Transportome Malfunction in the Cancer Spectrum: Ion Transport in Tumor Biology (Reviews of Physiology, Biochemistry and Pharmacology, 181) 3030909190, 9783030909192

Table of contents :
Preface
Acknowledgements
Contents
Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer Progression
1 Introduction
2 Impact of Tumor Microenvironment on Breast Cancer Hallmarks
2.1 Extracellular Matrix
2.1.1 Collagen 1 and Breast Cancer Cell Phenotype
2.1.2 Cytokines and Growth Factors
2.2 Impact of Hypoxia on Breast Carcinoma Behavior
2.3 pH in Mammary Tissue
3 Dialogue Between Microenvironmental Elements and Ion Channels: Effect on Breast Cancer Hallmarks
3.1 Collagen Induces Breast Cancer Survival and Migration Through Potassium Channels
3.1.1 Stiffness, Mechanosensitive Ion Channels, and Breast Cancer
3.2 EGF and TGF-β Modulate EMT, Invasion, Migration, and Proliferation Through Potassium, Calcium, and Sodium Channels
3.2.1 EGF
3.2.2 TGF-β
3.2.3 ATP, via Purinergic Receptors, Regulates Proliferation, Invasion, Migration, and EMT
3.3 Involvement of Ion Channels in the Adaptation of Cells to Live in:
3.3.1 Hypoxic Conditions
3.3.2 Acidic Conditions
4 Conclusion and Perspectives
References
Ion Channel Profiling in Prostate Cancer: Toward Cell Population-Specific Screening
1 Introduction
2 Stromal Cell Profiling
3 Endothelial Cell Profiling
4 Neuronal and Neuroendocrine Tumor Cell Profiling
5 New Methods for Cell Population Separation
5.1 Cell Isolation Techniques
5.1.1 Explant Culture or Enzymatic Separation
5.1.2 Laser Capture Microdissection (LCM)
5.1.3 Antibody-Based Cell Sorting
5.2 Cell Characterization Techniques
5.2.1 Digital Spatial Profiling
5.2.2 Single-Cell RNA Sequencing
5.2.3 Cell Painting
6 Conclusions
References
Ion Channels in Lung Cancer
1 Introduction
2 Ion Channels in Lung Cancer
2.1 Transient Receptor Potential (TRP) Channels in Lung Cancer
2.2 Voltage-Gated Ion Channels in Lung Cancer
2.3 K2P Channels
2.4 Ca2+-Activated Potassium Channels
2.5 Chloride Channels in Lung Cancer
2.6 Nicotine Acetylcholine Receptors (nAChRs)
3 Outlook
References
Contribution and Expression of Organic Cation Transporters and Aquaporin Water Channels in Renal Cancer
1 Renal Cell Tumors
1.1 Epidemiology and Risk Factors
1.2 Genetic Factors Associated with RCC
1.3 RCC Subtypes
1.4 Grading of Renal Cell Carcinoma
1.5 Diagnosis and Therapy
2 Renal Transport Processes
2.1 Kidneys Function as a Filtration and Reabsorption Organ
2.2 Transporters in Cancer
2.2.1 Organic Cation Transporters in Renal Cancer
3 The Aquaporin Protein Family
3.1 Aquaporins in Cancer
3.2 AQP1
3.3 AQP2
3.4 AQP3
3.5 AQP4
4 Conclusion
References
Transportome Malfunctions and the Hallmarks of Pancreatic Cancer
1 Epidemiology in Western and Eastern Countries
2 Genetic Drivers in PDAC
3 History of PanIN Progression Model
4 The Typical Hallmarks of PDAC
5 The Molecular Subtypes of PDAC
6 Ion Malfunction in PDAC
6.1 ICT in Genetic Database Sets
6.2 pH Regulation and H+ Transporters
6.3 Ca2+ Channels and Signal Mediators
6.4 K+ Channels
6.5 Na+ Transporters
6.6 Cl- and Other Channels/Regulators
6.7 Therapeutic Options Based on ICT Analyses
7 Further Perspectives
References
