sense the change in level to take the necessary action. Also, nanoencapsules can be used for controlled-release enzymes whenever there is the change in the concentration in the body, for example, insulin release in the body to maintain the blood glucose level in the body. Claudia R. Gordijo et al. worked on Nanotechnology-Enabled Closed-Loop Insulin Delivery Device: In Vitro and In Vivo Evaluation of Glucose-Regulated Insulin Release for Diabetes Control. They used the bioinorganic nanocomposite membrane, which releases the insulin in response to the glucose level in blood [49].

1.2.1.2 Bioimaging Nanotechnology also can be used for the treatment of diseases in the symptomless stage. For diseases like cancer, if identified at a very early stage, it could be easy to treat the patient [50]. Imaging of cancer at an early stage helps in early recognition of the disease. Quantum dot can be used for cancer cell imaging. These crystals emit light when stimulated with light. This nanodevice can be used to identify the particular region in the DNA that helps in identifying the cell that is altered or to identify the cell different from other normal cells to distinguish between normal and mutated cell. The quantum dots give a wealth of information, which is helpful in recognition/identification. That is why the quantum dot has application in cancer treatment. But quantum dots may have some toxicity, so carbon dots are used for cancer cell imaging [50 53]. Susanta Kumar Bhunia et al. worked on the Imaging Cancer Cells Expressing the Folate Receptor with Carbon Dots Produced from Folic Acid [52]. Carbon dot was synthesized using folic acid as a carbon source and these C-dots then bind to target cancer cells, which expressed the folate receptors and fluorescent when stimulated with light. Hence it is easy to distinguish cancer through bioimaging and help in the diagnosis of cancer. Gold nanoparticles (AuNPs) are also used for bioimaging. Carbon dots are synthesized by using natural precursor and used in bioimaging or many medical fields [54 57]. Ji-Ho Park et al. worked on Micellar Hybrid Nanoparticles for Simultaneous Magnetofluorescent Imaging and Drug Delivery [58]. In their work they created hybrid nanoformulation which

Chapter 1 Nanotechnology and its application: a review

consists of quantum dots and magnetic iron oxide nanoparticles and also doxorubicin, an anticancer drug within micellar made up of polyethylene glycol. This micellar hybrid nanoparticle enables the detection of cancer or tumor cells by nearinfrared fluorescence imaging and magnetic resonance imaging (MRI) of tissues and their treatment by target drug delivery. Various multifunctional nanoformulation can be synthesized, which can work two or more simultaneously. Today, computed tomography (CT) imaging is used by doctors to check if there is any damage from a tumor inside the body and for diagnosis. In CT imaging iodine is used as a contrast agent. But CT imaging is not specific, and also once iodine gets cleared by kidney then imaging is not possible [59]. Rachela Popovtzer et al. worked on Targeted Gold Nanoparticles Enable Molecular CT Imaging of Cancer. They synthesized gold nanorods and conjugated it with the UM-A9 antibody and used this against squamous cell carcinoma [59]. The synthesized AuNPs conjugated with UM-A9 antibody binds to the cancer cells and gave distinguish CT image as AuNPs attached to a cancer cell in high density than that to other tissues. This way the AuNPs could have proved to be molecular imaging of cancer cells and also the size of the cancer cell [60].

1.2.1.3

Nanotechnology for diagnosis and treatment

Nowadays, the use of AuNPs for cancer diagnosis because of their nontoxicity to the body. The surface of AuNPs is modified with polymer or therapeutic agents, which specifically target cancer cells. The nanoparticles selectively invade the cancer cell, and after invading the therapeutic dissociate and release the toxin, resulting in apoptosis of cancer. This is used to treat tumors that cannot be removed by surgery. Moustafa R. K. Ali et al. studied nuclear membrane-targeted AuNPs that inhibit cancer cell migration and invasion [61]. Results obtained showed that AuNPs had held back cancer cell invasion speed as well as inhibit metastasis, which caused death in most cancer patients. They found that the AuNPs which were trapped in the nuclear membrane increased the stiffness of the nucleus and thus retarded cancer cell invasion. The AuNP can also be used as a tool for cancer cell imaging over CT scan, MRI, and X-rays. Rachela Popovtzer et al. also mentioned the use of AuNPs for molecular imaging of cancer cell [59]. Metals like copper, silver, gold, brass nickel, iron, etc. exhibit antimicrobial activity against a wide number of microorganism capable of causing diseases [59 64]. But a high level of some

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metal in the body can be toxic. So using nanotechnology, nanoparticles of these metals be made and used. The nanoparticles can penetrate deep inside the cell and in the capillary, and show its action even in minute concentrations. Researcher found various application of nanotechnology to deal with viruses and diseases causing bacteria. For instance, Ponnusamy Manogaran et al. studied mycosynthesis, characterization, and antibacterial activity of silver nanoparticles (AgNPs) against multidrug resistant (MDR) bacterial pathogens of female infertility cases [65]. AgNPs were synthesized from fungus oxysporum NGD and characterized them using X-diffraction, scanning electron microscopy, UV Vis spectroscopy, energy dispersive spectroscopy. The results on inhibitory potential of AgNPs on Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterobacter spp., and Escherichia coli. showed that AgNPs have high inhibitory effect against these bacteria. Other than AgNPs, which are coupled with ampicillin, also show inhibitory action. They found that as compared to AgNPs, AgNPs coupled with ampilline sensitize the bacteria more. Marwah M. Mohamed et al. studied the antibacterial effect of AuNPs against Corynebacterium pseudotuberculosis [66]. The causative agent of chronic caseous lymphadenitis in goats and sheep is C. pseudotuberculosis. They used AuNPs and AuNPs combined laser therapy against this bacterium. They found that the AuNPs penetrate deep inside the cell wall and the laser combined therapy help to improve the antibacterial effect of AuNPs. G. Prasannaraj and P. Venkatachalam studied on Enhanced Antibacterial, Anti-biofilm and Antioxidant (ROS) Activities of Biomolecules Engineered Silver Nanoparticles against Clinically Isolated Gram Positive and Gram Negative Microbial Pathogens [67]. In their study, they used 10 species of medicinal plant such as Alstonia scholaris, Andrographis paniculata, Aegle marmelos, Centella asiatica, Eclipta prostrata, Moringa oleifera leaves and barks of Thespesia populnea, Terminalia arjuna and root bark of Plumbago zeylanica, and Semecarpus anacardium nuts to synthesis AgNPs. The synthesized nanoparticles were then tested for their antibacterial and antibiofilm activity against bacterial species Staphylococcus aureus, Staphylococcus epidermidis, P. aeruginosa, E. coli, K. pneumoniae, Proteus vulgaris, which were isolated from patients. The result they obtained showed that AgNPs synthesized from these medical plants are very effective as antibacterial and also inhibit the biofilm formation by S. epidermidis and P. aeruginosa, and also increase the antioxidant generation. Similar study was performed by U. Jinu et al. biofabrication of Cubic Phase Silver Nanoparticles Loaded with Phytochemicals from Solanum nigrum Leaf Extracts for Potential

Chapter 1 Nanotechnology and its application: a review

Antibacterial, Antibiofilm and Antioxidant Activities against MDR Human Pathogens. They synthesized AgNPs from leaf extract of S. nigrum [68]. These studies showed that nanoformulation of plant extract very effective against MDR strain and are required in a very small amount to its effect.

1.2.1.4

Nanotechnology for treatment of cancer

Cancer defined as a multistep carcinogenesis process requiring various physiological arrangements such as cell apoptosis and imaging, causing it a highly uncoherent and complex disease. The major factor for the better or successful treatment of cancer is its early detection. Chemotherapy, surgery, and radiation therapy are the limited cancer treatment. To get more achievement toward the treatment of cancer patients, nanotechnology can play an important role to redefine it in better, cheaper, and easier ways [69 71]. On comparing with the bulk materials, large surface area to volume ratio of nanoparticle makes them a potential candidate for the cancer detection shown in Fig. 1.2. In some cancers, both radiotherapy and chemotherapy remain ineffective. Today, there are lot of research going on for the use of nanotechnology in cancer treatment. Nanoparticles can detect cancer in early stage by attaching to cancer marker targeting antibodies. This opens a door for nanotechnology toward its applications for cancer treatment. There are various therapy based on

Figure 1.2 Nanotechnology improves cancer detection and diagnosis [71].

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nanotechnology have been used for the treatment of cancer. Few of them are explained below: 1. Nanotechnology-based photodynamic therapy (PDT): It is based on the activation of photosensitizer. In this, a specific wavelength of light causes a release of reaction oxygen species to kill cancerous cell as well as tumor-associated vasculature. It leads to breaking of tumor infraction. Use of pH sensitive nanoparticle as a potential candidate for tumor targeting and PDT was performed by Peng et al. [72]. 2. Nanotechnology-based gene therapy: This therapy relies on the concept that to produce a tumoricidal effect, a specific exogenous gene can be placed into the tumor cell genome. This therapy is one of the most rapidly improving and developing areas in clinical cancer research. Jere et al. [73] have efficiently delivered Akt1 small-interference-RNA-loaded biodegradable nanopolymeric carrier, leading to silencing of Akt1 protein and reduced cancer cell survival, proliferation, malignancy, and metastasis. 3. Nanotechnology-based cancer theragnostics: Theragnostics is the combination of diagnosis and therapy used in the biomedical field for cancer treatment. The primary goal of theragnostics is to develop therapeutic accuracy for selectively target-specific (diseased) tissues or cells to make them safer, shorter, and more efficient. Shim et al. shows the theragnostic studies for cancer treatment [74]. They have coated AuNPs on small-interfering-RNA-encapsulating polyplexes via acid-cleavable linkages to explore the possibility of getting combined stimuli-responsive multimodal optical imaging and stimuli-enhanced gene silencing. 4. Nanotechnology-based radiotherapy and radio-frequency therapy: From long time use of high atomic number has been used for the enhancement of radiation dose. For the clinical usefulness, a radiosensitizer should be easily utilized, readily available, nontoxic, and have high therapeutic ratio. Nanogold (AuNPs) showed dose-enhancing effects in cell experiments. Chang et al. [75] have investigated the dose-enhancing effect and apoptotic potential of AuNPs in combination with single-dose clinical electron beams on B16F10 melanoma tumor-bearing mice. For cancer and other medical applications, three important functions requires are imaging with single and dual modality, targeting using one or more ligands and use of different therapy (Fig. 1.3). It gives various opportunities for the tuning of different properties that are impossible for other therapeutic drugs. Because of this they have a bright and long future toward the cancer therapeutics.

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Figure 1.3 Application of different nanotechnology therapy for cancer treatment [71].

1.2.1.5

Nanotechnology in genetic material sequencing

Nanopore technology is another emerging aspect. Nanopore technology is used for sequencing DNA or RNA [76 78]. It uses polymer membrane containing protein nanopores, which are electrically resistant. Any one strand of DNA or RNA is allowed to pass through the nanopore, and the change in current depends on which base passes. It offers quick and reliable sequencing in very lesser cost as compared to the conventional technique. This nanopore technology for the identification of cancer, as cancer cell may different DNA sequence as compared to other normal (Fig. 1.4) so offer early identification. Not only for cancer cell identification but this technique can be used for whole genome identification of viruses or bacteria, detection of any mutation in human genome, etc. This technique offers quick, rapid analysis of the DNA sequence. Molecular diagnostics are a part of genetic material sequencing and also extends its limits to nanoscale using nanotechnology. Conversion of nucleic acid into strings of nucleotides using nanopore technology and then directly into electronic signals has also been analyzed [79].

1.2.1.6

Nanotechnology in biosensors

Nanobiosensors are the small biosensors incorporated in the biologically derived sensitized elements linked to physicochemical

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Figure 1.4 Nanopore acting as a nanodevice for reading genetic code [50].

Figure 1.5 Advancement in nanotechnology toward biosensor application.

transducers and used to detect the presence or concentration of various molecules, toxic compounds, or microorganisms. Biosensors comprise of bioreceptors and transducers, which sense elements, and transducers detect this signal and convert the signal to electric signal [80,81]. Application of nanotechnology toward the biosensor has been shown as Fig. 1.5

Chapter 1 Nanotechnology and its application: a review

If the compounds or pathogens are present in a small number, nanobiosensor can easy sense and produce a signal. They can detect the presence of compounds present in the minute concentration in the environment. There are different types of biosensors developed depending on transducing mechanism. Biosensors

Transducing

Resonant biosensors

An acoustic wave transducers is coupled bioelements, which measure the frequency change due to change in the mass of membrane to which bioelement attached. Signal measured is light. The change in refractive index of the medium due to change in the absorbance or fluorescence caused in the reaction. In biological reaction, heat generates changes the temperature of the medium in which reaction happens. The biosensor senses the temperature. Measurement of temperature of temperature is done using thermistors, that is, enzyme thermistors. They are semiconductor field effect transistor having ionsensitive surface. When ion and semiconductors, the surface potential changes which measured. Ions or electors produces in the chemical reaction changes the electric properties of the solution. Electrochemical biosensors are used to measure this variation. These biosensors sense electroactive type in the biological samples. Measures the oxidation or reduction potential of the electrochemical reaction.

Optical biosensors

Thermal detection biosensors

Ion-sensitive biosensors Electrochemical biosensors Amperometric biosensors Potentiometric biosensors

1.2.1.7

Nanotechnology in controlled release

Apart from the use of a biosensor, different carrier vehicles are used for controlled release of agrochemical in the field. These carrier vehicles are easy biodegradable, cheap, and low toxic. The use of controlled-release system to agriculture allow controlled delivery of agrochemical, which reduces the quantities of agrochemical required and so reduces the toxicity to human health and environment. Biofertilizers consist of living microorganisms, which helps to convert organic material into simple compound essential for plant growth, maintain the fertility of soil, increases crop yield, and maintains soil quality. But these are temperature and pH sensitive. So the controlled-release system reduces the loss of agrochemicals due to leaching, evaporation, and other aspects [82 86]. Nanocapsules are made, which act as a carrier vehicle for

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controlled release of various agrochemicals in the field. Nanocapsules are the hollow nanoparticles, which are made up of nontoxic polymer. Fertilizer and pesticides are encapsulated for controlled release. The outer shell protect the agrochemical from damage by various outer factor present in surrounding and helps to penetrate deep in the tissue. The opening of the shell can also be controlled by changing the external environment. Liposomes and polymers have been made for this purpose. Estefaˆnia Vangelie Ramos Campos et al. worked on Polymeric and Solid Lipid Nanoparticles for Sustained Release of Carbendazim and Tebuconazole in Agricultural Applications [87]. In their study they used carbendazim and tebuconazole, which are commonly used as a fungicidal in the agricultural field. They prepared the solid lipid nanoparticles and polymeric nanocapsules as a carrier system for the mixture of carbendazim and tebuconazole. They then observed for the release profile of these fungicides and also for their cytotoxicity. They found that both the nanoparticles showed 99% association efficiency and there was a decrease in cytotoxicity of these fungicides. Similarly, Jhones Luiz de Oliveira worked on Solid Lipid Nanoparticles Coloaded with Simazine and Atrazine: Preparation, Characterization, and Evaluation of Herbicidal Activity [88]. They used atrazine as well as simazine herbicides for their study. Solid lipid nanoparticles, having these herbicides, were prepared. They found that use of solid lipid nanoparticles improved the release profile of these herbicides in water. The treatment of species Raphanus raphanistrum with the nanoparticles containing herbicides showed the effectiveness of this formulation, and the toxicity of these herbicides in the presence of solid lipid nanoparticles was decreased. Harrison Wanyika worked on sustained release of fungicide metalaxyl by mesoporous silica nanospheres [89]. He used nanoparticles for the delivery of the pesticides. He prepared the mesoporous silica nanoparticles by sol gel process and loaded metalaxyl molecules into the pores of mesoporous silica nanoparticles by a rotary evaporation method. He found that nearly 76% of free metalaxyl was released in the soil within 30 days while only 47% of metalaxyl was released by mesoporous silica nanoparticles in the soil within the same time period. This shows that the use of nanoparticle as a carrier for the controlled release can significantly decreased their release in soil. Srinivasa Rao Yearla and Kollipara Padmasree worked on Exploitation of subabul stem lignin as a matrix in controlledrelease agrochemical nanoformulations: a case study with herbicide diuron [90]. In this study they exploited the ability of subabul stem lignin as a matrix material for agrochemical formulation.

Chapter 1 Nanotechnology and its application: a review

They employed the nanoprecipitation method then optimized to fabricate a stable herbicide “diuron nanoformulation” (DNF). This optimized DNF (ODNF) have nonlinear biphasic release nature for diuron. ODNF efficiency for release of diuron was tested using Canola (Brassica rapa). B. rapa seedling was grown in the soil supplemented with ODNF. They observed that the B. rapa showed early sign of leaf chlorosis and mortality in soil compared with B. rapa grown in the soil supplemented with commercial diuron formulation and bulk diuron. Through this study they also concluded that subabul stem lignin could be utilized as a matrix for another agrochemical also which are associated with growth and development of the plant. Similarly, El-Refaie Kenawy and M.A. Sakran also worked on Controlled Release Formulations of Agrochemicals from Calcium Alginate [91]. In their study, calcium alginate was used as a matrix for controlled release of 1naphthalene acetic acid and pentachlorophenol which act as a growth regulator and plant herbicide (Fig. 1.6). In addition they also used poly (ethylene imine) (PEI) for coating alginate beads. They found that after coating the gel beads by PEI, the release rate from the gel beads retarded. The release rate after coating varied completely. So the coating of beads with PEI can increase the duration of the release of agrochemical.

Figure 1.6 Interaction of different nanoparticles with plant.

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1.2.1.8 Nanotechnology in bioremediation Bioremediation is use of microbes for removal of pollutant from environment. Pesticides and herbicides are used to protect the plant from diseases and from attack by pests. But these pesticides get accumulated in the environment. Nanotechnology plays the keen role in the cleaning of the environment. Nanotechnology has application in the bioremediation of pollutants such as resistant pesticides [92 95]. Accumulation of these pesticides can affect the soil quality of the agricultural field and disturb the biodiversity of soil microflora, which helps in the fixation of various elements in the soil. This pollutant comes from various industries, agriculture, and domestic waste, and from the degradation of an organic compound and this resistant pollutant or compound persists for a longer time and has a harmful effect on the environment as well as on the human and animal health. Titanium dioxide (TiO2) enhances the growth and photosynthesis in plant and also shows its activity in the degradation of pesticides. Many metal oxide nanoparticles like ZnO, CuO, and TiO2 nanoparticles can be used for removal of resistant pesticides (Fig. 1.7) [94,95]. If these

Figure 1.7 Nanoparticles for bioremediation.

Chapter 1 Nanotechnology and its application: a review

pollutants enter the food chain and get an entry in the human body then can affect kidney, liver, or other parts. So the elimination of these pollutants from the environment is crucial, and it requires a very long period of time to elimination of these compounds. Nanotechnology can be useful for the elimination of these hazardous compounds. These compounds can enter the food chain and can cause serious health problems. So nanotechnology can be used for health and environment safety. Nanoparticles can act as a catalyst to enhance the degradation of this pollutant in natural sunlight and helps in the removal of these compounds. Punitha M. and J. Caroline Rose worked on biodegradation of organophosphorus pesticide using immobilized esterase and toxicity assessment [96]. In their study they used Quinalphos, Chlorpyriphos, and monocrotophos pesticides as organophosphorus pesticides which were degraded by esterase enzyme from Staphylococcus spp. Staphylococcus was isolated from the pesticide-contaminated soil from the farm. In their research, they immobilized the enzyme on sodium alginate beads and magnetic nanoparticles because the immobilized enzyme has several benefits over normal enzymes. They found 80% degradation of 0.5% Quinalphos in four days by the isolate and they also found that the enzyme immobilized on magnetic nanoparticles were more stable and reusable up to seven cycles. The effluent from pharmaceutical industries and medicinal component, which have been releasing in the water bodies can have a severe effect on health. These medicinal components such as antiseptics or pharmaceutical effluents containing antibiotics can produces resistant in organisms. This leads to the occurrence of various multiple drug resistance organisms. Also these effluents can be hazardous to the environment and can be toxic to the aquatic environment or can produce long-term adverse effects in the aquatic environment. So biodegradation of this component is essential. But pharmaceuticals are designed in such a way that they show their effect in minute concentration and resistant to biological degradation. Researcher has used the photocatalysis method using TiO2 nanoparticles for biodegradation of these pharmaceuticals. Mona Bakr Mohamed studied on Comparative Study of the Photocatalytic Activity of Semiconductor Nanostructures and Their Hybrid Metal Nanocomposites on the Photodegradation of Malathion [97]. Malathion is a pesticide which acts against wide range of pest. They are chemically stable and toxic, so they resist the biodegradation. They persist for a long time in the human body and have a lethal effect such as kidney failure, anemia, etc. Different semiconductor nanoparticles and their metal hybrid

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nanocomposites were synthesized such as TiO2, Au/TiO2, ZnO, and Au/ZnO. These materials were used as a catalyst for photodegradation of Malathion pesticide. The degradation of malathion was evaluated with high-performance liquid chromatography and UV visible spectra in the presence of these nanocomposites. The result shows a hybrid composed of semiconductor metal hybrid serves as a better catalytic system compared with semiconductor nanoparticles itself. Existence of gold with nanocomposites increased adsorption of pollutant and increased the photocatalytic activity of nanocomposite in the natural sun light. Ali Nickheslat et al. had done their research on Phenol Photocatalytic Degradation by Advanced Oxidation Process under Ultraviolet Radiation Using Titanium Dioxide [97]. A lot of research on the degradation of phenol has been done. Phenol or phenolic compounds have a harmful effect on both human and animal health and they persist for a long time in the environment. They studied photocatalytic degradation of phenol from laboratory sample, and petrochemical industrial wastewater using titanium dioxide (TiO2) as a photocatalyst under UV radiation [98]. TiO2 nanoparticles in anatase crystal form were coated on inside and outside of quartz tube by dip coating sol gel method. Degradation was studied under different factors such as pH of the solution, initial application of phenol concentration, TiO2 catalyst dose, duration of UV radiation and contact time. The results showed that the phenol removal efficiency increased with the decrease of the pH solution and initial phenol concentration and increasing contact time. The phenol removal efficiency was equal for both synthetic solution and petrochemical wastewater solution at the same condition.

1.2.1.9 Nanotechnology in agriculture and environment Agriculture contributes greatly to the developing countries economy. In India agriculture contributes 18% of India’s gross domestic product. So there has to be a new technology to increase the yield of agriculture. Nature is a mixture of different physical, chemical, and a biological factor which shows their effect on agriculture production. So slight change in any of this factor can show they effect the plant and crop health in turns to affect human and animal health. Deficiencies of macro- and micronutrient, the low water content of the soil, industrialization, population, erosion of soil, and soil condition in different areas—all these factors also contribute to affect agriculture. All these problems led to the use of fertilizer to overcome these deficiencies. For all these problems nanotechnology can be a

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good solution. They monitors the changes caused due to use of various fertilizer, pesticides, and also monitor changes in physical condition such as pH of soil, moisture level, toxicity produce in the field, growth condition of crops, etc. benefits of applying nanotechnology to agriculture [92,99]. Different application of nanotechnology in the agriculture field is presented as Fig. 1.8. The specificity of nanosensors and aptasensors allows analysis of different types of heavy metal ions, pathogenic microbes, toxins, small metals, nucleic acid, and proteins. They concluded use of nanosensors to agriculture is really beneficial, and future research requires more attention for the development of more reliable material, method, and smart delivery system and devices on the nanoscale and also to the evaluation of the impact on the human health and environment. S. Baruah and J. Dutta in their review paper on nanotechnology application in pollution sensing and degradation in the agriculture discussed about the use of biosensors in agriculture and environment for recognition of toxic pesticides, herbicides, heavy metal ions, organic compounds, contamination, and harmful microbes in agriculture fields, and the use of photocatalysts for the study of degradation assay of various pesticides and also the effect of these nanostructure [100]. They concluded that nanotechnology is useful for the degradation of persistent chemicals into harmless and sometimes useful compounds. The antioxidant and

Figure 1.8 Application of nanotechnology in agriculture.

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antimicrobial properties of nanoparticles can be used for the safe storage of crops. In agriculture, they are used to monitor the microbes, contamination, pollutants and freshness of food in the agriculture. Nanobiosensors senses the changes in the soil and send signal so that necessary action would be taken. For instance, Enisa Omanovi´c-Miklicˇ anin and Mirjana Maksimovic studied on the nanosensors applications in agriculture and food industry [101]. In their study, they develop various nanosensors for various purposes like nanosensor for monitoring soil condition, nanosensor for detection of food borne contamination, aptasensor for the determination of pesticides and insecticides, etc. Aptasensors are biosensors consist of aptamer which is target-recognition complex. Aptamer is highly specific and selective toward their target compound because of their precise and well-defined threedimensional structure. Also they studied the toxicity and safety aspect of nanosensor utilization in agriculture and food industry. Through their study they concluded that development in nanotechnology has a positive influence on agriculture and food industry. It helps in improving crop, health quality of soil, influence growth of plants, processing, distribution, and storage.

1.2.1.10

Nanotechnology in water treatment

Water is a very essential element of life. From unicellular to multicellular, prokaryotes to eukaryotes, every single organism requires water for growth and development and to carry out their essential metabolic pathway and energy generation. It is the most important element of life on earth. But the pesticides from agriculture fields, industrial effluents containing dyes or chemicals, domestic wastewater, oil spills, etc. pollute water and disturb the biodiversity of water. Polluted water contains both organic and inorganic pollutants. Dyes released from the textile, paper, pharmaceutical industries, etc. can be carcinogenic or mutagenic. Water polluted by these pollutants are used for agriculture, cooking, and drinking purposes. Pollutants, once entering the human body, can cause cancer of bladder, liver, or can cause mutation. Sometimes parent compounds can be harmless, but by the action of liver or intestinal enzymes these compounds get converted into harmful mutagenic products. Drinking water contains pathogenic organisms, which causes various water-borne chronic diseases. Water acts as a carrier for these organisms. Removal of these pollutants and organic matter from water and wastewater is essential to keep the environment clean and maintain human health and safety [102]. Algae biosensors could be used to detect the pollution

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in which pollution level in water can be detected by measuring the metabolic activity of algae, which is affect if the pollutant are present in the surrounding [80]. In their review on microalgae biosensors, they have described briefly about the microalgae-based biosensors for detection of contaminants in water. Titanium dioxide has a photocatalyst activity for the degradation of organic waste present in wastewater. The TiO2 nanoparticles absorb light of higher energy, electrons (e2) move to produce holes (h1). The hole interacts with water around it and form free hydroxyl radical (Fig. 1.9). These free radicals interact with harmful organic pollutants and convert them into harmless CO2 and H2O. Researchers are putting in efforts to increase the phytopathogenic disinfection efficiency of TiO2 thin films by dye doping and other suitable methods [103]. S. Peltier et al. worked on nanofiltration: improvements of water quality in a large distribution system [104]. The water quality was compared before and after nanofiltration. Two treatment plant had two trains: the old one is a conventional treatment plant and the other is the nanofiltration plant. The study was conducted for 4 years to compare the quality. They found a change in the chemical quality of final water. The pH, conductivity, and alkalinity had decreased, and also decreased in the mean value of free residual chlorine. The aluminum concentration were lowered due to the removal of ions by the membrane. They found a decrease in the level of biodegradable dissolved organic compounds in the distribution system after nanofiltration treatment. Their study shows that the water generated after the nanofiltration treatment had a low biodegradable dissolved organic compound, and chlorine residuals were stable with no or excessive chlorine residuals (because of rechlorination).

Figure 1.9 Photocatalysis of organic pollutants using TiO2.

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Yuan Zhuang et al. worked on Magnesium Silicate Hollow Nanostructures as Highly Efficient Absorbents for Toxic Metal Ions [105]. They prepared magnesium-silicate hollow spheres, core-shell spheres, and nanotubes by hydrothermal process. Different concentration of NaOH was used to synthesize a hollow sphere and core-shell sphere. Silicate nanotubes were synthesized by adding glycol. Pb(NO3)2, CrCl3
6H2O, Cd(NO3)2
4H2O, and Fe(NO3)3
9H2O were used as a source of Pb(II), Cr(III), Cd (II), and Fe(III) toxic metal ions. The silicate nanomaterial has lamellar or chain structure intercalated with mobile magnesium ions so magnesium ions can be easy and can be exchanged with toxic ions. The result they obtained showed that these silicate nanomaterials had the brilliant capacity to remove toxic metal ions. And they also found that these nanomaterials can be reuse after desorption. This technique can be used for removal of toxic ions in the water treatment process. Sampath Marimuthu et al. worked on Evaluation of green synthesized AgNPs against parasites [106]. AgNPs were synthesized from Mimosa pudica Gaertn (Mimosaceae). The synthesized nanoparticles are used against the larvae of the malaria vector, Anopheles subpictus Grassi, filariasis vector Culex quinquefasciatus Say (Diptera: Culicidae), and Rhipicephalus (Boophilus) microplus Canestrini (Acari: Ixodidae). The larvae of the parasite exposed to variable concentration of aqueous extract of M. pudica and AgNPs. They found the highest mortality rate in synthesized AgNPs against the larvae of A. subpictus as well as against C. quinquefasciatus. This study showed the efficiency of AgNP as an antimicrobial agent. This way AgNPs can be used for the removal of mosquito larvae from water in the water treatment process. Hui Ying Yang et al. studied carbon nanotube membranes with ultrahigh specific adsorption capacity for water desalination and purification [107]. The study showed that the ultralong carbon nanotubes have the capacity to absorb the salt. This opens the option of desalination through salt adsorption. They also found that these ultralong nanotubes had ability to remove organic and metal nanoparticles from the soil. Nanotechnology can be used for water treatment. Nanotechnology offers better treatment efficiency over the conventional method.

1.2.1.11

Nanotechnology in food industry

Nanotechnology can be used in food industry to prevent wastage of food due to microbial contamination, to increase shelf life of the food product and also to increase the safety of

Chapter 1 Nanotechnology and its application: a review

Figure 1.10 Use of nanotechnology in food industry.

food product. Application of nanomaterial such as nanocomposites for improving shelf life, biodegradation, active packaging in which nanomaterial are incorporated with antimicrobial agent to control the microbial population, intelligent packaging in which nanosensors are used to check the food, microbial contamination in the food, to increase the nutritional value of food, enhance flavor, etc. (Fig. 1.10) [108]. In food processing, for purification of raw material, nanopores have nanofiltration membrane used to separate molecules like amino acids, vitamin, and other substance, and this could enhance the nutritional value of food [109]. In food packing, nanotechnology-based packing material may be inorganic polymer, metal, or metal oxide, which can increase the shelf life of fruits and vegetables, and also decrease the decay rate of the food product [109]. 1.2.1.11.1

Active packing and intelligent packaging

Active packing is the packaging that maintains the food quality. In active packaging, materials that can maintain the food quality are incorporated along with packaging material like antimicrobial or antioxident, which releases slowly onto the food or diffuses in the food and maintains the food quality [110]. Such packing can be used for meat and meat products. Antimicrobial substances slowy diffuses on the surface of meat or meat product and inhibit the growth of microbes on the surface of food. For example, Japan developed zeolite, which contains silver atoms on the surface incorporated into plastic. Zeolite used to laminate the food contact polymer surface and when the aqueous solution from food comes in contact to this porous structure, it release silver ions [111]. E.L. Bradly et al. in application of nanomaterial in food packaging with a consideration of opportunity for developing countries, point out the use of nanoencapsulation in active packing for release of

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preservatives on food which will reduce the amount of additive required [12]. Fang et al. in their review on active and intelligent packing in meat industry discussed about the use of active packing in meat industry for meat and meat product such as antimicrobial active packing, carbon dioxide generating active packing, and antioxidant active packing and intelligent packaging for meat [110]. Intelligent packaging provide the information about internal or external environmental of the food, quality of the food to the consumer or food manufacturer, product manufacturing, storage condition, microbial quality of food, specific pathogenic bacteria by using barcode, radio frequency identification tag, time-temperature indicators, gas indicator, freshness indicator, pathogen indicator, and biosensor [110]. 1.2.1.11.2 Nanomaterial as barrier To maintain the food freshness and to increase shelf life of food nanostructure form of silica oxide, titanium oxide, magnesium oxide, aluminum coated plastics films are used, which acts as a barrier to keep away moisture, oxygen, and light and prevent the food spoilage [12,112]. Also, to increase the bioavailability of nutritionally important food ingredient with poor solubility. Like CoQ10 is an antioxidant, effective against various disease but bioavailability is very low. To overcome this problem D.D. Ankola prepared nanomisceller formulation for oral delivery [113]. N. Bumbudsanpharok et al. in Applications of Nanomaterials in Food Packaging described various nanoformulation to be used in food packaging such as AgNP due to its antimicrobial activity, nanoclay acts as a barrier for moisture gases and titanium nanoparticles due to its antimicrobial activity as it produces ROS and free radicals and also protects from light used for pasteurized milk to reduce light effect [114]. Aryou Emamifar et al. observed the effect of nanocomposite packaging containing of ZnO and Ag on inactivation of Lactobacillus plantarum in orange juice [115]. Lin et. al studied the effect of moringa oil/chitosan nanoparticles embedded gelatin nanofibers for food packaging against Listeria monocytogenes and S. aureus on cheese [116]. They found that moringa oil loaded in chitosan nanoparticle showed antimicrobial activity against both pathogenic microorganism L. monocutogenes and S. aureus without affecting the cheese quality. 1.2.1.11.3

Nanosensors

Nanomaterials are very sensitive as biosensors so they used in microbiological detection, food detection, and also toward the

Chapter 1 Nanotechnology and its application: a review

gases released by the spoiled food [109,117,118]. Nanosensors can detect change in temperature, pH in food, for example, in the use of protein-based halochromic electrospun nanosensor for monitoring trout fish freshness [119]. Nanotechnology has various applications in the food sector, and many researchers are working on application of nanotechnology in the food industry. Use of nanomaterial for improving the packaging, intelligent packaging in which nanosensor are incorporated, which provide information on the food, active packaging using antimicrobial activity of different substances to reduce growth of microbes, etc. There are various different applications of nanotechnology in meat or meat product industry, dairy industry, nanotechnology in food sector also used to increase the food quality, flavor, and color to increase nutritional value of food. For all this purpose various nanoformulations such nanoencapsulation, nanoparticles, nanofibers for separation, biosensor, etc., and many more. Guillermo Fuertes et al. in their review on Intelligent Packaging Systems: Sensors and Nanosensors to Monitor Food Quality and Safety discussed application of nanotechnology [120].

1.3

Conclusion

Nanotechnology is definitely a very useful tool, having a wide range of application to the biological system, and can be synthesized from various biological sources. From increasing the productive agricultural products to the bioimaging of the cancer cell and diagnosis, nanotechnology played a very important role. With rapid increase of population, agricultural productivity should also increase to meet the demand of food, the use of nanotechnology has increased the food productivity. In this review paper some of the encouraging application of nanotechnology in various fields have been discussed. Prevents the excessive loss of agrochemical. So biosensor conjugated with controlled-release system can help in release of nutrient by sensing the surrounding. Due to the small size of these nanoparticles and nanotubes, it penetrates deep inside and reaches deep inside the soil and maintain its fertility. Biosensors, which can monitor the amount of gases, release or present in the environment which contributes to global warming should be design so that proper measure can be taken to control or minimize the release of these toxic gases in the environment. Use of nanotechnology to the field reduced the effort and is very economical. Nanoencapsulation of water slowly releases water so

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decreases excessive loss of water. Bioremediation of resistant pesticides, pharmaceutical effluent, petrochemical, etc. using nanoparticles shows good results without causing any harm to the environment. These small nanoparticles have the ability to react with organic compound and adsorb heavy metal; they also found their application in water and wastewater treatment. The treatment of wastewater using nanoparticles shows great effect over conventional method. Tertiary treatment plant should be there during wastewater treatment to remove the heavy metal and also to kill microorganism present in the water. Nanotechnology also has application in target drug delivery, cancer imaging, and antimicrobial activity of metal nanoparticles against harmful microbes. Even bioimaging of tumors is easier and requires less cost as compared to CT scan and X-rays. Various disorders, which can be caused by imbalances of hormones, can be treated using nanodelivery systems. In health science, various nanodevices can be synthesized, such as multifunctional nanodevices, which can perform imaging, identification of infected tissue or cell, and target delivery of drug to the site of interest, which be useful for identification as well as for diagnosis of disease. Active packaging used to maintain the food quality, nanosensors used to sense the pH, temperature, or any change occurs in food.

1.4

Future and challenges

Although nanotechnology has outstanding application in various biological fields, but the effect on human and animal health should also be studied. Due to the small size of nanoparticles they can accumulate in organs and that can lead to toxicity. Toxicity of nanoparticles to body cells and tissues should be checked. A nanoparticle produces free radicals during the degradation process or inside the body, which produces toxicity. This free radical can damage DNA or protein. Due to its small size, nanoparticles can get excessive in the blood and easily enter the cell, so nanoparticles should be synthesized, which can be easily degradable and can easily clean up in the body. Until now the harmful effects of nanotechnology on human health and environment are not noticed but may show up after some time. Concentration of nanoparticles to be introduced should be properly studied to avoid toxicity. In future, more research should be done on the application of nanotechnology to treat various diseases by detection in early stages with less cost so that all people can afford it, making these techniques available to everyone.

Chapter 1 Nanotechnology and its application: a review

Acknowledgment Authors thanks to their respective universities for supporting their work. PR thanks NRF for Korea Research Fellowship (2019H1D3A1A01070741).

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Exploring biomarkers and diagnostics system for cancer management

2

Kamil Reza Khondakar1, Ajeet Kumar Kaushik2 and K. Mohsin Reza3 1

Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia 2NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States 3Department of Conservative Dentistry and Endodontics, Navodaya Dental College, Raichur, India

2.1

Introduction

Cancer is one of the high mortality diseases which is a threat to human lives for immature deaths [1,2]. Therefore the early and accurate detection of cancer is highly important for clinical diagnosis using cancer biomarkers [3,4]. Cancer biomarkers have been developed as promising noninvasive, real-time probes for cancer screening, diagnosis, monitoring, and recurrence [2,5]. Biomarkers provide crucial information regarding the cancer disease in various stages of cancer (Table 2.1). One of the approaches to identify cancer biomarkers are based on preliminary clinical or pathological observations in blood and tissues. Cancer biomarkers comprises variety of molecules, including cell, DNA/RNA, proteins, lipids, exosomes, etc. in human body fluids that can be objectively measured and evaluated as an indicator for a normal biological process, pathogenic process, or pharmacological responses to a therapeutic intervention (Fig. 2.1) [6,7]. The detection and analysis of cancer biomarker are being investigated to develop reliable, cost-effective, powerful detection and monitoring strategies for cancer risk indication, early cancer detection, tumor classification, cancer treatment, and cancer recurrence [8 10]. However, there are challenges for precise diagnostics in cancer treatment using current technologies. Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00004-4 © 2021 Elsevier Inc. All rights reserved.

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Chapter 2 Exploring biomarkers and diagnostics system for cancer management

Table 2.1 Some of the prominent cancer biomarkers used in clinical settings. Biomarkers

Cancer type

Clinical stage

CA 125 EGFR ALK B-RAF HER-2 CA 15-3 PSA K-RAS CA 19-9

Ovarian Colon Lung Melanoma Breast Breast Prostate Colorectal Pancreatic

Monitoring Predictive Predictive Predictive and therapeutic Predictive and monitoring Monitoring Screening and monitoring Predictive Monitoring

ALK, Anaplastic lymphoma kinase; B-RAF, v-raf murine sarcoma viral oncogene homolog B; CA 125, cancer antigen 125; CA 15-3, cancer antigen 15-3; CA 19-9, cancer antigen 19-9; EGFR, epidermal growth factor receptor; HER-2, human epidermal growth factor receptor 2; K-RAS, Kirsten rat sarcoma viral oncogene; PSA, prostate-specific antigen.

Protein

Cancer biomarkers

Exosomes

Figure 2.1 Various cancer biomarkers utilized in cancer management.

RNA

Cell

DNA

In the point-of-care diagnostics, clinicians are considering various approaches for quick therapeutic decision in cancer therapy. One of the biggest challenges for the clinical oncologist is to comprehend the cancer disease heterogeneity [7]. Cancer originate from tumors due to accumulated genetic and epigenetic alterations, but the origin and individuality of the tumor is largely unknown [11]. Although monoclonal in origin, most tumors appear to contain a heterogeneous population of cancer. Sotiriou et al. reported that breast cancer is not a single disease, with variable morphologic features and biomarkers, but rather, a group of molecularly distinct neoplastic disorders [12].

Chapter 2 Exploring biomarkers and diagnostics system for cancer management

Therefore approaches are urgently needed to understand the mystery of cancer heterogeneity by studying the molecular mechanism [13,14]. Individual profiling, multiple screening, combining therapies of cancer biomarkers are some of the approaches that could shed light about the molecular differentiation and mutations that lead to cancer and could provide better cancer management [6,15]. Cancer cells, proteins, and nucleic acids have been investigated as standard biomarkers for this purpose. There are gold standard techniques that have been developed based on flow cytometer, enzyme linked immunosorbent assay (ELISA), Western blot, PCR, gene analysis, immunohistochemistry, etc., for analysis of cancer biomarkers [5]. These methods are standard for cancer diagnostics; however, complex operating procedure makes it time consuming and labor intensive. Also, these techniques involve complex procedure for the analysis of the results. In order to profile the cancer biomarkers for better cancer management, nanotechnology-based techniques are being developed that could be rapid, sensitive, and highly specific to analyze the tumor cells. We have summarized some of the gold standard techniques for cancer detection and its limitations. One of the gold standard techniques for circulating tumor cells (CTC) detection and quantification is Cell Search method which is FDA approved for whole blood analysis in cancer patients [6]. This immunoaffinity based method for CTC analysis works on antigen antibody interaction with one single biomarker expression of epithelial cell adhesion molecule (EpCAM) limiting its application to only EpCAM positive CTCs. This kit is used for monitoring of patients with metastatic breast, colorectal, or prostate cancer. This single biomarker is inadequate for capturing and detecting highly heterogeneous tumor cells, unable to get the true condition of cancer plasticity. Flow cytometry is another technique for the cell surface analysis based on protein expression, which is achieved by using fluorescence tags [16]. Although it can analyze thousands of cells, it has some limitations. The overlapping fluorescence bands of this technique restrict its routine application for multiple biomarkers detection in clinical settings. Meanwhile, robust instrumental setup and related cost as well as requirement for trained personals for operational purpose limit its application. Similarly, ELISA have been used for analysis of cancer protein biomarker (cells, proteins), that utilized antibody-antigen interaction to capture the target molecules followed by fluorescence detection [17]. While fluorescence-based detection is not suitable for multiplex analysis; one of the major problems in

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ELISA is the slow diffusion of target molecules that restricts the successful interaction between the targets and the antibody. This technique is not suitable for early detection of cancer as it cannot detect low protein amount in cancer patients. Moreover, recent understanding of cancer progression pathways limits the single biomarker-based disease detection approaches short and highlighted the need of screening multiple biomarkers simultaneously to understand more vigorously about the disease progression mechanisms and to facilitate treatment selection [8]. However, the presence of circulating biomarkers (CTCs, soluble protein, circulating DNA/RNA, exosomes, etc.) at the early stage of cancer is very rare, making it extremely difficult to trace them in blood for the clinicians. Thus, we require sophisticated techniques which can sensitively detect the CTCs as well as the minute amount of the circulating biomarkers. Because there are some improvement for the assay, biomarker detection is still challenged by the long-time procedure, sensitivity, multiplexed capability, and specificity, in particular, for the detection in the complex biological sample or the patient samples. Nanotechnology-based immunoassay has been demonstrated as an attractive alternative to other methods for its versatility in cancer management (Fig. 2.2). These are due to the great advantages of the current nanotechnology driven techniques and tools that have shown ultrahigh sensitivity, high specificity, rapid data analysis, point-of-care diagnostics, etc. [5]. Recent advances in nanotechnology for tumor analysis have made it possible to investigate biomarkers in a miniaturized platform coupled with multiple detection system [6,18]. Nanotechnology-based techniques are being explored as a

Figure 2.2 Schematic illustration showing nanotechnology in cancer management.

Chapter 2 Exploring biomarkers and diagnostics system for cancer management

noninvasive tool for cancer detection with electrochemical, surface enhanced Raman spectroscopy (SERS), fluorescence, and in vivo detection of tumors [19]. One of the major causes of cancer mortality among the humans is due to late diagnosis. Early detection of cancer would aid in its prognosis or predict therapeutic response for cancer treatment. Also, an efficient cancer diagnostics system at early stage would be helpful for selecting effective diagnostics for targeted cancer therapy. This would be very much useful for oncologists to understand cancer progression, monitoring and therapy assessment for cancer management resulting in better patient life.

2.2

Efficient and miniaturized diagnostics system

Further, another challenge in cancer management is the expensive and sophisticated instruments for carrying out all the relevant cancer pathological examinations in hospitals. Currently, common cancer treatments are restricted to chemotherapy, radiation and surgery which are also expensive and sometimes nonresponsive to patients. To reduce the cancer mortality, we require micrototal analysis systems (µTAS) as an efficient lab on a chip platforms [20,21]. Significant progress in µTAS has been achieved due to multiple advantages: highly efficient, high sensitivity, multitasking, scale-able sample handling, rapid sample processing and the precise control of fluids in an assay, etc. [22,23]. These miniaturized microfluidic systems (or µTAS) have transformed the point-of-care diagnostics into a reality for its automation and high-throughput capability. These innovative platforms could be applied to biology research to streamline complex assay protocols; to reduce the sample volume substantially; to reduce the cost of reagents and maximize information gleaned from precious samples. It also provides gains in scalability for screening applications and batch sample processing analogous to multiwell plates; and the investigator with substantially more control and predictability of the spatiotemporal dynamics of the biomolecule microenvironment. Also, PDMS (poly(dimethylsiloxane)) channels have revolutionized the µTAS as a cheaper option for various biomolecule analysis. Further, the extensive usage of PDMS which is a biocompatible, optically transparent polymer have provided innovation to embed microfluidic devices for in vivo clinical application. This micro/ nanotechnology has demonstrated significant advancement

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towards precise cancer diagnostics and management with a focus on miniaturization as well as high-throughput analytical devices.

2.3

Conclusion

The identification of a biomarker and selection of an efficient diagnostics analytical tool has emerged as a key component to manage cancer. The chapter briefly explains the overview of cancer biomarkers and over the time development in diagnostics system. We believe that understanding of new frontier in cancer biomarker analysis is a significant step forward in understanding cancer genesis and metastasis. The aspects of each concept covered in this chapter are elaborated in other chapters of this book.

Acknowledgment Authors acknowledge respective departments and institutions for providing support and facilities.

Conflict of interest Authors have no conflict of interest.

References [1] C.E. Meacham, S.J. Morrison, Tumour heterogeneity and cancer cell plasticity, Nature 501 (2013) 328 337. [2] J. Shi, P.W. Kantoff, R. Wooster, O.C. Farokhzad, Cancer nanomedicine: progress, challenges and opportunities, Nat. Rev. Cancer 17 (2017) 20. [3] P.M. Kosaka, et al., Detection of cancer biomarkers in serum using a hybrid mechanical and optoplasmonic nanosensor, Nat. Nano 9 (2014) 1047 1053. [4] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2017, CA: Cancer J. Clin. 67 (2017) 7 30. [5] L. Wu, X. Qu, Cancer biomarker detection: recent achievements and challenges, Chem. Soc. Rev. 44 (2015) 2963 2997. [6] K.R. Khondakar, S. Dey, A. Wuethrich, A.A.I. Sina, M. Trau, Toward personalized cancer treatment: from diagnostics to therapy monitoring in miniaturized electrohydrodynamic systems, Acc. Chem. Res. 52 (2019) 2113 2123. [7] I. Dagogo-Jack, A.T. Shaw, Tumour heterogeneity and resistance to cancer therapies, Nat. Rev. Clin. Oncol. 15 (2018) 81. [8] K.K. Reza, et al., Parallel profiling of cancer cells and proteins using a graphene oxide functionalized ac-EHD SERS immunoassay, Nanoscale 10 (2018) 18482 18491.

Chapter 2 Exploring biomarkers and diagnostics system for cancer management

[9] K.M. Koo, S. Dey, M. Trau, Amplification-free multi-RNA-type profiling for cancer risk stratification via alternating current electrohydrodynamic nanomixing, Small 14 (2018) 1704025. [10] C.M. Platnich, F.J. Rizzuto, G. Cosa, H.F. Sleiman, Single-molecule methods in structural DNA nanotechnology, Chem. Soc. Rev. 49 (2020) 4220 4233. [11] M. Shipitsin, et al., Molecular definition of breast tumor heterogeneity, Cancer Cell 11 (2007) 259 273. [12] C. Sotiriou, L. Pusztai, Gene-expression signatures in breast cancer, N. Engl. J. Med. 360 (2009) 790 800. [13] M. Qian, D.C. Wang, H. Chen, Y. Cheng, Detection of single cell heterogeneity in cancer, Semin. Cell Dev. Biol. 64 (2017) 143 149. [14] M.E. Warkiani, et al., Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics, Nat. Protoc. 11 (2016) 134 148. [15] J.I. Hare, et al., Challenges and strategies in anti-cancer nanomedicine development: an industry perspective, Adv. Drug Delivery Rev. 108 (2017) 25 38. [16] Z. Darzynkiewicz, et al., Features of apoptotic cells measured by flow cytometry, Cytometry 13 (1992) 795 808. [17] M.M. Billingsley, R.S. Riley, E.S. Day, Antibody-nanoparticle conjugates to enhance the sensitivity of ELISA-based detection methods, PLoS One 12 (2017) e0177592. [18] Z. Tang, Z. Ma, Multiple functional strategies for amplifying sensitivity of amperometric immunoassay for tumor markers: a review, Biosens. Bioelectron. 98 (2017) 100 112. [19] S. Gholizadeh, et al., Microfluidic approaches for isolation, detection, and characterization of extracellular vesicles: current status and future directions, Biosens. Bioelectron. 91 (2017) 588 605. [20] K.K. Reza, et al., A SERS microfluidic platform for targeting multiple soluble immune checkpoints, Biosens. Bioelectron. 126 (2019) 178 186. [21] K. Kamil Reza, et al., Electrohydrodynamic-induced SERS immunoassay for extensive multiplexed biomarker sensing, Small 13 (2017) 1602902. [22] J.M. Jackson, M.A. Witek, J.W. Kamande, S.A. Soper, Materials and microfluidics: enabling the efficient isolation and analysis of circulating tumour cells, Chem. Soc. Rev. 46 (2017) 4245 4280. [23] A. Wuethrich, et al., Interfacial nano-mixing in a miniaturised platform enables signal enhancement and in situ detection of cancer biomarkers, Nanoscale 10 (2018) 10884 10890.

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Electrochemical detection: Cyclic voltammetry/differential pulse voltammetry/impedance spectroscopy

3

Saurabh Kumar1 and Ashish Kalkal2 1

Centre for Nano Science and Engineering (CeNSE), Indian Institute of Science, Bengaluru, India 2Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, India

3.1

Introduction

In this chapter, we study about electrochemical techniques in which current, potential or charge generates at interface of electrode and electrolyte serve as an electrochemical signal. This signal generates due to chemical reaction occur in a cell called electrochemical cell that contains electrodes and electrolyte. International Union of Pure and Applied Chemistry have prepared recommendation on electrochemical based biosensors. According to recommendation “An electrochemical biosensor is a self-contained integrated device, that is capable of providing specific quantitative or semi-quantitative analytical information using a biological recognition element (biochemical receptor) which is kept in direct spatial contact with an electrochemical transduction element” [1,2]. The three electrode based electrochemical cell setup is most common setup in electrochemical biosensor. These three electrode are working electrode (WE), reference electrode (RE), and a counter (or auxiliary) electrode (CE). The WE works as a transduction element, which convert chemical signal in form of electrical signal, that are measured by electrochemical setup consist of potentiostat (Fig. 3.1). Usually ITO/gold coated glass or glassy carbon or platinum electrodes are used as working electrodes. The RE has a stable and known electrode potential; therefore, it is used as a reference for potential measurement/control in electrochemical cell. The most common RE is Ag/AgCl electrode. The counter electrode with Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00008-1 © 2021 Elsevier Inc. All rights reserved.

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Figure 3.1 Assembly of different electrode in electrochemical measurements.

WE provide a circuit over which current is applied or measured and usually made of inert materials such as pt, Au, graphite, glassy carbon, etc. [3]. The detection of clinical biomarkers is known to play a crucial role in the early detection of a cancer, design of individual therapies, and to identify underlying processes involved in the disease [4]. These biomarkers are chemical substances related with the elevation of malignant tumors which are found in blood, urine, or body tissues [5]. They are normally produced directly by the embryonic tissue or tumor tissue. These markers indicate changes in the expression of a protein that is correlated to risk or progression of a disease or its response to treatment, and that can be measured in tissues or in the blood [6]. An ideal cancer biomarker should have high clinical sensitivity and specificity, quick release in the blood enabling early diagnosis, capability to remain elevated for longer time in the blood, and ability to be assayed quantitatively [7]. The various biomarkers are currently being used for management for cancer according to the National Academy of Clinical Biochemistry (NACB) recommendation [8]. Carcinoembryonic antigen (CEA) biomarker used primarily for monitoring, prognosis and recurrence prediction of colon cancer. Estrogen, progesterone, and HER2 biomarkers are mainly associated with breast cancer. This cancer

Chapter 3 Electrochemical detection

biomarker has a major role in deciding therapy. Estrogen and progesterone positive patient go for endocrine therapy, whereas HER2 positive patient recommended for trastuzumab therapy. In case of testicular cancer, human chorionic gonadotropin-β (HCG-β) biomarker used for diagnosis, staging, recurrence and monitoring therapy. Neuron-specific enolase (NSE) is a sensitive specific and reliable serum biomarker primarily useful for predicting the earlier response to therapy and early diagnosis of small cell lung cancer (SCLC) [9,10]. In the same way CA125 biomarker used for detection of ovarian cancer and it is also used for detecting recurrence and monitoring after pre and post-therapy. Calcitonin, use for diagnosis and monitoring of medullary thyroid carcinoma whereas thyroglobulin used for monitoring of thyroid cancer. Similarly, prostate specific antigen (PSA) is being used for screening and diagnosis of prostate cancer [11]. CYFRA-21-1, a salivary biomarker is useful for the early stage detection of oral cancer due to its specific cut off value and higher secretion [12–14]. In case of germ-cell hepatoma, alfa-fetoprotein biomarker test is recommended for diagnosis, staging, detecting recurrence and monitoring. There are many techniques for cancer biomarker detection such as immunohistopathology [15], radioimmunoassay [16], enzyme-linked immune sorbent assay (ELISA) [17], reverse transcriptase polymerase chain reaction (RT-PCR) [18], positron emission tomography [19] has been developed. These techniques are time-consuming, expensive, require highly skilled personnel and necessitate exposure to harmful radiations [20]. For the last two decades, simpler and faster analytical procedures based on electrochemical methods have been developed that has potential to solve these problems. This method has great potential in detection of cancer biomarkers at early stages. They allow multitarget analyses, high sensitivity, specificity, lower detection limits, portability, low-cost, and fast response time. It works with very small volume of sample and development of disposable devices could be possible. These devices can be miniaturized to handheld size that has potential to be used for regular monitoring at home [21,22]. These electrochemical biosensors measure the change in the electrochemical signal (current/charge/potential, etc.) due to interaction with biorecognition molecule/bioreceptor and analytes. Fig. 3.2 shows the block diagram of electrochemical biosensor (Inset). There are mainly two component of electrochemical biosensor: Biological and Physical. The biological component is basically bioreceptor which are very specific to individual analytes/marker. Bioreceptor could be enzymes, nucleic acid (DNA, RNA), aptamers, antibodies/antigen, bacteria, etc. It interacts with

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Figure 3.2 A general schematic of an electrochemical detection strategy. Working electrode (WE) has been modified with nanomaterials to improve the electrochemical performance. Further electrochemical signal has been measured in presence of electrolyte with different concentration of analyte.

analyte to produce some physical and chemical changes that can be detected through transducer. Next, the physical component is consisting of transducer, microprocessor (amplifier and signal processor) and display unit. A transducer is a device which converts any type of signal to an electrical signal. The signal produced as a result of interaction between bioreceptor and analyte in the form of electrochemical response is further converted to electrical signal with the help of transducer. Next, electronic signal produced by transducer is very small therefore it amplified and processed at microelectronics. These processed and interpreted

Chapter 3 Electrochemical detection

signal further displayed in suitable units. Fig. 3.2 shows a pictorial representation of electrochemical detection strategy. Here WE (glassy carbon) has been modified with nanomaterials to improve the electrochemical performance. Next, bioreceptor were immobilized on immobilization matrix and signal were measured in presence of electrolyte with different analyte concentration. Moreover in electrochemical biosensor architecture, immobilization matrix plays an important role in selection of technique, sensing performance and signal.

3.2

Matrix for immobilization of biorecognition molecule

For the fabrication of an efficient biosensing platform, immobilizing matrix plays a crucial role. A successful matrix should immobilize or integrate biomolecules at a transducer surface and efficiently maintain the functionality of the biomolecules, while providing accessibility toward the target analyte and an intimate contact with the transducer surface [23]. In this context, nanomaterials have recently aroused much interest as an immobilization matrix for biosensor. This is because nanomaterials exhibit interesting properties such as a large surfaceto-volume ratio, high surface reaction activity, high catalytic efficiency and strong adsorption ability that make them potential candidate materials to play a catalytic role for the fabrication of a biosensor [24,25]. It enhances the performance of a biosensor in terms of sensitivity, detection limit and stability. Besides this, large surface area of the nanomaterials provides a better matrix for the immobilization of biomolecules leading to its increased loading with desired orientation. Currently, nanomaterial-based biosensor have drawn considerable interest for early detection of cancer. Rusling et al. developed nanostructured electrodes composed of carbon nanotubes for detection of prostate cancer biomarker (PSA) [26]. The high sensitivity (B800 times higher) was achieved by attaching HRP-tag secondary antibody to carbon nanotube with detection limit of 4 pgmL21. Kumar et al. fabricated electrochemical biosensor for oral cancer biomarker (CYFRA-21-1) detection using nanostructured zirconia (ZrO2) platform [27]. The ZrO2 modified electrode shows linear detection range of 2–16 ngmL21 with stability up to six weeks. ZrO2 has been known for biocompatibility, excellent electrical and surface charge properties. The oxygen moieties in ZrO2 have been used for functionalization with silane to

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anchor the bioreceptor. But it has been also reported that zirconia nanoparticles tend to aggregate and form large clusters which affect the sensor performance. Therefore to overcome this problem, metal oxide nanoparticles grown on 2D sheets of reduce graphene surface oxide (RGO) to prevent the agglomeration as well as taken the advantage of excellent electrochemical properties [28]. In this context, zirconia decorate reduced graphene oxide based biosensor show a linear detection range of 2–22 ngmL21 and stability of up to eight weeks for CYFRA-21-1. Similarly, nanostructured hafnium oxide integrated RGO (nHfO2@RGO) sheets were synthesized. These kinds of hybrid structure prevent agglomeration of metal oxide and subsequently improve the sensing characteristics. In earlier study, It has been known that the Brownian motion of nanostructured metal oxide in solution result in agglomeration. Moreover, the reduced agglomeration was obtained by inhibiting Brownian motion by providing additional surface, in this case RGO use as a supporting matrix, resulting in improve biosensing parameters [29]. This nanohybrid based platform exhibit improve biosensing parameters including wider linear detection range (0–30 ngmL21), and higher sensitivity (18.24 A mLng21). Emami et al. covalently bound HER2 antibody with iron oxide nanoparticle and resulting bioconjugate were immobilized over cysteamine modified gold electrode for detection of breast cancer biomarker, HER2 [30]. The fabricated nanostructure modified bioconjugate not only facilitate electron-transfer in redox probe but also improve the sensitivity by increase loading of antibodies. Norouzi et al. used gold and ZnO nanoparticles as an immobilization matrix for detection of carcinoembryonic antigen, a cancer biomarker released in colon, rectal, breast, ovary and lung cancer [31]. The fabricated electrochemical biosensor shows wide detection range (0.1–70 ngmL21 and 70–200 ngmL21) with detection limit of 0.01 ngmL21 and fast response time (less than 20 s). Ali et al. fabricated label-free, high sensitive (7.76 kΩ μM21) and wide detection range (1.0 fM-0.5 M) impedometric biosensor to detect breast cancer biomarker (ErbB2) using ZnO nanofibers as an immobilization matrix [32]. The mesoporous structure of ZnO nanofibers provide numerous and favorable absorption sites for immobilization of bioreceptor and promote higher electron mobility, that provide an excellent conduction path between protein and electrodes that enhance charge transfer properties resulting in a higher sensitivity of the biodevices. Veisi et al. reported an electrospun polyaniline nanofiber modified interdigitated microelectrode for detection of cancer biomarker (COX-2) [33]. The high surface area of electrospun nanofiber improved the characteristics of biosensor.

Chapter 3 Electrochemical detection

It is clear from the above report that nanomaterial could enhance the biosensor characteristics such as sensitivity, linear detection range, detection limit, fast response time and stability. Additionally, there are various procedure and protocol with wide variety of matrices like gold nanoparticles, nanostructured polymers, dendrimers, nanostructured metal oxide, carbon nanotubes, reduced graphene oxide; Ti3C2 MXene, etc., have been used for immobilization of the bireceptors for fabrication of efficient electrochemical biosensor. Device design and integration of different transducing principle play an important role. In this context, Wang et al. demonstrated a novel electrically magnetic-controllable gold electrode based electrochemical biosensor for micro-RNA detection in saliva samples of oral cancer patients. The fabricated electrode provides the advantages of both magnetic and heated electrode, thereby regulating the direction and strength of magnetic field. The utilization of gold electrode and magnetic beads-based enzymatic catalysis amplification, allow the biosensor for ultrasensitive detection of mi-RNA with a recovery of 93%
108% and low detection limit of 0.22 aM. The easiness of electrode fabrication, reusability and good stability made this biosensor a promising alternative for the early diagnosis of oral cancer [34]. Recently, the analysis of DNA methylation based cancer biomarkers has obtained tremendous attention as a hallmark of early stage cancer detection. Traditionally, a number of different techniques, such as enzymatic treatment [35], bisulfite modification [36], and affinity enrichment [37] are being used for detecting DNA methylation. These methods are of good diagnostic value however possess a number of limitations including degradation of DNA due to the long incubation, expensive instrumentation and data analysis, the laborious and time-consuming procedure, and requirement of trained professionals [38]. Over the last decade, different point-of-care (POC) biosensing platforms based on optical [39], electrical [40], microfluidic [41], and electrochemical techniques [42] have been developed as a better alternatives to conventional methods. Chen et al. reported Au nanoparticlecoated gold electrode based highly sensitive electrochemical biosensor for detection of DNA Methylation (Fig. 3.3). The stem– loop–tetrahedron composite DNA probes were anchored at the coated gold electrode. The detection principle was based on hybridization chain reaction followed by horseradish peroxidase (HRP) enzymatic catalysis. The fabricated biosensor exhibited ideal specificity, stability, repeatability, and wider linear detection range from 1 aM to 1 pM with a detection limit of about 0.93 aM [43]. Similarly, Huang et al. reported graphene oxide coupled with

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Figure 3.3 Pictorial representation of the electrochemical biosensor indicating multiple signal amplification for the detection of DNA Methylation. Source: Copyright 2019, ACS.

anti-5-methylcytosine antibody based electrochemical biosensor for the identification of DNA methylation sites and the detection of DNA methylation level. The electrochemical reduction signals were generated through the oxidation of hydroquinone into benzoquinone in a solution containing HRP-labeled IgG secondary antibody, H2O2 and hydroquinone. The electrochemical signal was directly proportional to number of 5-methylcytosine, thereby quantifying the methylation level. On the other hand the steric hindrance differences from
CH3 hydrophobic sphere to electrode surface results in the decrease of peak current with reducing distance from the electrode surface. The measurement of corresponding peak current responses provided the identification of DNA methylation sites. The proposed method revealed high specificity, stability, repeatability, and wider linear detection range from 10215 to 1028 M with a detection limit of about 1 fM [44].

Chapter 3 Electrochemical detection

3.3

Electrochemical transducers for cancer biomarker detection

As we discuss earlier, electrode is worked as a transduction element in electrochemical sensor. Therefore the electrochemical reaction happen at electrode surface is measured in terms of electrical signal. The most explore electrochemical technique use to detect cancer biomarkers is cyclic voltammetry (CV), differential pulse voltammetry (DPV), electrochemical impedance techniques (EIS).

3.3.1

Cyclic voltammetry based biosensor for cancer detection

In a CV, we measure the electrochemical current with respect to applied potential at working electrode and the working potential is swept at particular sweep rate (or scan rate in volt per second). As we discuss earlier, the potential is measured between working and RE whereas current is measured between working and counter electrode. The electrochemical current is plotted in x-axis and WE potential at y-axis. During measurements, as the WE potential reaches to set potential (on given value) it reverse back to its initial potential. This is the reason we called it CV. We may repeat this cyclic experiment much time as our need. Thus CV is performed by cycling the potential of WE and measuring the resulting electrochemical current generate during oxidation and reduction process of redox species. During redox reaction the electron are transferred from analyte to the WE or from electrodes to analyte [45]. It is used to study the electrochemical properties of analyte in solution or of a material that is coated/filmed onto the electrode surface Using CV technique, kumar et al. detected oral cancer biomarker (CYFRA) using nanostructured zirconia (nZrO2) as a transducer surface [46]. The amine functionalized nZrO2 deposited onto ITO electrode (WE) were used for covalent immobilization of the receptor antibody (anti-CYFRA). In this work, phosphate buffer worked as a electrolyte containing ferro/ferricyanide ([Fe(CN)6]32/42) as a redox probe. During electrochemical response study, the magnitude of the electrochemical current change and found to be directly propotional with CYFRA concentration in range of 2–16 ngmL21 with a sensitivity of 2.2 mA mLng21. This is due to formation of an antigen–antibody complex on the surface of the WE which accelerate/diminished (depend on charges/orientation of bio-complex on WE) the charge transfer via the redox probe, leading to a change in

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the electrochemical current. Wang et al. detected prostate cancer biomarker PSA using glassy carbon electrode (WE) modified with silver hybridized mesoporous silica nanoparticles (Ag@MSNs) [47]. The mesoporous silica nanoparticles were used to enhance the physical adsorption of bioreceptor (anti-PSA) and silver nanoparticle were used to improve the electron-transfer rates. Although working principle is similar to CYFRA detection as discuss earlier but here hydroquinone is used as a redox probe. The fabricated electrochemical sensor detected PSA over a wide concentration range from 0.05 to 50.0 ngmL21 with a detection limit of 15 pgmL21. Similarly in a recent report, kumar et al. detected CEA biomarker using two-dimensional Ti3C2-MXene nanosheets with a wide detection range of 0.0001–2000 ng mL21 [48]. The response of different redox probe on the electrochemical behavior of functionalized Ti3C2-MXene was investigated and found that hexaammineruthenium [Ru(NH3)6]31 was the preferable redox probe for bio-sensing (Fig. 3.4A). This work was also based on similar principle i.e. formation of immune complex on the surface of the WE which diminished the charge transfer via the redox probe; resulted in decrease of electrochemical current. MUC1 is a protein which is responsible for tumor genesis of several cancer types such as breast and ovarian cancer. Taleat et al. detected MUC1 protein by sandwich approach where MUC1 was conjugated between MUC1 monoclonal antibody (which was immobilized onto poly-aminobenzoic acid modified graphite screen printed electrode) and methylene blue modified aptamer (a kind of specific ss-DNA) [50]. Methylene blue is an electrochemical indicator that directly binds to the G base of aptamers. A CV based study was performed to detect MUC1 protein concentration. With an increasing MUC1 protein concentration, more aptamers bound and similarly, more magnetic bead (MB) probes accumulated on the electrode surface. Thus, we obtained large MB redox peak as the concentration increases. A linear detection range of 3–10 ppb with a detection limit of 2.4 ppb was obtained. This work simplifies the labeling procedure which is usually used for tagging of detection antibody. Here, MB interacted directly with aptamers making this approach simple, cost-effective and avoid external modification steps. In another sandwich approach, Feng et al. claimed simultaneous detection of AFP and CEA by tagging of detection antibody with dissimilar graphene-polymer nanotag: rGO-H/Pt-PV and rGO-PLL/RuSi@Au respectively (Fig. 3.4B) [49]. In this work CV and electrochemiluminescence (ECL) technique was coupled. The rGO-H/ Pt-PV was used as a CV nanotags while rGO-PLL/Ru-Si@Au for ECL. The CV nanotag produced a cathodic current at 0.3 V and

Chapter 3 Electrochemical detection

53

(A) 60

Current (µA)

40

GC

20 0 -20 -40 -60 -0.8

-0.6

-0.4

-0.2

0.0

0.2

Potential (V)

(B)

Figure 3.4 (A) Schematic of the electrochemical CEA detection mechanism using hexaammineruthenium [Ru(NH3)6]31 as redox probe and bioreceptor were covalent immobilized over Ti3C2-MXene modified glassy carbon (GC) electrode. [48] (B) Schematic illustration of stepwise immunosensor fabrication process and the signal generation mechanism by labeling of detection antibody with dissimilar graphene-polymer nanotag (rGO-H/Pt-PV and rGO-PLL/Ru-Si@Au respectively) [49]. Source: Reproduced with permission from Kumar, S.; Lei, Y.; Alshareef, N.H.; Quevedo-Lopez, M.; Salama, K.N., Biofunctionalized two-dimensional Ti3C2 MXenes for ultrasensitive detection of cancer biomarker. Biosens. Bioelectron. 2018, 121, 243– 249. Copyright 2018, Elsevier. This is label-free technique and change in CV current mainly depends on extent of charge transfer via the redox probe at electrode and electrolyte interface. Reproduced with permission from Feng, X.; Gan, N.; Zhang, H.; Yan, Q.; Li, T.; Cao, Y.; et al., A novel strategy for multiplexed immunoassay of tumor markers based on electrochemiluminescence coupled with cyclic voltammetry using graphene-polymer nanotags. Electrochim. Acta 2015, 170, 292
299. Copyright 2015, Elsevier. Here nanotags were used to amplify the CV current and to generate the ECL signal in a single platform to detect CEA and AFP respectively.

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the ECL nanotags emitted an anode luminescent signal at 1.25 V, which were respectively used for CEA and AFP detections. Apart from detection of various analyte concentration CV could also be used to calculate various other parameters such as diffusion coefficient, redox potential for the analyte, surface concentration of immobilized biomolecule and can be coupled easily with other techniques.

3.3.2

Differential pulse voltammetry based biosensor for cancer detection

DPV is one of the most widely used electrochemical techniques due to their high sensitivity and rapidness. In this technique, a series of electrochemical pulse of fixed amplitude (10–100 mV) is superimposed onto a slowly changing base potential and the resulting current difference is measured and plotted against the base potential. The obtained peak current is used to measure the concentration of an analyte. Using DPV technique, various approach has been explore to detect early cancer and to study the performance of drug related to cancer. Lin et al. fabricated a reusable biosensor based on magnetic graphene oxide modified gold electrode (MGO-Au) to detect vascular endothelial growth factor (VEGF) in human plasma for cancer diagnosis [51]. The fabricated DPV based sensor provided the efficient sensitivity and fast response time for clinical diagnostics and have wide linear detection range (31.25
2000 pgmL21) compared to available ELISA technique. In this work, Avastin (VEGF antibody fragment) was conjugated onto the surface of MGO/Au and electrochemical response current was measured with increasing concentration of VEGF. Amjadi et al. used DPV technique to study the impact of doxorubicin (DOX) and Flavonoid modified drug (FMD) on lung cancer cells (A549) [52]. The DPV study revealed that chemotherapy drug FMD has better effect to treat cancer cell compare to DOX. For this, A549 cancer cell line was immobilized on glassycarbon electrode and DPV exhibited that increasing the drug concentration induces the decrease in electrochemical response. In another works by Pacheco et al. and Wang et al. modified WE with breast cancer cell and use electrochemical methods (CV, DPV) to determine the number of cancer cells in the unknown sample using calibration curve of known cancer cells [53,54]. Epidermal growth factor receptor (EGFR) is a cancer biomarker and it is overexpression is associated with breast, head/neck, ovarian, and colorectal cancers. Ilkhani et al. detected EGFR via aptamer/antibody (Apt/Ab) based sandwich approach using DPV

Chapter 3 Electrochemical detection

55

technique [55]. In this study, magnetic bead (MB) modified aptamer was served as a capture probe while gold conjugated antiEGFR used as a signaling probe (Fig. 3.5). In presence of EGFR, an aptamer/EGFR/anti-EGFR complex was formed on the MB surface and this complexation was evaluated by measuring the DPV current of gold nanoparticles (associated with anti-EGFR). The fabricated sensor shows dynamic linear detection range from 1 to 40 ngmL21 with detection limit of 50 pgmL21. The proposed sensor shows high sensitivity and fast separation of complex molecules (aptamer/EGFR/anti-EGFR) that leads to high specificity. In electrochemical measurement electrode fabrication and modification play a major role. In this context, screen printing technology is extensively used for the fabrication of portable lowcost electronics, specifically for fabricating disposable electrodes. This technique has various advantages over other traditional

Figure 3.5 Schematic representation of the aptamer/antibody sandwich assay of epidermal growth factor receptor (EGFR) [55]. Source: Reproduced with permission from Ilkhani, H.; Sarparast, M.; Noori, A.; Bathaie, S.Z.; Mousavi, M.F., Electrochemical aptamer/antibody based sandwich immunosensor for the detection of EGFR, a cancer biomarker, using gold nanoparticles as a signaling probe. Biosens. Bioelectron. 2015, 74, 491
497. Copyright 2015, Elsevier.

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electrode fabrication techniques including precise control over electrode dimensions, versatility in electrode design, miniaturization of the device, reducing the manufacturing costs, easy-to-use and array of electrode fabrication is possible [44,56]. In addition, screen printed electrodes provide customization of the electrode surface by further modifying with various nanomaterials thereby increasing the surface area, biomolecule immobilization efficiency and introducing interesting electrochemical properties [57]. Zani et al. reported sensitive and simple scheme for PSA detection by using eight disposable screen printed microelectrode arrays as the transducer surface. In this labeled assay, magnetic beads were used to capture the primary PSA antibody. The captured beads were bathed with antibody labeled enzyme alkaline phosphatase (AP) and the electrochemical measurements were recorded using DPV. This biosensor exhibited linear detection range (0–20 ngmL21) with a lower detection limit of 1.4 ngmL21 [58]. Similarly, Erdem et al. reported multichannel screen-printed array of electrodes (MUX-SPE16) based electrochemical biosensor for measuring the nucleic acid hybridization of different miRNA sequences (miRNA-16, miRNA-15a and miRNA-660). In this work, streptavidin coated magnetic beads were deposited onto the electrode surface followed by the immobilization of biotinylated inosine substituted DNA probe. After the hybridization process, the electrochemical response was recorded by measuring the guanine oxidation signal utilizing DPV technique. The usage of MUX-SPE16 system as the transducer surface provided various advantages such as portability, cost-effectiveness, higher sensitivity, easy-to-use and faster detection. The consecutive 16 analysis requiring 3 L sample per measurement were performed in 15 min. Additionally, compared to the detection limit of disposable pencil graphite electrode (PGE) (230 pmole in 110 L sample), the MUX-SPE16 system provided 53 times lower detection limit (4.3 pmole in 3 L sample) [59]. Additionally, measurement or tracking of single biomarker is not sufficient for accurate detection of cancer due to low sensitivity and specificity of particular biomarker. Moreover single tumor marker detection has been often criticized for the high rate of false positives and negatives [60,61]. In this context, simultaneous detection of multiple tumor markers has obtained extensive attraction amid the researchers as it provides the more accurate and reliable results. The specificity and sensitivity of Serum VEGF-C was 68% and 85% respectively, while MMP-9 was having 75% specificity and 63% sensitivity. Similarly, VEGF was having a specificity of 59% and sensitivity of 80% and however, the combination of these three markers provided higher sensitivity and

Chapter 3 Electrochemical detection

specificity (83% and 76%) than single biomarker approach [60]. Also it has been reported that CEA when used with other biomarkers, the prediction of the disease improves. For example, the sensitivity of CEA increases from 89% to 96% in combination with CA 15-3 [62]. Therefore it can be anticipated that multiplexed marker detection approach could be a superior diagnostic tool for the reliable and accurate cancer detection in clinical applications. Multianalyte detection can provide rapid, highly accurate, sensitive and cost-effective point-of-care diagnosis. Many efforts have been made for the simultaneous detection of multiple cancer biomarker. Wu et al. reported disposable two-throughput immunoelectrode array for the simultaneous detection of CA 19-9 and CA 125 cancer biomarker. The graphite working electrodes (W1 and W2) of a screen-printed chip were modified with cellulose acetate membrane followed by co-immobilization of thionine/CA 19-9 and thionine/CA 125 respectively. Both WI and W2 shared the same graphite counter electrode and Ag/AgCl RE. Thereafter, corresponding HRP labeled antibodies were captured on the working electrodes. The electrochemical signals were generated by the electron shuttling between HRP and the electrodes by the immobilized thionine for the enzymatic reduction of H2O2 by HRP. The immunosensor exhibited linear detection in the ranges of 0 to 24 U/ml and 0 to 25 U/ml for CA19-9 and CA125 with a LOD of 0.2 and 0.4 U/ml, respectively [63]. In another study, Wu et al. demonstrated reduced graphene oxide-tetraethylene pentamine (rGO-TEPA) and Au@mesoporous carbon CMK-3 based highly sensitive immunobiosensor for the simultaneous detection of cervical cancer biomarkers (carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCCA). Specific primary and secondary antibodies were conjugated to rGO-TEPA and Au@mesoporous carbon CMK-3 respectively through the EDCNHS coupling chemistry. Thionine and neutral red were used as labels to provide the well-separated detection peaks. The electrochemical response of the fabricated immunosensor revealed good stability and reproducibility, low detection limit (0.013 ngmL21 and 0.010 ngmL21), and wider linear detection range (0.05 to 20 ngmL21 and 0.03 to 20 ngmL21) for CEA and SCCA, respectively [64]. Further, Chang et al. reported functionalized metal
organic frameworks (MOFs) based enzyme free and label free homogeneous electrochemical biosensor for the simultaneous detection of miRNA-21and let-7a (Fig. 3.6A). These promising tumor biomarkers belong to miRNAs family and known to play a crucial role in the early cancer detection and design of individual therapies. The UIO-66-NH2 MOF was immobilized with target miRNAs carboxylated ss-DNA (Cx) through

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Figure 3.6 (A) Fabrication procedure for the nucleic acid-functionalized metal–organic frameworks (MOFs) and (B) Pictorial representation indicating the principle of the fabricated electrochemical biosensor for the detection of multiple miRNAs. Source: Copyright 2019, ACS.

the standard EDC-NHS coupling chemistry, followed by the conjugation with MB and TMB electroactive dyes to provide the functionalized MOFs i.e. MB@UIO and TMB@UIO respectively. Thereafter, the functionalized MOFs were capped with another completely complementary ss-DNA (Px) to provide dsDNAcapped MOFs. The electrochemical signals were based on the release of the entrapped electroactive dyes. The addition of target analyte provides the formation of RNA
DNA complex via the toehold-mediated strand-displacement reaction, resulting in the release of the entrapped dyes (Fig. 3.6B). The strong electrochemical signal related to the released dyes were recorded by the DPV. The results of electrochemical biosensor revealed high sensitivity and good selectivity. The limit of detection were obtained to be

Chapter 3 Electrochemical detection

8.2 fM for mi-RNA-21 and 3.6 fM for let-7a. The fabricated biosensor also exhibited high accuracy and reliability for the simultaneous determination of let-7a and mi-RNA-21 in human serum samples [65]. In another approach, two different cancer biomarkers (CEA and AFP) has been detected simultaneously via DPV technique using metal ions tagged immunocolloidal gold nanocomposite as signal tag [66]. In this method, signal antibody were modified with two different metal ions (AuNPs/anti-CEA/Cu21 and AuNPs/anti-AFP/Pb21). As we know, Cu21 and Pb21 metal ions give different voltametric peaks that have direct relationship with different concentration of CEA and AFP. Therefore, in this work, author used inherent electrochemical properties of metal ions for multiplexed detection of cancer biomarker on a single platform with excellent sensitivity. The results were also validated with standard ELISA, which showed potential for clinical applications. Recently, circulating tumor markers (CTMs), which include various blood circulating biomolecules such as extracellular vesicles (exosomes), circulating tumor cells (CTC), and circulating nucleic acids have evolved as an important biomarkers for quantitative real-time assessment and early diagnosis of cancer [67]. The concentrations of these CTMs have been proposed as a low-cost, highly reproducible, dynamic and non-invasive diagnostic tool for the early stage cancer detection and progression. Many efforts have been made for the detection of CTMs, including quartz crystal measurement (QCM), microcantilevers, colorimetric, enzyme-linked immunosorbent assay (ELISA) assay, surface enhanced Raman scattering (SERS), surface plasmon resonance, polymerase chain reaction (PCR), and electrochemical. Moscovici et al. fabricated a novel microfabricated glass chip with exposed gold apertures based cell counting device by recording the electrochemical signal with the increasing number of cells utilizing DPV. The developed biosensor can explicitly count 125 prostate cancer cells within 15 min in both mixed cell population containing nontarget cells and complex media having serum [68]. Yang et al. demonstrated nanostructured palladium (B500 nm) electrodeposited microelectrodes based electrochemical biosensor for micro-RNA detection. The deposited chip was modified with PNA probes and then exposed to total RNA for hybridization. The electrochemical reduction current of RuIII/FeIII redox system was recorded using DPV technique. After hybridization with the target mi-RNA, RuIII was found to accumulate on the electrode surface. The signals obtained with RuIII were amplified by the inclusion of FeIII

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that chemically regenerate RuIII after its electrochemical reduction. The detection of as low as 10 aM of target was reported with a 30 min hybridization time [69]. Similarly, Han et al. reported an electrochemical biosensor based on ssDNA probe decorated DNA origami nanostructure for the label-free detection of miRNA using methylene blue (MB) as the hybridization redox indicator (Fig. 3.7). The DNA nanostructures were immobilized with the chitosan modified gold electrode via the physical absorption of DNA origami by the chitosan film instead of covalent immobilization, via thiol
Au interactions. The electrochemical response studies of the fabricated biosensor recorded through the DPV technique exhibited a wide linear detection range from 0.1 pM to 10.0 nM, with a lower detection limit of 79.8 fM. Moreover, the biosensor was found to be effective to distinguish single base mismatched sequences from target mi-RNA-21 [70]. Yadav et al. demonstrated inexpensive and simple electrochemical immunosensor for the detection of

Figure 3.7 Representation of an electrochemical biosensor based on DNA origami for mi-RNA detection. Source: Copyright 2019, ACS.

Chapter 3 Electrochemical detection

disease specific exosomes from cell culture media. Firstly the bulk exosomes were captured using the tetraspanin biomarker (CD9) antibody and then the detection was performed through the human epidermal growth factor receptor -2 (HER-2) specific cancer antibody. It was observed that the addition of exosomes to the electrode surface block the electron transfer of [Fe(CN) 6]42/32 redox system, and the decrease in electrochemical signal was measured utilizing DPV technique [71]. DPV has also been widely used by researcher for the label-free detection and screening of anti-cancerous drugs. Zhang et al. reported stacked graphene nanofibers (SGNF) and gold nanoparticles (AuNPs) nanocomposite based electrochemical biosensor for the determination of the anticancer drug capecitabine. The electrochemical reduction of capecitabine on the fabricated AuNPs/SGNF-modified GCE electrode was measured using the DPV. The fabricated biosensor revealed a wider linear detection range ranging from 0.05 to 80.00 M, with a remarkable limit of detection of 0.017 M [72]. Similarly, Venu et al. reported a ZrO2/ rGO nanocomposite based electrochemical biosensor for the detection of an anticancer drug (regorafenib, REG). The fabricated biosensor exhibited a wider linear detection range ranging from 11 to 343 nM, with a remarkable limit of quantifications and lower detection limit of 59 and 17 nM, respectively. The efficacy of the biosensor was also satisfactory in both serum samples and pharmaceutical formulations for the accurate determination of REG. Moreover, the biosensor was useful for the simultaneous detection of REG, uric acid and ascorbic acid [73].

3.3.3

Electrochemical impedance based biosensor for cancer detection

Electrochemical impedance spectroscopy (EIS) is an effective tool to measure the impeded flow of ions through solution, interface and coatings, for studying interfacial properties of the surface-modified electrodes. The EIS technique is commonly applied for the investigations of electrode kinetics, adsorption behavior and interaction of biomolecule with the electrode surface. Electrochemical impedance is usually measured by applying an AC potential (sinusoidal alternating voltage) of different frequencies to an electrochemical cell and measuring the current through the cell. The resulting current signal lags the voltage by a phase of ϕ. The time dependent signal Z(t) is converted into a frequency dependent signal Z(ω) by a Laplace

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transformation, whereby the impedance becomes a complex number and can be calculated as follows (Eq. 3.1) [74] Z ðωÞ 5 E=I 5 E0 cosðωtÞ=I0 cos ðωt 1 ϕÞ 5 Z0 exp ðiϕÞ 5 Z0 ðcos ϕ 1 i sin ϕÞ

ð3:1Þ ω: frequency of the applied potential, ϕ: phase angle, E: alternating voltage, E0: amplitude of the alternating voltage, I: alternating current and I0: amplitude of the alternating current Z 2 5 Zim 2 1 Zreal 2

ð3:2Þ

However, Nyquist plot (Fig. 3.8) represents the real part of impedance at X-axis and imaginary part at y-axis. This Nyquist plot can be modeled by an equivalent circuit (Randles circuit) comprising of the solution resistance (RS), charge transfer resistance (Rct), Warburg impedance (ZW) and double layer capacitance (Cdl) (Fig. 3.9). Nyquist plot, (a faradic impedance spectrum) includes a semicircle region observed at higher frequency corresponding to electron- transfer limited process and is followed by a linear straight line at 45 to the real axes at lower frequencies, revealing diffusion-limited electron transfer process as shown in Fig. 3.8. The semicircle diameter of EIS spectra gives value of Rct that reveals electron-transfer kinetics of redox probe at the electrode interface. Moreover, RS and Warburg impedance (ZW ) representing bulk properties of the electrolyte solution and

Figure 3.8 Nyquist plot with depressed arc where, the polarization is due to combination of kinetic and diffusion processes [75].

Figure 3.9 The electrode-solution interface can be modeled by an equivalent circuit (Randles circuit) comprising of the solution resistance (RS), charge transfer resistance (RCT), Warburg impedance (ZW), and double layer capacitance (CDL) [76].

Chapter 3 Electrochemical detection

diffusion of applied redox probe respectively. ZW can be estimated from the Nyquist plot to describe the electrical response at electrode. It can be expressed as an intercept of the straight line having slope of 45 . An equivalent electrical circuit could also be designed for electrode (Fig. 3.9). EIS is a label-free detection method and has been widely used by researcher to detect cancer cells. Elshafey et al. fabricated a label-free impedimetric biosensor for cancer biomarker (EGFR) detection [77]. The electrochemical sensing was performed in PBS (pH 7.4) containing [Fe(CN)6]32/4 as a redox probe. Protein G and gold nanoparticles (AuNPs) modified gold electrode (WE) were used as an immobilization matrix for fabrication of efficient and highly sensitive biosensor. Further, the charge transfer resistance (obtained from Nyquist plot) was measured with different concentration of EGFR. The obtained calibration curve shows wide dynamic range of 1pgmL21 to 1 gmL21 and limit of detection was as low as 0.34 pgmL21 in PBS and 0.88 pgmL21 in human plasma. Human plasma contains some protein, glucose, electrolyte, hormones etc., which usually act as interference. Therefore in real sample studies there is small deviation in electrochemical signal were observed. In another approach, Han et al. combined phage display technology and EIS to develop a label-free cytosensor for detection of cancer cells (SW620) [78]. This approach used SW620 cell specific phage (immobilized on gold WE) for capture the human colorectal carcinoma cells (SW620) (Fig. 3.10). The Rct value increases with increasing cell concentration from 200 to 2 3 108 cells mL21 that directly reflect the binding of cell hinder the electron transfer efficiency between the redox probe and WE electrode surface. In this work, [Fe(CN)6]32/42 was used as a redox probe indicator. This method is free from complicated purification process of recognition element, shows high specificity, good inter and intra assay reproducibility. Hu et al. detected liver cancer cell via EIS technique, that are based on the interaction between carbohydrates and lectin [79]. Usually cancer development is associated with glycosylation alteration in glycoproteins and glycolipids. For this a mannose-specific lectin, (concanavalin A or con A) was immobilized on a gold disk electrode and incubated with cancer cell, Bel-7404 (a human hepatocellular carcinoma with membraneassociated glycoprotein). The binding between con A and cancer cells (Bel-7404) result into the change of charge transfer resistance. This change in Rct value is directly proportional to Bel-7404 cell concentration with the limit of detection upto 234cells/mL. This work does not require labeling of probe and con A directly targeting the cancer cell, which is more direct, simple, highly

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Figure 3.10 (A) Schematic illustration of the phage-based cytosensor for cancer cells (SW620). (B) EIS responses of fabricated cytosensors after immunological recognition with different concentrations of SW620 cells: (a) 0, (b) 2.0 3 102, (c) 2.0 3 103, (d) 2.0 3 104, (e) 2.0 3 105, (f) 2.0 3 106, (g) 2.0 3 107, and (h) 2.0 3 108 cells/mL. (C) The calibration curve for SW620 cells: the Rct as a function of the logarithm values of SW620 cell concentration. (3-mercaptopropionic acid (MPA) is a self assembled monolayer and 1-ethyl-3-(3dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) is a linker which helps to immobilized phage) [78]. Source: Image adopted from Han, L.; Liu, P.; Petrenko, V.A.; Liu, A., A label-free electrochemical impedance cytosensor based on specific peptide-fused phage selected from landscape phage library. Sci. Rep. 2016, 6, 22199.

selective and sensitive approach. Further, Azzouzi et al. demonstrated gold nanoparticles (AuNPs) conjugated with biotinylated DNA/LNA molecular beacon (MB) probe based impedimetric electrochemical biosensor for micro-RNA-21 detection in spiked serum samples. The biosensor combined the dual-function biotin-MB-AuNPs bio-label and the neutravidin modified transducing surface for the efficient detection of miRNA21. The EIS response of the biosensor exhibited high selectively over other miRNAs (i.e., mi-RNA-205and mi-RNA-221), good reproducibility (RSD 5 3.3%) wide linear detection range from 1 to 1000 pM, with a limit of detection of 0.3 pM. The utilization of neutravidin as a recognition element on the electrode surface instead of streptavidin provides better biosensing parameters including the higher

Chapter 3 Electrochemical detection

sensitivity [80]. On the other hand Gao et al. reported a different label-free approach for the detection of circulating Mi-RNA in Serum and mi-RNA in total RNA extracted from cultured cells, based on electrochemical impedance spectroscopy technique and hybridized mi-RNA-templated deposition of poly(3,3´-dimethoxybenzidine) (PDB) film. A monolayer of charge neutral morpholino capture probe was deposited on ITO coated glass substrate. The hybridized mi-RNA strands converts the neutral surface of the biosensor to anionic. The deposition of the PDB film, was carried out by the HRP-catalyzed polymerization in the presence of H2O2. The biosensor exhibited a linear correlation between the charge transfer resistance (Rct) and the target mi-RNA concentration in the range of 5.0 fM and 2.0 pM with a lower detection limit of 2.0 fM [81].

3.4

Conclusions and outlooks

The most important steps in fabrication of a miniaturized electrochemical biosensor are efficient transducer surface or immobilization matrix. The integration of nanomaterials can significantly enhance the sensitivity and facilitate the biomolecule immobilization. We should wisely choose our materials depends on electrochemical technique and method of fabrication for better performance of biosensor. The electrochemical biosensor have great potential to detect small amount of analyte in complex sample like serum, blood and other body fluids that release in cancer patient. The different detection approach (signal amplification, tagging of biomolecule with efficient probe, etc.) enable the detection of cancer biomarker even in pico-gram range. Further, few reports on effect of different drug on cancer therapy has been reported that can help clinician to obtain quick response of drug on cancer cell and further studies. Commercialization of biosensor could be possible when biosensing platform works efficiently in real sample environment with high selectivity, sensitivity and stability. Cross reactivity of sensor with complex clinical sample leads toward inaccuracy of results. Therefore it is a challenge to work together with novel biorecognition element, materials and detection approach to commercialize the device that works efficiently for patient sample analysis. A careful device design, selection of novel nanomaterials and efficient detection strategies could be a solution for POC devices. These POC devices have potential to provide low-cost diagnostic and monitoring of cancer in remote location as well. Although the electrochemical biosensing protocols are available for cancer

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detection, but all of them are limited to single biomarker detection which is not sufficient to predict specific cancer. There is a panel of biomarkers that should be studied for specific type of cancer diagnosis. Effort should be made for high-throughput and cost-effective multiplex electrochemical based POC device for cancer diagnosis, therapy, and monitoring.

Acknowledgments Dr. Saurabh Kumar acknowledges the Department of Science and Technology, New Delhi, India, for the DST-INSPIRE Faculty Award (DST/INSPIRE/04/2017/ 002750) and Centre for Nano Science and Engineering (CeNSE) at the Indian Institute of Science (IISc), Bengaluru, for providing necessary facilities. Ashish is thankful to the Indian Institute of Technology, Roorkee, for the award of financial assistance and CeNSE, IISc., Bengaluru, for hosting him as a visiting scholar. S.K and A.K thank Microfluidics Devices & Heterogeneous System Lab, CeNSE, IISc. Bengaluru, India for their support.