How Dysregulated Ion Channels and Transporters Take a Hand in Esophageal, Liver, and Colorectal Cancer
1 Introduction
1.1 Risk Factors Dysregulating Ion Channels and Transporters
2 Esophageal Cancer
2.1 Ca2+ Channels and Transporters
2.2 Transient Receptor Potential (TRP) Channels
2.3 K+ Channels
2.4 Cl- Channels
2.5 Na+/H+ Exchanger 1 (SLC9A1)
2.6 Divalent Metal Transporter
3 Hepatocellular Carcinoma
3.1 Ca2+ Channels and Transporters
3.2 Transient Receptor Potential (TRP) Channels
3.3 K+ Channels
3.3.1 Voltage-Gated K+ Channels
3.3.2 Ca2+-Sensitive K+ Channels
3.3.3 ATP-Sensitive K+ Channels
3.3.4 Two-Pore Domain K+ Channels
3.4 Na+ Channels
3.5 Cl- Channels
3.5.1 Voltage-Gated Cl- Channels
3.5.2 Ca2+-Activated Cl- Channels
3.5.3 Cl- Intracellular Channel Proteins (CLICs)
3.6 Na+/H+ Exchanger NHE1 (SLC9A1)
3.7 Monocarboxylate Transporters (MCTs, SLC16As)
3.8 Magnesium Transporter MagT1
3.9 Organic Anion and Cation Transporters
3.9.1 Organic Cation Transporters (OCTs/SLC22As)
3.9.2 Organic Anion Transporters
4 Colorectal Cancer
4.1 Ca2+ Channels and Transporters
4.2 Transient Receptor Potential (TRP) Channels
4.3 K+ Channels
4.3.1 Voltage-Gated K+ Channels
4.3.2 Ca2+-Sensitive K+ Channels
4.3.3 Two-Pore Domain K+ Channels
4.4 Na+ Channels
4.4.1 Voltage-Gated Na+ Channels
4.4.2 Acid-Sensing Ion Channel
4.5 Cl- Channels
4.5.1 Voltage-Gated Cl- Channels
4.5.2 Ca2+-Activated Cl- Channels
ANO1
4.5.3 Cl- Intracellular Channels
4.5.4 CFTR
4.6 Na+/H+ Exchangers
4.7 NBC (SLC4A4, NBCe1)
4.8 Cl-/HCO3- Exchanger (DRA, SLC26A3)
4.9 Monocarboxylate Carriers (MCTs, SLC16As)
4.10 SO42- Transporter (SLC26A2, DTDST)
4.11 Zn2+ Transporters
4.12 Organic Cation Transporters
4.13 Organic Anion Transporters
5 Conclusion
References
Ion Channels in Glioma Malignancy
1 Brain Tumors
2 Biological Processes Involved in Brain Tumor Malignancy
2.1 Cell Migration and Invasion
2.2 Cell Cycle and Cell Proliferation
2.3 Apoptosis
2.4 Cell Volume Regulation
2.5 Ca2+ Signaling
3 Ion Channels Primarily Involved in Glioma Malignancy
3.1 Ca2+-Activated K+ Channels
3.1.1 The KCa3.1 Channel
3.1.2 The KCa1.1 Channel
3.2 Cl- Channels
3.2.1 VRAC
3.2.2 ClC-3 Channel
3.3 TRP Channels
3.3.1 TRP Channels in Glioblastoma
3.4 Low-Threshold (T-Type) Voltage-Activated Calcium Channels
3.4.1 T-Type Ca Channels in Glioblastoma
4 Targeting Ion Channels as Therapeutic Adjuvant in Brain Tumors
References
Membrane Transporters and Channels in Melanoma
1 Introduction
2 Main Text
2.1 ABC Transporters (ATP-Binding Cassette Subfamily A-G)
2.1.1 ABCBs
2.1.2 ABCCs
2.1.3 ABCGs
2.2 ANOs (Anoctamins)
2.3 AQPs (Aquaporins)
2.4 ASICs (Acid-Sensing Ion Channels)
2.5 ATPs (ATPases)
2.5.1 ATP1s (Sodium-/Potassium-Transporting ATPase)
2.5.2 ATP2As (Sarcoplasmic/Endoplasmic Reticulum Calcium ATPase)
2.5.3 ATP2Bs (Plasma Membrane Calcium ATPases)
2.5.4 ATP7s (Copper-Transporting ATPases)
2.6 CACNs (Calcium Voltage-Gated Channels)
2.7 CLICs (Chloride Intracellular Channels)
2.8 CLCs (Chloride Voltage-Gated Channels)
2.9 CLCAs (Chloride Channel Accessory Proteins)
2.10 CNNM1-4 (Cyclin and CBS Domain Divalent Metal Cation Transport Mediators)
2.11 HCNs (Hyperpolarization-Activated Cyclic Nucleotide-Gated Potassium Channels)
2.12 KCNs (Potassium Channels)