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[45] B.D. Malhotra, Biosensors: Fundamentals Applications. Smithers Rapra (2017). [46] S. Kumar, S. Kumar, S. Tiwari, S. Srivastava, M. Srivastava, B.K. Yadav, et al., Biofunctionalized nanostructured zirconia for biomedical application: a smart approach for oral cancer detection, Adv. Sci. 2 (8) (2015) 1500048. [47] H. Wang, Y. Zhang, H. Yu, D. Wu, H. Ma, H. Li, et al., Label-free electrochemical immunosensor for prostate-specific antigen based on silver hybridized mesoporous silica nanoparticles, Anal. Biochem. 434 (1) (2013) 123
127. [48] S. Kumar, Y. Lei, N.H. Alshareef, M. Quevedo-Lopez, K.N. Salama, Biofunctionalized two-dimensional Ti3C2 MXenes for ultrasensitive detection of cancer biomarker, Biosens. Bioelectron. 121 (2018) 243
249. [49] X. Feng, N. Gan, H. Zhang, Q. Yan, T. Li, Y. Cao, et al., A novel strategy for multiplexed immunoassay of tumor markers based on electrochemiluminescence coupled with cyclic voltammetry using graphene-polymer nanotags, Electrochim. Acta 170 (2015) 292
299. [50] Z. Taleat, C. Cristea, G. Marrazza, M. Mazloum-Ardakani, R. Sa˘ndulescu, Electrochemical immunoassay based on aptamer–protein interaction and functionalized polymer for cancer biomarker detection, J. Electroanalytical Chem. 717 (2014) 119
124. [51] C.-W. Lin, K.-C. Wei, S.-S. Liao, C.-Y. Huang, C.-L. Sun, P.-J. Wu, et al., A reusable magnetic graphene oxide-modified biosensor for vascular endothelial growth factor detection in cancer diagnosis, Biosens. Bioelectron. 67 (2015) 431
437. [52] M. Amjadi, J.M. Khoshraj, M.R. Majidi, B. Baradaran, M. de la Guardia, Evaluation Flavonoid Derivative DoxorubicEff. Lung Cancer Cell (A549) Using. Differential Pulse Voltammetry Method. (2018). [53] K. Wang, M.-Q. He, F.-H. Zhai, R.-H. He, Y.-L. Yu, A novel electrochemical biosensor based on polyadenine modified aptamer for label-free and ultrasensitive detection of human breast cancer cells, Talanta 166 (2017) 87
92. [54] J.G. Pacheco, M.S. Silva, M. Freitas, H.P. Nouws, C. Delerue-Matos, Molecularly imprinted electrochemical sensor for the point-of-care detection of a breast cancer biomarker (CA 15-3), Sens. Actuators B: Chem. 256 (2018) 905
912. [55] H. Ilkhani, M. Sarparast, A. Noori, S.Z. Bathaie, M.F. Mousavi, Electrochemical aptamer/antibody based sandwich immunosensor for the detection of EGFR, a cancer biomarker, using gold nanoparticles as a signaling probe, Biosens. Bioelectron. 74 (2015) 491
497. [56] E.S. Fakunle, I. Fritsch, Low-temperature co-fired ceramic microchannels with individually addressable screen-printed gold electrodes on four walls for self-contained electrochemical immunoassays, Anal. Bioanal. Chem. 398 (6) (2010) 2605
2615. [57] C.K. Dixit, K. Kadimisetty, B.A. Otieno, C. Tang, S. Malla, C.E. Krause, et al., Electrochemistry-based approaches to low cost, high sensitivity, automated, multiplexed protein immunoassays for cancer diagnostics, Analyst 141 (2) (2016) 536
547. [58] A. Zani, S. Laschi, M. Mascini, G. Marrazza, A. New, Electrochemical multiplexed assay for PSA cancer marker detection, Electroanalysis 23 (1) (2011) 91
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[60] J. Ahn, J.Y. Cho, Current serum lung cancer biomarkers, J. Mol. Biomark. Diagn. 4 (2013) 2. [61] F.-Y. Kong, B.-Y. Xu, Y. Du, J.-J. Xu, H.-Y. Chen, A branched electrode based electrochemical platform: towards new label-free and reagentless simultaneous detection of two biomarkers, Chem. Commun. 49 (11) (2013) 1052
1054. ¨ . Alatas¸, M. Metintas¸, O ¨. C [62] F. Alatas¸, O ¸ olak, E. Harmanci, S. Demir, Diagnostic value of CEA, CA 15-3, CA 19-9, CYFRA 21-1, NSE and TSA assay in pleural effusions, Lung Cancer 31 (1) (2001) 9
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120. [64] D. Wu, A. Guo, Z. Guo, L. Xie, Q. Wei, B. Du, Simultaneous electrochemical detection of cervical cancer markers using reduced graphene oxide-tetraethylene pentamine as electrode materials and distinguishable redox probes as labels, Biosens. Bioelectron. 54 (2014) 634
639. [65] J. Chang, X. Wang, J. Wang, H. Li, F. Li, Nucleic Acid-Functionalized Metal
Organic Framework-Based Homogeneous Electrochemical Biosensor for Simultaneous Detection of Multiple Tumor Biomarkers, Anal. Chem. 91 (5) (2019) 3604
3610. [66] T. Xu, X. Jia, X. Chen, Z. Ma, Simultaneous electrochemical detection of multiple tumor markers using metal ions tagged immunocolloidal gold, Biosens. Bioelectron. 56 (2014) 174
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946. [69] H. Yang, A. Hui, G. Pampalakis, L. Soleymani, F.-F. Liu, E.H. Sargent, et al., Direct, electronic microRNA detection for the rapid determination of differential expression profiles, Angew. Chem. Int. Ed. 48 (45) (2009) 8461
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14605. ¨ ller, Biomaterial interface investigated by [74] M. Moisel, M.L. de Mele, W.D. Mu electrochemical impedance spectroscopy, Adv. Eng. Mater. 10 (10) (2008) B33
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Chapter 3 Electrochemical detection

[76] B.-Y. Chang, S.-M. Park, Electrochemical impedance spectroscopy, Annu. Rev. Anal. Chem. 3 (2010) 207
229. [77] R. Elshafey, A.C. Tavares, M. Siaj, M. Zourob, Electrochemical impedance immunosensor based on gold nanoparticles–protein G for the detection of cancer marker epidermal growth factor receptor in human plasma and brain tissue, Biosens. Bioelectron. 50 (2013) 143
149. [78] L. Han, P. Liu, V.A. Petrenko, A. Liu, A label-free electrochemical impedance cytosensor based on specific peptide-fused phage selected from landscape phage library, Sci. Rep. 6 (2016) 22199. [79] Y. Hu, P. Zuo, B.-C. Ye, Label-free electrochemical impedance spectroscopy biosensor for direct detection of cancer cells based on the interaction between carbohydrate and lectin, Biosens. Bioelectron. 43 (2013) 79
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1630.

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4

Surendra K. Yadav Department of Chemistry, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

4.1

Introduction

The biomolecular detection has contended an extended journey since 1953, Prof. Leland C Clark Jnr, published his decisive paper on the oxygen electrode [1]. In 1981, the first description of a biosensor associate amperometric enzyme electrode for glucose sensor [2]. Now the level of detection has come to the ng/mL [3
5]. It is all possible because of nanotechnology, the word itself was first coined by Prof. Richard P. Feynman in the 1960s. There are several methods that have been used to detect biomolecule and subsequently the signature of few diseases as well [6]. There are several detection methods exists in practice now a day. Transduction methods are widespread use in practice such as electrochemical, electrical, optical, electromechanical etc. The significant advantages of optical imaging compared with other transduction methods are superior sensitivity, extremely low energy radiation, the ability to probe multiple independent optical biomarkers simultaneously, and relatively simple imaging hardware [7]. Optical techniques provide an accurate and rapid route to detect cancer markers [8] but we are still same way from being able to optically locate tumors lying deep within the body’s organs. The spectral ranges ultraviolet (UV) to visible of absorption and emission of most native fluorophores (NADH, collagen, tryptophan, elastin, flavin etc.) within tissue. Low absorption and scattering of light by tissue, allows light to penetrate up to several centimeters into tissue with in the spectral window as far-red to near-infrared (NIR) range (650
1100 nm).

Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00005-6 © 2021 Elsevier Inc. All rights reserved.

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The prime goals are detection of cancer, complete removal of tumors, and accurate differentiation between normal and cancerous tissues. The fluorescence microscopy has great potential in drug screening and discovery for intracellular measurements of RNA or protein expression in living cells. Imaging oral lesions with optical probes that sample mostly stromal fluorescence may result in a similar loss of fluorescence intensity and may fail to distinguish benign from malignant lesions. Improved diagnostic accuracy may be achieved by designing optical probes that distinguish epithelial fluorescence from stromal fluorescence and by using excitation wavelengths in the UV range [8]. The investigation of many fundamental processes in the life sciences relies on the fast, sensitive, reliable and reproducible detection of the interplay of biomolecules with one another and with various ionic or molecular species. A substantial number of elegant experimental approaches have been developed to image the distribution and dynamics of DNA, mRNA, proteins, organelles, metabolites, and ions in living plant cells. Fluorescence techniques are very well suited to realize these goals [9
12]. Fluorescence methods encompasses several unique experimental parameters (for instance, excitation and emission wavelength, intensity, fluorescence lifetime and emission anisotropy) and offer nanometer-scale resolution and possible sensitivity down to the single-molecule level [13]. A method explained in late-sixties fluorescence microscopy, essentially cuts the processing time as well as of scanning of specimens in exfoliative cytology. Anxious cells show flaming orange-red fluorescence of the cytoplasm on a black background that significantly differentiate malignant cells from normal cells [14]. Fluorescent probes are useful for enhancing visualization of small tumors but are typically limited by either high background signal or the requirement for administration hours to days before use. Researchers have synthesized dyes that rapidly triggered fluorescence for selective fluorescence imaging probe. The quickly responsive probes are practically useful for clinical application during surgical or endoscopic procedures because of its rapid and strong activation upon contact on the surface of cancer cells [15
17]. Additionally, fluorescence microscopy is in a state of rapid headway, with innovative techniques, probes, and equipment appearing almost day-to-day. Familiarity with fluorescence spectroscopy is a qualified for taking advantage of many of these developments. Indeed, a wide variety of methods have been established to analyze the localization, dynamics and interactions of molecules in living cells. The uses of the

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

fluorescent protein together with live-cell microscopy, fluorescence recovery after photobleaching, and fluorescence resonance energy transfer have all delivered a breakthrough in the field of cancer research [17,18]. This chapter attempts to provide a framework for understanding excitation and emission by fluorophores, the way fluorescence microscopes work, the ways fluorescence can be optimized and application in detection and diagnosis of cancer and malignancy.

4.2 4.2.1

Fluorescence spectroscopy Development history

In 1565, A Spanish physician and botanist Nicola´s Monardes, published the first edition of “Historia medicinal de las cosas que se traen de nuestras Indias Occidentales,” later published in other editions with different titles. He described the bluish opalescence of the water infusion from the wood of a small Mexican tree [19]. When made into cups and filled with water, a peculiar blue tinge to the water was observed, later being used as tea. In 1646, a German priest Athanasius Kircher wrote a book called “Ars Magna Lucis et Umbrae” in which he described the wood extract Lignum nephriticum. Light passing through an aqueous fermentation of this wood seemed more yellow while light reflected from the solution appeared blue. In 1603, Vincenzo Casciarolo, a Bolognian shoemaker who was dreaming of producing gold, discovered that a after baking a stone it emitted a purple-blue light in the dark. The stone was barium sulfate, named as lapis solaris. The discovery start a sparkling debate between scientists at the time. Galileo Galilei (1612) commented on the emission of light (phosphorescence) from the famous Bolognian stone, “It must be happens that the light is conceived into the stone, and is given back after some time, as in childbirth.” Robert Boyle (1664) was encouraged by Monardes report and examined this system closely. He revealed that after many infusions the wood vanished its power to give color to the water and confirmed that there was some “essential salt” in the wood accountable for the effect. He also discovered that addition of acid eliminated the color and that addition of alkali fetched it back. David Brewster (1833) pronounced that when a beam of white light passed through an alcohol solution of leaves, a red beam could be detected from the side (which was of course chlorophyll fluorescence). He assumes the effect is due to “dispersion.” John Herschel (1845) made the first

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experiment of fluorescence from quinine sulfate. He termed said phenomenon “epipolic dispersion.” Edmond Becquerel (1842) excite calcium sulfate by UV light and he discover that the emission occurs at a wavelength longer than that of the excitation light. Later (1858) builds the first phosphoroscope allowing him to measure the decay times of phosphorescence. George Gabriel Stokes (1852) published his massive paper on “the Change of Refrangibility of Light” [20]. He initially used the term “dispersive reflection” to describe the phenomenon offered by quinine sulfate. The infrared absorption of dicobaltoctacarbonyl, has led to the discovery of a nonbridged isomer [21]. R. Meyer (1897) used the term “fluorophore” to describe functional groups which inclined to be associated with fluorescence. The word “chromophore” was first used in 1876 by O. N. Witt to designate functional groups associated with color. In 1856, at the age of 18, William Henry Perkin set out with idea of making quinine by oxidizing ally toluidine-instead he serendipitously discovers synthetic dye, mauve, an aniline based derivative of coal tar. Adolph Von Baeyer (1871) a German chemist, synthesized Spiro. He apparently coined the name “fluorescein,” from “fluo” and resorcin (resorcinol), which he reacted with phthalic anhydride. In 1905 he was awarded the Nobel Prize in Chemistry “in recognition of his services in the advancement of organic chemistry and the chemical industry, through his work on organic dyes and hydroaromatic compounds.”

4.3

Fundamentals

Sir George G. Stokes (British scientist) described fluorescence in 1852 and was the one who coined the word after seeing that the mineral fluorspar emitted red light, illuminated by UV excitation. It has been noted by Stokes that the fluorescence emission occurred always at a longer wavelength than that of the excitation [22]. Investigations in the early 19th century discovered that many specimens such as minerals, crystals, resins, crude drugs, butter, chlorophyll, vitamins, and inorganic compounds, fluoresce when irradiated by UV light. However, the use of fluorochromes was not initiated until the 1930s, in biological investigations to tinge tissue components, bacteria, and other pathogens. Several of these stains were highly specific and stimulated that helps in the development of the fluorescence microscope. In a broad sense, the emission of light from any substance is termed as luminescence and occurs due to the relaxation of

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

electronically excited molecule or crystal. This may further be divided into two forms: Fluorescence and Phosphorescence. The simplest model to understand luminescence is by considering a 3-state system comprising Singlet ground state S0, Singlet excited state S1, and Triplet state T. Molecules undergoes a transition from ground state to excited state by absorbing photons of appropriate wavelength equal to the energy gap of the ground state and excited states. In the ground state, both the electron in the relevant orbital are oppositely paired. Because of excitation, one of the electrons makes a transition to the singlet excited state S1. Consequently, A return to the ground state is spin allowed, and this process occurs rapidly, emission rates  108 s21. So, the average time between excitation and coming back to ground state is about 10 ns. On the other hand, during phosphorescence, the electrons in the S1 state transit to energetically favorable (low energy) triplet state. During inter-system crossing, the electron spin flips. So, the electron is paired by the same spin to the electron in the ground state, thereby the transition is forbidden by the selection rules and the emission rates are slow. Consequently, the lifetime elongates to milliseconds or even seconds. Longer lifetime embodies phosphorescence process. However, it may be noted that, there are many deactivation processes that compete with radiative emission such as non-radiative decay. Phosphorescence is just one of them. There is no sharp distinction between phosphorescence and fluorescence, except the decay time. Fluorescence spectroscopy is an essential tool in the biomedical sciences, biology and in materials science because of the characteristics that are not readily available in other contrast modes with traditional optical microscopy. The use of an array of fluorochromes has made it possible to recognize cells and cellular components with a high degree of specificity among nonfluorescing materials. Even the fluorescence spectroscope can expose the presence of a single molecule. Using multiple fluorescence labeling, different probes can simultaneously identify several target molecules. Although the microscope cannot afford spatial resolution below the diffraction limit of specific sample features, the detection of fluorescing molecules below such limits has been achieved [23
26]. A variety of materials exhibit autofluorescence when they are irradiated, a phenomenon that has been thoroughly exploited in the fields of botany, petrology, and the semiconductor industry. Fluorochromes are stains that attach themselves to visible or subvisible structures, are often highly specific in their attachment targeting and have a significant quantum yield. The growth in application of fluorescence microscopy is extensively and closely linked to the development

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of new synthetic and naturally occurring fluorophores with known intensity profiles of excitation and emission, along with well-understood biological targets.

4.3.1

Excitation and emission fundamentals

4.3.1.1 Kasha’s law, Stokes shift, and Franck
Condon principle There must be the absorption of light before emission (fluorescence or phosphorescence) occurs. The molecules within the sample gets excited after absorption of photons. The BeerLambert law characterizes the absorption process and can be written in the form Eq. 4.1 I 5 I0 e2Acz

ð4:1Þ

where, A, c and z are respectively the molar extinction coefficient (expressed in M21 cm21), concentration (moles/lit.) and path length or width of the cuvette where loght passing through. Note that, the extinction coefficient is wavelength dependent and is related to the molecular absorption cross-section (σ) by, AðλÞ 5 Naν σðλÞ. Fluorescent molecules which are essentially polyatomic can undergo numerous transitions involving electronic and vibrational states. Note that the rotational transition is avoided as far as fluorescence spectroscopy is concerned. Out of these, only certain transitions are allowed by the quantum mechanical selection rules. Two selection rules applied for adsorption process; First involving symmetry of the molecular orbitals. Allowed transitions have intense absorption and emission while, forbidden transitions are weak. The basis for spectroscopic selection rule quantume mechanically is based on transition moment integral, i.e. Eq. 4.2, ðN  ψi μ ψf dτ ð4:2Þ 2N

where, ψi and ψf are the wave functions of the initial and final states involved in the transition; μ is the transition moment operator. If the value of this integral is zero, then the transition is strictly forbidden. It is important to realize that it is enough  to determine the symmetry of the moment function, i.e., ψi μψf . If this function is odd (i.e., has an odd symmetry), then the integral is zero and the corresponding transition is forbidden. The second kind consists of spin-forbidden transitions. For an allowed transition, the electron with spin up in the excited state must be paired with a spin down electron in the ground state electron. Therefore, the transition between singlet-singlet and triplet-triplet are allowed but the transition to triplet-singlet and

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

79

singlet-to-triplet are forbidden. Exception exists for molecules having strong spin-orbit coupling which is essentially, the interaction between the orbital magnetic moment and the spin of the electron. Kasha’s law: Irrespective of the nature of electronic excitation, the emission occurs from the lowest vibrational state of the excited electronic state. The rule is to understand the emission process of a molecule where, several relaxation pathways are available, and often it becomes difficult to pin-point a transition. Depending upon the energy E 5 hc/λ of the incident light, the electrons in the ground electronic state goes to the excited state. So, the electron can be in any of the higher excited states, Sn, n . 0. According to Kasha’s law, intense fluorescence emission is expected only from the lowest excited electronic state S1. This is because vibrational wave functions of the excited electronic states stay near and have similar energies. This results in substantial overlap, causing a nonradiative transition to the lowest vibrational level of the lowest excited state as shown in Fig. 4.1. This is called internal conversion. Note that the energy gap between excited states is small as compared to that between the first excited and ground state. Finally, the molecule relaxes to the ground state S0 from the lowest excited state S1, giving fluorescence in the process. This is equivalent to the statement that the emission spectrum is independent of the excitation spectrum. It is interesting to note the time required for each process: absorption normally occurs in 10215 s, internal conversion occurs in 10212 s, and fluorescence occurs in 1029
1027 s. Stoke’s shift: The emission always occurs at higher wavelengths or equivalently at lower energy than the excitaion wavelength or equivalent energy. The Stoke’s shift is well manifested in the Jablonski energy diagram shown in Fig. 4.2. To avoid inner filter effect, reabsorption of

S2

Internal conversion

S1 hνA

S0

hνA

hνf

Figure 4.1 Florescence from a molecule, shifting of frequency of incident radiation toward red end.

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Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

S1 Internal conversion T

Nonradiative transition S0 Figure 4.2 Phosphorescence from a molecule, because of delayed in decay process.

emitted fluorescence and autofluorescence, the large Stoke’s shift is preferred to eliminate overlap of absorption and emission spectra. Small Stoke’s shift require expensive filters and unnecessarily make the imaging system complex. Fortunately, molecular engineering over the last decade has given freedom of choice of the fluorescent molecules with distinct absorption and emission spectra. What is even more striking is that the Stoke’s shift can be engineered for a desired application. the absorption and emission spectra for some of the well-known fluorophores and its derivatives for which that Stokes shift varies from few nanometers to tens of nanometers. Frank
Condon principle: The Frank
Condon principle is essentially a remanifestation of Born-Oppenheimer approximation and it states that all the transitions involving ground and excited states are vertical. Accordingly, the most intense transition is from the first vibration state (ν 5 0) of the electronic ground state S0 to the first vibrational state (ν 5 0) of first electronic excited state (S1). The consequence of Frank
Condon principle in fluorescence is the symmetric nature of these transitions as shown in Fig. 4.3 for the classical Anthracene molecule [27]. According to this principle, all the electronic transitions occur without the change in the position of nuclei. This leaves the electronic and vibrational energy levels unchanged. So, if a transition probability between the vibrational levels of S0 and S1 is prominent in absorption then the corresponding emission is also equally probable. The spectra for anthracene molecule are the result of symmetric transitions being involved in both absorption and emission. This is due to the involvement of similar vibrational energy levels of singlet ground and first excited singlet state. It may however be note that, many fluorescent molecules do not follow symmetric transitions [27].

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81

Figure 4.3 The absorption and emission spectra of Anthracene depicting symmetric transitions. Source: Reproduced with permission from P.V.E., McClintock, Fundamentals of fluorescence microscopy: exploring life with light, by Partha Pratim Mondal and Alberto Diaspro: Scope: Textbook. Level: Professional Physicists and Biologists, Postgraduates, Undergraduates, Taylor & Francis, 2017, pp. 181
182.

4.3.2

Quantum yield and lifetime of florescence marker

A molecule in the excited singlet state S1 relaxes either by radiative means, by which it goes back to singlet ground state S0 or undergoes intersystem crossing to an energetically favorable metastable triplet state T1. Due to spin-forbidden nature of the T1-S0, the emission process takes 103
105 longer time to relax as compared to S1-S0 transition. The corresponding rates for these relaxation processes are indicated by kr and knr, respectively. Fluorescence quantum yield is defined as the ratio of the number of photons emitted to the number of photons absorbed. So, this is essentially the ratio of radiative rate constant to that of the sum of both radiative and nonradiative rate constants, i.e. Eq. 4.3, Qy 5

kr kr 1 knr

ð4:3Þ

Depending upon the relaxation process, the quantum yield varies between 0 and 1. The quantum yield approach unity for

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fluorescent molecules with negligible nonradiative transition (kr .. knr) and consequently they appear brighter. Fluorescence lifetime is defined as the average time spend by the molecule in the excited state before it returns to the ground state. Accordingly, the fluorescence lifetime is defined as Eq. 4.4, τ fl 5

1 kr 1 knr

ð4:4Þ

The emission is a poisoning process, which spans over a longer time for completion. Considering exponential decay of fluorescent molecules, (1
1/e) % molecules decay prior to t-τfl, and 1/e % molecules after the decay. The fluorescence lifetime is thus the average time spent by the molecule in the excited state. The time scales of various processes in a molecule has been given below. The molecule absorbs incoming photon in about 10215 s and vibrational relaxation occurs in 10214 2 10211 s. Thereafter the molecule may undergo intersystem crossing to triplet state within a range of 1028
1023 s or may undergo phosphorescence to relax to singlet ground state S0. The timescale for phosphorescence ranges from 1024 to 10 s. On the other hand, the molecules may revert directly to the singlet ground state from excited state. The lifetime of first excited singlet state is in the range of 1029
1027. It may be noted that, measured lifetime is different from the intrinsic natural lifetime of the molecule. Both the fluorescence lifetime and intrinsic lifetime are equivalent when there are no non-radiative processes. Accordingly, natural lifetime is defined as the emission time of the first electronic state of fluorescent molecules to decrease by a factor of 1/e immediately after excitation. Natural lifetime is thus given by Eq. 4.5, τn 5

1 kr

ð4:5Þ

The quantum yield, fluorescence lifetime and natural lifetime are related by the following relation as evident by Eq. 4.6 τ fl QY 5 ð4:6Þ τn

4.3.3

Florescence lifetime imaging

Molecules in an excited state stays in that state for small amount of time before relaxing back to the electronic ground state. This is the time when it has the highest probability to undergo processes like bonding, energy transfer and others. So, molecules are delicate in the sense that they are ready to

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

undergo bleaching and quenching via complex formation. This gives a wealth of information about the chemical surroundings and its affinity to react with. To start with the first effect called fluorescence lifetime imaging. Suppose a pulse of light excites the sample containing florescent dye. The lifetime is the average time that a molecule stays in the excited singlet state S1 after excitation. Statistically, this can be calculated by averaging time t over the intensity decay of the molecule extending for a very long time , t . 5 τ. It is supreme importance to realize that life time is a statistical event and the molecules emit throughout the decay. So, all the molecules do not emit at a time equal to lifetime t 5 τ. It is only, (1
1/e) %  63% molecules emit before t 5 τ and the remaining 37% molecules emit after t 5 τ. In fluorescence lifetime imaging, the image is obtained by calculating lifetime at each point of the lateral plane in the specimen. Then the image is obtained by simply replacing the points by its respective lifetime values rather than intensity. So, the lifetime is fundamental quantity than intensity as life time does not counts on the photobleaching effects. Fluorescence lifetime imaging has the added advantage of providing information and measurements that are independent of probe concentration or equivalently fluorescence intensity. This gives much better insight about the chemical environment inside the specimen such as, pH or presence of analytes such as, Ca21, K1 etc. Lifetime measurements have the potential to sense the concentration of analytes and the trace biochemical reactions inside a live cell. Suppose a cell or tissue few parts has the steady-state fluorescence intensity. The same cell within different compartments has probes or analytes with different lifetimes τ 1 ; τ 2 ; . . . ; τ n . Varying lifetimes in different compartments could be due to the presence of different analytes or ionic species. The intensity image will show a uniform intensity, but the lifetime image may clearly reveal different compartments based on the lifetime of the analytes. So, FLIM contrast is due to lifetimes in the region of interest. Briefly, the lifetime measurement technique begins by exciting the sample with a pulse of light (picosecond or femtosecond) with pulse-width much smaller than the fluorescence lifetime of the molecule. This results in the emission of photons from the sample for a prolonged time (nanoseconds), thereby giving rise to a waveform. The measurements are adjusted to detect one photon per pulse. The time difference between the start of excitation pulse and emission photon are stored in histogram. The histogram represents the waveform of the decay. To perform these fast measurement, dedicated electronics and fast detectors are essential.

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4.3.4

Fo¨rster resonance energy transfer

Forster resonance energy transfer (FRET) is a mechanism that describes the energy transfer between two light sensitive molecules by resonance. The first Quantum theory given by Forster in 1948 [28] and subsequently improved by Dexter [29]. Consider a system of two nearly identical oscillators. There exists a weak coupling between the pair of stationary states of two similar atoms with equal energies. This is a quantum analogy of the classically coupled mechanical oscillators or coupled pendulums. When the weakly coupled oscillators are in resonance, the probability of first and second oscillators to be in excited states will vary periodically. The maximum probability is for both the oscillators out-of-phase: So, when the first oscillator has the maximum probability of being in excited state, the other oscillator will have minimum probability. The system evolves with time and eventually the second oscillator will have maximum probability and the first oscillator will have minimum probability. This will continue periodically. The excited state of the coupled system can be represented by the linear superposition of individual stationary states of each oscillator. The resonance condition is the one in which the quantum mechanical states repeatedly exchange between the states and consequently the maximum probability changes. This phenomenon is experimentally observed between two similar molecules/atoms in close proximity. During resonance, the energy of the first molecule/atom gets transferred to backward and forward the second atom in a nonradiative way. The energy transfer promotes the second molecule to the excited state from ground state and the molecule can dissipate energy radiatively. Consider an oscillating electric dipole that with an electric dipole moment varies with time which makes an angle with the surrounding electric field. We seek the interaction between two oscillating electric dipoles with two different dipole moments. For simplification, we assume that the first dipole is at the origin and second is a distance r from the origin. So, we can assume that the second dipole is in a potential generated by the first dipole located at the origin and due to the potential, there must be electric field generated between these dipoles. Now the interaction energy between these two dipoles is the electric field times the moment of the second dipole. It is noted that the interaction energy has the dipole-dipole interaction term which decays as r23 and is strongly dependent on the orientation of dipole. The FRET rate from donor to acceptor can be easily obtained by using Fermi’s golden rule. So, the rate of

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

energy transfer has two prominent parts: first one is spectral overlap between the donor and acceptor molecules. Second is the inverse sixth-power dependence on the distance between the donor and acceptor molecule. Now, let us introduce Forster’s distance r0 which is defined as the distance for which the rate of energy transfer kDA(r) is equal to the rate of excitation decay of the donor molecule, i.e., kfD 5 1/τ fD. This distance is significant because at this distance, half of the total number of donor molecules undergo deexcitation through resonance energy transfer and one-half of the donor molecules decay both through radiative and nonradiative processes. Accordingly, the rate of energy transfer can be expressed as Eq. 4.7, kDA hr0 i6 1 hr0 i6 5 or kDA 5 ð4:7Þ τ fD r kfD r The FRET efficiency (E) is the ratio of the rate of transfer to the acceptor with the sum of the total rates Eq. 4.8 E5

1 1 1 ðr=r0 Þ6

ð4:8Þ

where, kfD is the fluorescence decay rate of the donor (both radiative and nonradiative). This shows that, FRET efficiency has a sixth-power dependence on the inter-molecule distance (r), purely due to dipoledipole interaction. This process facilitates altogether a different pathway for energy dissipation via resonance energy transfer. There have been several FRET studies on a variety of specimens and under varying experimental conditions. As an example, a recent study by Menon et al. [30] demonstrating magnified crops of both CFP and YFP protein tags signals in the bleach region are depicted for pre- and postbleach for each FRET pair.

4.3.5

Quenching and photobleaching

There are conditions comes often which affect the re-radiation of fluorescence emission that commonly reduce fluorescence emission intensity. The general causes for a reduction of fluorescence emission intensity are quenching and photobleaching phenomena. One of the common modes of deexcitation of molecules is called quenching that also reduces the ability of a molecule to fluoresce. In a solution, the fluorophores undergo random collisions with other species of molecules called quenchers. Upon contact with the quencher, the excited fluorophores get deactivated by various means including, energy transfer to other molecules and complex

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formation. This dynamic process is well encapsulated in the SternVolmer equation that quantifies the deexcitation process [31]. The other form of quenching is static quenching which occurs due to the formation of a nonfluorescent ground state complex with the quencher molecules. When excited, the complex subsequently returns to the ground state following a nonradiative decay pathway. Many situations involve quenching by both complex formation as well as by collisions. In these cases, the fall in fluorescence is due to both static and dynamic quenching. The light emitted by the fluorescent markers continuously fades with time. This phenomenon is called photobleaching or dye photolysis and involves a photochemical modification of the dye thereby effecting its ability to fluoresce. Although these molecules get switched off for small time, the fluorescence can be switched on again after an apparent loss of emission ability. Most of the fluorescence imaging systems based on single photon excitation such as wide-field fluorescence microscopy suffer from photobleaching of the entire specimen. This severely reduces the signal to noise ratio (SNR) of the detected signal. Under these imaging conditions, the fluorescence emitted is often observed to decrease substantially with time because of photobleaching effects thereby further reducing the SNR. In most of the single and multiphoton excitation, the high peak power of the laser pulses causes photodamage to the fluorescent probes [32
34]. Especially in multiphoton imaging, the fluorescence signal is very low. Moreover, due to both linear and nonlinear photobleaching effects the process becomes complex. Photobleaching can happen due to a lot of reasons including, molecular collisions, energy transfer and presence of metastable triplet states. It’s been assumed that the sample is fixed and does not have spectral overlap. This ensures that the sample can bleach only through triplet state relaxation thereby eliminating other relaxation pathways.

4.4

Instrumentation

The basic mechanism of a fluorescence microscope is to irradiate the sample with a desired and specific band of wavelengths, and then to separate the much weaker emitted fluorescence from the excitation light. In a properly configured microscope, only the emission light should reach the detector so that the resulting fluorescent structures are superimposed with high contrast against a very dark or black background. The limits of detection are generally

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87

governed by the darkness of the background, and the excitation light is typically several hundred thousand to a million times brighter than the emitted fluorescence. To achieve maximum fluorescence intensity, a fluorophore is usually excited at wavelengths near or at the peak of the excitation curve, and the widest possible range of emission wavelengths that include the emission peak are selected for detection. In addition, the spectral response of a microscope optical system will depend on such aspects as glass transmission efficiency, the number of lens, mirror elements and the responsivity of the detector. The active recognition of emission wavelengths would be achieved in fluorescence microscopy through the choice of appropriate filters to block or pass specific wavelength bands in the UV, visible, and NIR spectral regions [35]. Fluorescence vertical illuminators are designed with the purpose of controlling the excitation light through the application of identical filter insertions into the light path on the way to the sample, and again in the path between the sample and the detector. Perhaps the most important criteria, in view of relatively low fluorescence emission intensities is that the light source utilized for excitation would be enough bright so that even the weak emissions could be maximized, and the fluorochromes possess adequate absorption and emission quantum yields. The diagram of a fluorescence microscope Fig. 4.4. The vertical illuminator in the

Figure 4.4 Diagram of a microscope for transmitted light. The vertical illuminator in the center of the diagram has the light source at one end and the filter cube at the central par.

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center of the diagram has the light source positioned at one end and the filter cube turret at the other. The design consists of a basic reflected light microscope in which the wavelength of the reflected light is longer than that of the excitation. In a fluorescence vertical illuminator, light of a specific wavelength band often in the UV, blue or green regions of the visible spectrum, is produced by passing multispectral light from an arc-discharge lamp or other source through a wavelength selective excitation filter. Wavelengths passed by the excitation filter reflect from the surface of a dichromatic mirror or beam splitter, through the microscope objective to shine the sample with intense light. If the sample fluoresces, the emission light gathered by the objective passes back through the dichromatic mirror and is subsequently filtered by a barrier or emission filter, which blocks the unwanted excitation wavelengths. The emitted light re-radiates spherically in all directions, regardless of the excitation light source direction. Fluorescence illumination is the overwhelming choice of techniques in modern microscopy, and the reflected light vertical illuminator is interposed between the observation viewing tubes and the nosepiece housing the objectives. The illuminator is designed to direct light onto the specimen by first passing the excitation light through the microscope objective on the way toward the sample, and then using that same objective to capture the emitted fluorescence. This type of illuminator has several advantages. The fluorescence microscope objective serves first as a well-corrected condenser and secondly as the imageforming light gatherer. Being a single component, the objective/ condenser is always in perfect alignment. Most of the excitation light reaching the specimen passes through without interaction and travels away from the objective, and the illuminated area is restricted to that which is observed through the eyepieces. Unlike the situation in some contrast enhancing techniques, the full numerical aperture of the objective is available when the microscope is properly configured for Ko¨hler illumination. Finally, it is possible to combine with or alternate between reflected light fluorescence and transmitted light observation and the capture of digital images.

4.5

Fluorescence light sources

An unfortunate consequence of low emission levels in most fluorescence microscopy applications is that the number of photons that reach the eye or camera detector is also very low. In most cases, the collection efficiency of optical microscopes is

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

less than 30 percent and the concentration of many fluorophores in the optical path ranges in the micromolar or nanomolar regions. To generate enough excitation light intensity to produce detectable emission, powerful compact light sources, such as high-energy short arc-discharge lamps, are necessary. The most common lamps are mercury burners, ranging in wattage from 50 to 200 W, and the xenon burners that range from 75 to 150 W. These light sources are usually powered by an external direct current supply, furnishing enough startup power to ignite the burner through ionization of the gaseous vapor and to keep it burning with a minimum of flicker. The microscope arc-discharge lamp external power supply is usually equipped with a timer to track the number of hours the burner has been in operation. Arc lamps lose efficiency and are more likely to shatter if used beyond their rated lifetime. The mercury burners do not provide even intensity across the spectrum from UV to infrared, and much of the intensity of the lamp is expended in the near UV. Prominent peaks of intensity occur at selected wavelengths. At other wavelengths in the visible light region, the intensity is steady although not nearly so bright. In considering illumination efficiency, mere lamp wattage is not the prime consideration. Instead, the critical parameter is the mean luminance must be considered, considering the source brightness, arc geometry, and the angular spread of emission. In past few years, optical microscopy had experienced an increase in the application of laser light sources, particularly the argon-ion and argon-krypton lasers. These lasers have the virtues of small source size, low divergence, monochromaticity, and high mean luminance. They have become essential in scanning confocal microscopy, a technique that has proven to be a powerful tool in rendering very sharp fluorescence images through rejection of nonfocused light removed from the specimen focal plane. Confocal microscopes accomplish this task through point or line scanning with coincident imaging through a conjugate aperture. Choosing the right illumination tool can not only improve the quality of experimental results, but also the microscope’s economic and environmental footprint. While arc lamps have historically proven to be a reliable light source for wide-field fluorescence microscopy, solid-state light-emitting diodes (LEDs) have become the light source of choice for new fluorescence microscopy systems. It has been demonstrating that LEDs have superior light stability on all timescales tested and use less electrical power than traditional light sources when used at lower power outputs. They can be readily switched on and off electronically, have a longer lifetime and they do not contain mercury, and thus are better

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for the environment. It is also to note that to measure light source power output during warm-up and switching, a light source’s response can be quite variable. Several general protocols for testing light source stability are present. A detailed life cycle analysis shows that an LED light source can have a fourfold lower environmental impact when compared to a metal halide source. The narrow band LEDs replace conventional white light sources to produce high contrast images with excellent SNR, enabling the detection of weak signals and fine details in applications ranging from routine biomedical research to complex live-cell imaging [36
38]. The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables highspeed cellular imaging across 0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca21 spiking in .200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca21 spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens [39]. Wide-field fluorescence microscopy commonly uses a mercury lamp, which has limited spectral capabilities. A tunable and programmable integrating sphere light source which consists of LEDs that carried out multispectral fluorescence imaging of living cells [40].

4.6

Nanoparticles and organic dyes for florescence sensors

The world of organic dyes has been confined for a long time to standard biological tagging applications and to certain analytical tests. Recently, the field has undergone a major change of direction, driven by the dual needs to develop organic electronic materials and to fuel the summarily developing nanotechnologies [41]. The undesirable photophysical properties of various fluorophores still constrain the full potential of their

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

applications. For instance, all these bright organic dyes usually have the serious disadvantage of very small Stokes shifts less than 25 nm, which can lead to serious self-quenching and fluorescence detection errors because of excitation backscattering effects. On the other hand, measuring fluorescence by an increase of the fluorescence intensity without much shift of either excitation or emission wavelength can be influenced by many factors, such as the localization of the probe, changes of environment around the probe pH, polarity, temperature, emission collection efficiency, effective cell thickness in the optical beam, and changes in the excitation intensity [42]. The significantly large shift has been seen in visible spectrum region and able to sense colors efficiently [43]. There are organic dyes which have very large stokes shift up to 227 nm which makes it suitable candidate for utilizing it as two photon probe bioimaging and sensing [44]. Red and green are two of the most-preferred colors from the entire chromatic spectrum, and red and green dyes are widely used in biochemistry, immunohistochemistry, immune-staining, and Nano chemistry applications. Selective dyes with green and red excitable chromophores can be used in biological environments, such as tissues and cells, and can be irradiated with visible light without cell damage [45]. The dependence on the nature and the substitution pattern of the aryl ring, naphthylamides are the prime candidates to probes as the changes in spectroscopic properties such as absorption, dichroism, and fluorescence can all be used to monitor their binding to biomolecules. This also makes them useful species for monitoring their uptake and location within cells without the use of co-staining [46]. The dye nanoaggregate contains double internal proton transfer shows significant emission enhancement and fluorescence switching or color switching in under UV light [47]. Melucci et al. have reported a strategy to realize self-assembled monolayers (SAMs) on quartz and silicon with a multicolor fluorescence pattern from a single, proton sensitive oligothiophene dye. SAMs emission color over the entire visible range, including white, has been shown and integration of SAMs in patterned thin layer cells for sensing in devices [48]. Organic dyes have made significant progress, especially in infrared dyes that overcome the limitations of poor hydrophobicity photostability, low quantum yield, insufficient stability in biological systems. Potentially, such dye-encapsulated nanoparticles by conjugation with tumor specific ligands (such as small molecules, peptides, proteins and antibodies) used for tumor targeted imaging. There are newly developed NIR dyes exits, which have potential applications in cancer targeting and imaging. The development of future

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multifunctional agents with combination of targets, imaging and even therapeutic routes would also be possible along with the tumor targeted imaging and the diagnosis and therapeutics for the treatment of cancer [49]. The NIR, Heptamethine carbocyanine dyes used as optical imaging agents for the rapid detection of human kidney cancer [50]. The organic dyes immobilized onto layered double hydroxides utilized for cysteine sensors [51]. Using small-molecule organic dye nanoparticles to encapsulate NIR dyes to enable efficient FRET for NIR probes with remarkably enhanced performance for in vitro and in vivo imaging. NIR fluorescence imaging in the 700
1000 nm wavelength range has been attractive for cancer detection in early stage [52]. NIR fluorescence imaging agents are promising tools for noninvasive cancer imaging. Authors explored the mechanistic properties of a specific group of NIR heptamethine carbocyanines including MHI-148 dye to achieve cancer-specific imaging and targeting via a hypoxiamediated mechanism [53]. Fluorescence imaging in the second NIR window (NIR-II, 1000
1700 nm) features deep tissue penetration, reduced tissue scattering, and diminishing tissue autofluorescence. Here, NIRII fluorescent probes, including down-conversion nanoparticles, quantum dots (QDs), single-walled carbon nanotubes, and organic dyes, are constructed into biocompatible nanoparticles using the layer-by-layer platform due to its modular and versatile nature. Overall, rare-earth-based down-conversion nanoparticles demonstrate optimal biological and optical performance and are evaluated as a diagnostic probe for high-grade serous ovarian cancer, typically diagnosed at late stage. Authors have successful detection of orthotopic ovarian tumors by in vivo NIR-II imaging and confirmed by ex vivo microscopic imaging. Collectively, they indicate that LbL-based NIR-II probes can serve as a promising theragnostic platform to effectively and noninvasively monitor the progression and diagnosis of serous ovarian cancer [54].

4.7

Quantum dots for florescence imaging and cancer diagnostics

Russian physicist Alexei Ekimov of the State Optics Institute Vavilov (Leningrad) synthesized nanocrystals of copper chloride and then of cadmium selenide in a molten glass matrix. He then observed a fluorescence and a gradient of colors. These first observations were published his results in 1981 in Russian.

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

Alexander Efros, another Russian physicist, published in 1982 the first theory aiming at explaining the behavior of these tiny crystals by the confinement of their electrons. An American chemist Louis Brus, Bell Labs, inspired by Alexei Ekimov and successfully synthesize colloidal suspension of nanocrystals in a liquid and published his results in 1983. He predicted the characteristics of said particles by fitting the data in suitable model [55]. In his two papers published in 1983 and 1984, he described QDs as “small semiconductor crystallites.” The electrons in quantum dots are confined in a small space (quantum box) because of the tiny size of the QDs, and if the radii of the semiconductor nanocrystal is smaller than the exciton Bohr radius, there is quantization of the energy levels happens according to Pauli’s exclusion principle [56,57]. Generally, as the size of the crystal decreases, the difference in energy between the highest valence band and the lowest conduction band increases. More energy is then needed to excite the dot, and synchronously, more energy is released when the crystal returns to its ground state, resulting in a color shift from red to blue in the emitted light. Because of this characteristic, QDs can emit any color of light from the same material simply by changing the size. Additionally, because of the high level of control possible over the size of the nanocrystals, it is possible to choose the emission of color from QDs [58]. Recently, fluorescent probes have been considered a valuable detection method because of their ability to provide detailed and sensitive illumination in terms of cell structure and molecular content. QDs are emerging as a new molecular fluorescent probe that caries unique advantages over traditional fluorescent dyes and fluorescent proteins (FP), including their broad excitation spectra, narrow and symmetric photoluminescence bands, chemical stability and photostability and versatility in surface modification. The broad absorption band of QDs allows QDs with different fluorescence emission wavelengths to be excited with a single excitation light, resulting in several emissions of different colors that provide opportunity to detect multiple analytes simultaneously. Moreover, the photostability of QDs makes long-term tracking of biological molecules possible. The straightforward separation of excitation and emission of the QDs allow the fluorescence signal to be distinguished from cellular autofluorescence, thereby enhancing the specificity of the probe. Based on these promising properties, QDs combined with specific recognition molecules, represent a promising and attractive luminescent probe system for biomedical applications in detection, imaging and clinic diagnosis. Targeted delivery of

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Figure 4.5 The spectral analysis (A) and image (B) of the tumor site showed that the QD fluorescence was localized in the tumor sites (red arrow) and the normal tissue adjacent to the tumor site (green arrow). (C) The HE staining of the tumor section. (D)The microscope imaging showed the specific binding of probes to the tumor cells. Source: Reprinted with permission from L.-D. Chen, et al., The biocompatibility of quantum dot probes used for the targeted imaging of hepatocellular carcinoma metastasis, Biomaterials 29(31) (2008) 4170
4176.

QDs and QD-photosensitizing conjugates in cancer cells is an essential requirement for selective imaging and effective photodynamic therapy of cancer. Over expressed receptors in many cancers are ideal targets in cancer cells. The methods for delivering QDs inside cells include physical and biochemical techniques [59]. Physical techniques such as electroporation and microinjection have practical limitations for in vivo applications, whereas biochemical techniques such as peptide, antibody, and secondary antibody-based targeting are promising for selective labeling of cancer cells with QDs. The application of semiconductor QDs as labels in two important areas of biology, bioimaging and biosensing Fig. 4.5. Researchers have utilized biologically relevant properties of QDs focusing on surface treatment and stability, labeling of cellular structures and receptors with QDs, incorporation in living cells, cytotoxicity and influence of the biological environment on the biological and optical properties. It’s been also utilized as an agent in high-resolution bioimaging techniques that can provide information at the molecular levels. The live-cell QDbased imaging techniques with resolution far beyond the diffraction limit of light is examined [60]. The fabrication and detection of QDs-based prostate specific antigens (PSAs) cancer protein biochips by using enhanced surface plasmon-coupled emission measurements (SPCE). Due to the excellent brightness of the QDs and the high directionality of emission, as well as the high light collection efficiency of

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Figure 4.6 Accurate Breast cancer (HER2) diagnosis by the probe QDs-immunohistochemistry (IHC). (A) Specimens with different HER2 IHC scores detected by QDs
IHC. (B) Control for (A) by conventional IHC. (C, D) Fluorescence In-Situ Hybridization positive (C) and negative (D). Scale bar, 100 μm for (A) and (B) 20 μm for (C) and (D). Source: Reprinted with permission from C. Chen, et al., Quantum dots-based immunofluorescence technology for the quantitative determination of HER2 expression in breast cancer, Biomaterials 30(15) (2009) 2912
2918.

SPCE, the limit of detection is down to 10fg/mL (equal to 0.3fM) for the PSA chips by using QDs-based cancer protein. The low detection limit (0.3fM) supplies a great potential for detecting [61]. Fig. 4.6 various cancer biomarkers that are present in only low concentrations within the human body [62]. The fluorescence emission can be effectively quenched by gold nanoparticles (Au NPs) via fluorescence resonance energy transfer (FRET). Thiocholine, which was produced from acetylthiocholine by the hydrolysis of butyryl cholinesterase, could cause the aggregation of Au NPs and the corresponding recovery of FRET-quenched fluorescence emission. By evaluating the

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fluorescence emission intensity a FRET-based sensing platform for prostate cancer was established [63]. The fluorescence intensity of ZnSe QDs could be quenched by Cu21. Foreign ions showed insignificantly effect on the use of QDs as florescence senor probe [64]. There are report on the synthesis of watersoluble and nontoxic QDs used for fluorescence sensors [65].

4.8

Cancer detection

The culmination of cancer is accompanied by biochemical and structural changes in the tissue and can be diagnose by various optical techniques. Human tissue contains several native fluorophores in the form of proteins, amino acids, and enzymes. Cancer progression leads to biochemical transformations in intrinsic fluorophores [66]. Optical spectroscopic techniques have considerable impact in the field of biomedical diagnostics, providing novel methods for the noninvasive diagnosis in early stages of various medical conditions. Fluorescence spectroscopy has been the most widely explored mainly because fluorescence is highly sensitive to the biochemical markers (Table 4.1). It has been shown that tumors were easily detected on account of altered fluorescence properties with respect to fluorescence of ordinary tissue. There are three major category of fluorophores used for cancer detection: exogenous fluorophores, endogenous fluorophores, and fluorophores synthesized in the tissue from a precursor molecule that is given externally [67]. Endogenous fluorophores give rise to autofluorescence phenomenon. Examples of endogenous fluorophores include collagen, elastin, nicotinamide adenine dinucleotide (NADH),

Table 4.1 Few recent reports on fluorescence microscopy and spectroscopy-based cancer detections techniques. Methods

Transducer element

References

Fluorescence emission-based nano-barcodes

Organic dye Quantum dots Carbon dots Lanthanide-doped nanocrystals Fluorescence lifetime (time-domain) Phase angle (frequency-domain) Fluorescence pattern, optical pattern

[90
92] [93
95] [96
98] [99
103] [104] [105] [106
110]

Fluorescence kinetics-based nano-barcodes Graphical

Chapter 4 Fluorescence microscopy of organic dye, nanoparticles, quantum dots and spectroscopy

tryptophan, porphyrins, and flavin adenine dinucleotide (FAD) [68]. Collagen and elastin are mainly responsible for spectral changes associated with structural changes within the tissues and cells [69]. Other fluorophores like FAD, NADH, tryptophan, and porphyrins are mainly responsible for spectral changes associated with changes in cellular metabolism and functional processes [70]. Cancer tissues have an increased rate of metabolism, which gives rise to alternation in endogenous fluorophores, giving rise to spectral characteristics different from normal tissue [71,72]. Many groups have performed studies to explore various endogenous fluorophores for cancer diagnosis [73
76]. Autofluorescence phenomenon has been used for diagnosis of premalignant or malignant tissues in various organs of the body including the oral cavity [77], cervix [78], skin [79], lung [80], breast [81], esophagus [82], head and neck [83]. The 40
1000 nm sized extracellular vehicles (EVs) membranous particles are secreted by most of the cells and in the bodily fluids like urine, plasma and saliva [84]. The secreted EVs have transmembrane and cytosolic proteins and nucleic acids. EVs play a crucial role in promote cancer progression and metastasis through the cargo they carry. EVs supports the pathophysiological condition of the cells they originate from and thus may hold a key for a breakthrough in the field of noninvasive diagnostics [85,86]. Tumorigenesis is a multistep process that progressively converts normal cells into malignant cells [87]. To visualize single molecules in living cells, specific fluorophore labeling is required. Among the different types of fluorophores, green fluorescent protein and its derivatives can achieve high specificity of labeling through construction of fusion proteins with the target protein [88]. The fusion protein usually has low perturbation to cell physiology and thus is a great choice for single-molecule detection in live cells. To image FP in a live cell at single-molecule level, it is essential to distinguish single FP fluorescence from the cell autofluorescence background. One strategy among others is to reduce the excitation volume. Several different imaging methods fall into this category [89]. Conventional diagnostic techniques such as white-light endoscopy (e.g., micro laryngoscopy, esophagoscopy) and tissue biopsy have been used by pathologist to identify premalignant and malignant lesions, among which tissue biopsy with histopathology is gold standard. Tissue biopsy is an invasive method with the complication to decide the best area for biopsy, since the lesions are spread over a large area.4
6 A major problem faced with throat cancer is the accessibility to the region.

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Different noninvasive techniques such as fluorescence spectroscopy, Raman spectroscopy, diffuse reflectance spectroscopy etc. have been extensively used to differentiate premalignant and malignant lesions. Among these spectroscopic techniques, fluorescence spectroscopy is widely used by several researches for in vivo detection of cancer and in this technique endogenous fluorophores present in human tissue and other mediums (saliva, blood, etc.) are excited by a fixed excitation wavelength, which give rise fluorescence. Some of the fluorophores, present in the tissue are structural proteins (collagen and elastin), coenzymes NADH, and FAD, porphyrins etc. Fluorescence spectroscopy has demonstrated promising results for early diagnosis and screening of cervical neoplasia. Current medical practice utilizes cytology smear for initial screening of cervical cancers and cervical intraepithelial neoplasia (CIN), but it is associated with a 20
30% false negative error rate. Ramamujam et al. have utilized fluorescence spectroscopy successfully for in vivo diagnosis of CIN by use of 337 nm excited laser-induced fluorescence with a specificity of 90% and sensitivity of 92% [111]. Gao et al reported a strategy for highly sensitive recognition and in vivo imaging of cancer cells [112]. Fig. 4.7, taking advantage of their spontaneous ability to generate silver nanoclusters with high NIR fluorescence emission by intracellular reduction of innocuous silver salts [113]. Circulating tumor cells (CTC), a component of the “liquid biopsy,” hold great potential to transform the current landscape of cancer detection. It is challenging to unlock the clinical utility of CTCs lies in the ability to detect and isolate these rare cells using methods amenable to downstream characterization and other applications [114]. The transition from bulk to single-cell analyses on patient-derived CTCs brings it to the genomic level; they have identified clinically relevant alterations, ranging from small-scale such as single nucleotide variation, microsatellite instability to large-scale mutations like copy-number variation, large-scale state transition, and inter/intrachromosomal rearrangement [115]. The promising strategies for highly sensitive, selective, and rapid techniques for diagnostics of cancer cells is acknowledged earlier.

4.9

Conclusion

The chapter delves deeper into the depth knowledge of fluorescence spectroscopy as a possible diagnostic tool for early stage cancer diagnosis. Application of fluorescence techniques,

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Figure 4.7 Live animal imaging of self-assembled monolayer-QDs carrying Lewis antigen-related oligosaccharides. (A) Time course after injection of 100 pmole of glyco-PC-QDs (4
7). (B) Distribution of glyco-PC-QDs carrying Lex (5), sialyl LacNAc (6), and sialyl Lex (7) uncovered preliminarily by dissection. Source: Reprinted with permission from T. Ohyanagi, et al., Importance of sialic acid residues illuminated by live animal imaging using phosphorylcholine self-assembled monolayer-coated quantum dots, J. Am. Chem. Soc. 133(32) (2011) 12507
12517.

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such as spatially resolved fluorescence, polarized fluorescence, and synchronous fluorescence spectroscopy on human tissue has shown potential for early cancer diagnosis. Multiple fluorophores may have overlapping absorption and emission spectra, which limits the scope of steady state fluorescence spectroscopy and can be overcome through time-resolved fluorescence spectroscopy and fluorescence lifetime imaging. Due to differences in morphology of cancerous and healthy tissues, the amount of light scattered and, consequently, depolarization vary significantly with cancer progression. This chapter will briefly review some of the research aimed at capturing the spectral features and the dynamics pertaining to cancer progression in human body through fluorescence-based spectroscopy and microscopy.

Acknowledgment I sincerely thankful to Norway Research Council for financial support Postdoctoral Fellowship (Grant number NRC-90221903) and Department of Chemistry, NTNU Trondheim, Norway for hosting me as a Post Doc.

Conflict of interest Author declares no conflict of interest for this work.

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1756. [3] E. Gorodkiewicz, A. Sankiewicz, P. LaudaAski, Surface plasmon resonance imaging biosensors for aromatase based on a potent inhibitor and a specific antibody: Sensor development and application for biological material. (Report), Cent. Eur. J. Chem. 12 (5) (2014) 557. [4] D. Kinnamon, et al., Portable biosensor for monitoring cortisol in low-volume perspired human sweat, Sci. Rep. 7 (1) (2017). 13312-13312. [5] M.K. Patel, et al., Nanostructured magnesium oxide: a suitable material for DNA based biosensors, Mater. Focus 3 (1) (2014) 1
11. [6] R.P. Feynman, R.B. Leighton, M. Sands, Definitive ed The Feynman Lectures on Physics: Vol. 2: Mainly Electromagnetism and Matter, 2, Pearson Addison Wesley, San Francisco, 2006. [7] Y. Pu, et al., Characterization and three-dimensional localization of cancerous prostate tissue using backscattering scanning polarization imaging and independent component analysis, J. Biomed. Opt. 17 (2012). SPIE. 1-9, 9.

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Raman spectroscopy/SERS based immunoassays for cancer diagnostics

5

Kamil Reza Khondakar1, Prasanta Kalita2, Nicoleta Hickman3 and Ajeet Kumar Kaushik4 1

Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia 2Terrablue XT, New Delhi, India 3Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States 4NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States

5.1

Introduction

Cancer is one of the high mortality diseases which is a threat to human lives for immature deaths [1
4]. Therefore, the early and accurate detection of cancer is highly important for clinical diagnosis using cancer biomarkers [5
7]. Cancer biomarkers comprises variety of molecules, including cell, DNA/RNA, proteins, lipids, and exosomes, etc. in human body fluids that can be objectively measured and evaluated as an indicator for a normal biological process, pathogenic process, or pharmacological responses to a therapeutic intervention [8
10]. The detection and analysis of cancer biomarkers are being investigated to develop reliable, costeffective, powerful detection and monitoring strategies for cancer risk indication, early cancer detection, tumor classification, and cancer recurrence [11
13]. However, there are challenges for precise diagnostics in cancer treatment using current technologies including Raman-based immunoassays. Significant progress in nanotechnology-based cancer treatment has been achieved due to multiple advantages: high efficient, high sensitivity, multitasking, scalable sample handling, rapid sample processing and the precise control of fluids in an assay, etc. [14
18]. These new revolutionized platforms have transformed the point-of-care diagnostics into a reality for its automation and Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00007-X © 2021 Elsevier Inc. All rights reserved.

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high-throughput capability. The evolution of micro- and nanosystems with high-throughput analytical microscale devices shows great potential for the high-sensitivity detection of various chemical and biological molecules including tumor cells [19]. Among the various detection platform, Raman/surface-enhanced Raman spectroscopy (SERS) has emerged as an alternative to for the development of diagnostic tools for cancer disease [20
22]. This has been achieved by conjugating noble metal nanostructures (gold or silver nanostructures) with various Raman reporters to the analyte to amplify SERS signals by the localized surface plasmon resonance (SPR)-induced electromagnetic field enhancement. Apart from high sensitivity and minimal photo bleaching, SERS barcodes of individual analytes exhibit excellent multiplexing capabilities because of the very narrow spectral width of Raman peaks (typical enhancement factor 106
109) [22]. SERS-based immunoassays have been utilized for sorting, separating, mixing, and detecting the various cancer disease biomarkers [23
26]. A typical SERS immunoassay consist of SERS nanotags with a detection platform for sensing biomolecules (Fig. 5.1). We have provided significant facts on the use of SERS nanotags in conjugation with the nanosystems as the molecular detection for in vitro diagnostics, in vivo spectroscopic detection of cancer biomarkers. We finally conclude with a discussion of challenges and opportunities in developing next-generation SERS-based assay for translational research opportunities.

Figure 5.1 A schematic illustration of a Raman-based assay for biomolecule sensing. SERS, Surface-enhanced Raman spectroscopy.

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

5.2

History and working principle

SERS is considered as one of the most powerful and highly sensitive technique to analyze inorganic material, chemical, and biological samples [27
29]. As the name suggest SERS works on the principle of Raman spectra with enhanced Raman signals through surface modification in the substrate. After discovery of Raman effect by one of Indian physicist Sir Chandrasekhara Venkata Raman in 1928, it finds a huge popularity in scientific world as a highly sensitive tool to provide molecular spectroscopic finger printing for individual materials [30]. Raman spectroscopy is an inelastic scattering of light that probes the molecular vibration energy level due to interaction of light with the material [31,32]. In Raman scattering, monochromatic light interacts with the molecules of the analyte material and polarize the electron cloud. The electrons in the sample absorb energy from the incident photon and get excited to the higher energy state (hʋi) for very short period, where h is plank constant and ʋi is the frequency of incident light. The excited electron falls back to the ground state releasing energy (hʋs) in the form of another photon, where ʋs is the frequency of the scattered photon. If the energy of the released photon is equal to the energy of the incident photon, i.e., the frequency of the incident photon and scattered photon is same (ʋi 5 ʋs), then it is called Rayleigh scattering. However, sometimes when the electrons fall from excited state to different vibrational state that has slight different energy (either higher of lower than ground state). In that case, the frequency of incident photon and released photon no longer remain the same (ʋi ¼ 6 ʋs). This kind of scattering is known as Raman scattering (Fig. 5.2). Depending up on the final energy state, Raman scattering are categories in to

Figure 5.2 A typical Raman scattering mechanism.

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two types. If the energy of the final state is higher than that of ground state, i.e., electron absorbs energy (ʋi . ʋs), then it is called stokes line. On the other hand, if the energy of the final state is lower than that of ground state, i.e., electron released energy (ʋi ,ʋs), then it is called antistokes line. The scattered light will have mostly the same wavelength as incident light and a small amount (1026%) of the scattered light will have different wavelength based on the molecular structure of the material. These scattered light gives the fingerprint of the molecular pattern of the interacting material. For the discovery of this scattering phenomenon, Sir C. V. Raman received the Nobel prize in 1930. Raman spectroscopy is a nondestructive characterization technique that allow users to choose any excitation wavelength incident light specific to a material [32]. It can study large molecules including chemical and biological samples without using any marker. But due to a low scattering cross-section it is limited to many applications which is a major drawback in simple Raman spectroscopy. However, the Raman intensity can be increased by increasing the intensity of the incident beam. Mathematically, the dependence of Raman intensity can be correlated to incident bean as follows:  Irs N

@α Eo ½cosðωo 2ωγ Þt 1cosðωo 1wγ Þt @Q

2

where Irs is Raman scattering intensity, α is molecular polarizability, Q is nuclear displacement, ωo and Eo are angular frequency and amplitude of the incident beam. Stokes and antistokes components of the beam are given as ћðωo 2 ωγ Þ and ћðωo 1 ωγ Þ, respectively. To counter this limitation, several theories proposed to enhance the electromagnetic field strength of the illuminating beam. Cavity-enhanced Raman, photonic crystal enhancement, Raman surface enhancement, etc. are the methods that enhanced the Raman signal multifold. Among these, surfaced enhanced Raman technique is the most popular in scientific community and find huge application due to its simplicity and effective [33,34]. The surface-enhanced Raman spectrum was discovered by Fleichmann et al. in 1974 while recoding Raman spectra of pyridine (Py) molecule adsorb on a electrochemically roughened silver (Ag) substrate [35]. The group reported to observed multifold enhancement in Raman signal strength due to multiplexed cross-sectional area. Afterwards, in 1977, Jeanmaire and Van Duyne stated that the surface area is not only the prime factor

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

in the above phenomena, and they bring the concept of surface plasmon-enhanced mechanism to explain the enhancement in the Raman signal strength [36]. The Raman signal get enhanced when the analyte molecule remains in close proximity to a metal nanostructured surface. The metal nanostructure provides very high electron density in the interface to the analyte which leads to show SPR effect upon interaction with incident light. Local electromagnetic field strength in the molecule near the metal surface enhances due to SPR effect which results in high Raman signal strength. This theory is wide accepted by the scientific community and renamed the phenomena as SERS. Although electromagnetic theory is applicable to most of the analyte, yet it could not explain the magnitude of enhancement in certain molecules specifically the molecules having lone pair of electrons in which molecule can form bond with the metal substrate. Later, another theory attempted to explain the SERS effect according to which charge transfer takes place from adsorb molecule to the metal. This leads to a modified Raman spectrum with multifold enhancement in certain cases which is known as chemical enhancement. These two theories explained the contribution in enhancement of multiplexed Raman signal.

5.3

Application of Raman-active nanostructures

To get a proper Raman scattering signal, in general, nanostructured materials are either fixed on to a large surface or free in suspension for liquid sample in the form of colloid particles [37]. Suitability of the materials depends upon the sample and the shape and size. There is a huge impact on the SPR properties based on the size of the nanostructures which can vary from 1 to 500 nm which leads to the overall impact on the Raman signal. In the nano regime, metal atoms remain closely packed to a confined area providing more surface to volume ratio, which results in the discretization of the energy level due to overlapping of the electron orbits of neighboring atoms. As a result, large number of electrons are available on the surface of nanomaterials which couple with the excited electrons from the metal adsorb Raman scattering molecule (analyte) and energy exchange takes place leading to polarization of the molecule. This phenomena results resonance vibration of the electron cloud and enhance the electromagnetic molecular scattering by multifold time (about the order of 104
107). Therefore,

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electromagnetic enrichment in the scattered Raman intensity is considered as the prime factor for enhancement mechanism [38]. The nanostructured plasmonic materials can have various shape in the form of particles, quantum dot, nanowire, nanofilm, shell, core shell, sea urchin, even cage, etc. In SERS, selection of material plays an important role to get enhanced Raman spectra. The suitability of the materials depends on many factors like stability, Raman enhancement strategy, compatibility with the analyte sample, cost and availability, chemical bonding with the substrate. Few materials dominate electromagnetic enhancement, few chemical enhancements and few contribute both electromagnetic and chemical enhancement. Secret recipe of material selection lies on the strategy for Raman enhancement as mentioned. Plasmonic nanomaterials (such as Au, Ag, Cu) have been widely used for various applications specially for clinical, healthcare monitoring, and biomolecule identification [39]. These metal particles show SPR effect in the entire visible range in electromagnetic spectrum which contributes to electromagnetic enhanced Raman signal. Specially the Au and Ag surface modification and apart from these 2D materials (graphene), carbon derivatives (carbon nanotubes), alkali metals (Li, Na, K, Rb, Cs, Al, Ga, In, Pt, Rh), semiconductor materials (TiO2), and hybrid materials (metal composite, SiO2 encapsulated Au particles) have been also reported to use in SERS [35,37]. Raman enhancement from these materials are mostly due to chemical enhancement or both. Still, research is going on in the scientific community to explore other noble materials to further enhance the Raman signal.

5.4

Surface-enhanced Raman spectroscopy platforms in cancer diagnostics

Cancer is one of the major causes of high mortality among humans. Therefore, early screening of cancer would aid in its prognosis, or predict therapeutic response, is to use blood and tissue biomarkers by combining nanotechnologies [40]. The high sensitivity, selectivity, and multiplexing capabilities of SERS technologies are attractive aspects that have supported their integration into molecular diagnostics for in vitro cancer detection. The most common approach involves immunoassays that rely on the recognition of circulating biomarkers (like cancer cells, protein, nucleic acids, etc.) with antibodies and nucleic acids that are conjugated to SERS substrates known as SERS nanotags [24].

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

Every nanotag provide a unique barcode for each set of targets proving very specific and sensitive detection of cancer biomarkers. The results can be analyzed based on SERS spectra as well as imaging of target molecules. Apart from that, Raman-based immunoassays are being investigated as the point-of-care diagnostics for quicker analysis of human blood samples in healthcare sector. Currently, most the researchers have focused their attention to detect and analyze circulating biomarkers (cells, proteins, nucleic acids, etc.) in human blood in clinical settings.

5.4.1

Cell analysis

Cell analysis has various application in a clinical setting to understand the various diseases [41]. The presence of various proteins on the cell surface has been used to identify the disease condition. SERS nanotags are conjugated with various cell-specific biomarkers like peptides, antibody, aptamer, etc. to identify the cell type [42]. Cell analysis includes different types of processes like sorting, isolation, detection, etc. Sorting of cells is a successful application of SERS-based immunoassays, for detection and classification of cells (e.g., stem cells, CTCs, T cells). Generally, cells are distinguished by various proteins on their surfaces. Cells are being sorted using SERS nanotags: decorated with cell biomarkers expressing the levels of proteins on the cell surfaces, which eventually contributes to the identification of cells. One of the interesting works of CTC analysis was done by Reza et al. where they captured and detected single CTCs using SERS enabled alternating current electro hydrodynamics (ac-EHD) immunoassay platform (Fig. 5.3) [43]. Fig. 5.3 also shows false color SERS image of a captured cancer cell (SKBR-3 cell from a breast cancer tumor spiked in patient serum) captured on the graphene functionalized gold electrodes. Also, Pallaoro et al. used a hydrodynamic flow focusing device to sort out mammalian cells (a mixture of cancerous and noncancerous prostate cells incubated with SERS biotags) in a single-file line located at the center of the microfluidic channel to cross a focused laser beam at the interrogation region [44]. SERS identification of the cells was realized by measuring the relative signal from a cancer-specific marker versus a cellidentifying universal control marker. Further, SERS microfluidic assay have improved the cell detection technology by scanning single cancer cells [43]. Syme et al. reported about a PDMS structure to trap living cells functionalized by a labeled colloid and thus realized the time-resolved Raman mapping of intracellular nanoparticle labels [45]. These SERS-based assays have

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Figure 5.3 Schematic diagram of cell and protein biomarker detection using an ac-EHD induced SERS-immunoassay. SERS, Surface-enhanced Raman spectroscopy.

improved the cancer diagnostics to understand the clinical stages of the various cancer patients.

5.4.2

DNA and RNA analysis

The sensitive and specific detection of DNA sequences coding for particular diseases is extremely important when trying to understand disease progression and in developing novel detection methods [46]. Current methods of DNA detection, such as PCR and fluorescence, are limited in multiplexing capabilities and are at a higher risk of contamination issues. DNA/RNA detection is increasing in popularity due to the increasing knowledge of sequences identifying pathogens, cancerous mutations, and inherited genetic diseases. The detection of DNA sequences coding for cancer disease is very significant to understand disease condition and stage determination for better diagnosis. However, current methods of DNA detection using PCR and fluorescence lack multiplexing capabilities. Further, nucleic acid detection methodologies can have costly complex procedures and problems with false positive signals. Alternatively, SERS provide an easy and cheaper detection platform with high sensitivity and specificity even in complex sample. SERS labeled DNA oligonucleotides can be identified by complementary nucleotides decorated within SERS microchannels. The first time detection of oligonucleotides in a Raman-based assay were developed by Frances et al. [47]. They constructed a simple microfluidic platform for sensing three types of nucleic acids. Furthermore,

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

various SERS-based systems have enabled single DNA detection improving the sensitivity up to the single analyte level [48]. Recently, Zhang et al. used micro RNA as the next-generation cancer biomarker for developing a smart multifunctional probe for dual cyclical nucleic acid strand-displacement polymerization in SERS-based platform [49]. Currently, circulating tumor DNA/RNA (ctDNA/ctRNA) are being considered as a potential biomarker for detection of cancer. The greater challenge in detection of (ctDNA/ ctRNA) is the presence of very minute amount in human blood. It is very important to develop highly sensitive sensors to track these circulating biomarkers in human body. In this regard, a highly sensitive enzymatically amplified SERS-based frequency shift assay was developed to detect ctDNA in serum samples from lung cancer patients [50]. They achieved subfemtomolar-level sensitivity in fetal bovine serum. These results show promising SERS platform for cancer diagnostics.

5.4.3

Protein analysis

The understanding of specific protein interactions can provide abundant information on particular biological pathways, especially in disease progression. Furthermore, detection of specific disease-related protein biomarkers can be invaluable for the detection and diagnosis of disease. Since, there are no such available methods for protein amplification like PCR for DNA amplification. Therefore, it is crucial that highly sensitive detection methods are developed for the detection of the low concentrations of proteins present in clinical samples [46]. SERS multiplexing has also made an impact on the detection of low concentration of proteins where SERS analysis methods have been developed for the detection of specific antigens and protein interactions, to monitor specific biorecognition events and for the detection of cellular proteins. SERS-based protein detection system has been well explored and achieved a significant step toward cancer diagnostics in various ways [51]. Here, we explored some of the well achieved detection platforms. In one of the pioneering works, Wu et al. fabricated a SERS-assisted 3D barcode chip for parallel detection of multiple protein targets (lower detection limit was 10fg/mL) in multiple samples using Au@Ag nanorods composites [52]. Further, Lee et al. developed another Raman-based immunoassay (gold array-embedded gradient microfluidic device) for multiple α-fetoprotein samples detection [53]. Also, Wang et al. showed that sera from patients with pancreatic cancer (pc) produced a significantly higher SERS response for mucin protein MUC4 compared to sera from

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healthy individuals [54]. In addition to these SERS-based immunoassays, Trau group developed an indigenous platform known as SERS ac-EHD platform for multiple protein analysis from cancer patient samples. This ELISA like microfluidic platform enabled them to detect and analyze 20 different concentrations of protein biomarkers in a single chip which consist of five channels of gold based asymmetric electrodes. These results indicate that SERS-based immunoassays can monitor protein levels in patient samples, representing a much needed first step toward assessing the potential of this protein to serve as a serum marker for the early stage diagnosis of cancer.

5.4.4

Extracellular vesicles analysis

Extracellular vesicles (EVs) or exosomes are secreted nanovesicles present in healthy and diseased human body [55,56]. This nanosize circulating biomarkers are present in abundance in normal and pathophysiological conditions and the detection and characterization of EVs are challenging because of their small size, low refractive index, and heterogeneity [57]. Recent theory suggests that they act as the communicating agent between different tumor cells. It has been shown that cancerous cells release exosomes in large quantity and plays a pivotal role in cancer disease progression [58]. Recently, EVs, especially exosomes, has emerged as a potential new class of biomarkers for early detection and treatment monitoring in cancer and other diseases [59
64]. Zong et al. developed a SERS-based strategy for the detection of tumorderived exosomes (1200) using a sandwich-type immunocomplex can be formed between the SERS nanoprobes, exosomes and magnetic nanobeads obtained from the SKBR3 cancerous cell [65]. Further, Jing et al. developed a multiplex EV phenotype analyzer chip for monitoring patient treatment responses based on the plasma EV phenotypic evolution of eight melanoma patients receiving targeted therapy and checked the drug response on the EVs for monitoring treatment responses [66].

5.5

5.5.1

Other bioanalysis application: the notable application of Raman-based assays Bioimaging

SERS nanotags have been established as proven imaging agents and promising drug-delivery sensors for disease detection

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

[67]. SERS-active nanostructures may have emission crosssections rivaling those of fluorescence, implying that well-crafted SERS biotags are in principle possible that are almost as bright as fluorescence biotags [68]. The narrow SERS bandwidths offer much greater facility in deconvoluting the various contributors to a composite SERS spectrum resulting from the simultaneous use of multiple labels. Pallaoro et al. demonstrated bioimaging application of SERS using Ag clusters integrating both the pHsensitive Raman probe molecule 4-mercaptobenzoic acid and a fluorescent dye [67]. They determined the local pH from the spatially mapped surface-enhanced Raman spectra correlated with the fluorescence, allowing simultaneous single-particle tracking and local pH sensing.

5.5.2

Drug delivery

Currently, a lot of work toward cancer research in drug delivery to the human body for precise diagnostics are being explored extensively. Therapeutic drug monitoring is one such approach in cancer therapy for the investigation of newly synthesized drugs for the assessment of drug concentration in clinical conditions and find a suitable dose for a narrow therapeutic range [69,70]. Among them, SERS has emerged as the promising portable tool for rapid analysis of several drug concentrations in complex biological samples like human serum or plasma [71,72]. One of earliest work in this arena is done by Ackerman et al. They reported about the online detection of gradient-driven concentration fluctuations of two different drugs, namely the antihistamine and tranquilizer promethazine and the anticancer agent mitoxantrone [73]. They demonstrated that drugs can be monitored directly for hours applying the highly sensitive SERS technique without the need of any washing or rinsing steps of the studied chips with aggressive chemicals. Sun et al. reported about a highly sensitive SERS-based analytical system to quantify the dynamic concentration of anticancer drug doxorubicin (DOX) in human blood plasma and demonstrated continuous real-time monitoring of the free DOX concentration [71].

5.5.3

Raman spectroscopy to evaluate drug binding and release

Raman spectroscopy has emerged as a powerful to evaluate functional changes in materials associated with a process and procedure. For example, exploring drug-delivery system (DDS) with reference to a targeted disease is getting attention in order

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to develop next-generation therapy based on the concept of nanomedicine or nanotherapeutics [74]. Developing a DDS is a multistep procedure and every step must be optimized to achieve best efficacy of a nanomedicine. This can be accomplished in timely manner, if scientist introduce effective, rapid, and efficient analytical tool to evaluate various type of bonding takes place between material and bio-actives compounds. Kaushik et al. design and developed a nanomedicine consist of magneto-electric nanoparticles (MENPs composed on BaTiO3 as shell and CsFe2O4 as core) [75] and CRISPR-Cas9/gRNA (an edited gene) to recognize and eradicate latent HIV virus in the brain [76]. In this approach, Cas9/gRNA binds with MENPs via electrostatic binding and released from MENPs surface on applying AC-magnetic field stimulation. This magnetically guided and on-demand controlled approach is demonstrated in appropriate cell types and Cas9/gRNA binding and released was also verified using Raman spectroscopy as illustrated in Fig. 5.4. Raman spectroscopy successfully confirmed the formation of MENPs, binding with Cas9-gRNA with electrostatic binding, and release of Cas9/gRNA on applying external AC-magnetic field, and correlated the spectra of MENP pure along with after the

Figure 5.4 Raman spectra of MENPs (A) and successful demonstration of Cas9/gRNA binding with MENPs and release on applying AC-magnetic field (B); Raman spectra of Cas9/gRNA (a), Cas9/gRNA-MENPs nanomedicine (b), pure MENPs (c), and release of Cas9/gRNA from MENPs surface after AC-magnetic field stimulation. MENPs, magneto-electric nanoparticles. From: (A) Scientific Reports 2014; (B) Scientific Reports 2018.

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

release of drug. The kind of possible binding and debonding between MENPs and Cas9/gRNA during DDS formulation and treatment procedure was clearly demonstrated by Raman spectroscopy within the minutes. Such advancement projects Raman spectroscopy as an essential analytical tool in biomedical sciences.

5.5.4

Raman to evaluate nanoparticle-bio interface

Kaushik et al. have utilized Raman spectroscopy and microscopy based combinational approach to evaluate biocompatibility of MENPs at the interface of brain and peripheral tissue of nonhuman primates [77]. The MENPs were administrated in a baboon for delivery to the brain using magnetically guided approach. In this process, the MRI was used as a tool to navigate nanoparticles to the brains and confirm nanoparticle delivery via pre/postimaging. One of the challenges in this research was to evaluate biocompatibility of nanoparticle to suggest future application as development of novel therapy. In practice approaches such as ELISA and blood toxicity profiling are effective bot not capable to explore MENP-tissue interface. To solve this puzzle, Raman spectroscopy was utilized to evaluate functionality of MENPs (Fig. 5.5A). The Raman microscopy was utilized for visual inspection of MENPs presence at major region of interest, mainly brain and peripheral organs (Fig. 5.5B
G). The Raman spectroscopy of MENP-tissue interface confirmed the tissues does compromised bands associated with DNA, RNA, lipid, amine group, carboxylic group, C
H bonds, C
N bonds, etc. confirmed that MENP does not affect tissue integrity. These findings confirmed that MENPs are safe for tissues can be used for developed MENP based biomedical application.

5.6

Future challenges and conclusions

The future of the Raman-based assays are being explored towards developing the point-of-care testing in order to improve the human health through a constant monitoring system, regarding the cancer diagnosis. The future technology would be consisting of assay automation, minimal hands-on processing and quicker decision making. With more research focused on the analysis of clinical sample in real time, this immunoassay could replace current gold standard techniques like ELISA kits and immunohistochemistry. Currently, the FDA-approved i-STAT

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Figure 5.5 A Raman combinational approach. Raman spectroscopy and microscopy to evaluate functionality of magneto-electric nanoparticle (A) and exploring its biodistribution in the brain on nonhuman primates (B
D) along with peripheral organs (E
G). MENP, magneto-electric nanoparticle. From: copyright permission ACS-2019, Kaushik et al.

Portable Clinical Analyzer (microfluidic chip) can perform a wide variety of point-of-care tests on the same instrument providing multiple test results for patients. The multiplexing, highthroughput capability, and portability features of these immunoassays can speed up the diagnosis, monitoring, treatment and transfer of patients as they potentially can be utilized in the hospitals, intensive care unit or emergency room. However, for successful clinical studies of these assays, it is also important to establish the standardization of sample collection protocol, statistical consideration for designing training and validation sets, and randomized clinical trials in multitude patients. Further, current technology development also focuses on understanding of cancer biology as well as assessing cancer

Chapter 5 Raman spectroscopy/SERS based immunoassays for cancer diagnostics

diagnosis. It would be interesting to see the transformation of Raman/SERS-based systems into a clinical device for quick decision making regarding cancer diagnostics and treatment.

Acknowledgment Authors acknowledge respective departments and institutions for providing support and facilities.

Conflict of interest Authors have no conflict of interest.

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4836.

Bioinformatics computer programming

6

Muhammad Sarmad Iftikhar1,2, Ghulam Mohyuddin Talha2, Muqadas Aleem2,3 and Amen Shamim4,5 1

School of Agriculture and Food Sciences, The University of Queensland, St Lucia, QLD, Australia 2Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan 3National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, Jiangsu, China 4Department of Molecular Cell Biology, School of Medicine, Samsung Medical Center, Sungkyunkwan University, Suwon, Korea 5Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan

6.1

Introduction

The prevalence of cancer is increasing day by day and it is the second leading disease in the world increasing death toll. Most incidence and mortality rates lie in Asia because around 60% of the world population lives there (Fig. 6.1). Europe and America come after Asia in cancer incidence and death rate. There are 23.4% of total cancer cases in Europe while the death rate is 20.3%. The United States accounts for 21% incidence and 14.4% mortality rate worldwide. The death rate in Asia (57.3%) and Africa (7.3%) is much higher than incidence (48.4% and 5.8%, respectively) due to different cancer types and management issues. It has been reported that one in five men and one in six women develop cancer during a lifetime and the death rate is one in eight men and one in eleven women. Hence, cancer is a life threat to humanity which should be cured by specific diagnoses followed by the efficacy of treatment [1,2]. Cancer could be due to several genetic or epigenetic lethal changes occurring by successive mutations in the genes, changing the functions of the cell [3]. Chemical compounds that are sometimes carcinogenic, e.g., smoking, have an obvious role leading to the formation of cancer cells [4]. Cytoplasm and nucleus can directly be affected by environmental chemicals ultimately leading to genetic disorders or mutations [5]. There are other factors as well, e.g., bacteria, viruses, and radioactive Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00009-3 © 2021 Elsevier Inc. All rights reserved.

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Figure 6.1 Pie chart presenting the percentage of the population in five continents.

rays, which can become carcinogenic and is responsible for 7% of all cancers [6]. Cancer results in disruption of cellular relations and loss of function in vital genes leading to abnormal proliferation of cells [7]. Genes responsible for normal cell growth and division are known as proto-oncogenes but become oncogenes due to dangerous mutations lethal for cell existence [8]. In addition, lack of tumor repressor genes is also the cause of uncontrolled cell proliferation [9]. Considering the cancer incidence, lung, breast, and colorectal cancers are the most prevalent types and ranked among the top five diseases in terms of mortality (1st, 2nd, and 5th). Worldwide, these three types are responsible for one-third of cancer mortality and incidence. Breast and lung cancer are leading in terms of detection of new cases; around 2.1 million diagnoses were estimated during 2018 for each of these types. Blood, lymph nodes, and brain cancer are most prevalent in children [10,11]. Being lethal this disease needs to be timely detected and cured. Many different techniques and methodologies have been developed for this purpose, but bioinformatics is time saving and efficient. Bioinformatics originated when Mendel discovered laws of inheritance back in 1865 and a big revolution came when Watson and Crick determined the structure of DNA in 1953 [12]. The work of bioinformatics started with the experiments of Dayhoff regarding atlas of protein sequences and modeling the structures of protein [13]. Afterward, the term “bioinformatics” was coined

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and used in the 1990s which was described by the analysis of data coming from DNA, RNA, or protein [13]. Another achievement was the announcement of an initial draft of the Human Genome Sequence in 2003. After 13 years of research, the Human Genome Sequence Project provided around 25,000 human genes. Hence, there was a bulk amount of genetic data that needed a platform to gather and organize this data. It opened the doors for the marriage of biology with computer science bearing a new baby known as bioinformatics. This meant to gather, organize, analyze, classify, and store the big genetic data in an efficient and powerful way. Computer science provided its space, algorithms, computational, and statistical techniques to biological data forming a new field and an era of modern biology. In a nutshell, this new field provided an information management system for molecular biology with plenty of practical applications. Bioinformatics can be defined as a transdisciplinary field that integrates biology, medicine, statistics, computer science, information technology, and machine learning. It also includes the development of new algorithms, construction and design of new software and providing theories to solve biological data problems. The main objectives of this field are • Organizing the biological data in a way that scientists can easily store and access the present information. • Developing and designing software tools to analyze and manage the data. • Using biological data to analyze and interpret the results in the biological sense. • Assisting pharmaceutical researchers to understand the structures of proteins helping in the drugs industry. • Assisting medical physicians to understand the structures of genes helping in diagnosis of diseases, e.g., cancer.

6.1.1

Bioinformatics in cancer research

Research in the medical field is improving day by day and much effort is expended to find ways to diagnose and treat hazardous diseases like cancer. With the discovery of the Human Genome Project, bioinformatics researchers started to apply this on cancer therapy and is now being applied in an efficient manner [14]. It was found that researchers use multiple databases and search engines to find biological data and apply bioinformatics tools for cancer diagnosis and treatment. It is need of the time to make available all the research and finding over databases to make it easy for others working in cancer treatment.

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After the availability of Human Genome Project publicly, bioinformatics has found its applications in many areas [15,16] • Locating genes by analyzing DNA sequences. • Predicting protein structures by analyzing RNA sequences. • Predicting the location of proteins in the cell. • Analyzing the images from gene expression. • Understanding hazardous diseases, e.g., cancer, sickle cell anemia, and cystic fibrosis. • Gene therapy for cancer and in general as well. • Drug designing for cancer treatment, avoiding side effects of the drugs, and developing an efficient drug delivery system.

6.2

Biological data

Biological data is always bulky and there could be four data types being generated at biological research [15], i.e., DNA, RNA, protein, and microarray photos. First three of these are text, and the last one is digital image. All of these can be represented with different data types, e.g., strings, graphs, trees, subgraphs, and subtrees. Strings are used to represent the sequence data of DNA, RNA, or protein while graphs for metabolic pathways and trees or subtrees to visualize protein structures. Moreover, strings are also used to write different comments on data reflecting biological meaning to scientists. The big volume of data collected during the course of biomedical research has increased, thanks in large part to powerful new research technological platforms to physically analyze, store, and understand data. In these technologies, the field of bioinformatics tackles big data by utilizing computational power. The main infrastructure of bioinformatics is based on storage data, integrate and access to large volumes of biological data and related information. In bioinformatics, scientists deal with a large amount of biological data, which is maintained by computational programming in a more intellectual way. In the biological dataset, genomics and proteomics dataset included advance imaging, whole-genome sequencing, protein biological samples, and clinical annotations. However, it is often difficult to deal with a bulk amount of data on these platforms. Researchers often lack access to raw or basic data generated by other studies or do not have enough infrastructure for the integration and analysis of data. Nowadays, scientists are focusing on virtual repositories as data clouds for integrating and improving access to the research dataset. These efforts of speeding up data integration are still in

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process; however, many questions are being raised to organize and coordinate clouds. Sequence databases are characterized by sequence information of the organisms. Gene Bank at NCBI (National Centre for Biotechnology Information), Bethesda, DDNJ (DNA Data Bank Japan), and EMBL (European Molecular Biology Laboratory) are some examples of DNA sequence databases. For protein sequences, SWISS PROT (protein sequence database at the Swiss Institute of Bioinformatics) can be explored. Microarray databases include the differential gene expression, i.e., under different biological conditions, e.g., Gene Expression Omnibus and ArrayExpress. Genome databases are comprised of gene sequences (DNA), e.g., Xenbase, SEED, Corn, and RGD [17]. The most common and important algorithmic trends in bioinformatics are • To find similarities among strings. • To detect patterns within strings. • To find similarities among spatial structures or motifs. • To construct phylogenetic trees. • To classify the data according to previously clustered annotated data. • Reasoning about microarray datasets and behavior of pathways.

6.3

Cancer nanomedicine

Cancer is becoming the most detrimental health problem globally, so effective treatment is required to cure it economically and efficiently. Some of the ongoing treatments include radiation therapy, chemotherapy, and surgery but these can affect normal tissues of the body as well along with the tumor tissues. There were six hallmarks determined for differentiation between tumor and normal tissue and also to provide better treatment options. These hallmarks consist of sustaining proliferative signaling, evading growth suppressors, activating invasion and metastasis, enabling replicative immortality, inducing angiogenesis, and resisting cell death [18]. Reprogramming energy metabolism and evading immune destruction are emerging hallmarks of cancer. Due to these developments, we can find better and improved options for its treatment, and nanomedicine is one of them. It can be defined as the use of nanomaterials ranging between one and 100 nm being applied to medicine for health [19]. We are facing the problems in treating cancer like rapid drug clearance, biodegradation, low specificity, and limited target of

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medicine [20]. Use of nanomedicines can reduce or minimize these problems as of their drug release profiles, size of the particles, high surface to volume ratios, and specific targeting, which allows the medicine to better reach the specific target and stable drug release in a controlled manner [21]. We can increase the targeting of medicine by using internal and external stimuli; also for controlled release of drugs to tumor tissue and leaving normal tissue safe. Bioavailability can be increased and rapid clearance of drugs can be prevented by using nanocarriers for drugs facilitating their way through the bloodstream. These are also helpful in the early detection of cancer and using combination therapies to cure cancer effectively. There could be different platforms to use as nanocarriers that are being investigated these days, i.e., viral, inorganic, lipid-based, polymer-based, and drug conjugated nanoparticles. Use of engineered particles can pave the way for new and improved noninvasive strategies for the treatment of cancer, including targeted combination therapy, nanoparticle enhanced radiotherapy, photothermal therapy, and nanoparticle enhanced radiofrequency therapy.

6.4

Large-scale approaches to the study of cancer

It has been a traditional approach to select genomic regions or proteins from cancer and healthy tissues and compare them to understand the cure of cancer. However, advancement in technology and data analysis, this paradigm is changing [22]. The new branches, genomics, proteomics, transcriptomics, and bioinformatics have sparked the new hypothesis testing for fast development in cancer studies [23].

6.4.1

Genomics

The study of an organism’s whole DNA sequence at a large scale comes under genomics. It established when Sanger’s group developed techniques to map, sequence and store DNA sequences [24]. Talking more specifically, it established with the decoding of bacteria’s (Haemophilus influenza) genome sequence [25]. These days genomics has become a very basic component of advanced biological research due to improved sequencing methods and development of tools to store and analyze this large data.

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Genomics techniques have revolutionized the field of biomedical research and the most relevant area is cancer genomics. This includes the integration of large-scale data generation and computational resources to understand changes in the genomes of tumor tissue [3]. It was identified in a recent study of two lung cancer cell lines that at base-pair level there were tandem duplications, deletions, inversions, inverted duplications, and interchromosomal rearrangements [26]. Bioinformatics approaches were developed to find variations in the lung cancer genome using short sequences as input and the human genome was a reference sequence. In another study, breast and colon tumor samples were used to understand the possible mutations. Firstly, around 18,191 human genes were selected and sequenced their protein-coding exons which yielded around 800,000 possible mutations. Bioinformatics tools were then used to remove normal variants, artifacts, and synonymous substitutions. It was identified that on average there could be 80 mutated genes per breast or colon tumor [27,28]. Recently, the same study was carried out for glioblastoma and pancreatic tumors [29,30].

6.4.2

Transcriptomics

When a genome is transcribed at any time, a set of transcripts is produced which is said to be transcriptome and the branch dealing with it is transcriptomics. A transcriptome is dynamic as compared to the genome as it varies among different tissues of an organism and the same cells of normal and diseased tissues which makes it more reliable for cancer studies [3]. Based on this argument, there is plenty of research on expression profiles of a large number of genes to identify the patterns of gene expression in tumor cells [31]. A metasignature of gene expression under different cancer types was identified and a new computational protocol was developed [32]. In this approach, 40 published microarray datasets of cancer were used with around 38 million gene expression measurements from 3700 cancer samples. It was found that 67 genes overexpressed in more than ten cancer types compared to their normal tissues. Using the same strategy, other authors also tried to find signatures of gene expression in different tumor tissues [33 35]. In another study, a sequence-based approach was used in which the set of computational methods was integrated with next-generation sequencing to study mesothelioma tumors from six patients [36]. There were 15 newly identified nonsynonymous mutations in this tumor type.

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6.4.3

Proteomics

Proteins, the product after translation, are an integral part of all physiological and metabolic processes of cell and body [37]. The branch dealing with expressed proteins, their modifications and interactions are called proteomics (analogy with genomics and transcriptomics). It is considered as the next step in biological research and could be difficult to study as well due to the variability of posttranslational modifications and interactions with other proteins [16]. Moreover, the techniques for genomics are far more powerful than proteomics in spite of the advances in mass spectrometry. Despite the challenges, it is growing rapidly to make contributions in clinical diagnosis and disease management for cancer. Several studies were carried out and identified the variable amount of proteins in the esophagus, prostate, breast, and ovarian cancer [38]. For example, in the blood of ovarian cancer patients, tumor markers can be unambiguously identified [39].

6.4.4

Bioinformatics techniques

During the past few years, DNA microarray technology has emerged to discover the relationship between disease patterns and gene expression. Among the diseases, cancer is the most commonly explored disease through this technique. Microarrays produce a large amount of data and the need for highthroughput computational techniques to analyze it. These have been used to examine differentially expressed genes in tumor and healthy tissues, genes correlated with progression of tumors, and genes which are able to distinguish cancer from normal cells accurately [40]. Microarray is much better than traditional techniques such as clustering, which is generally limited to single experimental run for specific cancer type. New techniques are not limited to single-chip analysis and look for higher-level patterns across multiple disparate microarray experiments. The use of module maps could be better for delineating the usual gene expression patterns across heterogeneous tissues and disease processes for cancer. Modules are identified by comparing the sets of relevant genes with expression data and extracting the subset which is coexpressed in a significant manner. These modules are better to reflect true biological processes as are directly linked to actual expression. These modules can be compared for all cancer types to find out the common signatures for underlying processes. Some of the bioinformatics techniques are compared with their pros and cons in the table (Table 6.1).