2.12.1 KCNAs
2.12.2 KCNHs
2.12.3 KCNJs
2.12.4 KCNKs
2.12.5 KCNMs
2.12.6 KCNNs
2.12.7 Further KCN Channels
2.13 MAGT1 (Magnesium Transporter 1)
2.14 MCUs (Mitochondrial Calcium Uniporters)
2.15 MPCs (Mitochondrial Pyruvate Carriers)
2.16 MRS2
2.17 MTCH1s (Mitochondrial Carrier)
2.18 ORAIs (Calcium Release-Activated Calcium Modulator, ORAI1-3)
2.19 Piezo1 and 2
2.20 PKD2
2.21 P2X (Purinergic Receptors)
2.22 RYRs (Ryanodine Receptors)
2.23 SCNs (Voltage-Gated Sodium Channels)
2.24 SCNN1s (Sodium Channel Epithelial 1s)
2.25 SLCs (Solute Carrier Family)
2.25.1 SLC1As
2.25.2 SLC2As (Glucose Transporter)
2.25.3 SLC3As (L-Type Amino Acid Transporter)
2.25.4 SLC4As (Bicarbonate Transporter)
2.25.5 SLC5As (Sodium/Glucose Transporter Family)
2.25.6 SLC7As (Cystine-Glutamate Antiporter)
2.25.7 SLC9As (Sodium/Hydrogen Exchangers 9)
2.25.8 SLC10A-13As
2.25.9 SLC16As
2.25.10 SLC17As
2.25.11 SLC18s
2.25.12 SLC19As
2.25.13 SLC21As
2.25.14 SLC22As
2.25.15 SLC25As
2.25.16 SLC45A
2.26 SLCOs (Solute Carrier Organic Anion Transporter Family)
2.27 STEAPs (Six-Transmembrane Epithelial Antigen of the Prostate)
2.28 STIMs (Stromal Interaction Molecules)
2.29 TPCNs (Two-Pore Channel Proteins)
2.30 TRPs (Transient Receptor Potential Cation Channel Subfamilies)
2.30.1 TRPA1
2.30.2 TRPCs
2.30.3 TRPMs
2.30.4 TRPMLs
2.30.5 TRPP
2.30.6 TRPVs
2.31 VDACs (Voltage-Dependent Anion Channels)
2.32 Other Transporter Proteins Expressed on Melanoma
3 Conclusion and Perspectives
References
Ion Channel Dysregulation in Head and Neck Cancers: Perspectives for Clinical Application
1 Introduction
1.1 Head and Neck Cancer Characteristics and Treatment
1.2 Ion Channels and Channelopathies
2 Dysregulation of Potassium Channels
2.1 Voltage-Gated Potassium Channels
2.1.1 Pathobiological Role
2.1.2 Clinical Relevance
2.2 Calcium-Activated Potassium Channels
2.2.1 Pathobiological Role
2.2.2 Clinical Relevance
3 Dysregulation of Sodium Channels
3.1 Pathobiological Role
3.2 Clinical Relevance
4 Dysregulation of Calcium Channels
4.1 Voltage-Gated Calcium Channel Subunits
4.1.1 Pathobiological Role
4.1.2 Clinical Relevance
4.2 Other Calcium Channels
4.2.1 Pathobiological Role
4.2.2 Clinical Relevance
5 Dysregulation of Transient Receptor Potential Cation Channels
5.1 Pathobiological Role
5.2 Clinical Relevance
6 Dysregulation of Chloride Channels
6.1 Voltage-Gated Chloride Channels (ClCs)
6.1.1 Pathobiological Role
6.1.2 Clinical Relevance
6.2 Calcium-Activated Chloride Channels (CaCCs)
6.2.1 Pathobiological Role
6.2.2 Clinical Relevance
6.3 Chloride Intracellular Channels (CLIC) Family Proteins
6.3.1 Pathobiological Role
6.3.2 Clinical Relevance
6.4 Other Chloride Channels (ATP-Gated CFTR or Volume-Regulated Anion Channel Subunits)
7 Dysregulation of Ligand-Gated Ion Channels
7.1 Nicotinic Acetylcholine Receptors
7.1.1 Pathobiological Role
7.1.2 Clinical Relevance
7.2 Zinc-Activated Channels
7.3 P2X Purinergic Receptors
7.4 Inositol Triphosphate Receptor
8 Dysregulation of Porins
8.1 Aquaporins
8.1.1 Pathobiological Role
8.1.2 Clinical Relevance
8.2 Voltage-Dependent Anion-Selective Channels
9 Dysregulation of Gap Junction Proteins (Connexins)
10 Closing Remarks and Future Perspectives
References

Citation preview

Christian Stock · Luis A. Pardo Editors

Reviews of Physiology, Biochemistry and Pharmacology 181

Reviews of Physiology, Biochemistry and Pharmacology Volume 181

Editor-in-Chief Stine Helene Falsig Pedersen, Department of Biology, University of Copenhagen, Copenhagen, Denmark Series Editors Diane L. Barber, Department of Cell and Tissue Biology, University of California San Francisco, San Francisco, CA, USA Emmanuelle Cordat, Department of Physiology, University of Alberta, Edmonton, Canada Mayumi Kajimura, Department of Biochemistry, Keio University, Tokyo, Japan Jens G. Leipziger, Department of Biomedicine, Aarhus University, Aarhus, Denmark Martha E. O’Donnell, Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, USA Luis A. Pardo, Max Planck Institute for Experimental Medicine, G€ ottingen, Germany Nicole Schmitt, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark Christian Stock, Department of Gastroenterology, Hannover Medical School, Hannover, Germany

The highly successful Reviews of Physiology, Biochemistry and Pharmacology continue to offer high-quality, in-depth reviews covering the full range of modern physiology, biochemistry and pharmacology. Leading researchers are specially invited to provide a complete understanding of the key topics in these archetypal multidisciplinary fields. In a form immediately useful to scientists, this periodical aims to filter, highlight and review the latest developments in these rapidly advancing fields. 2019 Impact Factor: 4.700, 5-Year Impact Factor: 6.000 2019 Eigenfaktor Score: 0.00067, Article Influence Score: 1.570

More information about this series at https://link.springer.com/bookseries/112

Christian Stock
Luis A. Pardo Editors

Transportome Malfunction in the Cancer Spectrum Ion Transport in Tumor Biology

Editors Christian Stock Medizinische Hochschule Hannover Zentrum für Innere Medizin Hannover, Germany

Luis A. Pardo Max-Planck-Institut für Experimentelle Medizin G€ottingen, Germany

ISSN 0303-4240 ISSN 1617-5786 (electronic) Reviews of Physiology, Biochemistry and Pharmacology ISBN 978-3-030-90919-2 ISBN 978-3-030-90920-8 (eBook) https://doi.org/10.1007/978-3-030-90920-8 © Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Over the last two decades, research on ion channels and transporters – collectively referred to as the transportome – has revealed their significant involvement at every stage of cancer development, including initiation, adpatation to – and shaping of – the microenvironment, growth, survival, invasion, and metastasis. Every cell type relies on the transportome for functions as crucial and diverse as secretion, migration, or signaling. This is even more evident in the case of epithelial cells, which originate nearly 90% of malignant tumor diseases and, for the most part, rely on the transportome to fulfill their physiological core functions. Cancer cells profit from and exploit the transportome in order to survive and have an advantage over healthy cells. Dysregulated expression/function of ion transporters has been correlated with malignancy in the vast majority of tumor diseases, including breast, prostate, lung and colorectal cancer, pancreatic ductal adenocarcinoma, hepatocellular carcinoma, renal cell carcinoma, melanoma and glioblastoma, to mention some of the epidemiologically most relevant tumor types. The relation between transportome alterations and disease outcome implies that, in all those major cancer entities, the transportome could represent an Achilles heel of the tumor that could be used for diagnostic, prognostic, and therapeutic purposes. The present volume entitled “Transportome Malfunctions in the Cancer Spectrum” is the first one out of the three volumes dealing with dysregulated ion transport in tumor diseases. It gives an overview of the impressively wide variety of ion channels and transporters dysregulated in the most prevalent cancer types. The second volume, “From Malignant Transformation to Metastasis,” will describe the underlying mechanisms by which dysregulated ion transport contributes to cancer development and progression. The third volume, “Novel Targets of Cancer Diagnosis and Treatment,” will present diagnostic and therapeutic approaches based on the exploitation of ion transport proteins. Hannover, Germany G€ottingen, Germany