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Table 6.1 Comparison of advantages and disadvantages of bioinformatics techniques being used in cancer research [41]. Techniques

Advantages

Disadvantages

Microarray

• Gene expression of thousands of genes simultaneously • Detection of genetic markers for prostate cancer tissues • Predicting the survival rate for breast, lung, brain cancer and acute lymphocytic leukemia • Elucidates global patterns of the disease • Compares the same and different aspects of various tumors types • Applied to breast cancer • Detection of genetic regulators of cancer genes’ expression • Identification of mechanisms favoring metastasis • Detection of profiles expressed for a subset of tumor samples • Identifies the outlier expression profiles

• Relative insensitivity to detect low-level expressions • False microarray data can be generated • Provides information about the genes only present on the array

Module maps

SLAMS (Stepwise linkage analysis of microarray signatures)

COPA (Cancer outlier profile analysis)

6.4.5

• Lack of standardized and detailed information for annotation of experiments • Correlation may be due to chromosomal proximity • DNA copy number might not be associated to change in gene activity • Could be difficult to learn its programming language

Bioinformatics tools: application in cancer therapy

The second-most common and fourth leading cause of cancer death in colon cancer [42]. It is heterogeneous disease differing at each step, i.e., clinical therapy, response to therapy, gene mutation, epigenetics, and prognosis [43]. It has been reported that multiple genes and pathways are responsible for their occurrence [44]. It can be detected using microRNA (miRNA) that which genes are responsible for its development. MicroRNA (miRNA) is a small noncoding RNA molecule that comprises around 21 25 nucleotides and targets the messenger RNA (mRNA) for the regulation of gene expression at the translation stage either by its inhibition of breakdown [45]. These are responsible for epigenetic mechanisms controlling gene expression during many different pathological conditions and saving from cancer [46] while dysfunction of miRNAs can lead to the development of cancer [47]. Many researchers have reported that how the miRNAs lead to or save from cancer [48 51]. It is

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necessary to find out miRNA for predicting genes to develop early diagnostics and treatment of colon cancer. Following is the process of how miRNAs can be used to detect genes. Firstly the database is explored to get high quantity miRNAs expression data, i.e., Gene Expression Omnibus (GEO). This database includes gene array, sequences of DNA, RNA, and ChIP. Different keywords can be used to get the data, e.g., colon cancer, microRNA, Homo sapiens, etc. GEO2R is an online tool available at NCBI to compare different groups of differential miRNAs across all experimental conditions. Then target genes are predicted using the FunRich online tool. This can be used to perform miRNA enrichment analysis for prediction or to find miRNAs using provided target genes. Pathway analysis: To annotate the genes and classify biological attributes for genomic and transcriptomic data, Gene Ontology (GO) analysis is carried out. To understand the targeted genes online bioinformatics tools are used, i.e., KEGG (Kyoto Encyclopedia of Genes and Genomes) and DAVID (Database for Annotation, Visualization, and Integrated Discovery). Using these tools, biological processes, cellular components, molecular functions, and pathways are conducted [52,53]. Module Analysis: An online tool STRING (the Retrieval of Interacting Genes) is used to conduct PPI (protein-protein interaction) information. Further to find out relationships among differentially expressed genes, a software tool CYTOSCOPE is used and module analysis is carried out [54,55]. If we need to find out differentially expressed miRNAs then the online tools which can be used are; PITA, TargetScan, miRDB, miRWalK, and miRanda [56].

6.5

Artificial intelligence

It is an approach to create a product, e.g., computer or robot which can think smartly as humans’ brain understand, process, learn, and respond to solve a problem. Specifically, it is a branch of engineering with computations to understand the intelligence or intelligent behavior and creating the products having such behavior [57]. Most of the work in this field of modern era was inspired by Aristotle as per his three-part deductive reasoning, i.e., syllogisms. This made the basis for work to establish logical thinking. Those programs in the computer which make this gadget function more efficient than humans are artificial intelligent systems. A British mathematician (Alan Turing) is one of the earliest scientists as founder of AI and computer science. He coined the concept of gaining

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human level performance in different tasks through computers. Later, this idea got popularity as Turing test [58]. Researchers have discovered the applications of these techniques in almost all the fields to help humanity. The uses of AI in medical surgery was searched by Gunn in 1976 while diagnosing the abdominal pain through computer [59]. Last 20 years have proven as the area of technology where these techniques have been employed in the field of medicine as medical AI. This concept was first appeared in 1956 with the aim to build such machines having ability of thinking and reasoning on different tasks as humans do. Since then, AI has emerged as a reality to apply its theory in medical research laboratories. AI has now been expanding into many sub-branches, i.e., machine learning (ML), expert systems, recommendation systems, language processing, compute vision, fuzzy logic, and evolutionary computing. Basically, different algorithms are used in ML to process the data, learn underlying patterns, and providing predictions based on insights about real world data [60]. Traditional software has specific hard coding which can only solve specific tasks while ML uses big datasets to train itself and apply those patterns in learning the accomplishment of tasks. There are two modes of learning methods, i.e., supervised and unsupervised to train the deep neural network. Advancements in this field in recent years has provided different learning methods, e.g., residual network, making deep learning (DL) as learning method alone. Simply, ML is used to create AI and DL is used for implementation of ML. Though, there are some limitations of DL too [61]. • To get an accurate model, large amount of data are required while in real life there could be small quantities of biomedical data. • Some fields only require simple and traditional ML techniques. Complex DL methods are disregarded.

6.5.1

Artificial intelligence in cancer diagnosis

A clinician diagnoses the disease based on his knowledge and clinical experience while looking at the patient’s symptoms. This diagnosis could be misleading as he only has limited knowledge and experience hence accurate diagnosis will not be guaranteed. This is the limitation of human brain which cannot integrate the real data of whole world. Here come the AI models which can handle heaps of data for integrative processing. This results in the increased accuracy of diagnosis due to effectiveness of learning. DL describes the models able to extract

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information from images and have been used for unprecedented progress. All these algorithms have been successfully applied in various medical field and in most cases, they have attained performance better than human clinical experts. Additionally, DL is being used for image processing, which is not possible by human brain efficiently [62].

6.5.2

Solid tumor diagnosis

AI has been proved efficient in the diagnosis of both solid and nonsolid tumor. A model, deep convolutional neural network (DCNN), showed its accuracy in diagnosis of thyroid cancer by image analysis of clinical ultrasounds [63]. This model has shown efficacy in its sensitivity and specificity comparable to skilled radiologists which can further be enhanced by clinical trials. Hu believed that accuracy of DL models will positively influence the clinical practice [63]. DCNN model has been validated using largest number of images available to date [64]. Yet, the small-scale validation was not enough to refer it solely for diagnosis as it needs to be validated according to different geographical settings [65]. AI was applied for gastrointestinal endoscopy, but it still needs improvement and a breakthrough is suspected in following ten years [66]. A system, i.e., CNN-CAD (convolutional neural network computer-aided detection) was constructed based on images for endoscopic resection. This was accomplished with high specificity and accuracy for early gastric cancer being distinguished from submucosal invasion and overestimation of invasion depth [67]. AI also reduced unnecessary surgeries after endoscopic resection of colorectal cancer (CRC) without lymph node metastasis (LNM). AI has found its way in diagnosis of breast cancer. A DCNN model was used for its classification in digital breast tomosynthesis (DBT) [68]. For intermediate stage tuning of the tumor, a multistage learning technique using data from auxiliary domains [69]. Additionally, deep belief networks (DBNs) with extreme learning machine (ELM) classifiers can be used for fine tuning of network weights and biasness. Breast cancer diagnosis can be improved by addition of genetic algorithms. For pulmonary nodule detection, automatic classification of the nodules can make screening efficient and reduce the number of visits. The performance of this approach was quite closer to human expertise [70]. A neural network (BPNN) used each feature and three classifiers for decision making achieved AUC values of 96.65%, 94.45%, and 81.24%, respectively. This was

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quite high as compared to other techniques [71]. An automated nodule detection framework with a 2D CNN assisted the reading process having improved sensitivity with decreased false positivity. This illustrates the improvement in accuracy for pulmonary nodule detection [72]. A DCNN model was trained to classify lung tumor and normal tissues using images from The Cancer Genome Atlas [73]. Another DL-based model was proposed which was far better than physicians in classification and detection of malignant nodules in lungs from chest radiographs [74]. This model was good enough to aid clinicians as second reader. Other models based on Bayesian network meta-analysis are in use to evaluate efficacy and safety. These models are helping clinicians for diagnosis and policy makers for informative decisions [75,76]. ML-based models used quantitative texture analysis (QTA), which can differentiate subclinical adrenal tumor cells [77]. Different classifiers were added in the model, which helped in diagnosis of lesions on unenhanced MRIs which was 73% better than an expert radiologist [78]. For risk assessment of prostate cancer, ANN-based model was used with 90% sensitivity and 15% 20% enhanced specificity [79]. For the classification of skin tumor cells, CNNs could achieve performance better than experts which demonstrates the value of AI [80,81].

6.5.3

Nonsolid tumor diagnosis

Groups of lymphomas in nonsolid tumors with unequal growth can be distinguished with a combination of parameter instead of single one. This was confirmed by cluster and discriminant analyses from non-Hodgkin lymphomas (NHLs) [82]. DLbased models for automatic analysis from eosin stained images results in improved detection and accuracy for classification [83]. Additionally, metastatic breast cancer in lymph node biopsies could be detected by DL-based algorithm, i.e., LYNA (LYmph Node Assistant). This ultimately helps in productivity of pathologist and reducing the number of false negatives [84].

6.5.4

Artificial intelligence in cancer treatment

Analysis of human genomics has been facilitated by optimization algorithms and effective AI techniques. Previous studies presented an optimized DL approach based on BPSO-DT (binary particle swarm optimization with decision tree) and CNN for classification of various cancer types based on gene expression data of tumor RNA sequences. Cancer types under

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investigation were uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), lung squamous cell carcinoma (LUSC), breast invasive carcinoma (BRCA), and lung adenocarcinoma (LUAD). There were three phases of this approach. First phase was to optimize high-dimensional RNA sequence based on BPSO-DT and convert that to 2D images. Second phase was augmentation, i.e., to increase the dataset five times larger than original by the least manipulation of images. This helped the model to overcome the problem of overfitting and achieving better accuracy. Third phase was deep CNN architecture where convolutional and fully connected layers were described to classify different cancer types. This approach enhanced the accuracy of detection for five classes of cancer and was less complex [85].

6.5.5

Artificial intelligence-enabled nanomedicine

Drug synergism can be facilitated to improve effective cancer treatment by optimizing the drug combinations. This task is difficult as selection for the right combinations is tedious. This includes right drugs, their doses, and frequency of doses while reducing the toxicities too. Additionally, different combinations can generate unexpected toxicities in biological systems. Multifunctional nanomedicine is effective in its therapeutic efficacy but have optimization hurdles. Hence, the combination of nanomedicine and AI could overcome the problem and improve cancer therapy [86]. Recently, a feedback system control was constructed with the help of AI to standardize the drug combinations to produce maximum cytotoxicity. Various combinations were used for breast cancer cell lines. This resulted in better combinations of AIoptimized drugs [87]. Another feedback system control was streamlined for renal cancer using ten broad-spectrum drugs and found best combination presenting synergistic activity and reduced effect on non-malignant cells [88]. A quadratic phenotype optimization platform (QPOP) was developed to find optimal combination from 114 drugs for bortezomibresistant multiple myeloma. This model can be used to overcome problems of combinations, optimization, and selection [89]. Another AI platform known as CURATE. AI was constructed based on phenotypic response surface correlation. It was validated and used to standardized for tuberculosis therapy. It reduced prostate specific antigen in the patients and ceased disease progression [90].

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6.6

Programming language

A special language system used by the programmers to develop various scripts, application, and instructions for computers are called programming language (PL) and is divided into two components, i.e., syntax (structure of the code) and semantics (meanings assigned to characters, words or symbols). There are various language systems being used these days, e.g., A 1 , A11, B, NET, Bash, Babbage, C, C11, Go, R, Python, Java, JavaScript, Kotlin, and Swift [91,92]. The codes or scripts are given to computing devices for output. These are the devices which can execute the codes or input automatically and logically. Computer is one of the examples of computing devices which is being used worldwide as control console in various fields. This saves human resources, reduce human errors, and increase the speed of production by automation. A huge technological advancement has been observed in computers through recent years resulting in various new applications in all the fields [93].

6.6.1

Programming language in cancer diagnosis

Detection of cancer at an earlier stage can decline the unwanted death [94]. It is important to design mathematical models which can be used in low computing devices, i.e., smartphones, tablets, etc. Breast cancer, one of the leading cancer types, needs to be detected as early as possible to cure it properly. One of the ways to detect it is biopsy i.e. to take biopsy from the breast of the patient and analyzing it in the lab. This procedure has high accuracy but is painful for patients and many of them are not interested in this as a loss of part of the breast [95]. Newly developed procedures including conventional imaging (CI) or complex imaging of the breast is quite helpful in early cancer detection and without biopsy. There are other methods, e.g., magnetic resonance imaging (MRI), positron emission tomography (PET), but these are expensive too. These procedures were used recently for famous Hollywood actress Angelina Jolie, who endured a double mastectomy as she was carrying defective BRCA1 and has 87% risk of evolving breast cancer [96]. Various detection systems for breast cancer have been developed using multigene genetic programming and are successful too [97]. There is a model called select and test (ST) which uses input generation mechanism. This system employs the use of the mechanism for producing input. Different attributes from the

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dataset are translated using the developed mechanism into tokens recognized by the diagnostic model. Tokens are then processed by reasoning structures of model’s algorithm, which carried the diagnostic task based on ontological knowledge base [98]. Results are then formatted, and necessary decision making is done based on that. Once a model has been developed, it is then improved by feeding it the more data and improved and extended features of the dataset. The bigger the data and its features will be, the higher accuracy will be achieved in detection of cancer. Likewise, ST algorithm was improved by using other databases which have extended attributes [99].

6.6.2

Programming language in cancer treatment

For the treatment of cancer, there are various steps leading toward right selection of medication or cure process, i.e., diagnosis and consultation, patient positioning, and immobilization, computed tomography scanning or simulation, target and critical organ contouring and treatment planning, patient setup verification, and dose delivery. Computers are being used at every step of these and is monitored by quality assurance system which maintains the quality of treatment by preventing any system error. Today, due to advancement in computing processes, time has been reduced which is taken for dose calculation [100,101]. This ultimately reduces the time to cure. Improvements in computing helps image processing possible which benefits for quality assurance in daily to daily treatment using imaging modalities, e.g., ultrasound, computed tomography, MRI, and imageguided radiotherapy [102,103]. Dose calculation in radiation treatment planning is crucial point and is achieved by cloud computing technology. Monte Carlo dose calculation was performed by using electron beams and photon on a cloud computing infrastructure [104]. It was proved that cloud-based simulations were identical to single threaded implementation. Hence, it was concluded that cloud computing provided high efficiency in dose calculation for radiation treatment. In another study, cloud computing was used for dose calculation using GEANT4 Monte Carlo code [105]. It was demonstrated that this process reduces time and can be used in Monte Carlo dose calculation without the local computer hardware in radiotherapy. Cloud computing was also used in preclinical radiation treatment planning [106]. The EGSnrc MC code [107] was used and found that increasing the compute nodes does not increase the

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time but there is threshold point. Performance of 4D radiation treatment using MC simulation was also carried out [108]. Optimization was carried out for number of compute nodes, dose construction time and number of computed tomography image sets in image voxel tracking. It was found that computing time is affected by diminishing return of the number of nodes selected in MC simulations. Furthermore, web-based application was developed known as CloudMC which runs on cloud platform [109]. It is proved that cloud computing plays a significant role in dose calculation using MC simulations during radiotherapy [110]. Other dose calculation systems were also devised using improved coding systems e.g. based on Amazon EC2TM [111] and Knowledge as a Service (KaaS). It was proved in a study that KaaS provided the best services for collaboration.

6.7

Conclusion

Cancer bioinformatics is an outstanding platform for finding new ways for curing cancer. Scientists are producing a large amount of omics data through high-throughput experimentation on cancer management, which requires advance data management, analysis, and interpretation being carried out with the help of bioinformatics. There is a great need for the new intelligent bioinformatics pipeline for analysis of the growing body of high-throughput pangenomics, metagenomics, proteomics, and metabolomics data. The main infrastructure of bioinformatics based on storage data, integrate and access to large volumes of biological data and related information. These efforts of speeding up data integration are still in process; however, many questions raise to organize and coordinate data by introducing more intelligent ways.

Acknowledgment The authors acknowledge respective departments and institutions for providing support and facilities.

Conflict of interest The authors have no conflict of interest.

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Magnetic-based sensing

7

Appan RoychoudhuryT Centre for Biomedical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India TPresent Address: Infection Medicine, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, United Kingdom

7.1

Introduction

Cancer incidence and mortality are evolving rapidly across the world, and presently, cancer becomes one of the most likely causes of death worldwide. In 2018, around 18.1 million new cancer cases and 9.6 million cancer deaths were observed while, the cancer mortality is estimated to reach 12 million by 2030 [1]. Among all types of cancer, lung cancer is most predominant for males with maximum number of cancer deaths, followed by prostate, colorectal, liver and stomach cancer. In case of females, breast cancer is most frequent and leading cause of deaths, followed by the cases of colorectal, lung and cervical cancer. In such a lethal situation, proper diagnosis and treatment of cancer become an important objective to enhance life expectancy in almost every countries of the world. However, the chance of recovery from cancer increases several folds after early detection of the diseases followed by their accurate treatment. It has been observed that around 30% people who died of cancer, could have been cured if their disease was detected at early stages [2]. Thus new promising tools are urgently required for thorough checking of molecular profiles of the patients to provide useful information that can be proficiently used by doctors and clinicians for further treatment of the disease. Among the available detection methods, magnetic-based strategies provide great potential to detect cancer at the curable stage. Even, the magnetic-based techniques can be efficiently used in the transition towards point-ofcare diagnostic devices. Since the turn of the millennium, the use of magnetic-based sensing has gained plentiful attention of the researchers for the development of reliable, efficient and precise sensor and

Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00003-2 © 2021 Elsevier Inc. All rights reserved.

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biosensor systems to identify a wide variety of physical, chemical and biological agents. This newly developed detection procedure is now being extensively studied to conduct highly sensitive determination of biomolecular targets in relevant sectors, typically in clinical diagnostics with a focus on developing point-of-care testing platforms [3 5]. The ultrasensitive and high-resolution detection capability of a magnetic sensor is generally formed due to the proficient use of magnetic nanoparticles (diameter ,100 nm) or magnetic beads (diameter ,100 μm) as a label in combination with a suitable magnetic field detector. Although, the basic principle of a simple magnetic sensor lies in the responses of the device to a change or interruption of a magnetic field in a way that is proportional to that particular change or interruption. In case of magnetic biosensor, this principle is being used to determine the changes or interruption in the magnetic field of a magnetically labeled biomolecule which interacts with the complementary biomolecule and changes are measured through a magnetic instrument or sensor. For such implementation, magnetic elements like iron, cobalt, nickel, and their oxides are commonly used as a magnetic label for efficient detection of the biomolecular targets. Apart from that, superparamagnetic particles are also being employed as a magnetic label with the advantages of not retaining the residual magnetization in the absence of magnetic field. Moreover, such type of particles can only be magnetized effectually by applying the external magnetic field. Most importantly, magnetic particles reveal several advantages in terms of physicochemical stability, biocompatibility and easy-to-functionalization that might be highly useful for biosensing purposes. Due to having such utilities, magnetic particles are now being widely utilized in other significant biomedical applications, for example, catabolism of tumors using hyperthermia for cancer treatment [6,7], separation of magnetically labeled cells and other biological components [8,9], targeted delivery of therapeutic drugs [10,11], delivery of therapeutic or reporter gene in a nonviral transfection approach [12,13] and for contrast enhancement in magnetic resonance imaging (MRI) applications [14,15]. Along with the magnetic label, different types of magnetic field sensor also play a vital role during the development of rapid, reliable, miniaturized and sensitive biosensing platform. For instance, the applications of induction coils and superconducting quantum interference devices are restricted in medical diagnosis owing to their hefty size, high power consumption, and lower sensitivity [16]. Though, these limitations have been

Chapter 7 Magnetic-based sensing

overcome after the successful use of highly sensitive magnetoresistive sensors. However, these magnetic biosensors show several advantages when compared to other biosensors. For example, magnetic probes and labels exhibit much higher stability and durability as compared to fluorescent tags, which are commonly used in fluorescence-based sensing. Moreover, the background fluorescence noise, which is a common phenomenon of biological samples, can be avoided by using magnetic methods. The magnetic materials also show less background noise effects and can be used for remote regulation and detection of biological entities by applying a controlled external magnetic field. Above all, the magnetic assay provides an elevated sensitivity and lower cost as compared to fluorescence and other detection methods [17]. Even, the magnetic sensors with relatively high sensitivity are capable to detect biomagnetic field generated by the living systems such as biological tissues and organs after making them electrically excitable. Such kinds of magnetic detection methodology without any particle labeling has been used to directly measure magnetic cardiogram signals, as well as the localized biomagnetic field around the smooth muscle tissues with a detection sensitivity of pico-Tesla level [18 20]. Therefore this developed procedure provides a noninvasive approach with effective sensitivity to monitor cell activity and function with a considerable scope of disease diagnosis in a noninvasive way. This chapter presents an overview of magnetic techniques which have been used for the development of efficient biosensors for cancer diagnosis. This is followed by the recent progress and achievements of such sensing mechanisms and their applications toward medical diagnostics with a particular focus on determination of potential cancer biomarkers. Further, the outlook and future directions of these magnetic-based biosensing techniques are also critically discussed.

7.2

Magnetic sensors

Magnetic sensors continue to receive extensive attention due to their widespread use in different industrial sectors, especially for consumer electronics, mobile phones, embedded memory systems, security and military applications to perform thousands of functions like detection, discrimination, and localization of the conducting and ferromagnetic items, proximity sensing, navigation, digital compassing, position tracking, wheel speed sensing, angle measurement, linear displacement

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measurement, current sensing, magnetic field measurement, noncontact switching, and many more. Nowadays, the utilities of the magnetic sensors and biosensors are being widely investigated in various clinical applications by exhibiting ultrasensitive detection of a broad range of biomolecular targets. For a simple magnetic biosensor, alteration of magnetic field intensity is measured by a magnetic field sensor after performing biochemical reaction in between magnetically labeled bioanalyte such as cancer biomarker with the complementary biomolecule (Fig. 7.1). These biorecognition molecules are usually immobilized over the magnetic field sensors which are used to measure signal responses for biological interactions. Besides, an alternative approach based on secondary detection principle (Fig. 7.2) is frequently used by tagging the target molecule with a small biochemical label, like biotin. The magnetic labels are then functionalized with streptavidin which is a complementary molecule to biotin and used for the attachment of biotinylated target molecules with the sensor surface-bound probe molecules. This type of detection procedure is particularly popular among deoxyribonucleic acid (DNA) hybridization and immunoassay-based techniques for cancer diagnosis. During detection of a specific biomolecular target, magnetic nanoparticles, or microparticles act as an effective source of labels because of their easy functionalization with the

Figure 7.1 Schematic illustration of a simple magnetic biosensor for magnetically labeled cancer biomarker detection.

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Figure 7.2 Schematic illustration of a magnetic biosensor based on secondary detection principle using biotinstreptavidin markers and magnetic labels.

biomolecules such as DNA, antibodies, and proteins, and even with the whole cells. Another advantage of using magnetic particles as a label lies in their strong magnetic properties as compared to the native biological systems and the exploitation of these magnetic properties permits highly sensitive detection of the analytes using a variety of magnetic instruments. These magnetic instruments are mainly used to sense the magnetic fields and most of them are based on magnetoelectric effect which comprised with the intimate correlation between magnetic and electrical phenomena. The magnetoelectric effect is formed owing to the appearance of magnetization in a material upon applying an electric field or on the other hand, due to the appearance of electric polarization in the material when a magnetic field is applied [21,22]. The magnetoelectric effect was theoretically presumed in 1894 by Pierre Curie [23] and thereafter first experimentally perceived in 1961 for antiferromagnetic Cr2O3 single crystal [24]. Since then, numerous studies have been exhibited to explore the applicability of magnetoelectric effect in different perspectives. For the development of magnetic biosensors, the use of magnetoelectrics is being observed since 1998, after developing a magnetoresistive biosensor by Baselt et al. to sense the presence of magnetic microbeads which

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were used as biomolecular label [25]. Afterwards, many approaches including giant magnetoresistance (GMR) [26 28], tunneling magnetoresistance (TMR) [29 31], spin valves [32 34], anisotropic magnetoresistance [35 37], giant magnetoimpedance (GMI) [38 41], Hall effect [42,43], superconducting quantum interference [44,45], and nuclear magnetic resonance [46,47] were utilized effectively to develop magnetic biosensors. Among them, magnetoresistance [28,30,34,48,49], magnetoimpedance [50 53], and Hall effect [54,55] based techniques were predominantly used for cancer diagnostics. The obtained results of these biosensors indicate the efficacy of magnetic-based techniques for localization, ultrasensitive detection, and estimation of very low concentration of cancer biomarkers that might be highly useful for screening and early diagnosis of cancer. In the following sections, a brief overview of the techniques, majorly used for detection of magnetic field and their applications so far towards cancer management, as well as for other significant clinical applications are described.

7.2.1

Magnetoresistive sensors

This type of magnetic sensor is based on the magnetoresistive effect, a change in the resistivity of a current carrying ferromagnetic material upon the exposure of a magnetic field. More precisely, when the current is passed through a ferromagnetic material like permalloy (an alloy of nickel and iron), the internal magnetization vector remains parallel to the current flow. If an external magnetic field is then applied perpendicular to the current, the direction of magnetization will rotate towards the direction of the magnetic field. The change of angle due to the rotation of direction of the magnetization or the change in internal magnetization vector is depended upon the strength and amplitude of the external magnetic field. The angle formed between the internal magnetization vector of the material and the direction of current flow controls the generated resistance. The resistance of the material is highest when the flow of current and the internal magnetization vector are parallel and lowest if the magnetization vector is perpendicular to the current flow. The sensitivity of the magnetoresistive-based sensor is determined through the ratio of change in resistance to the minimum resistance of the material. The concept of magnetoresistance was first given by Lord Kelvin in 1857, after observing 0.033% increase in the electrical resistance of iron when positioned in a magnetic

Chapter 7 Magnetic-based sensing

field [56]. Though, it took another hundred years to develop the first magnetoresistive sensor by Hunt in 1971 [57]. Yet after another twenty years, IBM first introduced the magnetoresistive head as a device to detect bits in a hard drive. Magnetoresistive sensors offer several advantageous features such as noncontact operation with unlimited number of operating cycles, high sensitivity even for weak magnetic fields, low and stable offset, rapid response, smaller size, low sensitivity to mechanical stress, high operating temperature range, sustainable to harsh environments, broad operating frequency range (0 to 1 MHz), more insensitive to vibrations than inductive sensors and for high reliability and durability with reasonable cost. Though, there are some disadvantages of using magnetoresistive sensors mostly due to temperature drift, poor temperature characteristics, limited linear range and high interference effect in a strong magnetic field. Nevertheless, the principle of magnetoresistance has been used to develop some specialized magnetic sensors for cancer diagnosis, which are depicted below.

7.2.1.1

Giant magnetoresistance based sensors

Giant magnetoresistance (GMR) refers to the huge change in resistance of the device (typically about 10% 75%) when it is placed in an external magnetic field as compared to the few percent changes in the resistance for other magnetic sensors. This quantum mechanical magnetoresistance effect can be observed for the devices made of multilayers of alternating ferromagnetic and nonmagnetic conductive layers. For the inven¨ nberg have been tion of GMR effect, Albert Fert and Peter Gru honored with 2007 Nobel Prize in Physics. They independently discovered the effect of GMR in 1988. For GMR effect, the colossal change in resistance is obtained due to the use of multilayer structure in which the ferromagnetic and nonmagnetic thin films are sandwiched one after another. With the absence of an external magnetic field, the magnetization of all the ferromagnetic layer is oppositely coupled to their neighboring nonmagnetic conductor. As a result, high-resistance state is formed due to the spinning of electrons with both orientations and the spin collision at the interfaces between ferromagnetic and nonmagnetic conductors. After the application of an external magnetic field, the magnetization of all the ferromagnetic layers is saturated in the magnetic field direction. The external magnetic field does not create spin collision at the interfaces because of

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spinning of the electrons with orientation in the same direction. Hence, a high conductance spin channel is formed and this state is referred to low-resistance state. The GMR effect has been largely utilized during the making of hard disks for data storage. However, the GMR devices are capable to detect a very low magnetic field and thus this technique has been used to develop magnetic biosensors for the identification of various biomolecules. As mentioned previously for magnetoresistive biosensors, Baselt et al. first introduced the concept of GMR to sense magnetically labeled biomolecules through the measurement of intermolecular forces that bind DNA DNA, antibody-antigen and/or ligandreceptor pairs together [25]. Such a concept of using GMR for biomolecule detection was successively used in several studies. Schotter et al. established a method for DNA detection using the principle of GMR and compared the efficacy of the developed method with conventional fluorescent-based DNA detection techniques [58]. Recently, Rizzi et al. presented DNA detection by the denaturation of double-stranded polymerase chain reaction (PCR) products on the GMR sensor array [59]. The target DNA strand was biotinylated and sensed using the GMR sensor probe by linking streptavidin-labeled magnetic nanoparticles to the sensor surface. Beside this, Krishna et al. recently prepared a GMR-based biosensor for diagnosis purposes by exhibiting simple and sensitive determination of influenza A virus [60]. In this experiment, magnetic nanoparticles were combined with the monoclonal antibodies of viral nucleoprotein and the presence of influenza virus allowed the magnetic nanoparticles to bind with the GMR sensor probe. The binding of the nanoparticles to GMR sensor resulted in the changes of resistance which were determined by using real-time electrical readout, whereas the attachment of magnetic nanoparticles to the GMR sensor probe was proportional to the concentration of the influenza virus. The low detection limit of the developed biosensor was found as 1.5 3 102 TCID50/mL virus and the signal intensity was enhanced with increasing concentration of the virus up to 1.0 3 105 TCID50/ mL. Furthermore, in another recent application, Sun et al. combined the GMR sensor probe with magnetic nanoparticles label for detection of Escherichia coli O157H:H7 [61]. With the developed sensor system, a minimum detectable limit of 100 CFU/mL was attained for E. coli O157H:H7 antigens and such low detection range is well comparable for clinical diagnosis and environmental monitoring applications. For cancer

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determination, Li et al. fabricated a GMR based system (Fig. 7.3) for detection of interleukin-6 (IL-6) which is treated as a potential cancer biomarker [49]. The developed sensor was used to detect IL-6 in unprocessed serum with a low sample volume of just 4 μL. First, the GMR sensor probe was functionalized with capture antibodies to bind the analytes. Consequently, the detection antibodies labeled with magnetic nanoparticles were introduced to bind with the captured analytes. The GMR sensor was then used to detect the generated dipole field by the magnetic nanoparticles which were attached on the sensor surface. With the developed sensor, it was possible to detect low concentration of IL-6 down to 125 fM within 5 minutes. Moreover, the GMR sensor was designed with near 0 degree magnetization to eliminate the need for a high magnetic field and thus the developed system can be efficiently used for point-of-care applications. Beside this, another GMR-based biosensor for IL-6 cancer biomarker detection was developed by Srinivasan et al. after using multilayer GMR structure and magnetic label of 12.8 nm cubic FeCo nanoparticles [28]. The small-sized magnetic nanoparticles with higher magnetic moment were employed to avoid the interference from natural movement, recognition and binding of the immobilized biomolecules and to achieve sensitive detection and quantification of such biomolecules. Surface of the GMR sensor was sequentially modified with 3-aminopropyltriethoxysilane (APTES), followed by 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) to immobilize monoclonal anti-human IL-6 antibodies as capture antibodies, whereas polyclonal antihuman IL-6 antibodies as detection antibodies were magnetically labeled with FeCo nanoparticles for the detection of IL-6 via sandwich immunoassay. After binding of the recombinant human IL-6 to the capture antibodies, the magnetic nanoparticles-labeled detection antibodies were allowed to bind with IL-6 and the resulting magnetic signal from nanoparticles was measured by the underlying GMR sensor. With the developed system, a high zeptomole detection sensitivity was obtained and the methodology could be helpful in the realization of personalized medicine. More recently, a different approach based on time-domain magnetorelaxometry was established by Huang et al. using GMR-based biosensor and the feasibility of the developed method was tested for sandwich immunoassay [62]. In magnetorelaxometry process, the magnetic nanoparticles are magnetized initially and then the temporal response is measured after eliminating the magnetic

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Figure 7.3 Development of giant magnetoresistance (GMR) biosensor for interleukin-6 (IL-6) detection: (A) scanning electron microscopy image of the fabricated GMR sensor; (B) design of GMR sensor chip; (C) enlarged view of a single active area of the GMR chip with eight sensors (red); (D) transmission electron microscopy (TEM) image of cubic FeCo nanoparticles; (E) TEM image of APTES-modified FeCo nanoparticles; (F) TEM image of streptavidin-modified FeCo nanoparticles; (G) schematic illustration of analyte (IL-6) detection via double antibody (Continued)

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field. This new approach is unresponsive to the magnetic field homogeneity and more useful for portable applications with low-power requirement and thus more effective for point-ofcare diagnostics.

7.2.1.2

Spin-valve sensors

L

Spin valves are also operated using the principle of GMR but here the electrical resistance can differ in between two values depending on the mutual orientation of the magnetization in the layers. However, the change in electrical resistance is occurred due to the GMR effect. The mechanism of spin-valve was first shown in 1991 by Dieny et al. [63]. A traditional spinvalve device is usually made with two ferromagnetic layers which are detached by a nonmagnetic spacer. Among two layers, one of which is generally pinned by an antiferromagnetic substrate and the magnetization of this layer does not alter with the external magnetic field. This pinned layer is implemented to increase coercivity and acted as a hard layer, whereas the other layer is free and acted as a soft layer to perform switching of the spin-valve. The nonmagnetic spacer is usually made with metals such as copper, chromium, ruthenium or silver, while magnetic materials like iron, nickel, or cobalt are used to prepare the pinned and free layers. At lower magnetic field strength, the free layer changes polarity as compared to the pinned layer owing to their difference in coercivity. After providing a magnetic field of adequate strength, the free layer switches polarity and depending upon the relative alignment of the magnetizations of the pinned and free layers, the device can be in two distinct states: a low-resistance state (parallel orientation) or a high-resistance state (antiparallel orientation). The device shows lower resistance during parallel orientation of the electron spins of both the layers while the antiparallel conformation encounters higher resistance and the overall resistance of the device becomes larger. sandwich immunoassay with magnetic label of FeCo nanoparticles; (H) relation of GMR responce with IL-6 concentration for the developed biosensors [28,49]. Source: Reprinted with permission from John Wiley and Sons [B. Srinivasan, Y. Li, Y. Jing, Y. Xu, X. Yao, C. Xing, J.-P. Wang, A detection system based on giant magnetoresistive sensors and highmoment magnetic nanoparticles demonstrates zeptomole sensitivity: potential for personalized medicine, Angew. Chem., 121 (2009) 2802 2805], Copyright (2009) and American Chemical Society [Y. Li, B. Srinivasan, Y. Jing, X. Yao, M.A. Hugger, J.-P. Wang, C. Xing, Nanomagnetic competition assay for low-abundance protein biomarker quantification in unprocessed human sera, J. Am. Chem. Soc., 132 (2010) 4388 4392], Copyright (2010).

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The principle of spin-valve has been used to develop magnetically labeled biosensors by measuring stray field of the magnetic beads and nanoparticles. Primarily Graham et al. designed a spin-valve sensor of 2 3 6 μm dimensions and the magnetoresistive material was made by the stacking of two ferromagnetic layers of NiFe composite with a copper spacer to separate the ferromagnetic films [32]. The sensor surface was functionalized by probe DNA and then used to facilitate rapid focusing and hybridization of the magnetic dextran iron oxide particlelabeled target DNA. Each particle consisted of ,500 DNA molecules with an estimated 70 DNA DNA interactions per particle at the sensor surface. The detection range was found as B140 14,000 DNA molecules per sensor equivalent to B2 200 fmole/cm2. In a much recent application, Qiu et al. prepared GMR spin-valve sensors array to quasi-digitally determine magnetic reporters for biosensing applications [64]. The fabricated sensor digitally switched in between two states and the corresponding changes in the switching field were used to detect the presence of magnetic reporters. The spin-valve structure consisted with antiferromagnetically coupled Co/Ru/Co trilayers and the sensor demonstrated the detection of ten 500 nm Fe3O4 magnetic nanoparticles as well as a small number (B10) of 500 nm nanoparticles. The developed GMR spin-valve sensors array with appropriate functionalization could be used as an emerging platform for high-performance cancer diagnosis. Furthermore, Lee et al. proposed Wheatstone bridge-assisted GMR spin-valve biosensor for detection and counting of magnetic cells [65]. The biosensor was integrated with top-pinned spin-valve layer structure and a microchannel to process the function of hydrodynamic focusing that permitted the cells to flow in series one by one and providing high accuracy during detection. The magnetic cell passed through the microchannel which was placed above the GMR sensor and the variation in magnetoresistance due to the stray field of the magnetic cells was measured. In addition to the cell count, the developed system was capable to recognize cells according to their difference in magnetic moment and can be utilized for cancer biomarker detection after proper labeling. Moreover, the separation of cells into different channels was exhibited by applying a magnetic field gradient and such method could be highly useful for the development of versatile magnetic flow cytometers. Beside this, GMR spin-valve immunosensor (Fig. 7.4) was developed by Sun et al. for the determination of tumor biomarker carcinoembryonic antigen (CEA) [34]. The GMR sensor system was designed by microelectromechanical system (MEMS) technology to

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Figure 7.4 Development of spin-valve based biosensor for carcinoembryonic antigen (CEA) detection: (A) immunoassay for capturing and labeling CEA; (B) scanning electron microscopy image of CEA-conjugated Dynabeads on Au film-coated glass substrate; (C) schematic showing the method of antigen detection after placement of Dynabeads on sensor surface and application of magnetic field; (D) snapshot and microscopic image of fabricated sensor; (E) photograph of experimental setup; (F) relation of magnetoresistive ratio signal with CEA concentration for the developed biosensor [34]. Source: Reprinted with permission from Springer Nature Microchimica Acta [X.-C. Sun, C. Lei, L. Guo, Y. Zhou, Giant magneto-resistance based immunoassay for the tumor marker carcinoembryonic antigen, Microchim. Acta, 183 (2016) 1107 1114], Copyright (2016).

accommodate 200 spin-valve strips in serial connection and the developed sensor was used to detect superparamagnetic Dynabeads in a concentration down to 10 ng/mL. The sensing of CEA was done by sandwich immunoassay after modifying the sensor surface with a self-assembled monolayer and by using biotinylated secondary antibody against CEA and streptavidinylated Dynabeads. A low detection limit of CEA of just 10 pg/mL was attained with the developed system after applying DC magnetic fields in the range of 40 to 90 Oe and such sensor holds great promises for clinical applications. Kokkinis et al. employed a fully automated microfluidic platform with integrated

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spin-valve GMR sensors for separation and quantification of preisolated cancer cells after labeling with magnetic particles [48]. The separation channel of the microfluidic platform was designed with the integrated conducting microstructures, tapered conductors and a quantification area with GMR sensors to perform detection of leukemia cancer cells. Separation between magnetically labeled cancer cells and plain magnetic particles was exhibited due to fallback of magnetically labeled cells as compared to bare magnetic particles, when accelerated by the same magnetic force in a static fluid. Thereafter, array of magnetic particles was rearranged into a row formation by tapered conductors and then detected by GMR sensors. Kim et al. also presented the development of GMR spin-valve array-based magneto-nanosensor biochips for multiplexed detection of protein biomarkers, used in radiation exposure and cancer [66]. Analysis of multiple biomarkers were performed by magnetic immunoassay, while the detection signal as a form of resistance change of spin-valve sensor was generated due to stray magnetic field of superparamagnetic nanoparticle labels. The results of biomarker assay were obtained in real-time measurements with a sensitivity of 10 pM, 53 fM and 460 fM, respectively, for phosphorylated-structural maintenance of chromosome 1 (phosphor-SMC1), granulocyte colony stimulation factor (GCSF) and IL-6 and such modified platform may enable early stratification and therapy monitoring of patients with exposure to ionizing radiation and cancer. Besides, Dias et al. demonstrated cell-free DNA (cfDNA) fragment detection by using magnetic labels and a portable biochip platform, consisted with an array of 30 magnetoresistive spin-valve sensors [67]. The cfDNA acts as a significant marker for liquid biopsies in cancer diagnostics and also has a vital role to assess tumor staging and metastatic potential. In this work, ALU115 and ALU247 fragments were identified as cancer targets in cfDNA integrity assessment. First, magnetically labeled DNA targets were prepared after extracting cfDNA from collected blood samples, followed by amplification of ALU115 and ALU247 by PCR and then digestion and labeling of amplicons with magnetic particles. Subsequently, specific binding of magnetically labeled ALU115 and ALU247 DNA amplicons with their respective capture DNA probes were exhibited after immobilizing capture probes onto the sensor surface. The adopted strategy was capable to detect mutations, homologous or truncated sequences for ALU115 and ALU247 fragments that share high similarity. Even, the developed magnetoresistive sensor could accomplish detection of ALU elements within picomolar

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concentration range, thus showing great potential for cfDNA assay in cancer diagnostics.

7.2.1.3

Tunneling magnetoresistance-based sensors

The TMR-based device is also similar to the GMR except for the presence of nonmagnetic insulating layer in the place of nonmagnetic conducting layer as that present in GMR devices. However, the TMR devices are made of two ferromagnetic layers that are separated by a thin insulator (normally 1 2 nm thick) and due to the existence of such thin insulating layer, the electrons can tunnel from one ferromagnetic layer into another. The insulating layers of Al2O3 [68], graphene [69], Ga2O3 [70], and MgO [71] have been utilized and such layers are usually fabricated by using different thin film deposition techniques such as sputtering, thermal evaporation, pulsed laser and electron beam vapour deposition methods. The TMR effect was first described independently by Miyazaki and Tezuka [72] and Moodera et al. [68] and afterward several studies used TMR to sense magnetic beads of micro or nanoscale dimensions [73 75]. In those experiments, the thickness of the insulator has been proficiently varied to enhance the sensitivity for detection. With the help of TMR devices, it is possible to attain a magnetoresistance (MR) ratio of 20% 50% and for such high efficiency, the TMR is being widely used to develop the effective biosensor systems. In one such application, Shen et al. demonstrated real-time determination of moving superparamagnetic beads by directly measuring magnetic dipole fields from a single bead using TMR sensors, which were combined with microfluidic channels [74]. The single bead-associated dipolar field was adequate to attain a signal of 80 μV with a signal to noise ratio of 24 dB in an applied field of 15 Oe. This on-chip magnetoresistive sensor revealed the potential for biomolecular detection, especially for spintronic immunoassay in the presence of magnetic labels. Albon et al. also reported the development of TMR sensors array with MgO insulating layer for detection of high resolutive magnetic microbeads [29]. In this experiment, elliptically-shaped sensors of axis lengths of 400 and 100 nm were utilized for single bead detection. The signals of the TMR sensor were monitored with respect to magnetic bead positions and the fabricated elliptically-shaped sensors displayed linear response over a field range of 6 500 Oe with a sensitivity of up to 0.1%/Oe. Therefore the proposed sensor is highly suitable for cancer biomarker detection by measuring magnetic beads as a label. Furthermore, in a recent application, Amara et al.

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presented the development of TMR-based flow cytometer by introducing externally-magnetized magnetic beads labeling cells above the magnetoresistive sensor [76]. The developed TMR sensor was applied to measure the stray field surrounding the magnetic beads. A signal peak was observed each time when the magnetically labeled cells passed over the developed sensor. The target cells were human embryonic kidney 293 cells (HEK 293), which were magnetically labeled and passed through the polydimethylsiloxane (PDMS) microchannel. The corresponding resistance changes showing by the TMR sensor were monitored to operate the developed biochip cytometer. In another application, Lian et al. employed a fully automated in vitro diagnostic system for acute myocardial infraction by using magnetic tunnel junction (MTJ) arrays and superparamagnetic labels [77]. The sensor array was fabricated after integrating 12 3 106 MTJ devices onto a 3 metal layer complementary-metal-oxidesemiconductor (CMOS) circuit and the developed system can be used to analyze 48 different types of bio-target simultaneously. The fabricated chip was integrated into a microfluidic cartridge and used to detect three biomarkers: CK-MB, MYO, and cTnI with a detection limit of 0.1 ng/mL, 1 ng/mL and 10 pg/mL, respectively, by using biotin-streptavidin and immunoassaybased detection techniques. Cousins et al. designed a handheld magnetometer probe for the identification of sentinel lymph node using MTJ sensors and magnetic tracers [78]. This lymphatic system plays a significant role in the diagnosis of breast cancer, gastrointestinal cancer and melanoma, while the presence of metastasis in the sentinel lymph node has a strong prognostic value for cancers. The developed magnetometer probe was characterized in vitro and validated with preclinical swine model and this probe displayed a spatial resolution of 4.0 mm, with the potential to detect as few as 5 μg of magnetic tracer. Due to such high sensitivity, all first-tier nodes were detected in the preclinical experiments without any instances of false positive or false negative results. Furthermore, Lei et al. reported the detection of hepatic tumor biomarker alpha-fetoprotein (AFP) after labeling with Fe3O4 magnetic nanoparticles and by using MgO-based MTJ sensors [30]. The developed TMR based biosensor (Fig. 7.5) was contained with a sensing area of 4 3 2 μm2 to produce TMR of 122% and sensitivity of 0.95%/Oe at room temperature. The surface of MTJ sensors and magnetic nanoparticles were bio-functionalized with capturing anti-AFP antibodies and detecting anti-AFP antibodies, respectively to perform specific detection of target AFP antigens by sandwich immunoassay. Detection of the target AFP antigens produced variation of sensor

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Figure 7.5 Development of tunneling magnetoresistance biosensor for alpha-fetoprotein (AFP) detection: (A) schematic of AFP detection with sandwich assay configuration and transmission electron microscopy image of biofunctionalized magnetic particles; (B) magnetoresistive response curve of the developed biosensor showing variations of resistance change after binding with target AFP antigens; (C) relation between maximum resistance change with AFP antigen concentration for the developed biosensor [30]. Source: Reprinted with permission from AIP Publishing [Z.Q. Lei, L. Li, G.J. Li, C.W. Leung, J. Shi, C.M. Wong, K.C. Lo, W.K. Chan, C.S.K. Mak, S.B. Chan, N.M.M. Chan, C.H. Leung, P.T. Lai, P.W.T. Pong, Liver cancer immunoassay with magnetic nanoparticles and MgO-based magnetic tunnel junction sensors, J. Appl. Phys., 111 (2012) 07E505], Copyright (2012).

resistance which was enhanced logarithmically with increasing AFP antigen concentration. The maximum resistance changes after binding with magnetic label were calculated as 17, 143, and 271 Ω, respectively for target AFP antigen concentrations of 0.002, 0.010, and 0.050 mg/mL. The obtained results are highly promising for clinical diagnostics and early stage liver cancer indications. Sensing parameters of the magnetoresistive biosensors for cancer detection are summarized in Table 7.1.

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Table 7.1 The results of detecting cancers using magnetoresistive biosensors. Target analyte Sensor type

Magnetic label Detection range Lower detection limit

Reference

Interleukin-6 (IL-6) Giant magnetoresistive Interleukin-6 (IL-6) Giant magnetoresistive Carcinoembryonic Spin-valve antigen Leukemia cancer Spin-valve cells (Jurkat) IL-6, PhosphorSpin-valve SMC1, GCSF

FeCo nanoparticles

[49]

Cell-free DNA (cfDNA) ALU elements Sentinel lymph node Alpha-fetoprotein antigen

Spin-valve

125 fM

0 2.0 3 107 2.08 3 106 molecules of IL-6 molecules of IL-6 Superparamagnetic 10 pg/mL 10 ng/mL 10 pg/mL Dynabeads Superparamagnetic Dynabeads Microbeads IL-6: 0.46 460 pM, Phosphor-SMC1: 10 -2000 pM, and GCSF: 53 fM 0.53 nM Superparamagnetic beads FeCo nanoparticles

Tunneling Iron oxide magnetoresistive nanoparticles with dextran coating Tunneling Iron oxide magnetoresistive nanoparticles

7.2.2

125 fM 41.5 pM

[28] [34] [48] [66]

[67]

[78]

0.002 0.05 mg/mL

[30]

Giant magnetoimpedance based sensors

Giant magnetoimpedance (GMI) effect refers to the large variation of the impedance experienced by the soft magnetic materials carrying with alternating current (AC) when exposed to an external magnetic field. Because of its high utility, GMI is being used significantly to develop efficient instruments for analytical applications [79 82]. For sensor technology, the exploitation of GMI effect has become an important objective of research due to having the advantageous features such as high sensitivity, higher stability during operation, easy handling, smaller size, lower fabrication cost, fast response and negligible environmental impact etc. [82 84]. The GMI effect is termed as longitudinal GMI or transverse GMI effect depending upon the application of external magnetic field in the longitudinal or

Chapter 7 Magnetic-based sensing

transverse direction respectively, whereas the perpendicular GMI effect arises during the application of external magnetic field perpendicularly to the direction of material thickness of the soft magnetic materials. Among the three types of GMI effect, the longitudinal GMI effect has been widely used and become more popular for the development of sensors. The GMI effect is primarily dependent on two factors; magnetic anisotropies present in the material and the frequency of applied AC current [85]. In particular, the GMI effect is formed due to high-frequency skin effect [86,87] of the AC current and the magnetic permeability which is strongly dependent on the magnetic field strength and related with a specific magnetic domain structure [83 85]. Skin effect is a characteristic of the AC current and due to such effect, highest current density is obtained near the surface of the conductor and the current density decreases gradually with the depth of the conductor. The effective resistance of the conductor and the GMI effect are controlled by the skin effect and depth. In recent times, a substantial amount of research is being conducted to study and utilize such effect in soft ferromagnetic wires [88], ribbons [89] and thin films [90] for the fabrication of GMI-based sensors. The electrical impedance change of a ferromagnetic wire in the presence of a magnetic field was first noticed by Harrison et al. in 1936 [91]. Though, the work on GMI effect was started in the last two decades and first reported by Panina and Mohri [83]. For biosensing applications, Kurlyandskaya et al. initially proposed a GMI-based prototype as a model biodetection technique for highly sensitive detection of magnetic labels by monitoring the external fringe fields generated by the magnetic nanoparticles [92]. For that purpose, magnetoimpedance response of a Co67Fe4Mo1.5Si16.5B11 amorphous, ribbon-based element covered with a thin layer of commercial ferrofluid was studied and the results showed that the parameters like applied magnetic field strength, amplitude and frequency of the driving current and the presence of magnetic ferrofluids significantly controlled the effect of generated magnetoimpedance. With that approach, an effective biosensor with improved sensitivity can be developed to accomplish a two-step sensing process that would be highly significant for clinical and pharmaceutical purposes. The detection strategy of GMI biosensors primarily involves the following approaches. First, the appropriate functionalization of the magnetic particle labels is performed to capture target bioanalyte due to the implementation of a specific biochemical reaction. Second, the external magnetic field is applied to magnetize biomolecules conjugated-magnetic labels that can create a stray magnetic field to modulate the GMI

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effect of the sensor. Therefore the detection of target analytes has been done by determining the variations in GMI effect which is induced by the stray magnetic field of the magnetic labels. Nowadays, the GMI effect is being largely applied in the field of biosensors through the detection of magnetic ferrofluid [92], microbeads [93 95] and nanoparticles [39,96,97] to monitor the magnetically labeled biomolecules. So far, these magnetic labels combined with GMI detection techniques have been mostly utilized for precise determination of E. coli O157: H7 [98], HEK cells [96], C-reactive protein (CRP) [4], CEA [52], AFP [51,53], human papilloma virus (HPV) type 16/18 [97], gastric cancer cells [99], Lewis lung carcinoma (LLC) cancer cells [50], prostate adenocarcinoma cells [39] and the cell surface markers of Calu-3, Hela, A549, CaFbr, HEK293 and human umbilical vein endothelial cell (HUVEC) [38] and out of them, many are potential cancer biomarkers. In one such application, Blanc-Be´guin et al. showed the highly sensitive detection of maghemite (Fe2O3) nanoparticles-conjugated prostate adenocarcinoma cells in rat by using GMI sensor which was made of Co-rich amorphous-uncovered microwires as magnetoimpedance sensing element [39]. The prostate adenocarcinoma cells (Mat Ly Lu cells) were cultured for 24 hours with various Fe2O3 nanoparticles concentrations (0 6 mg/ml) and then X-ray fluorescence analysis was performed to measure the quantity of nanoparticles placed inside the cells, followed by their detection using GMI sensor. Such a semiquantitative approach for the determination of cancer cells using GMI technique can be applied in other biomolecular target detection. Furthermore, Chen et al. presented targeted detection of gastric cancer cells through the collective use of RGD-4C peptide-coupled and chitosan-covered superparamagnetic iron oxide particles (RGDFe3O4@chitosan) and GMI-based biosensing system [99]. The micropatterned GMI sensor was made with Co-based ribbon and developed via MEMS process. For gastric cancer cells detection, the Fe3O4 nanoparticles were covered with chitosan and functionalized with RGD-4C peptides and the developed RGDconjugated Fe3O4@chitosan particles were used to target gastric cancer cells, while the Fe3O4@chitosan particles without RGD4C peptide were not capable to do the same. The detection was exhibited in a typical in-situ method using the GMI effect and each sample measurement was performed in a tenfold manner followed by the determination of average value as a final result. The GMI responses were determined for four different samples using the external magnetic field of 150 Oe along the longitudinal direction of the sensor, driving frequency of 10 MHz and AC

Chapter 7 Magnetic-based sensing

current amplitude of 5 mA. This method laid a solid foundation for specificity detection and to distinguish between the targeted cells and nontargeted cells by using magnetic field. In another similar development, Kumar et al. combined Co64.5Fe2.5Cr3Si15B15 amorphous ribbon-based GMI sensor with a magnetic label of Fe3O4 nanoparticles for the detection of HEK 293 cells [96]. The superparamagnetic Fe3O4 nanoparticles of 30 nm diameter were embedded inside the HEK 293 cells with a concentration of B105 particles/cell by intracellular uptake. The detection of the cells after intercellular uptake of nanoparticles was performed on GMI sensor in a contact-type mode. The presence of cellconjugated-magnetic nanoparticles reduced the GMI ratio of the sensor. Besides this, Yang et al. performed quick and parallel genotyping of HPV type 16/18 using a GMI sensor made of soft magnetic ribbon material [97]. In this experiment, four different capture probes including negative control group (salmon sperm DNA), HPV type 16 detection region, HPV type 18 detection region and positive control group (primers) were immobilized on the surface of a PDMS microchannel in six detection regions. The HPV was labeled with magnetic nanoclusters via biotinstreptavidin and the genotyping of HPV was determined by measuring the changes in GMI ratio in respective detection regions after DNA hybridization. The results were highly promising for clinical diagnostics and can overcome the problem of photobleaching which is common for conventional fluorescentbased detection method. Bao et al. prepared NiFe/Cu/NiFe film-based GMI biosensor for rapid one-step detection of surface markers of magnetically labeled cancer cells [38]. For such purpose, magnetic Fe3O4@chitosan nanoparticles were modified with RGD-4C peptide and then used for targeting the cultured cancer cells on NiFe magnetic sensing element and PDMS cavity. The amount of cell surface receptor-integrin was distinguished for the model samples of human lung epithelial adenocarcinoma cells (Calu-3), human epithelial cervix adenocarcinoma cells (Hela), human lung carcinoma cells (A549), carcinoma associated lung fibroblasts (CaFbr), human epithelial cells (HEK293), and HUVEC with different integrin expressions. This qualitative screening approach showed fast, sensitive, easy operative and low-cost detection of the cell surface markers with a very little human intervention. Hence, this method has a high potential for early diagnosis of cancer and could be used in other molecular recognition based clinical applications. Wang et al. recently combined a NiFe/Cu/NiFe film-based GMI sensor with sandwich immunoassay for ultrasensitive and quantitative determination of CEA [52]. The sandwich

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immunoassay was performed using Dynabeads as magnetic labels of CEA and for the detection of different concentrations of CEA, specially designed microcavities were made by oblongshaped Au films, covered with SU-8 photoresists. The quantification of CEA was done by a separated-type method and the obtained results displayed a linear dependency of the GMI response with CEA concentration in a broad range (1 pg/ mL 10 ng/mL) with a detection limit of 1 pg/mL. Though, a weaker target signal was obtained beyond the CEA concentration of 10 ng/mL because of the formation of a high-density cluster of Dynabeads. Nevertheless, the developed biosensor was capable of quantifying low concentrations of CEA and wellsuited to exhibit ultrasensitive detection of the biomolecules. Yang et al. also developed a GMI biosensor integrated with sandwich immunoassay for the detection of magnetic beadlabeled CRP which is treated as a potential biomarker for cardiovascular disorders and inflammation [4]. The flexible GMI platform was prepared by MEMS techniques to fabricate a micro-patterned Co-based amorphous ribbon as a sensing element, followed by the deposition of Au film to provide the support for immunosensing. Afterwards, sandwich immunoassay with biotin-streptavidin modifications was executed for different concentrations of the antigen against CRP and the corresponding changes in GMI ratio of the sensor were denoted for quantitative analysis. The results showed that the developed system can retain a linear detection range in between 1 to 10 ng/mL for CRP determination with a detection limit of 1 ng/ mL and such developed method can be used in point-of-care diagnostic devices for cardiac and inflammatory bowel diseases. In another recent application, Yang et al. used tortuous-shaped GMI sensor of NiFe/Cu/NiFe films in conjugation with an open-surfaced microfluidic system and sandwich immunoassay to perform quantitative determination of E. coli O157:H7 pathogen [98]. For immuno-binding of that pathogen, streptavidin-tagged super-magnetic Dynabeads were attached with the biotinylated polyclonal antibody to capture E. coli O157:H7. The E. coli loaded Dynabeads were then introduced into a straight and open-surfaced microchannel, consisted of a rectangular Au film unit to perform sandwich immuno-binding. The Au film was contained with the specific monoclonal antibody which formed an immunocomplex with the E. coli loaded Dynabeads. As a result, the GMI ratio of the attached sensor was strongly reduced at high frequency with the presence of E. coli O157:H7 pathogens. With the application of 2.2 MHz working frequency, the developed system demonstrated a linear

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171

response in 50 to 500 cfu/mL concentration range of the analyte and also a detection limit of 50 cfu/mL. Therefore this GMIbased microfluidic system could be used for ultrasensitive detection of pathogenic bacteria and in other biomedical applications. Table 7.2 shows the obtained sensing parameters for magnetically labeled cancer biomarkers detection using the developed GMI biosensors. For in-situ detection of liver cancer biomarker AFP, Wang et al. reported the utilization of Dynabeads-labeled sandwich immunoassay and an integrated GMI sensor (Fig. 7.6) that was made of multilayer films (Cr/Cu/NiFe/Cu/NiFe/Al2O3/Cr/Au) [53]. The top Au layer was functionalized with 11Mercaptoundecanoic acid (11-MUA) to immobilize AFP monoclonal antibodies, whereas the AFP antigens were first magnetically labeled with Dynabeads and then specifically

Table 7.2 Giant magnetoimpedance based sensing platforms for detection of clinical biomarkers and their respective sensing parameters. Target analyte

Sensor type

Magnetic label

Prostate adenocarcinoma Semiquantitative Maghemite cells (Mat Ly Lu) in rat (Fe2O3) nanoparticles Gastric cancer cells Qualitative Fe3O4@chitosan MGC-803 nanoparticles Human embryonic kidney Qualitative Fe3O4 (HEK 293) cells nanoparticles Human papilloma virus Quantitative Magnetic type 16/18 nanoclusters Qualitative Fe3O4@chitosan Cell surface markers; Calu3, Hela, A549, CaFbr, nanoparticles HEK293 and HUVEC Carcinoembryonic Quantitative Magnetic antigen Dynabeads C-reactive protein Quantitative Magnetic Dynabeads Alpha-fetoprotein (AFP) Quantitative Magnetic antigen Dynabeads AFP antigen Quantitative Magnetic Dynabeads

Linear detection Lower Reference range detection limit [39]

[99] [96] 4 copies 400 copies 4 copies

[97] [38]

1 pg/mL 10 ng/mL

1 pg/mL

[52]

1 ng/mL 10 ng/mL

1 ng/mL

[4]

1 pg/mL 1 ng/mL

1 pg/mL

[53]

0.2 ng/mL 1 ug/mL

0.2 ng/mL

[51]

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Figure 7.6 Development of giant magnetoimpedance (GMI) biosensor for alpha-fetoprotein (AFP) detection: (A) schematic illustration of the sensor and detection of AFP by magnetic immunoassay; (B) frequency dependency of GMI response for detection of AFP antigens; (C) magnetic field dependency of GMI response for detection of AFP antigens; (D) relation of GMI responce with AFP concentration in linear response range for the developed biosensor [109]. Source: Reprinted with permission from Elsevier [T. Wang, Y. Zhou, C. Lei, J. Luo, S. Xie, H. Pu, Magnetic impedance biosensor: A review, Biosens. Bioelectron., 90 (2017) 418 435], Copyright (2017).

captured through double antibody sandwich immunoassay. The qualitative detection of AFP antigens was performed in the concentration range of 1 to 10 ng/mL, by measuring the GMI responses of the attached sensor. The results showed improved GMI effect with the existence of magnetically labeled AFP on the sensor surface because of induced magnetic dipole of the superparamagnetic Dynabeads, while the corresponding GMI ratio of the sensor was enhanced significantly at higher frequencies. In another similar development, Guo et al. fabricated GMI-based separable biosystem for AFP detection by exhibiting magnetic immunoassay [51]. The GMI sensor was made of

Chapter 7 Magnetic-based sensing

symmetrical meandering of Ni77Fe23/Cu/Ni77Fe23 as sensing element for biomagnetic detection and with an integrated microsolenoid coil for signal amplification. The measurements of AFP antigen were accomplished by the combined use of Dynabead magnetic labels, streptavidin-biotin interactions and double antibody sandwich immunoassays and the obtained results showed a minimum detectable limit of 3 ng/mL for streptavidin-coupled Dynabeads and 0.2 ng/mL for AFP, respectively. These results indicate that such GMI-based bioanalyte detection system has high potentiality for early diagnosis of hepatic cancer. Apart from that, Devkota et al. recently presented the detection of LLC cells after labeling with magnetically weak MnO nanoparticles and by measuring the magnetoreactance effect of a soft ferromagnetic amorphous ribbon with a microhole-patterned interface [50]. The magnetic moment of the MnO nanoparticles was comparatively weak and therefore the magnetoimpedance sensors were not capable to detect them in solution (0.05 mg/mL MnO lipid micellar nanoparticles), as well as inside the cells at lower concentration (8.25 3 104 cells/mL). Although, the magnetoreactance biosensor was successfully used to detect the MnO nanoparticles before and after their uptake by LLC cells, which, respectively, showed the detection sensitivities of B3.6% and 2.8% in comparison of blank cells. Besides, the obtained detection sensitivity of the magnetoreactance sensor was one order superior to the magnetoimpedance (B0.4%) sensor. The MnO nanoparticles are usually considered as an emerging contrast agent for MRI of the lung cells. Hence, the developed magnetoreactancebased biosensing process can be utilized efficiently during the predetection method of MRI for lung cancer examination. Devkota et al. also demonstrated the application of magnetoreactance biosensor for quantitative detection of anticancer drug Curcumin [41]. In this experiment, superparamagnetic Fe3O4 nanoparticles were used as a magnetic label and for such purpose, the nanoparticles were first modified with Alginate followed by their tagging with Curcumin. The detection and quantification of Curcumin were performed by measuring the magnetoreactance changes of a Co65Fe4Ni2Si15B14 amorphous ribbon sensing element with varying concentrations of Curcumin-loaded-Fe3O4 nanoconjugates. A high capacity of the magnetoreactance biosensor was observed in the concentration range of 0 to 50 ng/mL, beyond which the detection sensitivity became constant. The sensitivity of the developed magnetoreactance-based biosensing system was reached to a high value of 30%, which was about 4 5 times greater than that of a magnetoimpedance-based biosensor.

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7.2.3

Hall effect based sensors

The Hall effect is a well-known technique and commonly used to determine the magnetic fields since last five to six decades. Nowadays, the Hall effect based devices are widely available and utilized in various instruments including computers, medical instruments, automobiles, aircraft and different types of machine tool, etc. However, in Hall effect, a voltage difference is produced across an electrical conductor instead of a resistance change as in the case of magnetoresistive sensors. The generation of voltage difference which is known as a Hall voltage is resulted transversely to the direction of current, when the magnetic field is applied perpendicular to the current flow. A Hall effect based sensor is associated with the Hall element that is made of a thin layer of conductive material and the output connections of this element are placed perpendicular to the direction of current flow. After the application of a magnetic field, the Hall element reacts with an output voltage which is proportional to the applied magnetic field strength. The output voltage is in generally μV range and needs supporting electronic circuitry to reach in the useful voltage levels. Thus the complete Hall effect sensor is formed after combining the Hall element with additional electronic accessories. Hall effect based sensing devices reveal several advantages in magnetic measurements such as higher signal to noise ratio in room temperature or even in low temperature conditions, high magnetic moment sensitivity in a broad field range and unresponsiveness to magnetic saturation etc. [100,101]. Furthermore, the Hall sensors exhibit higher durability, repeatability, broader linear range, logic compatible input and output, wider temperature range and high-speed operations [101]. Thus the Hall effect devices can be utilized in many types of sensing purposes and used effectively in speed detection, positioning, proximity switching and current sensing applications [102]. However, the Hall effect sensors show much lower sensitivity as compared to magnetoresistive sensors. Beside this, sensitivity of the magnetoresistive sensor is adjustable by changing the film thickness and line width, but such feature is not available with the Hall sensors. Nevertheless, the efficacy of the Hall sensors has been used to detect local electric and magnetic fields [103], magnetic beads [104,105] and nanostructures [106,107] labels in different biosensing and biomedical applications. For example, Kazakova et al. prepared a scanned micro-Hall (μHall) probe system which was sensitive enough to detect single micron-sized paramagnetic beads at high scan rates in a broad linear scan range [105]. These

Chapter 7 Magnetic-based sensing

paramagnetic Dynabeads were used as a magnetic label and made by polymer matrix-embedded ferrite particles with an additional coating of streptavidin monolayer that can provide a strong attachment to the biotin-labeled target biomarkers. The developed sensor was capable to detect slight changes in local fields (,1 μT/OHz) in the presence of a large DC polarizing field. Moreover, the sensor was operative in room temperature, liquid and noninvasive conditions and such beneficial attributes are highly suitable for cancer diagnostics. In another application, Aledealat et al. designed a μHall magnetic sensor with microfluidics assembly for real-time determination of moving streptavidin-coated superparamagnetic beads [108]. Such superparamagnetic beads can be utilized as a magnetic label for manipulating and monitoring of target cancer cells for separation and detection purposes. The μHall sensor was made with InAs quantum well and attached to a PDMS microchannel. For detection purpose, the beads were first magnetized by providing an external magnetic field in a perpendicular direction of the sensor plane and then transported within and around the Hall cross area to produce positive and negative Hall voltage signals, respectively. The random distribution of the immobilized superparamagnetic beads over the sensor surface was monitored by measuring the relative magnitudes and polarities of the obtained signals and the results were in good agreement with the calculated values that helped to deduce the shape of the dynamic signals. Further, Ledermann et al. proposed development of a tactile sensor for palpation-based tumor detection by measuring three-dimensional magnetic field [55]. A permanent magnet and a three-dimensional Hall sensor AS54xx were embedded in a silicone pad for development of sensing device. An external force was then applied and the corresponding changes in threedimensional magnetic field due to position variations of magnet with respect to Hall sensor were measured. As a result, the sensor provided three-dimensional information of the external forces which make the sensor suitable for tumor detection by palpitation. The sensor size can also be reduced to 10 mm diameter, smaller than a finger, and thus meet the requirements for prostate cancer diagnostics. Apart from that, Issadore et al. reported fabrication of a microfluidic chip-based μHall platform for circulating tumor cell (CTC) detection in whole blood [54]. The developed Hall sensor can detect immunomagnetically tagged single cell within large number of blood cells and unbound reactants without any washing or purification steps. The cells were first labeled with antibody-conjugated-magnetic beads, specific to particular cell surface molecule. Afterwards, the magnetically

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labeled cells were passed through microfluidic channel, where tiny Hall detector sensed their presence. The developed μHall detector was utilized to sense CTC in whole blood for 20 ovarian cancer patients with high sensitivity. Moreover, the sensor was demonstrated for simultaneous detection of epithelial cell adhesion molecule (EpCAM), epidermal growth factor receptor (EGFR) and human EGFR 2 (HER2)/neu, biomarkers on individual cells. Therefore such single-cell analytical technique can be efficiently utilized in cellular and molecular diagnosis and for early detection of cancer at curable stages.

7.3

Conclusions and outlook

The coupling of magnetic sensors with magnetic particle labels offers a unique and efficient platform for cancer detection owing to nonappearance of magnetic background for almost all the biological samples. However, the proper sensing operations in presence of these magnetic labels are largely relied upon monodispersion, biocompatibility, and easy functionalization and such features help to reduce the effect of nonspecific binding. Moreover, the appropriate functionalization of magnetic labels play a vital role to capture target cancer markers and to obtain high amount of biological signal. Beside this, the pertinent use of biodetection molecules over the sensor surface with suitable surface immobilization techniques are also equally important to achieve significant improvements in sensing parameters for cancer diagnosis. In this regards, a considerable amount of research on synthesis, characterization, and functionalization of magnetic nanoparticles or composites label and monitoring of their behavior for biosensing purposes is recommended to accomplish higher sensitivity in cancer diagnostics. Even, the proper utilization and functionalization of these magnetic particles can lead to multiplexed detection of cancer biomarkers in a point-of-care testing platform. However, the appearance of large number of magnetically labeled biomarkers can form agglomeration or cluster of particles. This may lead to the low-performance of the magnetic sensors because of canceling the exciting magnetic fields of adjacent particles to one another in the accumulated form. In such cases, the magnetic labels are needed to be well-dispersed and distributed in a single layer throughout the entire testing platform for preventing the formation of high-density particle aggregation and thus to increase sensitivity in the quantitative analysis. The performance of the sensor can be improved

Chapter 7 Magnetic-based sensing

remarkably, if the magnetic particles are monodispersed and the separation distance between them are maintained at least equal to their particle diameter. Furthermore, the perpendicular magnetization can make the distribution of magnetic particles uniform on the flat surfaces, and therefore more suitable for magnetoimpedance and magnetoresistance-based applications. Apart from that, the possibility of single magnetic nanoparticle detection by using magnetic field sensors has paved the path for single molecular analysis and thus highly promising for ultrasensitive detection of cancer biomarkers at early stages. The magnetic field sensors are usually fabricated using soft magnetic sensor element in the form of film, wire, and ribbon. Though, the formation of film reveals several advantages in terms of better homogeneity, integration and optimal structures of the layers. The sensitivity of the magnetic wires can be enhanced significantly after the inclusion of coupled microwires, while the acid-treated ribbons show better detection sensitivity. However, the magnetic films with multilayer structure reveal better applicability in magnetic particles detection owing to their high field sensitivity. Though, the development of films via electroplating can result in lower performance due to the instability in structure. In this context, vapor deposition or sputtering techniques can be more effective for thin film formation with uniform magnetic properties throughout the sensor surface. The fabrication of magnetic field sensors are now regularly performed by using different microfabrication processes to attain micro/nanometer scale dimensions and for integrating with microfluidic structure. In this direction, the next step is to take this technology into lab-on-achip platform to perform multiple operations such as sample preparation, molecular labeling, sample detection and analysis in a single common device. Moreover, such lab-on-a-chip devices possess multiplexing capability for simultaneous analysis of multiple cancer biomarkers in a single step for early cancer discovery. Implementation of theoretical models and simulations toward the optimal designing of magnetic sensors can help to enhance feasibility, accuracy and reliability in sensor performances. The future perspectives of the magnetic sensors indicate rapid development in device design and sensing methodology with the help of interdisciplinary field of research involving molecular diagnostics, bionanotechnology, and material sciences. The attractive features of magnetic sensing techniques are highly promising for providing better healthcare platform for cancer diagnostics and therapeutic applications. With further development in resources and miniaturization techniques, such portable technology can expedite cancer diagnosis and making the results available in

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doctor office and/or bedside of the patients within a few minutes. It is highly anticipated that in near future, such magnetic-based techniques might be capable to identify cancer at very early stages, producing much higher chances of recovery.

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Chapter 7 Magnetic-based sensing

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Microfluidics for early-stage cancer detection

8

Shuvashis Dey Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, QLD, Australia

8.1

Introduction

Cancer is the second leading cause of death worldwide after heart disease [1]. One of the major reasons of cancer-related morbidity and mortality can be attributed to the heterogeneous nature of disease progression and late detection often after the spread of cancer throughout the body [2]. Conventional cancer diagnosis involves tissue biopsy, which is invasive, and detection is mostly possible after disease spread. To overcome the current limitations associated with cancer diagnosis, several cancer biomarkers (e.g., cells, DNA, protein, etc.) have been identified in blood and other body fluids that present long before the visible symptoms of cancer and are considered as ideal candidates for cancer diagnosis [3]. Despite their close relevance for early-stage disease detection, utilization of this candidate signatures for routine disease diagnosis and monitoring is extremely challenging mainly due to the dearth of highly sensitive and specific techniques for their analysis [4,5]. More recently, microfluidic techniques for biosensing have gained much attention for cancer diagnosis as they permit the detection of extremely low amount of target analytes which is highly desirable for early-stage cancer diagnosis. Few of the inherent advantages of microfluidic assay techniques are high sensitivity and specificity, low sample requirement and reagent consumption, etc. [6]. By definition, a device with channel dimensions of less than 1 mm is considered as a microfluidic device [7]. In a typical microfluidic assay, a biological fluid containing target biomolecules is flown through the microfluidic compartment and targets are either separated and collected in the outlet based on their physical properties or captured on the microfluidic surfaces functionalized with capture antibodies Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00002-0 © 2021 Elsevier Inc. All rights reserved.

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specific to the target biomolecules of interest. Post-separation, targets are tagged with secondary antibodies and detected utilizing standard detection techniques, e.g., fluorescence detection, Raman microscope, etc. The microfluidic compartments can be designed in a way to produce distinct flow patterns for separating biomolecules in different streamlines based on their size and other physical properties for label-free separation of the targets [8,9]. Furthermore, micro or nanoscopic physical barriers can be introduced within microfluidic device to facilitate size-based retrieval of targets from complex biomolecule mixture. Different surface modification techniques also enable to immobilize microfluidic compartments with target antibodies that simplify immunoaffinity isolation of biomolecules based on their biological characteristics. Antibodies can be immobilized by different techniques that include (1) intermolecular forces, (2) bioaffinity interaction, (3) covalent bond, and (4) use of spacer [10]. In this regard, antibody immobilization on gold patterned microfluidic surface via biotin-streptavidin chemistry is a common approach for antibody functionalization within microfluidic device [11]. Moreover, the integration of physical barriers and surface modification with target antibodies within a microfluidic device empowers the system for separating cancer cells from other blood cells through their size and purifies the targets based on their cell surface protein biomarker expression. Flow manipulation within microfluidic compartments enhances the capture performance on an antibody functionalized surface by increasing the collision between target biomolecules to the immobilized antibody surfaces. This manipulation can be achieved by one of many methods: (1) specific microchannel geometry, that is, herringbone, circular device geometry; (2) electric field-induced fluid flow manipulation [8,12]. The introduction of specific structures within a microfluidic compartment promotes local fluidic vortices which in terms facilitates better diffusion of targets to the capture surface. Detection of biomolecules can be carried out both within a microfluidic device and off-device based on the working principle of the immune assay protocol. In general, microfluidic approaches that include physical properties for target isolation employ off-chip detection and analysis of the target conventional detection approaches (e.g., fluorescence, SERS, etc.). In most of the microfluidic assays that employ immune affinity-based target isolation utilize tagged detection biomolecules for on-device target detection and analysis using fluorescence microscope or Raman microscope [12,13]. Colorimetric approaches can also be applied for naked eye detection of target biomolecules within a

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187

microfluidic device. One of the most common approaches for colorimetric detection involves tagging of captured biomolecules within a chip by HRP labeled secondary antibody and subsequent flowing of 3,30 ,5,50 -Tetramethylbenzidine (TMB) solution through the channel to enable colorimetric readout. In this chapter, we discuss the key biomarkers and the existing challenges for their detection. Microfluidic approaches for cancer diagnosis with an aim to deliver the fundamentals of the techniques and their applicability in next-generation biosensor development for cancer diagnosis are also presented with relevant examples.

8.2

Blood-based cancer biomarkers and challenges in analysis

The inquest for early-stage cancer diagnosis has triggered the discovery of different blood-based biomarkers (Fig. 8.1) that are present in circulation well before the visible symptoms of cancer. These signature biomolecules are considered as potential indicators for non-invasive and early-stage disease diagnosis and therapy monitoring [3]. Blood-based biomarkers include circulating tumor cells (CTCs), circulating protein biomarkers, cancer cell-derived exosomes, and circulating tumor-specific nucleic acids (e.g., DNA, RNA). CTCs are released from the primary tumor site by metastatic process into bloodstream and form secondary lesions in different parts of body distant from the site of their origin [14]. These CTCs overexpress protein biomarkers related to cancer and cargo significant molecular information for cancer diagnosis and therapy selection. Along with CTCs, mutated

Figure 8.1 Blood-based biomarkers for early-stage cancer diagnosis and therapy management.

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proteins derived from cancer cells are also available in bloodstream that can be detected and analyzed for cancer diagnosis [15]. More recently, cancer-derived exosomes are identified in blood circulation that carry important information for cancer burden [16]. Along with the above mentioned biomarkers, circulating nucleic acids (i.e., cfDNA) also make them an ideal candidate for cancer diagnosis [17]. These nucleic acid biomarkers are primarily excreted from apoptotic cancer cells and released in blood thus identification and sequencing of mutated sequence can lead to important insight into the disease status, progression pathway, and therapeutic target selection. Despite their significant importance in cancer diagnosis, utilization of the aforementioned biomarkers for cancer management is significantly challenged due to their extremely low abundance in biological fluid and lack of suitable methods for their identification and analysis. CTCs can be found in blood in extremely low number (about one tumor cell per 1 billion blood cells) which make the task of their isolation within a background of blood cells extremely challenging [18]. Furthermore, protein biomarkers in blood are also present in very low amount ranging from femto to picomolar level [19]. A similar concentration range is also reported for circulating nucleic acids [20]. Conventional techniques for cell analysis, for example, flow cytometry require larger sample volume and are not suitable for extremely low number of target cells thus make these techniques unsuitable for CTC analysis. Moreover, detection of extremely low amount of circulating cancerspecific proteins or mutated nucleic acids are challenging through conventional western blot and PCR based techniques due to sensitivity issues. To overcome the current limitations for cancer biomarker analysis from biological fluids several microfluidic approaches have been developed or under investigation that showed significant improvements in cancer biomarker analysis. The following section discusses different microfluidic assay platforms for cancer biomarker analysis.

8.3

Fabrication of microfluidic biosensors

The utilization of microfluidics in biosensor development is greatly aided by the advancement of different fabrication techniques. One of the common and inexpensive methods for microfluidic channel preparation involves laminate manufacturing method [7]. In this method, microfluidic

Chapter 8 Microfluidics for early-stage cancer detection

devices are prepared by a stack of independently prepared layers with specific features and bonded together to form a complete device. A simplest layered microfluidic device has three layers including a top layer (glass or plastic) containing inlets and outlets, a patterned flow layer prepared of polymer layers (commonly polycarbonate, PMMA, and COC) and a bottom layer (glass or plastic). Although this method is easy and inexpensive, the widths of the prepared microfluidic channels are limited to 50200 μm which may not be suitable for applications that require microchannel width smaller than 50 μm. Molding is another kind of fabrication method that allows for the preparation of more precise and complex microfluidic devices (e.g., multilayer microfluidic channels). This method can be subdivided into three classes: (1) replica molding, (2) injection molding, and (3) hot embossing. Replica molding, more commonly known as soft lithography is a widely used method for microfluidic device fabrication. The method was first introduced by Xia and Whitesides in 1998 and since then have been extensively employed for microfluidic device fabrication for various purposes, for example, microfluidic biosensor development [21]. It is a low cost and faster fabrication technique and requires cheaper materials and tools. This method involves the preparation of photomask with microfluidic design of interest and transfer of the design on polymer-coated (e.g., SU 8 negative photoresist) silicon or glass wafer to generate a replica mold. This step is achieved by UV exposure of the photomask on a photoresist coated wafer surface and subsequent development of the exposed wafer to unveil the patterns on the wafer (master fabrication). After master mold preparation, a polymer mastermix (e.g., PDMS) is poured over the mold and cured to generate a patterned polymer layer and finally the cured polymer layer is peeled from the mold surface and attached to clean surface (e.g., glass, plastic, silicon, etc.) to form a complete microfluidic device (Fig. 8.2). Along with laminating and replica molding, recent advancements in 3D printing and nanofabrication techniques have significantly improved the current fabrication techniques and allow to generate nanofluidic channels with high precision. However, the methods are complex and require specialized training and sophisticated instrumentation for the production. Furthermore, relative high expenses, multistep processing, and low throughput are few of the bottlenecks for their commercial success.

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Figure 8.2 Step-by-step soft lithography process for microfluidic device fabrication.

8.4

Microfluidics for cancer diagnosis

Until now several microfluidic assay techniques have been developed for blood-based cancer biomarker analysis that hold great potential to be translated as point-of-care liquid biopsy for cancer management. This section discusses different microfluidic techniques for cellular and subcellular biomarker analysis from patient blood samples.

8.4.1

Microfluidic biosensors for circulating tumor cell detection

Circulating tumor cells are primarily shed from tumor site into the blood and carry molecular information of the tumors. Detection and characterization of these cells hold great potential for early-stage cancer diagnosis, treatment selection, and therapy monitoring. However, isolation of CTCs in blood is extremely challenging due to their very low abundance and require highly sensitive and specific method. The increasing knowledge about different physical and molecular characteristics of CTCs make it

Chapter 8 Microfluidics for early-stage cancer detection

possible to isolate them from billions of blood cells with high specificity and sensitivity. In the following sections, we discuss different microfluidic approaches that utilize physical and biological properties of CTCs for the isolation and analysis.

8.4.1.1

Size-based separation of circulating tumor cells in microfluidics

CTCs are generally larger than other blood cells, and this physical property leads to the development of several microfluidic approaches for label-free isolation of target CTCs from blood samples [22]. One of the common principles for microfluidic size-based separation relies on the fabrication of spatially distributed miro-nono structures within a microfluidic capture domain to selectively retain larger CTCs through deflection of their flow trajectory by the microstructures while removing smaller biomolecules through the microfluidic channel under continuous hydrodynamic fluid flow condition (Fig. 8.3A) [9,23]. Using this approach, Loutherback et al. successfully isolated CTCs from blood at a blood processing rate of 10 ml/min [23]. Another label-free method for CTC isolation employs the migration pattern of particles in different streamlines within a specially designed microfluidic compartment (e.g., circular microfluidic channel) [8,2426]. This phenomenon allows for the focusing of larger CTCs in different flow lines well separated from the trajectories of smaller biomolecules within a microfluidic channel [8,27]. At a constant fluid flow within the spiral microfluidic channel, CTCs and other biomolecules present in the sample experience inertial lift forces resulting from the parabolic nature of the laminar flow profile and shift closer to the channel wall from the center of the microfluidic channels. The migration pattern is dictated by the biomolecules’ sizes that facilitate to focus CTCs in distinct streamlines and subsequent retrieval of the targets in designated outlets (Fig. 8.3B). In their most recent study, Zhou et al. developed a novel microfluidic technique for label-free isolation and recovery of single CTCs or CTC clumps from complex biological fluids while minimizing the manual handling steps and also demonstrated the viability of recovered CTCs. This method relies on a purpose build microfluidic channel network comprises of upstream microfluidic conduits that act as cell separation region within the chip and a cell trapping domain with arrays of microchambers for capturing CTCs. Within the upstream microfluidic channel, the effect of shear induced diffusion (SID) generated from the pattern of blood flow separated by buffer

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Figure 8.3 Different microfluidic approaches for physical property and immunoaffinity based CTC isolation in microfluidics. (A) micropillar array for lateral displacement based CTC isolation microfluidic assay. (B) Inertial focusing circular microfluidic chip for CTC isolation [27] (C) Nanowire microfluidic chip for CTC isolation. (D) Microfluidic chip for size-based separation and immunomagnetic isolation under magnetic field. Source: Picture reproduced with modification from Khoo, B.L. et al. Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells. PLoS one 9, e99409 (2014).

fluid facilitates the streamlining of CTCs distinct from other cell types. These cells are then captured in patterned microcompartment arrays of the chip for enumeration, characterization and downstream analysis. Using this chip based method, Zhou et al. successfully trapped 70% of the target cells flown through the chip and demonstrated the viability of isolates after 10 days of on-chip cell culture [28]. Another good example of a microfluidic chip was proposed by Riberio-Samy et al. where the group developed a CROSS chip to isolate CTCs with 70% efficiency. This method contains a specially designed microfluidic chip with four modules containing sets of prefilters and filters for cell separation that allow the size and deformability based separation of CTCs from complex sample.in the prefilter sections micropillers are spaced by 120 μm where single row of 25 μm micropillars separated by 5 μm in the middle section comprise the cell separation area.

Chapter 8 Microfluidics for early-stage cancer detection

The technique is quick and 7.5 mL of blood can be processed using two chips simultaneously within 47 minutes [29]. Similarly, Su et al. reported a microfluidic system fabricated with arrays of microtraps for preferentially capture cells based on their size and deformability. The device contains four layers top of which is a gas control layer containing microvalves and micropump channels to control fluid movement. The middle two layers contain microfluidic channels for fluid movement throughout the chip. The bottom layer contains microcompartments where cells of interest are trapped while flow through the channels. Once trapped in the designated positions, cells can then be labeled with secondary antibodies for their detection and characterization [30]. Jiang et al. also developed a DLD-based microfluidic method that showed high-efficiency retention of CTCs from complex biological samples. This method combines lateral flow phenomena with immunomagnetic separation within the same microfluidic chip for delivering high purity CTC retention. Sample containing target cells are initially flown through microfluidic compartment containing arrays of microposts where larger cells are laterally displaced in the center of the chip. In the second step, white blood cells labeled with anti-CD45 magnetic beads are separated using external magnet and finally purified CTCs are collected from the chip. This chip based CTC retrieval process is quick, can handle 1 mL of blood per minute with CTC retrieval purity of 50% where viability remains 90% [31]. Although size-based separation provides multiple advantages: (1) label-free isolation, (2) requires no antibody labeling, (3) less complex workflow, etc., these methods are not free from drawbacks. One of the major limitations is the fact that CTCs have heterogeneous size distribution that results in low purity and loss of CTCs in many of the physical property based CTC isolation techniques [32,33].

8.4.1.2

Microfluidic immune-affinity separation of circulating tumor cells

In-depth knowledge of molecular properties of CTCs has led to the identification of several cell surface protein biomarkers [34]. These protein signatures are often upregulated in CTCs and provide attractive targets for immunoaffinity based isolation of CTCs from patient samples. Until now, overexpression of EPCAM is the most widely used biomarker for CTC analysis [35]. Other biomarkers, such as HER2 protein expression on breast cancer-associated CTC surfaces is a widely used

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biomarker for immunoaffinity isolation of target cells and is utilized in microfluidic assay techniques for disease detection [36]. Like direct ELISA technique, anti-HER2 antibodies and/or other cell surface protein biomarker specific antibodies can be attached on the microfluidic capture domain to specifically isolate target CTCs by flowing sample fluid through the microchannel. In their pioneering study, Nagrath et al. developed a microfluidic platform of micropillers functionalized with antiHER2 antibodies and successfully retrieved CTCs from patient samples [13]. The special geometry of these micropillars facilitates to increase chaotic micro-mixing of the sample fluid with antibody functionalized surface, hence increases capture efficiency. After capture, target cells can be labeled within the microfluidic compartments with fluorescent secondary antibodies that allow to detect and characterize targets on-chip. Surface modification with nanowires are also employed for high-efficiency CTC capture and selective release from the microfluidic domain that facilitates both target purification from blood samples and subsequent downstream molecular analysis (Fig. 8.3C) [37]. Along with direct antibody immobilization on microfluidic channels, labeling of antibody tagged magnetic beads on CTCs and subsequent retrieval of targets within a microfluidic domain is another common approach for cancer cell isolation. Commercial magnetic beads are available in varying sizes (50 nm5 μm) that can be functionalized with target antibodies. These antibody labeled magnetic particles can be used to capture CTCs from blood in a microfluidic compartment under magnetic field or can be deflected in distinct streamlines for their isolation in microfluidic outlets (Fig. 8.3D) [38,39]. Deliorman and colleagues developed an integrated microfluidic technique enable with atomic force microscopy (AFM) for simultaneous isolation of CTCs from whole blood sample tailored with their physical characterization, that is, elasticity and adhesiveness. Within their microfluidic system, the reversibly bonded PDMS patterned with microfluidic channel enable to flow and capture of prostate cancer CTCs to be captured on target specific antibody labeled glass surface and subsequent labeling with detection antibody. Furthermore, postcapture peeling off the PDMS chip from the glass slide facilitates to transfer the glass slide into AFM platform for investigating the elasticity and adhesiveness of individual captured cells. Using this integrated AFM-microfluidic technique, Deliorman et al. successfully captured CTCs from whole blood and reported the variability of adhesiveness among CTCs where metastatic CTCs

Chapter 8 Microfluidics for early-stage cancer detection

have lesser multiple adhesion tendencies than CTCs from localized cancer [40]. To directly quantify CTCs, Kong et al. proposed a microfluidic coulter counter aiming to detect and count CTCs directly from patient’s whole blood. In this approach, they utilized both immunoaffinity based purification and resistive pulse sensing for enumerating individual captured CTCs that passes through the detection zone. This platform comprises of a CTC isolation and a microfluidic coulter counter chip to empower the technique with high-efficiency purification and simple quantification. The microfluidic coulter counter contains pair of electrodes orthogonally placed through the length of microfluidic channel. An electric field is applied through the electrodes that results into change in resistance when single cell passes through the electrodes and provides unique signature for cell counting. In the first sept of experiment, sample fluid containing target cells are passed through a microfluidic capture chip already functionalized with antibody of interest for purification of rare number of CTCs from other sample components. Postcapture, cells are enzymatically released and flown through microfluidic coulter counter which allows for the easy and straightforward quantification of CTC population. Furthermore, these cells can be subsequently utilized for downstream analysis too which is not often for many of the currently available methods [41]. To improve cell capture with immunoaffinity approach, DNA structures attached with aptamers for CTCs isolation is also reported. In their method, Zhang et al. utilize a DNA nanolithography approach for device functionalization by utilizing sub-10 nm three-dimensional DNA structures (TDNs) attached with aptamer molecule specific to CTCs cell surface biomarker. This unique strategy for functionalization conserves the proper orientation of aptamers which intern ensures optimal interaction between target cells in sample fluid and the aptamer functionalized capture surface, hence improve isolation specificity and sensitivity. Furthermore, captured cells from the surface can be easily released by injecting DNase I and the viability of the released cells remains high. Using this method, they demonstrated 83% release efficiency where 91% of the released cells were viable [42]. A double mode microfluidic chip based method for CTC isolation is recently reported by Tsai et al. where both immunomagnetic and size exclusion strategies are utilized. Within this method, after RBC lysis, WBCs are depleted using anti-CD45 magnetic bead within WBC depletion zone of the microfluidic

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chip under magnetic field. The purified sample is flown in the target isolation zone where CTCs are labeled with aptamer coated magnetic beads and isolated using an external magnet placed underneath the chip. In the final step, the magnet is removed and target cells can be collected for subsequent analysis. Although the method is simple but recovery rate is poor (62 6 3%) [43]. Although microfluidic techniques have already shown their potential for biosensing applications, one of the major considerations for their translation into regular clinical screening is the complexity of microfluidic chip preparation. In almost all cases, the fabrication takes place in cleanroom equipped with expensive microlithography instruments. To address this issue, Chen et al. developed a 3D printed microfluidic platform for efficiently isolate CTCs from complex sample fluid. The inner surface of 3D printed microfluidic chip has mesh like designs to enable efficient capture antibody loading and maximize fluid mixing withing the channel. With this method, Chen et al. demonstrated high-efficiency capture ( . 90%) of spiked CTCs from four different cancer types where the optimal flow rate was 1 mL/hr. [44]. Despite their highly specific and sensitive performances, most of the current microfluidic assay techniques are limited to analyze small sample volume, ideally up to few mLs of blood. However, due to the extreme rarity of CTCs, only analyzing a small fraction of blood may not provide the exact cancer status and also may causes false negative assay outcome. To address this issue, Tang et al. developed a highly sensitive microfluidic technique with an aim to directly extract blood from patient body followed by following the extracted blood through microfluidic chip for immunomagnetic target screening and finally reinfusing the screen blood into the patient body. The microfluidic platform contains three main parts: peristelic pump, immunomagnetic separation chamber (microfluidic domain), and a heparin-based anticoagulation device. In their study Tang et al. demonstrated the utilization of their technique for CTC isolation from mouse blood. After inserting a polyethylene (PE) tube into the blood vessel of candidate mouse, blood was extracted using the peristelic pump and flown through the microfluidic capture domain, inside the capture domain, the captured surfaces were functionalized with capture antibodies that effectively isolated CTCs from the blood sample flow through the chip. After screening, blood was then reinfused to the patient body. The operational mode of this microfluidic platform is relatively simple and could be scaled up for its application of total blood analysis in human [45].

Chapter 8 Microfluidics for early-stage cancer detection

In most of the current CTC biosensing techniques, final readout is mainly carried out by fluorescence detection that claims expensive high-end microscopes and technical expertise. In an attempt to find an alternative, Prathap et al. reported a microfluidic platform coupled with electrochemical readout for high efficiency immunomagnetic isolation and detection of CTCs from sample fluid. This method employs current changes as a readout for CTC detection, thus does not rely on fluorescence based detection schemes which are complex to perform, expensive and often challenging for low number of cells. In this reported microfluidic system, a three-electrode electrochemical sensor is placed orthogonally along the bottom layer of a microfluidic channel. The working electrode is functionalized with capture antibodies and serves as a CTC capture domain. When sample fluid flows through the microchannel, target cells are captured on the antibody functionalized domain of this working electrode and readout is then carried out by realizing the current differences by applying external potential through the electrodes. Change in the current before and after cell capture is directly proportional to the number of target cells captured on the chip. Using this method, Prahap et al. successfully detected 1 melanoma specific CTCs from 1 mL of blood with detection range of 109000 melanoma cells/10 mL [46]. One of the important limitations exists in most microfluidics platforms is their ability to separate only one type of cancer cells from patient sample. This significantly impedes the translation of this techniques for regular clinical application as prior prediction is necessary to select screening platform. Realizing this, Gurudatta et al. developed a microfluidic electrochemical sensor that could potentially employ for separation all kinds of CTCs (e.g., high biomarker or low biomarker expressing CTCs, large or small CTCs, etc.) for patient blood. The method employs a microfluidic channel modified with conducting polymer that plays the key role for CTC separation. At applied AC potential, under hydrodynamic flow condition, cancer cells and other blood cells flow along the length of the microfluidic channel in a wavelike motion. Small size blood cell passes faster than larger CTCs which provides a mean of separation. Separated cancer cells are then detected utilizing electrochemical method by placing working and counter electrodes at the end of the microfluidic system. Using this method Gurudatt and coworkers successfully separated CTCs with 92 6 0.5% efficiency and showed high detection rate (90.9%) [47]. Although immunoaffinity based CTC isolation provides more specificity and purity, the extreme rarity of CTCs (as low as

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1 cell in 1 ml of blood) demands the processing of large sample volume (e.g., 7.5 ml of blood). Such large sample processing in microfluidic devices are not feasible for most of the current microfluidic settings. Further, biomarker expression levels in CTC is heterogenous which poses additional challenges for isolating targets with low protein expression. This limitation can be overcome by targeting multiple biomarkers within a microfluidic assay that will allow targeting multiple subpopulations of CTCs present in the same blood sample.