Christian Stock Luis A. Pardo

v

Acknowledgements

Contributions to this volume have partly been personally invited, with the kind support of the series editors D.L. Barber, E. Cordat, M. Kajimura, J. Leipziger, M.E. O’Donnell, L. Pardo, N. Schmitt, C. Stock.

vii

Contents

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer Progression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Halima Ouadid-Ahidouch, Hamid Morjani, Julie Schnipper, Alban Girault, and Ahmed Ahidouch Ion Channel Profiling in Prostate Cancer: Toward Cell Population-Specific Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Valerio Farfariello, Natalia Prevarskaya, and Dimitra Gkika Ion Channels in Lung Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Etmar Bulk, Luca Matteo Todesca, and Albrecht Schwab Contribution and Expression of Organic Cation Transporters and Aquaporin Water Channels in Renal Cancer . . . . . . . . . . . . . . . . . Giuliano Ciarimboli, Gerit Theil, Joanna Bialek, and Bayram Edemir

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Transportome Malfunctions and the Hallmarks of Pancreatic Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Qi Ling and Holger Kalthoff How Dysregulated Ion Channels and Transporters Take a Hand in Esophageal, Liver, and Colorectal Cancer . . . . . . . . . . . . . . . . . . . . . 129 Christian Stock Ion Channels in Glioma Malignancy . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Luigi Catacuzzeno, Luigi Sforna, Vincenzo Esposito, Cristina Limatola, and Fabio Franciolini Membrane Transporters and Channels in Melanoma . . . . . . . . . . . . . . 269 Ines B€ohme, Roland Sch€onherr, Jürgen Eberle, and Anja Katrin Bosserhoff Ion Channel Dysregulation in Head and Neck Cancers: Perspectives for Clinical Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Nagore Del-Rı´o-Ibisate, Rocı´o Granda-Dı´az, Juan P. Rodrigo, Sofı´a T. Mene´ndez, and Juana M. Garcı´a-Pedrero ix

Rev Physiol Biochem Pharmacol (2021) 181: 1–38 https://doi.org/10.1007/112_2020_19 © Springer Nature Switzerland AG 2020 Published online: 7 August 2020

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer Progression Halima Ouadid-Ahidouch, Hamid Morjani, Julie Schnipper, Alban Girault, and Ahmed Ahidouch Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Impact of Tumor Microenvironment on Breast Cancer Hallmarks . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Extracellular Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Impact of Hypoxia on Breast Carcinoma Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 pH in Mammary Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Dialogue Between Microenvironmental Elements and Ion Channels: Effect on Breast Cancer Hallmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Collagen Induces Breast Cancer Survival and Migration Through Potassium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 EGF and TGF-β Modulate EMT, Invasion, Migration, and Proliferation Through Potassium, Calcium, and Sodium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Involvement of Ion Channels in the Adaptation of Cells to Live in: . . . . . . . . . . . . . . . . . 4 Conclusion and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract In recent years, it has been shown that breast cancer consists not only of neoplastic cells, but also of significant alterations in the surrounding stroma or tumor microenvironment. These alterations are now recognized as a critical element for breast cancer development and progression, as well as potential therapeutic targets. Furthermore, there is no doubt that ion channels are deregulated in breast cancer and H. Ouadid-Ahidouch (*), J. Schnipper, and A. Girault Laboratory of Cellular and Molecular Physiology, UR UPJV 4667, University of Picardie Jules Verne, Amiens, France e-mail: [email protected] H. Morjani BioSpecT EA7506, Faculty of Pharmacy, Reims University, Reims, France A. Ahidouch Laboratory of Cellular and Molecular Physiology, UR UPJV 4667, University of Picardie Jules Verne, Amiens, France Department of Biology, Faculty of Sciences, Ibn-Zohr University, Agadir, Morocco

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some of which are prognostic markers of clinical outcome. Their dysregulation is also associated with aberrant signaling pathways. The number of published data on ion channels modifications by the microenvironment has significantly increased last years. Here, we summarize the state of the art on the cross talk between the tumor microenvironment and ion channels, in particular collagen 1, EGF, TGF-β, ATP, hypoxia, and pH, on the development and progression of breast cancer. Keywords ATP · Breast cancer · Collagen 1 · EGF · Hypoxia · Ion channels · pH · TGF-β · Tumor microenvironment

Abbreviations BC DDR ECM EGF EGFR EMT ER GSTO1 HIF MCU MMP ROS SICE TGF-β TME TNBC VEGF

Breast cancer Discoidin domain receptor Extracellular matrix Epidermal growth factor Epidermal growth factor receptor Epithelial-to-mesenchymal transition Endoplasmic reticulum Glutathione S-transferase omega 1 Hypoxia inducible factor Mitochondrial calcium uniporter Metalloproteinase Reactive oxygen species Store-independent calcium entry Transforming growth factor β Tumor microenvironment Triple-negative breast cancer Vascular endothelial growth factor

1 Introduction While enormous progress has been made in understanding the genetics of tumors and the fundamental molecular mechanisms involved in tumor progression, it is only in recent years that we have been interested in the role of the tumor microenvironment in cancer development including breast cancer (BC) (Soysal et al. 2015). Breast tissue represents an organ whose stroma plays a very important role in the development of the mammary gland. Indeed, during mammogenesis, the growth of the milk ducts and lobules requires infiltration of the epithelial cells into the surrounding stromal tissue. This mechanism requires remodeling of the microenvironment to allow the growth and migration of epithelial cells in a “similar” manner to an infiltrating tumor. Thus, many processes related to the microenvironment are

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer. . .

3

deregulated and used by cancer cells during its tumor progression. The tumor microenvironment (TME) communicates and dynamically interacts with cancer cells permanently. It is not surprising that its components are key players in the cancer development and progression. The TME is a dynamic entity composed of stromal cells, including fibroblasts, adipocytes, endothelial cells, and immune cells. Furthermore, it is also composed of extracellular matrix (ECM) which contains soluble factors and adhesive components, which greatly influence cancer progression (Hui and Chen 2015). The composition and the dynamic of TME in BC have been extensively reviewed (Soysal et al. 2015). However, very little data are reported in the literature concerning the relationship between ion channels and the TME in BC. Ion channels have recently been identified as “new markers” in oncological research. Studies over the last 20 years have clearly shown the contribution of these channels to the aggressiveness of cancer and more and more studies suggest them as key players in interactions between tumor cells and TME through signals’ transduction of cell signaling from the TME (Andersen et al. 2014; Arcangeli et al. 2014; Brucher and Jamall 2014). This review is divided into two parts. The first deals with the effect of the different components of extra cellular matrix (collagen 1, EGF, TGF-β, and ATP), hypoxia, and pH on BC progression. The second part will summarize the works that explored the possible involvement of ion channels in the TME-dependent effect on BC.

2 Impact of Tumor Microenvironment on Breast Cancer Hallmarks In recent decades, several works have underlined the importance of the microenvironment in BC progression (Balkwill et al. 2012; Dias et al. 2019). Indeed, several studies have highlighted the importance of bidirectional communication between tumor cells and their microenvironment in the modulation of their phenotype. The TME consists of stromal cells and ECM components. Stromal cells components include cancer associated fibroblasts (Houthuijzen and Jonkers 2018), cancer associated adipocytes (Attane et al. 2018), immune cells (Tower et al. 2019), and endothelial cells (Hida et al. 2018). ECM consists of adhesion factors, including type 1 and 6 collagens, which are overexpressed in aggressive breast tumors (Phillips et al. 2019). Soluble factors, which correspond to the “secretome” of stromal cells, include among others transforming growth factor-β (TGF-β) (Drabsch and ten Dijke 2012; Imamura et al. 2012) and epidermal growth factor (EGF) (De Luca et al. 2008; Masuda et al. 2012). All these factors are involved in cell proliferation, survival, epithelial-to-mesenchymal transition (EMT), migration, invasion, and metastasis.