8.4.2

Microfluidic biosensors for cancer protein detection

Protein biomarkers circulating in blood are another source of liquid biopsy for cancer diagnosis. Along with disease detection, these biomarkers are also important to understand disease progression mechanisms as well as for identifying new targets for further treatment [48]. However, the clinical thresholds for circulating protein biomarkers are usually in femtomolar to picomolar range which makes conventional techniques (e.g., western blot) insufficient for their utilization in routine pathology laboratories [19]. To circumvent the current limitations, several microfluidic approaches have been coined for ultrasensitive and specific isolation and detection of cancer protein biomarkers in patient blood samples [11,4953]. In a typical microfluidic immunoassay for circulating protein biomarker analysis, bottom surfaces of microfluidic domains are modified with immobilized capture antibody to isolate target protein biomarkers from complex blood sample. This antibody functionalization along with specific microscopic design of microfluidic channels allows the rapid diffusion of target analytes toward the microfluidic capture domain and enhances isolation of target proteins by antibody antigen interaction. In one approach, Goluch et al. developed a single disposable microfluidic chip for single protein biomarker detection [50]. The developed microfluidic device contains two domains: (1) protein capture domain and (2) detection domain. Within the capture domain, a serpentine microfluidic channel is primarily coated with antibody labeled magnetic beads under the application magnetic filled by placing a permanent magnet below the chip. The sample is then flown through the capture domain and targets are immobilized by the immunoaffinity interaction between capture antibodies and target proteins. This step is then followed by passing solution of secondary antibody and DNA barcode decorated gold nanoparticles (secondary antibody cluster) through the capture domain.

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Subsequently, barcode DNA strands are released from the captured secondary antibody cluster and transferred to the detection domain patterned with complementary DNA strands. A second set of gold nanoparticles tagged with complementary barcode DNA sequences is then injected to the detection domain for their hybridization with barcode DNA sequences and finally optical detection is carried out by introducing silver staining solution to the detection domain (Fig. 8.4A). This method is extremely

Figure 8.4 (A) Microfluidic approach for protein detection by isolating target proteins with antibody labeled magnetic beads and subsequent optical detection. (B) Electric field-induced hydrodynamic phenomena for protein detection in microfluidics and surface-enhanced Raman scattering based detection [56]. Source: Figure adapted from Kamil Reza, K. et al. Electrohydrodynamic-induced SERS immunoassay for extensive multiplexed biomarker sensing. Small 13, 1602902 (2017).

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sensitive and has been demonstrated for the detection of 500 aM concentration of prostate-specific antigens in buffer solution and goat serum samples [50]. Oteino et al. developed an integrated microfluidic platform for protein biomarker analysis as low as fg/mL. The microfluidic chamber employs an external magnetic stirrer for capturing target proteins with antibody labeled magnetic beads. This step is followed by multiple wash step to remove nonspecifically adsorbed molecules. Post-wash captured proteins on magnetic beads are transferred to detection zone by disengaging the external magnet and subsequently captured with antibody immobilized gold surface and electrochemical readouts are carried out for protein detection purposes. This method is extremely sensitive and demonstrated for detection of 5 fg/mL and 7.5 fg/mL of interleukin-6 (IL-6) and IL-8 in serum, respectively [54]. An example of nanoparticle modified microfluidic biosensor is reported by Nunna et al. where differences in capacitance before and after protein capture on antibody functionalized surfaces are used as readout method for the analysis. The attachment of gold nanoparticles on plain electrode provides more surface area for antibody functionalization, hence improve target capture and detection. Moreover the microfluidic flow condition within this proposed microfluidic system enhances target specificity and sensitivity while lowed noise from background molecules within sample fluid [55]. Electric field-induced hydrodynamic phenomena within a microfluidic domain with highly sensitive surface-enhanced Raman scattering (SERS) based detection are also utilized for protein biomarker detection from patient samples [11]. This proposed microfluidic system contains asymmetric planner of gold electrode pairs within the floor of microfluidic channels that are utilized to immobilize capture antibodies and to generate hydrodynamic fluid flow under applied electric field condition (Fig. 8.4B). Electric field-induced sample flow through the microfluidic domain enhances collision between target biomolecules to the capture antibodies hence increases capture efficiency and facilitates to remove nonspecifically adsorbed molecules from the biosensing surface. Post capture experiment, secondary antibody labeled SERS nanotags are flown through the capture domain and finally detection is carried out using Raman microscope. This method can also be applied for multiple cancer-associated protein biomarker analysis from same patient sample [56]. In another study, Seenivasan et al. developed a microfluidic platform integrated with electrochemical readout zone for ultrasensitive detection of prostate-specific membrane antigen (PSMA). Using this method, they have

Chapter 8 Microfluidics for early-stage cancer detection

successfully detected as low as 0.499 ng/40 μL PSMA in sample fluid. In this method, an indium tin oxide (ITO) three-electrode sensor surface is modified with gold nanoparticles functionalized with anti-PSMA antibody. A microfluidic channel is placed on the sensor surface for sample fluid transport and washing steps that allow for the minimal sample requirement while enable maximum capture on the functionalized surface. Post capture, detection is carried out using differential pulse voltammetry signal of a redox probe ([Fe(CN)6]3/ [Fe(CN)6]4) that reflects the amount of protein captured on the surface [57]. In a recent approach, Bahavarnia et al. developed a paper based microfluidic technique for screening cancer-related protein biomarkers. The fabrication of this highly sensitive paper microfluidic approach follows multistep development phases. For instance, the process starts with printing of Ag/RGO patterns on a flexible paper substrate using special nano-ink through a pen-on-paper technology. A layer of cysteamine caped gold nanoparticles (CysA/Au NPs) is then developed on the Ag/RGO coated surface using electrochemical technique. Sulphur and amie groups of Cys enable to anchor gold nanoparticles to the Ag/RGO surface. Finally, capture antibodies (e.g., anti-CA 125 antibody) are immobilized on the gold surfaces by electrostatic interactions to form a complete biosensors. Post-capture of target proteins from biological fluids, chronoamperometry technique can be utilized for detection purposes and showed the method has been demonstrated for the detection of protein samples (e.g., CA 125) as low as 0.78 U/mL from sample fluid [58].

8.4.3

Microfluidic biosensors for cancer exosome detection

Exosomes are small microvesicles of B30200 nm secreted by cells that carry cellular materials including nucleic acids, proteins, enzymes, etc. and are considered as important tools for cancer diagnosis and disease management [59]. In recent years, several microfluidic approaches have been employed for exosome isolation from patient samples. In a microfluidic setting, capture domain is initially modified with capture antibodies and subsequently, a patient sample is driven through the device for efficient exosome isolation. Post-capture, detection is carried out by labeling of the isolated targets with secondary antibodies. For exosome capture, the microfluidic chip can be designed with herringbone-patterns to increase mixing

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of sample fluid when flow through the microchannel under hydrodynamic flow condition [60]. Such a chaotic fluid flow pattern enhances collision between target molecules with capture antibody functionalized bottom surface of the microfluidic compartment and results in better recovery (Fig. 8.5A). In recent approach, Kamari et al. developed a microfluidic platform with high mixing facility withing the fluidic conduit to enhance target capture efficiencies. Withing their developed microfluidic system, arrays of micropillers are fabricated in a way to enhance collision between target microvesicles in the sample fluid with antibody functionalized micropillers. The method is highly efficient and can sufficient number of

Figure 8.5 (A) Herringbone microfluidic device for exosome isolation. [60]. (B) Nanostructure fabricated microfluidic device for exosome isolation [62]. Source: Figure adapted with modification from Rea´tegui, E. et al. Engineered nanointerfaces for microfluidic isolation and molecular profiling of tumor-specific extracellular vesicles. Nat. Commun. 9, 111 (2018). Figure adapted with modification from Chen, Z. et al. Detection of exosomes by ZnO nanowires coated three-dimensional scaffold chip device. Biosens. Bioelectron. 122, 211216 (2018), with permission from Elsevier, copyright 2019.

Chapter 8 Microfluidics for early-stage cancer detection

microvesicles to extract B214 ng of DNA from 2-ml plasma for downstream analysis [61]. Surface modification can also be achieved by introducing different nanostructures, such as ZnO nanowires within the bottom surface of the capture domain (Fig. 8.5B) [62]. This nanowire patterned microfluidic surface provides the basis of exosome specific antibody immobilization. Under hydrodynamic flow condition, sample fluid containing cancer-specific exosomes are captured by the immobilized antibodies and separated from other biomolecules of the biological fluid. Postcapture, horseradish peroxidase (HRP) labeled antibody solution is passed through the channel and finally colorimetric exosome detection is carried out by flowing 3,30 ,5,50 -tetramethylbenzidine (TMB) solution through the microfluidic compartment. In the presence of HRP, TMB gets oxidized and the colorless solution becomes blue. The intensity of color is directly proportional to the amount of HRP and correlates to the number of exosomes captured within microfluidic domain. Zhang et al. reported a microfluidic approach by employing graphene oxide/polydopamine (GO/PDA) nanointerface that assists to improve capture antibody loading and their correct orientation. In addition to that, the microfluidic chip contains arrays of Yshaped microposts that also enhances the mixing phenomena within the capture domain, hence improve target isolation efficiencies. The method is extremely sensitive and was able to isolate exosomes from as low as 2 μL of unprocessed plasma sample [42]. In a recent attempt, Zang et al. devised a microfluidic chip having patterned silica colloidal nanoparticles along the bottom surface of the chip to generate herringbone like arrays. These microstructures along the length of microfluidic domain disrupts laminar fluid flow patterns, introduces microvortices that ensure better mass transfer. Furthermore, the patterned nanoparticles containing nanopores that allow partial flow of fluid through the gaps between particles also minimize near-surface hydrodynamic resistance and assist to get better collision between targets and capture domain. The device is very sensitive and was evaluated for cancer exosome analysis from only 2 μL of plasma samples [63]. Acoustic microfluidics is one of the newest additions for label-free isolation of exosomes using a miniaturized technique. Basically, under applied ultrasound actuation, particles can be moved and spatially localized which are dictated by the physical characteristics of the particles and the nature of the applied sound. Within a microfluidic domain, acoustophoretic separation enables to separate and purify exosomes from other blood components with high specificity and sensitivity. This method was demonstrated for exosome isolation from whole blood while

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other blood cell removal rate was over 99.999% [64]. The benefit of microfluidic approaches for exosome analysis is expanded far from only purification and quantification. For example, Ai and coworkers encapsulated the benefits of immunoaffinity and hydrodynamic focusing withing a custom made microfluidic device in an attempt to purify specific exosome population from complex biological fluid. For this, they initially functionalized microbeads with capture antibodies specific for exosome capture, then incubated with samples for exosome capture and finally added fluorescent labeled secondary antibodies prior to flow in the microfluidic device. Herein, samples were driven through microchannels (width 5 50 μm) having microbead capture zones (30 μm aperture connected to a 10 μm narrow channel) where exosome containing beads were trapped and subsequently used for detection or downstream molecular analysis. This microfluidic flow based method is simple and rapid. Furthermore, exosomes from captured beads can be released and used for their nucleic acid and miRNA contents [65].

8.4.4

Microfluidic biosensors for cell-free DNA (cfDNA)

Cell-free DNA (cfDNA) released into body fluid derived from cancer cells carry signatures (i.e., mutations) associated with disease condition. Thus, isolation and downstream analysis of cfDNA from clinical samples can provide an effective and minimally invasive means for cancer diagnosis and therapy management [66]. However, extraction of these cfDNA is extremely challenging due to the relatively short size of the fragments (,150 bp) and requires multistep workflows that often results in poor yield [67]. Recent advancements in microfluidic techniques have significantly contributed to the efficient and specific cfDNA isolation from patient samples for their molecular analysis. Utilizing the advantages of microfluidic techniques, it is possible to isolate cfDNA as low as 0 to 342 ng/mL from serum sample of cancer patients [68]. cfDNA extraction microfluidic chip can be designed with a bed of positively charged microparticles for negatively charged DNA capture [68]. Upon the injection of serum sample within the microfluidic chamber, cfDNAs are captured on the microparticles and subsequently released by the application of elution buffer for downstream analysis. This method can be also extended for other circulating nucleic acid biomarker detection, for example, mRNA, miRNA, etc.

Chapter 8 Microfluidics for early-stage cancer detection

Another example of microfluidic approach for cfDNA extraction from plasma sample employs polymer and salt-induced condensation (psi-condensation) of DNA [67]. The device contains photoactive polymer layer for generating 2 COOH surface functionality by UV/O3 application. Under hydrodynamic fluid flow condition within the microfluidic chamber, neutralized DNA targets present in plasma sample condense onto the negatively charged surface. This allows for the purification of cfDNAs from complex biological fluid and subsequently, extracted cfDNAs can be eluted by flowing low ionic strength buffer through the capture domain of microfluidic platform. The method is highly efficient and successfully employed for the extraction of 90% of cfDNA fragments ranging from 100 bp 2 700 bp. Furthermore, shorter cfDNA fragments (50 bp) can also be recovered with an efficiency of .70% using this microfluidic approach. The method is less time consuming and requires lesser number of steps (requires 6 steps) compared to conventional commercial kits (requires 11 steps) [67].

8.5

Conclusions

Microfluidic techniques present an alternative to traditional assay methods for cancer biomarker analysis in biological fluids (e.g., blood). These methods utilize either physical properties of target biomolecules (e.g., size of CTCs) or expression of biomarkers (i.e., cancer-specific protein) to separate targets from other biomolecules in patient’s biological fluids. The inherent characteristics of microfluidic flow including rapid diffusion, rapid thermal transport, laminar and dean flows, high surface area relative to the sample volume enable to isolate extremely low amount of target molecules with high sensitivity and specificity from a complex of billions of blood cells and other biomolecules. Furthermore, low sample volume requirement, portability, low cost, easy to operate, etc. features make microfluidic approaches ideal candidates for point-of-care liquid biopsy for early-stage cancer diagnosis and therapy monitoring. Although potential, most of the microfluidic techniques are limited to proof of concept studies and are not commercially available for clinical diagnosis. Few of the major challenges associated with microfluidic biosensor development are intra- and interlaboratory reproducibility and lack of patient sample analysis. Thus, close collaboration between different laboratories working in the field of microfluidic biosensor development and longitudinal patient sample analysis could facilitate to overcome current challenges and commercialize microfluidic biosensor for early-stage cancer diagnosis.

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[20] L. Gorgannezhad, M. Umer, M.N. Islam, N.T. Nguyen, M.J.A. Shiddiky, Circulating tumor DNA and liquid biopsy: opportunities, challenges, and recent advances in detection technologies, Lab. Chip 18 (2018) 11741196. Available from: https://doi.org/10.1039/c8lc00100f. [21] V. Faustino, S.O. Catarino, R. Lima, G. Minas, Biomedical microfluidic devices by using low-cost fabrication techniques: a review, J. Biomech. 49 (2016) 22802292. [22] S.-J. Hao, Y. Wan, Y.-Q. Xia, X. Zou, S.-Y. Zheng, Size-based separation methods of circulating tumor cells, Adv. drug. delivery Rev. 125 (2018) 320. [23] K. Loutherback, et al., Deterministic separation of cancer cells from blood at 10 mL/min, AIP Adv. 2 (2012) 042107. [24] Y. Zhou, Z. Ma, Y. Ai, Hybrid microfluidic sorting of rare cells based on high throughput inertial focusing and high accuracy acoustic manipulation, RSC Adv. 9 (2019) 3118631195. [25] H. Chen, A triplet parallelizing spiral microfluidic chip for continuous separation of tumor cells, Sci. Rep. 8 (2018) 18. [26] M. Herrmann, T. Veres, M. Tabrizian, Quantification of low-picomolar concentrations of TNF-α in serum using the dual-network microfluidic ELISA platform, Anal. Chem. 80 (2008) 51605167. [27] B.L. Khoo, et al., Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells, PLoS one 9 (2014) e99409. [28] J. Zhou, et al., The label-free separation and culture of tumor cells in a microfluidic biochip, Analyst 145 (2020) 17061715. Available from: https://doi.org/10.1039/C9AN02092F. [29] S. Ribeiro-Samy, et al., Fast and efficient microfluidic cell filter for isolation of circulating tumor cells from unprocessed whole blood of colorectal cancer patients, Sci. Rep. 9 (2019) 8032. Available from: https://doi.org/ 10.1038/s41598-019-44401-1. [30] W. Su, et al., Integrated Microfluidic Device for Enrichment and Identification of Circulating Tumor Cells from the Blood of Patients with Colorectal Cancer, Dis. Markers 2019 (2019). Available from: https://doi. org/10.1155/2019/8945974. 8945974-8945974. [31] J. Jiang, et al., An integrated microfluidic device for rapid and high-sensitivity analysis of circulating tumor cells, Sci. Rep. 7 (2017) 42612. Available from: https://doi.org/10.1038/srep42612. [32] M. Alunni-Fabbroni, M.T. Sandri, Circulating tumour cells in clinical practice: methods of detection and possible characterization, Methods 50 (2010) 289297. [33] J.F. Chen, et al., Subclassification of prostate cancer circulating tumor cells by nuclear size reveals very small nuclear circulating tumor cells in patients with visceral metastases, Cancer 121 (2015) 32403251. [34] Yap, T.A., Lorente, D., Omlin, A., Olmos, D. & De Bono, J.S. (AACR, 2014). [35] S. Sharma, et al., Circulating tumor cell isolation, culture, and downstream molecular analysis, Biotechnol. Adv. 36 (2018) 10631078. [36] H. Cho, et al., Microfluidic technologies for circulating tumor cell isolation, Analyst 143 (2018) 29362970. [37] S. Wang, et al., Highly efficient capture of circulating tumor cells by using nanostructured silicon substrates with integrated chaotic micromixers, Angew. Chem. Int. Ed. 50 (2011) 30843088. Available from: https://doi. org/10.1002/anie.201005853. [38] Ozkumur, E. THE DISTILLERY.

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[39] H. Chen, et al., Hybrid magnetic and deformability based isolation of circulating tumor cells using microfluidics, AIP Adv. 9 (2019) 025023. [40] M. Deliorman, et al., AFM-compatible microfluidic platform for affinity-based capture and nanomechanical characterization of circulating tumor cells, Microsyst. & Nanoengineering 6 (2020) 20. Available from: https://doi.org/10.1038/s41378-020-0131-9. [41] C. Kong, et al., Label-free counting of affinity-enriched circulating tumor cells (CTCs) using a thermoplastic micro-Coulter counter (μCC), Analyst 145 (2020) 16771686. Available from: https://doi.org/10.1039/C9AN01802F. [42] P. Zhang, M. He, Y. Zeng, Ultrasensitive microfluidic analysis of circulating exosomes using a nanostructured graphene oxide/polydopamine coating, Lab. a Chip 16 (2016) 30333042. Available from: https://doi.org/10.1039/ C6LC00279J. [43] S.-C. Tsai, L.-Y. Hung, G.-B. Lee, An integrated microfluidic system for the isolation and detection of ovarian circulating tumor cells using cell selection and enrichment methods, Biomicrofluidics 11 (2017). Available from: https://doi.org/10.1063/1.4991476. 034122-034122. [44] J. Chen, et al., 3D printed microfluidic devices for circulating tumor cells (CTCs) isolation, Biosens. Bioelectron. 150 (2020) 111900. Available from: https://doi.org/10.1016/j.bios.2019.111900. [45] M. Tang, et al., Magnetic chip based extracorporeal circulation: a new tool for circulating tumor cell in vivo detection, Anal. Chem. 91 (2019) 1526015266. Available from: https://doi.org/10.1021/acs.analchem.9b04286. [46] M.U. Anu Prathap, E. Castro-Pe´rez, J.A. Jime´nez-Torres, V. Setaluri, S. Gunasekaran, A flow-through microfluidic system for the detection of circulating melanoma cells, Biosens. Bioelectron. 142 (2019) 111522. Available from: https://doi.org/10.1016/j.bios.2019.111522. [47] N.G. Gurudatt, et al., Separation detection of different circulating tumor cells in the blood using an electrochemical microfluidic channel modified with a lipid-bonded conducting polymer, Biosens. Bioelectron. 146 (2019) 111746. Available from: https://doi.org/10.1016/j.bios.2019.111746. [48] M.J. Duffy, E.W. McDermott, J. Crown, Blood-based biomarkers in breast cancer: from proteins to circulating tumor cells to circulating tumor DNA, Tumor Biol. 40 (2018). 1010428318776169. [49] S. Cesaro-Tadic, et al., High-sensitivity miniaturized immunoassays for tumor necrosis factor α using microfluidic systems, Lab. a Chip 4 (2004) 563569. Available from: https://doi.org/10.1039/B408964B. [50] E.D. Goluch, et al., A bio-barcode assay for on-chip attomolar-sensitivity protein detection, Lab. a Chip 6 (2006) 12931299. [51] X. Wang, M. Zhao, D.D. Nolte, T.L. Ratliff, Prostate specific antigen detection in patient sera by fluorescence-free BioCD protein array, Biosens. Bioelectron. 26 (2011) 18711875. [52] N. Triroj, P. Jaroenapibal, H. Shi, J.I. Yeh, R. Beresford, Microfluidic chip-based nanoelectrode array as miniaturized biochemical sensing platform for prostate-specific antigen detection, Biosens. Bioelectron. 26 (2011) 29272933. [53] F. Volpetti, J. Garcia-Cordero, S.J. Maerkl, A microfluidic platform for high-throughput multiplexed protein quantitation, PLoS One 10 (2015) e0117744. [54] B.A. Otieno, et al., On-line protein capture on magnetic beads for ultrasensitive microfluidic immunoassays of cancer biomarkers, Biosens. Bioelectron. 53 (2014) 268274. Available from: https://doi.org/10.1016/j. bios.2013.09.054.

Chapter 8 Microfluidics for early-stage cancer detection

[55] B.B. Nunna, et al., Detection of cancer antigens (CA-125) using gold nano particles on interdigitated electrode-based microfluidic biosensor, Nano Convergence 6 (2019) 3. Available from: https://doi.org/10.1186/ s40580-019-0173-6. [56] K. Kamil Reza, et al., Electrohydrodynamic-induced SERS immunoassay for extensive multiplexed biomarker sensing, Small 13 (2017) 1602902. [57] R. Seenivasan, C.K. Singh, J.W. Warrick, N. Ahmad, S. Gunasekaran, Microfluidic-integrated patterned ITO immunosensor for rapid detection of prostate-specific membrane antigen biomarker in prostate cancer, Biosens. Bioelectron. 95 (2017) 160167. Available from: https://doi.org/10.1016/j. bios.2017.04.004. [58] F. Bahavarnia, et al., Paper based immunosensing of ovarian cancer tumor protein CA 125 using novel nano-ink: a new platform for efficient diagnosis of cancer and biomedical analysis using microfluidic paper-based analytical devices (μPAD), Int. J. Biol. Macromol. 138 (2019) 744754. Available from: https://doi.org/10.1016/j.ijbiomac.2019.07.109. [59] L. Milane, A. Singh, G. Mattheolabakis, M. Suresh, M.M. Amiji, Exosome mediated communication within the tumor microenvironment, J. Controlled Rel. 219 (2015) 278294. [60] E. Rea´tegui, et al., Engineered nanointerfaces for microfluidic isolation and molecular profiling of tumor-specific extracellular vesicles, Nat. Commun. 9 (2018) 111. [61] N. Kamyabi, et al., Isolation and mutational assessment of pancreatic cancer extracellular vesicles using a microfluidic platform, Biomed. Microdevices 22 (2020) 23. Available from: https://doi.org/10.1007/s10544020-00483-7. [62] Z. Chen, et al., Detection of exosomes by ZnO nanowires coated three-dimensional scaffold chip device, Biosens. Bioelectron. 122 (2018) 211216. [63] P. Zhang, et al., Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip, Nat. Biomed. Eng. 3 (2019) 438451. Available from: https://doi.org/10.1038/s41551-019-0356-9. [64] Mengxi Wu, Yingshi Ouyang, Zeyu Wang, Rui Zhang, Po-Hsun Huang, Chuyi Chen, Hui Li, Peng Li, David Quinn, Ming Dao, Subra Suresh, Yoel Sadovsky, Tony Jun Huang, Isolation of exosomes from whole blood by integrating acoustics and microfluidics., Proc Natl Acad Sci U S A 114 (40) (2017) 1058410589. Available from: https://doi.org/10.1073/ pnas.170921011428923936. [65] M. Tayebi, Y. Zhou, P. Tripathi, R. Chandramohanadas, Y. Ai, Exosome Purification and analysis using a facile microfluidic hydrodynamic trapping device, Anal. Chem. 92 (2020) 1073310742. Available from: https://doi. org/10.1021/acs.analchem.0c02006. [66] M. Fleischhacker, B. Schmidt, Cell-free DNA resuscitated for tumor testing, Nat. Med. 14 (2008) 914915. [67] C.D.M. Campos, et al., Microfluidic-based solid phase extraction of cell free DNA, Lab. a Chip 18 (2018) 34593470. Available from: https://doi.org/ 10.1039/C8LC00716K. [68] K. Perez-Toralla, et al., Microfluidic extraction and digital quantification of circulating cell-free DNA from serum, Sens. Actuators B: Chem. 286 (2019) 533539. Available from: https://doi.org/10.1016/j.snb.2019.01.159.

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Scale-up of rapid diagnostics for clinical applications: device development for clinical applications (oral cancer)

9

K. Mohsin Reza1 and Ayub Khan2 1

Department of Conservative Dentistry and Endodontics, Navodaya Dental College, Raichur, India 2Department of Orthodontics, AME Dental College, Raichur, India

9.1

Introduction

Cancer or a malignant tumor (neoplasm) is an eminently mosaic disease to interpret, substantially a defect of gene mutation emerging from diffusion in clones of cells that enlarge in an allegedly unregulated aspect because of somatically obtained mutations [1,2]. A mutation is a genetic variation in the genome that increases the chance of developing cancer in the human body. Cancer continues to be one of the most complex and heterogeneous diseases in humans. Cancers are of four types, according to their tissue of origin. The first type of cancer is carcinomas that are found in epithelial tissue of the body. The second type is adenocarcinomas, which develops in human organs and is the most common type of cancer among human populations. The third type of cancer is squamous cell carcinoma, which originates from the squamous epithelium of organs. The fourth type is sarcomas found in connecting tissue (muscles, bones, etc.) of the body. Some of the most common cancers prevalent among the population are lung cancer, breast cancer, liver cancer, prostate cancer, colon cancer, etc. It is conceivably one of the utmost compelling health concerns of the 21st century as cancer diagnostics faces various challenges. The number of people expected to be diagonsed is around 22 million people worldwide by the end of 2030. Some of the prominent challenges are the early detection of cancer, continuous monitoring, treatment selection and precise diagnostics for more accurate Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00006-8 © 2021 Elsevier Inc. All rights reserved.

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anaylsis of cancer. The gold standards for most common cancer treatment are limited to chemotherapy, radiation, and surgery. However, the current medical technology need to develop more rapid diagnostics for clinical application through device development. In this chapter, we have discussed and covered some of the above challenges and its possible solutions in oral cancer treatment (Fig. 9.1). Oral/mouth cancer is a contentious cancer that accounts for 5% of all cancer [3] and is the eighth-most prevailing cancer worldwide [4]. The frequency of Oral cancer (OC) has been predicted to be relatively 280,000 cases/year, with two-thirds of these cases ensuing in developing countries [5,6] that mainly alter oral epithelial cells, develop metastasis, and even conclude in death [7]. The dominant type of malignancy is oral squamous cell carcinomas, which accounts for more than 90% of all oral/mouth cancers [8]. The highest prevalence rates occur in progressing countries, and also in developed countries. The crest incidence of OC is between the ages of 40 and 70 years. The prevalence rate has shown a 5.3-fold increase for men, and a two-fold increase for women, over the past two decades [9]. The specific progression and sum of events prescribed for oral carcinogenesis prevail anonymously. Oral cancer evolution is a multistep procedure implicating the growth of multiple genetic and epigenetic predilection and risk component. The risk factors for oral cancer include age, gender, alcohol, tobacco use, betel quid chewing, radiation or asbestos exposure,

Figure 9.1 This classification shows an overview of the nanomedicines currently being investigated in the clinic for cancer treatment. Lipid-based, polymer-based, inorganic, viral, and drug-conjugated nanoparticles are examples of platforms that have been established in clinical research.

Chapter 9 Scale-up of rapid diagnostics for clinical applications

poor oral hygiene, inflammation, etc. [10]. Limitations in oral/ mouth cancer treatment are an outcome of the current dispute to examine cancer therapies today, containing scarcity of early disease discovery, nonspecific systemic dispersion, insufficient drug concentrations embracing the tumor and failure to supervise therapeutic reactions. Inadequate drug release and dwelling at the marked site leads to significant complexity, like multidrug intransigence. Nanotechnology deals with a framework that extends from 1 to l00 nm—about the size of a virus—and acquires its name from the Greek word for “dwarf” [11]. Nanotechnology admits us to make materials that are thousands of times tinier than the smallest cell in the body, said James R Baker Jr. The idea of nanotechnology was amplified by Richard P Feynman in 1959. The term nanotechnology was first defined by Norio Taniguchi of the Tokyo Science University in a 1974 paper as follows: “Nanotechnology” mainly consists of the processing of, separation, consolidation, and deformation of materials by one atom or one molecule. It was promoted by K. Eric Drexler. Nanotechnology has the ability to extend solutions to these prevailing barriers in cancer therapies, due to unique size (1 100 nm) and large surface-volume ratios [12]. These materials are so tiny, they can effortlessly get inside cells and turnaround how they work [11]. Therefore the advancement of new methods of diagnosis is a blazing research field, where every small step is of extreme prominence. The promising applications are universally in the detection of disease diagnosis and imaging, monitoring, and therapeutics. Nanotechnology caters the proficiency to comprehend impairment of the most intricate biological systems at the molecular and atomic level. Nanotechnology treatments can be used in both precautionary and in disease-time access to manage with cancer. As more citified nanodevices are setup and are outfitted with persuasive targeting techniques for biomolecules, the capability to treat distinct kinds of cancer more and more effectively can be attained. The achievement of nanotechnology in cancer therapy is unbelievably encouraging due to the fact that innovative developments are steadily being scrutinized. This is specifically the case in the use of nanoparticles in both tumor diagnosis, as well as treatment.

9.2

Nanotechnology in cancer diagnosis

The advancement of nanotechnology has improved the cancer treatment through technological advancement. In this section, we have discussed about the treatment problems in oral cancer.

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Researchers are pursuing to develop nanodiagnostic tools destined to make detection of oral/mouth cancer priory. Oral/ mouth cancer (oral cavity and oropharynx) is a trivial and belligerent cancer that encroaches local tissues that can cause metastasis and have a high mortality rate [13]. Head and neck squamous cell carcinoma is most frequent cancer in the world, and the endurance rate has not revised fairly in the past two decades regardless of the innumerable studies on this malignancy [14]. Oral cancer is regularly diagnosed only after it has progressed to an untreatable stage [15,16] where the cancer cells have grown into aggressive and immune to therapeutic drugs. Detecting oral cancer at its earliest is thus crucial for elaborating the survival rate of this disease. Early detection will tremendously increase survival rates and in a situ tumor will be painless to annihilate the one that has metastasized [17]. Nanotechnology has transformed cancer detection and treatment. It has the competence to discover even a single cancerous cell in vivo and transfer the exceedingly toxic drugs directly. Nanotechnology is unduly decisive to recognize the cell changes. This new technology display enormous assurance in screening and imaging of oral/mouth cancer and also in confronting the meticulous insistence for sensitivity and costeffectiveness. Various nanodiagnostic tools being investigated consisted of cantilevers, Nanopores, nanotubes, Quantum dots (QDs), nanoshells, gold nanoparticles (AuNPs), etc. Most of the oral cancer cases are detected through cancer biomarkers as it indicates the various cancer stages.

9.2.1

Biomarkers

Tumor cells may impede or generate biochemical substances assigned to as tumor markers. Tumor markers may be present as intracellular substances in tissues or as accompanying substances in circulating body fluids, such as serum, urine, cerebrospinal fluid, and saliva [4]. Until recently, saliva was not examined for tumor markers of oral/mouth cancer. Nevertheless, with contemporary technological upgrading in diagnostic techniques, the role of saliva as an agent for diagnosis has developed aggressively. With cognizance to oral/mouth cancer, the pertinent tumor markers of concern include oncogenes (C-myc, C-FOS, C-jun), tumor suppressor genes (p53, p16), cytokines (transforming growth factor receptor beta 1), interleukin (IL)-8, growth factors (vasculoendotheilal growth factor, epidermal growth factor, and insulin-like growth factor), extracellular matrix-degrading proteinases (MMP1, MMP2, MMP9), hypoxia markers (hypoxia-inducible factor alpha,

Chapter 9 Scale-up of rapid diagnostics for clinical applications

carbonic anhydrase-9), epithelial-mesenchymal transition markers (e.g., E-cadherin, N-cadherin, and beta-catenin), cytokeratins (CK13, 14, and 16), microRNA molecules, and hypermethylation of cancer-related genes (p16) [18 23]. Pursuit has been and still is being made to promote nanodevices to analyze these tumor markers in saliva that may help in the initial apprehension of oral/mouth cancer. Nanotechnology can detect biomarkers of tumor cells, and this may acquiesce clinicians to see cells and molecules that are imponderable through conventional imaging, and thus devise them earlier, and boost the sensitivity of the test. Clinical imaging techniques such as CT and MRI would incredibly enhance from nanoparticle-based contrast agents that endeavor interminable circulation times and localized amassing at the disease site for upgraded diagnosis.

9.2.2

Nanomaterials

Among the nanomaterials, quantum dots are being used as probes for diagnosis of oral/mouth cancer. QDs are inorganic semiconductor fluorescent nanocrystals of cadmium-selenide that are tinier than 100 nm and glow very splendidly in ultraviolet light. They adhere to the protein correlated with cancer cells and thus can confine tumors [24]. QDs are applied for conduction of cell motility assay and to study cell-signaling events involved in migration and comprehend among invasive and noninvasive cancer cell lines. QDs have been preowned as contrast agents in in vivo and in vitro for MRI and ultrasound. QDs cruise through the bloodstream and aid in elaborating the visualization of tumor sites in alliance with MRI [25]. When used in conjunction with MRI, QDs can yield excellent images of tumor sites. AuNPs are also used as optical probes for initial discovery of oral cancer. AuNPs are being researched to overwhelm the limitations of imaging and chemical-based diagnostic techniques. AuNPs have adaptable physical, chemical, and biological characteristic that makes them applicable to many biomedical treatments. The optical properties of AuNPs are one-of-a-kind. The optical properties of AuNPs are advised by the synergy of light with electrons on the area. They can be conjoined to peptides or antibodies over electrostatic interaction or coordinate bonding to probe for specific cellular biomarkers with high-affinity and specificity. At a specific frequency (wavelength) of light, mutual oscillation of electrons on the AuNPs surface purpose a phenomenon called Surface Plasmon Resonance (SPR), emerging in potent extinction of light, that is, absorption and scattering. The appropriate frequency or wavelength of light where

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this arises is securely reliant on the size, shape, surface, and agglomeration state of AuNPs. Surface-enhanced Raman Spectroscopy is a dynamic technology that can be used for clinical medical diagnostics in vivo and single cell study. The edge of Raman spectroscopy is that it furnishes a report on molecular composition and structure of living tissue. Due to modulation of the scattered light by the vibration frequencies of the irradiated molecules, the aspect of Raman scattering of light appears, and this yield a fingerprint spectrum specific to the molecule. AuNPs are principally appealing for imaging and therapy due to their SPR-enhanced light scattering and absorption [26]. Advantages of using AuNPs for diagnosis of oral/mouth cancer are (1) it is elementary, (2) little invasive, (3) contribute increased contrast for diagnosis, (4) it is nontoxic to human beings, with no photo-bleaching or blinking that is built-in to many other fluorophores [27]. Nevertheless, there are few deprivations also. The optical signal of AuNPs may not be as active as that of QDs, and other complications aforementioned as biocompatibility, tumor targeting efficacy, in vivo kinetics, acute and chronic toxicity [28].

9.2.3

Nanoscale devices

Nanotechnology driven micro/nanodevices for cancer diagnostic approaches are being explored as promising tools for real-time, convenient, and cost-effective cancer management. One such device is nanoscale cantilever. The nanoscale cantilever is a multimolecular mechanical sensing apparatus [29,30] that has arisen as encouraging access. Nanoscale cantilevers are elastic beams used to bind to cancer-specific biomolecules. When specific biomolecules adhere, alterations of beam takes place, and this is detected by laser light or other methods. Further, nanopores are microscopic holes that allow transfer of DNA, one strand at a time, executing DNA sequencing highly efficient. Recently, the authors developed a new magnetic nanopore technique to isolate certain subsets of extracellular vesicles (EVs) from plasma. (ref: Ko, J.; Bhagwat, N.; Black, T.; Yee, S. S.; Na, Y.-J.; Fisher, S.; Kim, J.; Carpenter, E. L.; Stanger, B. Z.; Issadore, D., miRNA profiling of magnetic nanopore isolated EV for the diagnosis of pancreatic cancer. Cancer research 2018, 78 (13), 3688 3697.) Nanoshells also used as contrast agents with medical imaging science. AuNPs and Carbon nanotubes are essentially used in a sensor that distinguishes proteins exhibitive of oral/mouth cancer. Analysis has shown this sensor to be precise in encountering

Chapter 9 Scale-up of rapid diagnostics for clinical applications

oral/mouth cancer, and results can be stipulated in 1 hour. The cantilevers (flexible beams) cover with molecules capable of binding to cancer biomarkers can be used for oral/mouth cancer diagnosis [31]. Gold nanoshells are useful in encountering tumors and metastasis in many solid tumors, inclusive of oral/ mouth cancer. The main benefit of gold is its probability for cancer detection and treatment using near-infrared light.

9.3

Nanotechnology in cancer therapy

Nanomedicine can be defined as nanotechnology, or the use of materials between 1 and 100 nm, applied to health and medicine [32]. Nanomedicine is becoming one of the prominent methods for treating cancer.

9.3.1

Nanocarriers

Common problems in treating cancer include low specificity, rapid drug clearance and biodegradation, and limited targeting. The properties of nanocarriers, including their nanoscale sizes, high surface-to-volume ratios, favorable drug release profiles, and targeting modifications, can allow them to better reach target tumor tissue and release drugs in a stable, controlled manner [33]. Nanocarriers can accumulate in leaky vasculature, which is a characteristic of tumor tissue, in an effect known as the enhanced permeability and retention effect effect. Currently, a wide variety of platforms are being investigated as nanocarriers for cancer treatment, including lipid-based, polymerbased, inorganic, viral, and drug conjugated nanoparticles [34].

9.3.2

Drug targeting approaches for cancer therapy

9.3.2.1

Active target

The active targeting of the drug is the most suitable targeting approach for successful delivery of nanoparticle in cancerous cells without causing any toxicity. It is a specific type of targeting usually rely on ligand-receptor interaction, in which nanoparticles possess ligand that specifically binds to the receptor present on tumor cell surface. Active targeting decreases nonspecific interaction by conferring the strong ligand-receptor binding to deliver the drug in peripheral tissues.

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9.3.2.2 Passive target Passive targeting is the diffusion-mediated transport of drugs which involves the preparation of a drug carrier complex that can escape to body defense machinery. The drug carrier complex circulates in the blood stream and to be taken to the target receptor. Various properties of drug carrier complex such as molecular weight, surface charge, hydrophobic or hydrophilic nature of the surface and its size are key for efficient passive targeting of drugs [34]. (Table 9.1).

Table 9.1 Various nanocarriers, drugs, and targeted cancer [35]. Stimuli

Nanocarriers

Drug

Cancer

Ph

Hybrid micelles Mesoporous silica nanoparticles Dendrimers Chitosan nanoparticles Polymeric nanoparticles Mesoporous silica nanoparticles Polymeric conjugates Polymeric nanoparticles Chitosan nanoparticles Gold nanoparticles Magnetite nanoparticles Magnetic nanoparticles Magnetic nanoparticles Iron oxide nanoparticles PMAM- magnetite nanocrytallites Mesoporous bamboo charcoal Telluride PEG coblock polymeric Iron oxide nanoparticles Chitosan based Liposomes Beta cyclodextrin star polymer Polysaccharide based nanogels

Doxorubicin Doxorubicin

Breast cancer Cervical cancer

Doxorubicin Tamoxifen Cisplatin Doxorubicin

Breast cancer Breast cancer Ovarian cancer Glioblastoma

Doxorubicin Camptothecin Methotrexate 6-mercaptopurine Doxorubicin

Hepatocellular carcinoma Breast cancer Cervical cancer Lung carcinoma Lung cancer

Doxorubicin Homocamptothecin Cisplatin

Multiple myelomas Squamous cell carcinoma Colon adenocarcinoma

Doxorubicin

Breast cancer

Cispaltin

Breast cancer

Artemisinin Camptothecin Tamoxifen Paclitaxel

Breast cancer Breast cancer Breast cancer Liver cancer

Doxorubicin

Cervical cancer

Redox

Magnetic field

Light

Temperature

Chapter 9 Scale-up of rapid diagnostics for clinical applications

9.4 9.4.1

Oral cancer challenges, limitations, safety issues, and ethical issues Oral cancer challenges/limitations

Cancer addressing is profoundly determined by surface chemistry. Biocompatibility is a primary concern in the use of nanoparticles. Content scope all above the world at basic levels (primary healthcare, community healthcare, government hospitals etc.,) and expenses of nanotreatment are the predominant difficulties of nanoparticles. The pillar of medical care for oral/ mouth cancer is surgery, radiation, chemotherapy, antibody blocking therapy, or a combination of therapeutics. The kind of treatment or the consolidation of treatment approach suggested, rely upon the location, size, stage, and type of cancer, its growth, and general health of the patient [36]. Remedies at present applicable for oral/mouth cancer undergo consequential limitations. In oral/mouth cancer surgery, resection is restricted by several adjoining vital structures. In some cases, where the residual tumor may be left trailing adjoining vital structures or because it has advanced further the surgical margin, auxiliary treatments will be mandatory to carry out cure of the residual aliment. As considerably as radiation treatment is affected, it has a high failure rate for progressive tumors. Moreover, toxicity limits the extent of radiation that can be given to one full advance treatment. While the amount based on nanotechnology are literally landing the market, ample knowledge of combined toxicological hazards is still deficient. The literature on toxicological risks of the utilization of nanotechnology in medical testament is insufficient. Downsizing the structure to nanolevel results in clearly different properties. Chemical composition chiefly commands the intrinsic toxic properties; very small size seems to be an assertive indicator for toxic effects of particles. It is generally authorized that nanoparticles pose a segregate problem within the area of toxicology, entitle as nanotoxicology.4consequently, chemicals and materials in nanoformulation needed to be assessed for their activity and toxicity as nanoparticles. Chemical structure, which guides the intrinsic toxic nature of the chemical, is meaningful in deciding the toxicity of particles. It has been put on base that biodegradable substances are commonly decomposed and their waste by-products are excreted by the kidneys and intestines. Chemotherapy in oral/mouth cancer is restricted to an auxiliary role in association with radiation. Recent studies signify that chemotherapy given at the same time, as radiation therapy is

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more productive than it is given before a course of radiation therapy. Chemotherapy is combined along with radiation treatment program if the stage of the cancer is progressive (stage III or IV) [37]. Presently, oral/mouth cancer chemotherapies use anticancer medication, such as cetuximab, fluorouracil, cisplatin, paclitaxel, methotrexate, and docetaxel either solely or in coalescence [38 42]. Physicians may choose to use other pertinent drugs as well. The most essential advancement for the control of oral/mouth cancer has been the accelerating role of chemotherapy or antibody blocking therapy, for use in combination with radiation therapy to attain cure with organ maintenance [43]. Because of the assistance and capability for outpatient treatment, patients mostly choose oral administration as the route of administration of oral/mouth cancer drugs. Extended exposure to a cytotoxic agent is additional advantage facilitated by oral administration [44]. Nevertheless, low apparent permeability, low solubility in aqueous fluids and poor bioavailability have appeared as confined factors for oral/mouth cancer chemotherapy, in actual practice [45]. The most straightforward route is intravenous administration. It can survive the fluctuating absorption arrangement of the gastrointestinal tract, and can also manage actual and total bioavailability. Nevertheless, one of the probable hazards of this route of administration is that high concentrations of drugs deposited to normal tissues. This may account greater damage to normal healthy tissues and increases unfavorable responses [46]. Obstacles are routine in oral/mouth cancer patients. Medical complications that ensue during or after a disease procedure or treatment that make revival difficult are treated as complications. The complications can be one or the other side-effects of the disease or treatment, or they can be due to another objective. Oral/mouth cancer patients specifically have high hazards because of a few reasons. The result of chemotherapy and radiation therapy are restricting or ceasing the growth of fast-growing cells, containing cancer cells inside the oral cavity, normal cells in the lining of the mouth are also rapidly growing. Anti-oral/mouth cancer treatments can also stop these normal cells from growing. Thereby slowing down the effectiveness of oral tissue to restore it and generate new cells. Whereas radiation therapy probably cause direct damage and breakdown of oral tissues, salivary glands, and bone. Moreover, radiation therapy and chemotherapy are capable of obstructing the healthy balance of bacteria in the mouth. As a result of radiation therapy and chemotherapy, the alteration can happen in the

Chapter 9 Scale-up of rapid diagnostics for clinical applications

salivary glands (which produce saliva) and also in the lining of the mouth which, in turn, can disturb the healthy balance of bacteria. Thereby leading to progression of sores, infections, and tooth decay in the oral cavity. Other complexity includes a change in taste, pain, etc. This complexity can also lead to other problems, such as malnutrition and dehydration. To prevail with these disadvantages in oral/mouth cancer diagnosis and treatment techniques, the scientific community has transformed the development of new and more efficient techniques. In this scenario, more concern has been given to the development of nanotechnology-based techniques that could be conversely selected for oral/mouth cancer diagnosis, and also for drug carrier systems to revise oral, buccal, and intravenous treatment outcomes. Moreover, nonbiodegradable nanoparticles have been studied and it appears that they acquire in certain organs, chiefly in the liver. It is not explained, the potential impairment they may spark, or at what dosage, but further research is a need.

9.4.2

Safety issues

Regardless of all the benefit, nanotechnology has very few disadvantages relating to safety regards. Certain arguments are impeding the development of nanodevices. Although the newly engineered nanoparticles express undoubtedly reduced toxicity. Chances are that nanomaterials will be exceedingly reactive, and have increased the amount of absorption through the lungs, skin, and digestive system. After an extended time of use, these toxins may get gathered in different organs and may be carried to other organs via blood. In the lungs, these may lead to the inflammation of alveoli and consecutively damaging the cells. According to Upadhyay [47], the nanoparticles react with DNA, RNA, and other intracellular components thereby can lead to cause gene mutations. As nanomedicine is recently developing the field, and nanotechnology-based treatments are entirely distinct from other cancer treatments, there could be a lot of disorientation and difficulty in managing nanotechnology treatment and its uses. It could be tough to design rules and defy assessments for nanotechnology that could, therefore grant it to be used unsafely. The extreme cost of the innovative devices and the sophisticated production process presently prevent nanotechnology from being routinely practiced clinically for tumor detection. Nanotechnology carries a consequential probability for misuse and abuse, if not properly controlled and directed. A different concern is of the benefits, as well as

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possible limitations and safety of nanotechnology, are not yet completely recognize, as it is a relatively newer field.

9.4.3

Ethical issue

Nanoscience and nanotechnology, like any other awareness and correlated practices that were advanced previously, been involved in an argument about the degree of importance and interpretations of the new technoscience. Western countries, research on ethical, legal, social, and environmental dimensions of nanoscience and nanotechnology has been acknowledged as an authentic field of inquiry. The fact that nanotechnology treatments being completely different from other cancer treatments, there is a lot of complexity and dispute in regulating nanotechnology treatment and its uses. For these reasons, it could be difficult to constitute rules and risk assessments for nanotechnology. While the amount based on nanotechnology are indeed reaching the market, ample knowledge on the associated toxicological risks in still flawed. The literature on toxicological risks of the application of nanotechnology in medical practice is limited. It is mainly approved that nanoparticles pose a separate problem within the area of toxicology, designated a nanotoxicology. Therefore chemicals and materials in nanoformulation need to be assessed for their activity and toxicity. It has been found that biodegradable substances are normally decomposed and the waste products are excreted by the kidneys and intestines. However, nonbiodegradable nanoparticles have been studied and it seems that they acquire in certain organs, especially in the liver. It is not able to interpret, the probable harm they may provoke, or at what dosage, but further investigation is a need. Ethical and moral apprehensions also need to be addressed in parallel with the new development in some areas.

9.5

Nanobiochip devices for clinical application

Oral cancer generally develops on the surface of the tongue, mouth, lips or gums and salivary glands. Current standard techniques for oral cancer treatment are biopsy and histopathological tools. This procedure is invasive and collects tissue from the tumor surroundings causing pain for the patients. In order to mitigate this problem, researchers are working on noninvasive and painless technique for oral cancer diagnosis.

Chapter 9 Scale-up of rapid diagnostics for clinical applications

Nanobiochip sensor technique initiates to be encouraging new diagnostic tool for early detection of oral/mouth cancer. Further trials need to establish their effectiveness. Professor John McDevitt, the Brown-Wiess Professor of Chemistry and Bioengineering at Rice University has developed a protype nanobiochip for early oral cancer detection. Recently, two companies (OncAlert and SensoDX OraTech) have launched prototype devices for point of care treatment of oral cancer. OncAlert kit utilizes a small rinse pot where spit is tested on device. This kit detects CD44 and total protein levels to indicate early stage cancer screening before any physical symptom. Also, another company fabricated a programmable bio-nanochip (pBNC) known as The SensoDX OraTech, capable of detecting early stage cancer in mouth. This noninvasive technique uses small biopsy specimen and utilizes a computer algorithm to analyze the data.

9.6

Future perspectives

Ranking as one of the topmost cancers worldwide, oral/ mouth cancer has a poor prognosis and a high recurrence rate, and the time and precision of diagnosis directly influence disease outcome [48]. The depiction parameters of nanoparticlessuch as biocompatibility, function-specific size, and shape, blood circulation half-life, targeting to specific cell surface molecules can be structured by modulating their fabrication materials, surface chemistry, making nanoparticles an encouraging diagnostic material [49]. Designing nanorobots that travel through the human body under the control of computers might be feasible to deliver drugs. Drugs can be designed to act at specific sites and thereby avert side-effects by downsizing effective total dosage needed to treat the patient [50]. Currently, oral/ mouth cancer therapies confront several challenges. These include (1) cytotoxicity that can be intolerable, (2) inadequate concentrations of the drug that reaches the tumor site, (3) nonspecific systemic distribution of anticancer agents, (4) limited ability to monitor therapeutic responses, and (5) development of multiple drug resistance [51]. According to the US National Cancer Institute, constructed a novel and smart nanotherapeutics which may provide clinicians the ability to release an anticancer drug, or deliver multiple drugs eventually in a timed manner, or at several locations in the body [52]. Nanobased diagnostic methods act as an encouraging tool to provide realtime, convenient, and cost-effective diagnosis for oral/mouth

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cancer detection. Although these technologies have been studied in ex vivo studies of tissue and saliva samples and in vivo studies in animal models, further efforts should be engaged before this approach can be successfully applied in clinical diagnosis.

9.7

Conclusions

Nanotechnology is a fast expanding area of study expected to lead the development of novel, sophisticated functioning, which identifies cancer cells, deliver drugs to target tissue, disclosing the outcome of therapy, monitor intracellular changes which help avoid precancerous cells from becoming malignant. With advances in oral/mouth cancer biology and significant development in imaging technology and material science, we have optimistic that we are at the critical threshold of a major breakthrough in the cure of oral/mouth cancer. Nanotechnology will revolutionize dentistry, healthcare, and human life more thoroughly than many other developments of the past. Nanotechnology undeniably has the potential to be the most competent and most convenient form of future treatment and diagnosis of oral/mouth cancer. In the forthcoming years, it will play a key role for initial disease detection, diagnostic and therapeutic procedures to enhance oral health and general well-being of humankind. Assuming a future where nanoparticles can help detect cancer before it even has a chance to exhibit and selectively devastate cancer cells while leaving the normal cells unharmed. Cancer, in such a condition, could become an eminently manageable condition. Nanotechnology is still in its infancy, and a lot of work is still necessary. Nevertheless, nanotechnology is balanced to create a paradigm shift in early discovery and better treatment and control of oral/mouth cancer.

Acknowledgment Authors acknowledge their respective departments for providing support and facilities.

Conflict of interest Authors have no conflict of interest.

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References [1] D. Hanahan, R.A. Weinberg, The hallmarks of cancer, Cell 100 (2000) 57 70. [2] M.R. Stratton, Exploring the genome of cancer cells: progress and promise, Science 331 (2014) 1553 1558. [3] B. Virupakshappa, Applications of nanomedicine in oral cancer, Oral Health Dent. Manage. 11 (2) (2012) 62 68. [4] E. Omar, Current concepts and future non-invasive procedure for diagnosing oral squamous cell carcinoma a systematic review, Head Face Med. 11 (2015) 6. [5] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, T. Murray, et al., Cancer statistics, CA Cancer J. Clin. 58 (2008) 71 96. [6] R. Siegel, D. Naishadham, A. Jemal, Cancer statistics, CA Cancer J. Clin. 63 (1) (2013) 11 30. [7] T. Tanaka, R. Ishigamori, Understanding carcinogenesis for fighting oral cancer, J. Oncol. 2011 (2011) 603740. [8] S. Warnakulasuriya, Global epidemiology of oral and oropharyngeal cancer, Oral Oncol. 45 (2009) 309 316. [9] S.S. Suri, H. Fenniri, B. Singh, Nanotechnology-based drug delivery systems, J. Occup. Med. Toxicol. 2 (2007) 16 116. [10] D.L. Jones, K.V. Rankin, Oral cancer and associated risk factors, in: D.P. Cappelli, C.C. Mobley (Eds.), Prevention in Clinical Oral Health Care, Mosby Elsevier, St. Louis, MO, 2008, pp. 68 77. [11] V. Brower, Is nanotechnology ready for primetime? J. Natl. Cancer Inst. 98 (2006) 9 11. No1. [12] S.E. McNeil, Nanotechnology for the biologist, J. Leukoc. Biol. 78 (2005) 585 594. [13] G. Calixto, J. Ber neg ossi, B. Fonseca-Santos, M. Chorilli, Nanotechnology-based drug delivery systems for treatment of oral cancer: a review, Int. J. Nanomed. 9 (2014) 3719 3735. [14] P.Y. Chang, S.F. Peng, C.Y. Lee, C.C. Lu, S.C. Tsai, T.M. Shieh, et al., Curcuminurcumin, Y, Lu CC, Tsai SC, Shieh TM, TM, Shieh TM, eatm regulation of the function of MDR1 and reactive oxygen species in cisplatin-resistant CAR human oral cancer cells, Int. J. Oncol. 43 (2013) 1141- 1150. [15] M.F. Spafford, W.M. Koch, A.L. Reed, J.A. Califano, L.H. Xu, C.F. Eisenberger, et al., Detection of head and neck squamous cell carcinoma among exfoliated oral mucosal cells by microsatellite analysis, Clin. Cancer Res. 7 (2001) 607 612. [16] W. Zheng, K.C. Soo, R. Sivanandan, M. Olivo, Detection of neoplasms in the oral cavity by digitized endoscopic imaging of 5-aminolevulinic acidinduced protoporphyrin IX fluorescence, Int. J. Oncol. 21 (2002) 763 768. [17] S. Logothetidis, Nanotechnology in medicines: the medicine of tomorrow and nanomedicine, Hippokratia 10 (2006) 7 21. [18] L.R. Bigler, C.F. Streckfus, W.P. Dubinsky, Salivary biomarkers for the detection of malignant tumors that are remote from the oral cavity, Clin. Lab. Med. 29 (1) (2009) 71 85. [19] E. Bilodeau, F. Alawi, B.J. Costello, J.L. Prasad, Molecular diagnostics for head and neck pathology, Oral Maxillofac. Surg. Clin. North Am. 22 (1) (2010) 183 194. [20] S. Hu, M. Arellano, P. Boontheung, J. Wang, H. Zhou, J. Jiang, et al., Salivary proteomics for oral cancer biomarker discovery, Clin. Cancer Res. 14 (19) (2008) 6246 6252.

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[21] J.M.M. Lee, E. Garon, D.T. Wong, Salivary diagnostics, Orthod. Craniofac. Res. 12 (3) (2009) 206 211. [22] M. Sugimoto, D.T. Wong, A. Hirayama, T. Soga, M. Tomita, Capillary electrophoresis-mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles, Metabolomics 6 (1) (2010) 78 95. [23] M.D. Williams, Integration of biomarkers including molecular targeted therapies in head and neck cancer, Head Neck Pathol. 4 (1) (2010) 62 69. [24] A. Bhardwaj, A. Misuriya, S. Maroli, S. Manjula, A.K. Singh, Nanotechnology in dentistry: present and future, J. Int. Oral Health 6 (1) (2013) 121 126. [25] S. Hatziantoniou, C. Demetzos, Qualitative and quantitative one-step analysis of lipids and encapsulated bioactive molecules in liposome preparations by HPTLC/FID (IATROSCAN), J. Liposome Res. 16 (4) (2006) 321 330. [26] I.C. Sun, D.K. Eun, J.H. Na, S. Lee, I.J. Kim, I.C. Youn, et al., Heparin-coated gold nanoparticles for liver-specific CT imaging, Chemistry 15 (2009) 13341 13347. [27] I.H. El-Sayed, X. Huang, M.A. El-Sayed, Surface plasmon resonance scattering and absorption of anti-EGFR antibody conjugated gold nanoparticles in cancer diagnostics: applications in oral cancer, Nano Lett. 5 (2005) 829 834. [28] W. Cai, T. Gao, H. Hong, et al., Applications of gold nanoparticles in cancer nanotechnology, Nanotechnol. Sci. Appl. 1 (2008) 17 32. [29] S.L. Liu, S.S. Zhong, D.X. Ye, W.T. Chen, Z.Y. Zhang, J. Deng, Repression of G protein-coupled receptor family C group 5 member A is associated with pathologic differentiation grade of oral squamous cell carcinoma, J. Oral Pathol. Med. 42 (2013) 761 768. [30] R. Mubben, A. Singh, Nanotechnology in the field of oral medicine and diagnosis-a review, Indian Dent. Res. Rev. 5 (2010) 41 43. [31] H.R. Mody, Cancer nanotechnology: recent trends and developments, Internet J. Med. Update 6 (1) (2011) 3 7. [32] A. Wicki, D. Witzigmann, V. Balasubramanian, J. Huwyler, Nanomedicine in cancer therapy: challenges, opportunities, and clinical applications, J. Control Rel. 200 (2015) 138 157. [33] R. Sinha, G.J. Kim, S. Nie, D.M. Shin, Nanotechnology in cancer therapeutics: bioconjugated nanoparticles for drug delivery, Mol. Cancer Ther. 5 (8) (2006) 1909 1917. [34] K.C. Vivek, S.1 Anshuman, K.S. Vinay, M.P. Singh1, Cancer nanotechnology: a new revolution for cancer diagnosis and therapy, Curr. Drug Metab. 20 (6) (2019) 416 429. [35] P.N. Navya, K. Anubhav, S.P. Srinivas, K.B. Suresh, M.R. Vincent, K.D. Hemant, Current trends and challenges in cancer management and therapy using designer nanomaterials, Nano Convergence 6 (2019) 23. [36] J.P. Shah, W. Lydiatt, Treatment of cancer of the head and neck, CA Cancer J. Clin. 45 (6) (1995) 352 368. [37] C. Scully (Ed.), Oral and Maxillofacial Medicine. The Basis of Diagnosis and Treatment, third ed., Churchill Livingstone, Elsevier, New York, 2013, pp. 2014 2017. [38] D.J. Adelstein, Y. Li, G.L. Adams, H. Wagner Jr., J.A. Kish, J.F. Ensley, et al., An intergroup phase III comparison of standard radiation therapy and two schedules of concurrent chemoradiotherapy in patients with unresectable squamous cell head and neck cancer, J. Clin. Oncol. 21 (1) (2003) 92 98.

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[39] M. Agu¨eros, L. Ruiz-Gato´n, C. Vauthier, K. Bouchemal, S. Espuelas, G. Ponchel, et al., Combined hydroxypropyl-β-cyclodextrin and poly (anhydride) nanoparticles improve the oral permeability of paclitaxel, Eur. J. Pharm. Sci. 38 (4) (2009) 405 413. [40] J. Baselga, J.M. Trigo, J. Bourhis, J. Tortochaux, H. Corte´s-Funes, R. Hitt, et al., Phase II multicenter study of the antiepidermal growth factor receptor monoclonal antibody cetuximab in combination with platinum-based chemotherapy in patients with platinum-refractory metastatic and/or recurrent squamous cell carcinoma of the head and neck, J. Clin. Oncol. 23 (24) (2005) 5568 5577. [41] J.A. Bonner, P.M. Harari, J. Giralt, N. Azarnia, D.M. Shin, R.B. Cohen, et al., Radiotherapy plus cetuximab for squamous-cell carcinoma of the head and neck, N. Engl. J. Med. 354 (6) (2006) 567 578. [42] R. Haddad, S. Sonis, M. Posner, L. Wirth, R. Costello, P. Braschayko, et al., Randomized phase 2 study of concomitant chemoradiotherapy using weekly carboplatin/paclitaxel with or without daily subcutaneous amifostine in patients with locally advanced head and neck cancer, Cancer 115 (19) (2009) 4514 4523. [43] E.N. Myers, A.A. Simental, Cancer of the oral cavity, in: E.N. Myers, J.Y. Suen, J.N. Myers, E.Y. Hanna (Eds.), Cancer of the Head and Neck, Saunders, Philadelphia, PA, 2003, pp. 279 332. [44] J.M.M. Terwogt, J.H.M. Schellens, W.Wt.B. Huinink, et al., Clinical pharmacology of anticancer agents in relation to formulations and administration routes, Cancer Treat. Rev. 25 (2) (1999) 83 102. [45] H. Devalapally, A. Chakilam, M.M. Amiji, Role of nanotechnology in pharmaceutical product development, J. Pharm. Sci. 96 (10) (2007) 2547 2565. [46] C.M.F. Kruijtzer, J.H. Beijnen, J.H.M. Schellens, Improvement of oral drug treatment by temporary inhibition of drug transporters and/or cytochrome P450 in the gastrointestinal tract and liver: an overview, Oncologist 7 (6) (2002) 516 530. [47] Y. Upadhyay, Current state and future perspectives of nanotechnology in dentistry, IOSR J. Pharm. 3 (9) (2013) 68 71. [48] V. Ernani, N.F. Saba, Oral cavity cancer: risk factors, pathology, and management, Oncology 89 (2015) 187 195. [49] S.H. Lee, J.B. Lee, M.S. Bae, D.A. Balikov, A. Hwang, T.C. Boire, et al., Current progress in nanotechnology applications for diagnosis and treatment of kidney diseases, Adv. Healthc. Mater. 4 (2015) 2037 2045. [50] M. Fakruddin, Z. Hossain, H. Afroz, Prospects and applications of nanobiotechnology: a medical perspective, J. Nanobiotechnol. 10 (2012) 31. [51] B. Ehdaie, Application of nanotechnology in cancer research: review of progress in the National Cancer Institute’s Alliance for Nanotechnology, Int. J. Biol. Sci. 3 (2) (2007) 108. [52] L. Hull, D. Farrell, P. Grodzinski, Highlights of recent developments and trends in cancer nanotechnology research—view from NCI Alliance for nanotechnology in cancer, Biotechnol. Adv. 32 (4) (2014) 666 678.

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10

Kamil Reza Khondakar1 and Ajeet Kumar Kaushik2 1

Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia 2NanoBioTech Laboratory, Department of Natural Sciences, Division of Sciences, Art, and Mathematics, Florida Polytechnic University, Lakeland, FL, United States

10.1

Introduction

The development of new tools for cancer management in molecular oncology is largely credited to the growth of userfriendly methods of molecular analysis such as recognition of certain biomarkers for routine practice in clinical oncology [1]. Most of the current techniques like mammography (imaging of tissue), flow cytometry for cancer cell analysis, immunohistochemistry for specific antigen detection, and gene sequencing, ELISA for protein expression, and polymerase chain reaction (PCR) for DNA/RNA testing considered as the gold standard techniques for cancer diagnosis [2 4]. All of them have been very effective in cancer management; however, these techniques still have some deficits for advanced diagnostic applications as they failed to detect cancer at early stages [5]. Despite their improvement in detection of cancer biomarker for clinical applications, they lack high sensitivity for low sample volume, portability in remote areas, low cost materials, restricted to materials having fluorescent properties, complex machine handling, unable to handle multiple patient samples, etc. We still require performing multitude of clinical experiments in hospital settings for real-world patient sample for more robust outcomes. However, clinical application of these nanotechnologies is still need to be validated before commercialization become feasible. Therefore, with the demand in health care and clinical diagnostics, the future perspectives in cancer management Nanotechnology in Cancer Management. DOI: https://doi.org/10.1016/B978-0-12-818154-6.00001-9 © 2021 Elsevier Inc. All rights reserved.

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require developing an efficient, portable, quick detection platform with high sensitivity and selectivity, versatility, and highthroughput point-of-care diagnostics that could be introduced to personalized disease-monitoring [6]. Some of the future challenges that need to be addressed for a better cancer management include the growth of immunemonitoring strategies for the cancer treatment and the identification of new cancer biomarkers (immunotherapy approach, circulating DNA/RNA, extracellular vesicle, etc.) for better diagnosis of cancer [7]. The combining approaches of existing and new tools to improve clinical outcomes with more clinical trials over a longitudinal study.

10.2

Immunotherapy approach

Recently, immunotherapy approaches for cancer patients has been successful and could be a potential technique for future cancer diagnostics. For example, Programmed death-1 (PD-1), which is expressed by activated T cells and conveys inhibitory signals through interactions with its two major ligands, programmed death ligand-1 and -2 (PD-L1 and PD-L2), has been considered to play a key role in curing number of cancer types [8,9]. Recent investigations recommended that application of multiple proteins as immune checkpoint blockade could be beneficial to improve cancer diagnosis and provide higher chances of patient survival [10]. Therefore, versatile platform like microfluidic assay could provide serial measurements of these immune checkpoints biomarkers to understand the tumor immune microenvironment and diagnose the appropriate immunotherapies. Recently, Trau group have designed a SERS microfluidic platform to detect clinically relevant soluble immune checkpoints PD-1, PD-L1 and LAG-3. The sensitivity of the sensor found out to be 100 fg/mL in human serum. Their approach was developed utilizing the novel recombinant NY-scFv affinity reagents instead of monoclonal antibodies for capturing target immune checkpoints on the graphene oxide modified electrodes of the ac-EHD device [11].

10.3

Detection of circulating tumor DNA/RNA

Circulating tumor DNA/RNA (ctDNA and ctRNA) are promising for noninvasive assessment of cancer [12]. Detection of these circulating biomarkers is very challenging as they present in a very minute amount in body fluids. More recently, the term “liquid biopsy” has also been adopted for the analysis of ctDNA

Chapter 10 Challenges and future prospects of nano-enabled cancer management

released from apoptotic or necrotic tumor cells providing vital information for early stage of cancer, monitoring systemic therapies, and stratification of patients based on the detection of therapeutic targets and recurrence mechanisms [13]. According to Newman et al. levels of ctDNA were highly correlated with tumor volume and distinguished between residual disease and treatment-related imaging changes, and measurement of ctDNA levels allowed for earlier response assessment than radiographic approaches [14]. Further, accurate diagnosis from limiting samples such as ctDNA requires highly accurate readout systems. This led to the serious challenges regarding specificity and sensitivity of the current assays. Wee et al. demonstrated the sensitive and specific identification of three clinically important DNA point mutations in melanoma (BRAF V600E, c-Kit L576P and NRAS Q61K) using PCR/SERS detection method [15]. They successfully applied to cell lines and serum derived DNA where results were subsequently validated with droplet digital PCR. The above mentioned techniques show the significance of ctDNA for cancer analysis which could be a powerful biomarker for cancer management.

10.4

Extracellular vesicle analysis

Exosomes (from 30 to 200 nm in diameter) are small extracellular vesicles containing proteins and nucleic acids from their originating cells, playing vital roles in intercellular communication. They are considered as the next generation biomarkers for cancer diagnostics. Recently, it has been demonstrated that exosomes from breast cancer cells transfer microRNAs (miRNAs) to normal cells and stimulate them to become cancerous [16]. This potentially expands the mechanisms by which cancer proliferates and may provide opportunities to develop exosome-based diagnostics and therapies [17]. Zong et al. developed a Raman based strategy for the detection of tumor-derived exosomes (1200) using a sandwich-type immunocomplex. The exosomes have been obtained from the SKBR3 cancerous cell [18]. Recently, Li et al. developed a immunoassay platform that uses a small volume of serum extracted from cancer patients for the exosome-based diagnosis, classification and metastasis monitoring of pancreatic cancer using a glass slide [19]. They claimed to have detected one exosome with the requirement of only 2 µL serum samples for cancer detection. These aforementioned assays potentially show the development of exosome-based cancer biosensors for rapid

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detection and analysis in quick time. It may provide opportunities to develop more exosome-based diagnostics and therapies for more robust cancer management. There are diagnostic errors providing inaccurate or delayed diagnoses in some of the clinical settings of health care. One of the ways of mitigating the cancer casualties is to early detection and regular monitoring of body fluids released by human body on daily basis (for example, sweat, saliva, urine and feces, etc.). Professor Sanjiv Sam Gambhir recently conceptualized the idea of smart toilets (extracting information from stool and urine sample) to detect the biomarkers for a routine check-up for early sign of the disease [20]. Further, wearable chips can provide plenty of information to health care systems to track the health of individuals and help researchers to decide the treatment strategy in cancer patients. Recently, Dr. Hayes and his team have developed a wearable device that captures cancer cells from blood by scanning the bloodstream from human body and potentially providing better information for cancer treatment strategy [21].

10.5

Viewpoint

Genomic and proteomic analysis provide multitude of data from several patients which can be collected simultaneously for more precise diagnostics. The improvement in bioinformatics tools along with machine learning methods to analyze complex datasets to provide more options for more automated assessment of cancer disease.

Acknowledgment Authors acknowledge respective departments and institutions for providing support and facilities.

Conflict of interest Authors have no conflict of interest.

References [1] P. Navya, et al., Current trends and challenges in cancer management and therapy using designer nanomaterials, Nano Converg. 6 (2019) 23. [2] P.J. Tighe, R.R. Ryder, I. Todd, L.C. Fairclough, ELISA in the multiplex era: potentials and pitfalls, Proteomics Clin. Appl. 9 (2015) 406 422.

Chapter 10 Challenges and future prospects of nano-enabled cancer management

[3] E.A. Stadtmauer, et al., CRISPR-engineered T cells in patients with refractory cancer, Science 367 (2020). [4] T. Li, et al., Plasma circular RNA profiling of patients with gastric cancer and their droplet digital RT-PCR detection, J. Mol. Med. 96 (2018) 85 96. [5] J. Sierra, J. Marrugo-Ramı´rez, R. Rodriguez-Trujillo, M. Mir, J. Samitier, Sensor-integrated microfluidic approaches for liquid biopsies applications in early detection of cancer, Sensors 20 (2020) 1317. [6] S. Shrivastava, T.Q. Trung, N.-E. Lee, Recent progress, challenges, and prospects of fully integrated mobile and wearable point-of-care testing systems for self-testing, Chem. Soc. Rev. 49 (2020) 1812 1866. [7] A. Aalipour, et al., Engineered immune cells as highly sensitive cancer diagnostics, Nat. Biotechnol. 37 (2019) 531 539. [8] S. Koyama, et al., Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints, Nat. Commun. 7 (2016) 10501. [9] K. Yanaba, M. Hayashi, Y. Yoshihara, H. Nakagawa, Serum levels of soluble programmed death-1 and programmed death ligand-1 in systemic sclerosis: association with extent of skin sclerosis, J. Dermatol. 43 (2016) 954 957. [10] P. Sharma, J.P. Allison, Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential, Cell 161 (2015) 205 214. [11] K.K. Reza, et al., A SERS microfluidic platform for targeting multiple soluble immune checkpoints, Biosens. Bioelectron. 126 (2019) 178 186. [12] A.J. Bronkhorst, V. Ungerer, S. Holdenrieder, The emerging role of cell-free DNA as a molecular marker for cancer management, Biomol. Detect. Quantif. 17 (2019) 100087. [13] C. Alix-Panabie`res, K. Pantel, Clinical applications of circulating tumor cells and circulating tumor DNA as liquid biopsy, Cancer Discov. 6 (2016) 479 491. [14] A.M. Newman, et al., An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage, Nat. Med. 20 (2014) 548. [15] E.J.H. Wee, Y. Wang, S.C.-H. Tsao, M. Trau, Simple, sensitive and accurate multiplex detection of clinically important melanoma DNA mutations in circulating tumour DNA with SERS nanotags, Theranostics 6 (2016) 1506 1513. [16] S.A. Melo, et al., Cancer exosomes perform cell-independent microRNA biogenesis and promote tumorigenesis, Cancer Cell 26 (2014) 707 721. [17] E. Anastasiadou, F.J. Slack, Malicious exosomes, Science 346 (2014) 1459 1460. [18] S. Zong, et al., Facile detection of tumor-derived exosomes using magnetic nanobeads and SERS nanoprobes, Anal. Methods 8 (2016) 5001 5008. [19] T. Li, et al., An ultrasensitive polydopamine bi-functionalized SERS immunoassay for exosomes based diagnosis and classification of pancreatic cancer, Chem. Sci. (2018). [20] L. Minor, Discovering Precision Health: Predict, Prevent, and Cure to Advance Health and Well-Being, John Wiley & Sons, 2020. [21] T.H. Kim, et al., A temporary indwelling intravascular aphaeretic system for in vivo enrichment of circulating tumor cells, Nat. Commun. 10 (2019) 1478.

233

Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A Active packing, 23 24 Adenocarcinomas, 211 212 Aegle marmelos, 8 9 Affinity enrichment, 49 50 Agriculture and environment, nanotechnology in, 18 20 Alkaline phosphatase (AP), 55 56 Alpha-fetoprotein (AFP), 163 165 Alstonia scholaris, 8 9 Amazon EC2TM, 140 141 3-Aminopropyltriethoxysilane (APTES), 156 159 Amperometric biosensors, 13 Ampicillin, 7 8 Andrographis paniculata, 8 9 Anisotropic magnetoresistance, 152 154 Anti-5-methylcytosine antibody, 49 50 Antistokes line, 109 110 Application of nanotechnology, 3 25 biomedical, nanotechnology in, 3 25 agriculture and environment, nanotechnology in, 18 20 bioimaging, 6 7 bioremediation, nanotechnology in, 16 18 biosensors, nanotechnology in, 11 13 controlled release, nanotechnology in, 13 15

diagnosis and treatment, nanotechnology for, 7 9 drug delivery, 3 6 food industry, nanotechnology in, 22 25 genetic material sequencing, nanotechnology in, 11 treatment of cancer, nanotechnology for, 9 10 water treatment, nanotechnology in, 20 22 Aptamer, 20 Aptasensors, 20 Artificial intelligence, 134 138 in cancer diagnosis, 135 136 in cancer treatment, 137 138 -enabled nanomedicine, 138 nonsolid tumor diagnosis, 137 solid tumor diagnosis, 136 137 Atomic force microscopy (AFM), 194 195 ATRA, 4 Au@mesoporous carbon CMK3, 56 59 Autofluorescence phenomenon, 96 97 Avastin, 54

B Barium sulfate, 75 76 Bayesian network metaanalysis, 136 137 Beer-Lambert law, 78 Biofertilizers, 13 14 Bioimaging, 6 7

Bioinformatics, 126 127 artificial intelligence, 134 138 in cancer diagnosis, 135 136 in cancer treatment, 137 138 -enabled nanomedicine, 138 nonsolid tumor diagnosis, 137 solid tumor diagnosis, 136 137 biological data, 128 129 cancer nanomedicine, 129 130 in cancer research, 127 128 large-scale approaches to the study of cancer, 130 134 application in cancer therapy, 133 134 bioinformatics techniques, 132 genomics, 130 131 proteomics, 132 transcriptomics, 131 programming language (PL), 139 141 in cancer diagnosis, 139 140 in cancer treatment, 140 141 Biomarkers, 214 215 Biomarkers and diagnostics system for cancer management, 35 39 efficient and miniaturized diagnostics system, 39 40 Biomedical, nanotechnology in, 3 25

235

236

Index

Biomedical, nanotechnology in (Continued) agriculture and environment, nanotechnology in, 18 20 bioimaging, 6 7 bioremediation, nanotechnology in, 16 18 biosensors, nanotechnology in, 11 13 controlled release, nanotechnology in, 13 15 diagnosis and treatment, nanotechnology for, 7 9 drug delivery, 3 6 food industry, nanotechnology in, 22 25 active packing and intelligent packaging, 23 24 nanomaterial as barrier, 24 nanosensors, 24 25 genetic material sequencing, nanotechnology in, 11 treatment of cancer, nanotechnology for, 9 10 water treatment, nanotechnology in, 20 22 Biorecognition molecule, matrix for immobilization of, 47 50 Bioremediation, nanotechnology in, 16 18 Biosensors, nanotechnology in, 11 13 Bisulfite modification, 49 50 Blood-based cancer biomarkers and challenges in analysis, 187 188 Brassica rapa, 14 15 Breast cancer, 139, 149 Breast invasive carcinoma (BRCA), 137 138

C Calcitonin, 44 45 Calcium alginate, 14 15 Cancer biomarkers, 35 37, 36t, 40 Cancer detection, 96 98, 163 165, 176 Cancer exosome detection, microfluidic biosensors for, 201 204 Cancer protein detection, microfluidic biosensors for, 198 201 Carbon dot, 6 Carcinoembryonic antigen (CEA) biomarker, 44 45, 53f, 56 59, 160 163, 167 171 Cell-free DNA (cfDNA) fragment detection, 160 163 microfluidic biosensors for, 204 205 Cell Search method, 37 Centella asiatica, 8 9 Cervical cancers, 97 98 Cervical intraepithelial neoplasia (CIN), 97 98 Cetuximab, 220 Challenges and future prospects of nano-enabled cancer management, 229 circulating tumor DNA/RNA, detection of, 230 231 extracellular vesicle analysis, 231 232 immunotherapy approach, 230 Chemotherapy, 219 220 Chlorpyriphos, 17 Chromophore, 76 Circulating tumor cells (CTCs), 98, 174 176, 187 188, 190 191, 195 196 Circulating tumor DNA (ctDNA), 230 231 Circulating tumor markers (CTMs), 59 61

Circulating tumor RNA (ctRNA), 230 231 Cisplatin, 220 Clinical applications, 211 212 cancer diagnosis, nanotechnology in, 213 217 biomarkers, 214 215 nanomaterials, 215 216 nanoscale devices, 216 217 cancer therapy, nanotechnology in, 217 218 drug targeting approaches for cancer therapy, 217 218 nanocarriers, 217 ethical issue, 222 future perspectives, 223 224 nanobiochip devices for, 222 223 oral cancer challenges/ limitations, 219 221 safety issues, 221 222 Clinical diagnostics, 149 150, 167 171 Cloud computing, 140 141 CloudMC, 140 141 CNN-CAD (convolutional neural network computer-aided detection), 136 Colorectal cancer (CRC), 136 Complementary-metal-oxidesemiconductor (CMOS) circuit, 163 165 Computed tomography (CT) imaging, 7 Confocal microscopes, 89 90 Controlled release, nanotechnology in, 13 15 COPA (Cancer outlier profile analysis), 133t Corynebacterium pseudotuberculosis, 7 8 Counter electrode (CE), 43 44 CROSS chip, 192 193 CTC detection, 37

Index

Culmination of cancer, 96 CURATE, 138 Cyclic voltammetry (CV), 51 54 CV based biosensor for cancer detection, 51 54 CYFRA-21-1, 44 45 Cysteamine caped gold nanoparticles (CysA/Au NPs), 201 CYTOSCOPE, 134

D Deep belief networks (DBNs), 136 Deep convolutional neural network (DCNN), 136 Deep learning (DL), 135 136 Dendrimers, 5 6, 5f Deoxyribonucleic acid (DNA) hybridization, 151 152 Detection of cancer cyclic voltammetry based biosensor for, 51 54 differential pulse voltammetry based biosensor for, 54 61 electrochemical impedance based biosensor for, 61 65 Diagnosis and treatment, nanotechnology for, 7 9 Differential pulse voltammetry (DPV), 51 DPV based biosensor for cancer detection, 54 61 Digital breast tomosynthesis (DBT), 136 Dispersive reflection, 76 Diuron nanoformulation (DNF), 14 15 DNA microarray technology, 132 Docetaxel, 220 Doxorubicin (DOX), 54, 117 Drug-delivery system (DDS), 3 6, 117 119 Drug synergism, 138 Drug targeting approaches for cancer therapy, 217 218

active target, 217 passive target, 218 Dye photolysis, 86

E Eclipta prostrata, 8 9 EGSnrc MC code, 140 141 Electrochemical biosensor, 13, 43 44, 50f, 55 61, 60f Electrochemical detection strategy, 46f Electrochemical impedance based biosensor for cancer detection, 61 65 Electrochemical impedance spectroscopy (EIS), 61 62 Electrochemical impedance techniques (EIS), 51, 63 Electrochemical transducers for cancer biomarker detection, 51 65 cyclic voltammetry based biosensor for cancer detection, 51 54 differential pulse voltammetry (DPV) based biosensor for cancer detection, 54 61 electrochemical impedance based biosensor for cancer detection, 61 65 Electrochemiluminescence (ECL) technique, 52 54 Endogenous fluorophores, 96 97 Enterobacter spp., 7 8 Enzymatic treatment, 49 50 Enzyme-linked immunosorbent assay (ELISA), 37 38, 45 47, 54 Epidermal growth factor receptor (EGFR), 54 55, 55f Epithelial cell adhesion molecule (EpCAM), 37 Escherichia coli, 7 8, 156 159 Estrogen, 44 45

237

1-Ethyl-3-(3dimethylaminopropyl) carbodiimide (EDC), 156 159 Exosomes, 201 203 Extracellular vesicles (EV) analysis, 97, 116, 231 232 Extreme learning machine (ELM), 136

F Fermi’s golden rule, 84 85 Flavonoid modified drug (FMD), 54 Flow cytometry, 37 Fluorescence, 76 77 Fluorescence illumination, 88 Fluorescence lifetime, defined, 81 82 Fluorescence microscopy, 73 75 cancer detection, 96 98 excitation and emission fundamentals, 78 80 Kasha’s law, Stokes shift, and Franck Condon principle, 78 80 florescence lifetime imaging, 82 83 Fo¨rster resonance energy transfer, 84 85 fluorescence light sources, 88 90 fundamentals, 76 86 instrumentation, 86 88 nanoparticles and organic dyes for florescence sensors, 90 92 quantum dots for florescence imaging and cancer diagnostics, 92 96 quantum yield and lifetime of florescence marker, 81 82 quenching and photobleaching, 85 86 Fluorescence quantum yield, defined, 81 82

238

Index

Fluorescence resonance energy transfer (FRET), 95 96 Fluorescence spectroscopy, 75 76 development history, 75 76 Fluorochromes, 77 78 Fluorouracil, 220 Food industry, nanotechnology in, 22 25 active packing and intelligent packaging, 23 24 nanomaterial as barrier, 24 nanosensors, 24 25 Fo¨rster resonance energy transfer (FRET), 84 85 Forster’s distance, 84 85 Franck Condon principle, 78 80

G GEANT4 Monte Carlo code, 140 Gene Expression Omnibus (GEO), 134 Gene Ontology (GO) analysis, 134 Genetic material sequencing, nanotechnology in, 11 GEO2R, 134 Giant magnetoimpedance (GMI), 152 154 GMI based sensors, 166 173 Giant magnetoresistance (GMR), 152 154 GMR based sensors, 155 159 Gold nanoparticles (AuNPs), 6 7, 63 65, 95 96 Granulocyte colony stimulation factor (GCSF), 160 163 Graphene oxide, 49 50 Graphene oxide/polydopamine (GO/PDA) nanointerface, 203

H Haemophilus influenza, 130 Hall effect, 152 154 Hall sensors, 174 176 Heptamethine carbocyanine dyes, 92

HER2 antibody, 47 48 HER2 biomarkers, 44 45 Herbicides, 16 17 Horseradish peroxidase (HRP), 203 HRP-labeled IgG secondary antibody, 49 50 Human chorionic gonadotropin-β (HCG-β) biomarker, 44 45 Human papilloma virus (HPV), 167 171 Hydroquinone, 51 52

I IBM, 154 155 Immunoassay, nanotechnologybased, 38 39 Immunoassay-based techniques, 151 152 Immunohistopathology, 45 47 Immunotherapy approach, 230 Indium tin oxide (ITO) threeelectrode sensor surface, 200 201 Instrumentation, 86 88 Intelligent packaging, 23 24 Interleukin-6 (IL-6), 156 159 Internal conversion, 79 Ion-sensitive biosensors, 13

K Kasha’s law, 78 80 Kidney renal clear cell carcinoma (KIRC), 137 138 Klebsiella pneumoniae, 7 8 Knowledge as a Service (KaaS), 140 141

L Lactobacillus plantarum, 24 Lamivudine, 5 Lapis solaris, 75 76 Light-emitting diodes (LEDs), 89 90 Light microscope, 90 Liposomes, 3 4 Liquid biopsy, 230 231

Listeria monocytogenes, 24 Lung adenocarcinoma (LUAD), 137 138 Lung cancer, 149 Lung squamous cell carcinoma (LUSC), 137 138 Lymph node metastasis (LNM), 136

M Magnetic bead (MB), 52 55 Magnetic biosensor, 149 154, 152f, 153f, 156 159 Magnetic field sensors, 177 Magnetic graphene oxide modified gold electrode (MGO-Au), 54 Magnetic nanoparticles, 149 150, 156 159 Magnetic resonance imaging (MRI), 6 7 Magnetic sensors, 151 176 giant magnetoimpedance (GMI) based sensors, 166 173 magnetoresistive sensors, 154 165 giant magnetoresistance (GMR) based sensors, 155 159 spin-valve sensors, 159 163 tunneling magnetoresistance-based sensors, 163 165 Magnetoelectric effect, 152 154 Magneto-electric nanoparticles (MENPs), 117 119 Magnetoimpedance, 152 154 Magnetoresistance, 152 154 Magnetoresistive sensors, 154 165 giant magnetoresistance (GMR) based sensors, 155 159 spin-valve sensors, 159 163 tunneling magnetoresistancebased sensors, 163 165 Malathion, 17 18

Index

11-Mercaptoundecanoic acid (11-MUA), 171 173 Messenger RNA (mRNA), 133 134 Methotrexate, 220 Methylene blue, 52 54 Microarrays, 132, 133t Microelectromechanical system (MEMS) technology, 160 163 Microfluidic biosensors for cancer exosome detection, 201 204 for cancer protein detection, 198 201 for cell-free DNA (cfDNA), 204 205 for circulating tumor cell detection, 190 198 microfluidic immuneaffinity separation of circulating tumor cells, 193 198 size-based separation of circulating tumor cells in microfluidics, 191 193 Microfluidic biosensors, fabrication of, 188 189 MicroRNAs (miRNAs), 133 134, 231 232 Micrototal analysis systems (μTAS), 39 40 Mitoxantrone, 117 Module maps, 132, 133t Monocrotophos pesticides, 17 Monte Carlo dose calculation, 140 Moringa oleifera, 8 9 MUC1 protein, 52 54 μHall sensor, 174 176 Multichannel screen-printed array of electrodes (MUX-SPE16) based electrochemical biosensor, 55 56 Multidrug resistant (MDR) bacterial pathogens, 7 8 Multifunctional nanomedicine, 138

Mutation, 211 212

N Nanobiochip devices for clinical application, 222 223 Nanobiochip sensor technique, 223 Nanobiosensors, 5 6 Nanobiotechnology, 2 Nanocapsules, 13 14 Nanocarriers, 217 Nanoencapsules, 2 3, 5 6 Nanomaterials, 215 216 as barrier, 24 Nanomedicine artificial intelligence-enabled nanomedicine, 138 cancer nanomedicine, 129 130 Nanoparticles, 2 3 Nanopore technology, 11 Nanoscale devices, 216 217 Nanosensors, 24 25 Nanoshells, 216 217 Nanospheres, 2 3 Nanostructured hafnium oxide integrated RGO (nHfO2@RGO) sheets, 47 48 Nanosuspension of nonnucleoside, 4 Nanotubes, 2 3 1-Naphthalene acetic acid, 14 15 National Academy of Clinical Biochemistry (NACB), 44 45 Natural lifetime, defined, 82 Near-infrared (NIR) dyes, 91 92 Near-infrared fluorescence imaging, 6 7 Neuron-specific enolase (NSE), 44 45 Neutral red, 56 59 Nonbiodegradable nanoparticles, 222 Non-Hodgkin lymphomas (NHLs), 137

239

Noninvasive techniques, 97 98 Nuclear magnetic resonance, 152 154 Nyquist plot, 62 63, 62f

O Optical biosensors, 13 Optical microscopy, 89 90 Optimized diuron nanoformulation (ODNF), 14 15 Oral cancer challenges/ limitations, 219 221 Organic dyes, 90 92

P Paclitaxel, 220 Pauli’s exclusion principle, 93 PDMS (poly(dimethylsiloxane)) channels, 39 40 Pencil graphite electrode (PGE), 55 56 Pentachlorophenol, 14 15 Pesticides, 2, 16 17 Phosphorescence, 76 77, 80f Photobleaching, 86 Photodynamic therapy (PDT), 10 Plumbago zeylanica, 8 9 Point-of-care (POC) biosensing platforms, 49 50 Point-of-care testing platforms, 149 150, 176 Poly (3,3’-dimethoxybenzidine) (PDB) film, 63 65 Poly (ethylene imine) (PEI), 14 15 Polydimethylsiloxane (PDMS) microchannel, 163 165 Polyepsiloncaprolactone (PCL) nanoparticles, 5 Poly ethyl-glycol (PEG), 3 4 Polymerase chain reaction (PCR), 156 159 Positron emission tomography, 45 47 Potentiometric biosensors, 13 Progesterone, 44 45

240

Index

Programmed death-1 (PD-1), 230 Programming language (PL), 139 141 in cancer diagnosis, 139 140 in cancer treatment, 140 141 Promethazine, 117 Prostate cancer biomarker, 47 48, 51 52 Prostate specific antigen (PSA), 44 45, 51 52 Prostate-specific membrane antigen (PSMA), 200 201 Proto-oncogenes, 125 126 Pseudomonas aeruginosa, 7 8

Q Quadratic phenotype optimization platform (QPOP), 138 Quantitative texture analysis (QTA), 137 Quantum dots (QDs), 6, 92 94 for florescence imaging and cancer diagnostics, 92 96 Quenching and photobleaching, 85 86 Quinalphos, 17

R Radiation therapy, 219 221 Radioimmunoassay, 45 47 Raman intensity, 109 110 Raman scattering, 109 110, 215 216 Raman spectroscopy/SERS based immunoassays for cancer diagnostics, 107 108 application of Raman-active nanostructures, 111 112 bioanalysis application, 116 119 bioimaging, 116 117 drug delivery, 117 Raman spectroscopy to evaluate drug binding and release, 117

Raman to evaluate nanoparticle-bio interface, 119 future challenges, 119 121 history and working principle, 109 111 surface-enhanced Raman spectroscopy platforms in cancer diagnostics, 112 116 cell analysis, 113 114 DNA and RNA analysis, 114 115 extracellular vesicles (EV) analysis, 116 protein analysis, 115 116 Raphanus raphanistrum, 14 Rare-earth-based downconversion nanoparticles, 92 Rayleigh scattering, 109 110 Reduced graphene oxidetetraethylene pentamine (rGO-TEPA), 56 59 Reduce graphene surface oxide (RGO), 47 48 Reference electrode (RE), 43 44 Resonant biosensors, 13 Reverse transcriptase polymerase chain reaction (RT-PCR), 45 47 Rilpivirine, 4

S Select and test (ST), 139 140 Self-assembled monolayers (SAMs), 91 92 Semecarpus anacardium, 8 9 Shear induced diffusion (SID), 191 192 Signal to noise ratio (SNR), 86 Silver hybridized mesoporous silica nanoparticles (Ag@MSNs), 51 52 Silver nanoparticles (AgNPs), 7 8 SLAMS (Stepwise linkage analysis of microarray signatures), 133t

Small cell lung cancer (SCLC), 44 45 Solanum nigrum, 8 9 Sol gel process, 14 Spin valves, 152 154 Spin-valve sensors, 159 163 Squamous cell carcinoma antigen (SCCA), 56 59 Staphylococcus aureus, 24 Stern-Volmer equation, 85 86 Stokes shift, 78 80 STRING, 134 Superconducting quantum interference, 152 154 Surface-enhanced Raman scattering (SERS) based detection, 200 201 Surface-enhanced Raman spectroscopy platforms in cancer diagnostics, 112 116 cell analysis, 113 114 DNA and RNA analysis, 114 115 extracellular vesicles (EV) analysis, 116 protein analysis, 115 116 Surface-enhanced Raman spectrum, 110 111 Surface plasmon-coupled emission measurements (SPCE), 94 95 Surface plasmon resonance (SPR) effect, 107 108, 110 111, 215 216

T Terminalia arjuna, 8 9 3,3’,5,5’-Tetramethylbenzidine (TMB), 186 187, 203 Tetraspanin biomarker (CD9) antibody, 59 61 Thermal detection biosensors, 13 The SensoDX OraTech, 223 Thespesia populnea, 8 9 Thiocholine, 95 96 Thionine, 56 59 Thyroglobulin, 44 45

Index

Tissue biopsy, 97 98 Titanium dioxide, 16 17, 20 21 Titanium dioxide nanoparticles, 18 Transducer, 45 47 Trastuzumab therapy, 44 45 Treatment of cancer, nanotechnology for, 9 10 Tumor cell detection, microfluidic biosensors for circulating, 190 198 microfluidic immune-affinity separation of circulating tumor cells, 193 198

size-based separation of circulating tumor cells in microfluidics, 191 193 Tumor cells, 214 215 Tunneling magnetoresistance (TMR), 152 154, 163 165 TMR-based sensors, 163 165

U UM-A9 antibody, 7 Uterine corpus endometrial carcinoma (UCEC), 137 138

241

V Vascular endothelial growth factor (VEGF), 54

W Warburg impedance, 62 63 Water treatment, nanotechnology in, 20 22 White-light endoscopy, 97 98 Working electrode (WE), 43 44

Z Zeolite, 23 24