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2.1

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Extracellular Matrix

One of the components of the breast TME is the ECM, which plays an important role in the regulation of BC progression (Kaushik et al. 2016; Pickup et al. 2014). ECM contains adhesive and soluble factors and among adhesives components, type 1 collagen (collagen 1) is one of important factors that regulates the tumorigenesis, EMT, migration, invasion, metastasis, and response to anticancer therapies (Xu et al. 2019).

2.1.1

Collagen 1 and Breast Cancer Cell Phenotype

The collagen superfamily is the major component of this ECM, particularly type 1 collagen, which is the most abundant in several organs such as breast, skin, and lung. Biophysical investigations have given an evidence for different molecular fingerprints for collagen (fiber alignment, stiffness, and density) in breast carcinoma tissues when compared to normal tissues. In fact, analysis of mammographic and particularly collagen density, analyzed by second harmonic generation microscopy (SHG), has shown a relationship between collagen density and BC risk and progression (Boyd et al. 2009; Provenzano et al. 2008). Kakkad et al. have investigated the relationship between lymph node metastasis and the properties of collagen in the primary breast tumors. They demonstrated an increase in collagen density only in primary tumors associated with positive lymph node metastasis (Kakkad et al. 2012). Concerning the collagen stiffness, Stowers et al. have recently shown using the non-malignant MCF-10A epithelial breast cells, that matrix stiffening induces a malignant phenotypic transition and thus could be involved in the acquisition of invasive and metastatic properties in normal epithelial cells (Stowers et al. 2017). Finally, Morris et al. have shown that, in metastatic BC cells, higher collagen density induced an alteration in cell metabolism. Such observed shift was associated with changes in gene expression profile (Morris et al. 2016). Collagen 1 consists of three subunits, two α1 chains and one α2 chain. The combination of these three chains leads to a right triple helix measuring 300 nm long and 1.5 nm in diameter (Mouw et al. 2014). Amino acid sequence of the subunits consists of a Gly-X-Y triplet repeats. X and Y correspond frequently to proline and hydroxyproline, respectively. In addition to its architectural function, collagen 1 also modulates the behavior of surrounding cells by interacting with them via specific receptors. The most studied receptors of collagen 1 are β1-integrin heterodimers (α1β1, α2β1, α10β1, and α11β1) (Humphries et al. 2006). Several studies have underlined the importance of integrins in the regulation of cancer stemness, metastasis, and drug resistance (Seguin et al. 2015). α1β1 and α2β1 integrins have been reported to mediate invasion in mouse breast tumor cells (Lochter et al. 1999). Kim et al. have demonstrated that collagen is able to induce MMP-2 activation in BC cells and that α2β1 integrin signaling was involved in this process (Kim et al. 2007). Collagen also activates pro-MMP-2 and estrogen-induced proliferation in human

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breast epithelial cells via α2β1 integrin and β1 integrin, respectively (Kim et al. 2007; Xie and Haslam 2008). α2β1 integrin signaling has been identified as survival pathway in doxorubicin-induced apoptosis in BC cells (Aoudjit and Vuori 2001). The same group demonstrated later, but in other cell models, that such mechanism involves an overexpression of ABCC1/MRP-1 protein which is a member of the large ATP-binding cassette transporters (ABC) family (El Azreq et al. 2012). More recently, Bendas group described a functional role of collagen 1-β1 integrin axis in mediated chemoresistance via upregulation of ABC transporters in BC cells (Baltes et al. 2020). Discoidin domain receptors DDR1 and DDR2 have also been reported to interact with collagen 1 (Carafoli and Hohenester 2013; Fu et al. 2013; Leitinger 2014) and to play a role in tumor progression (Rammal et al. 2016; Valiathan et al. 2012). These receptors, which harbor a tyrosine kinase activity, recognize GVMGFO sequence of collagen 1 (Konitsiotis et al. 2008) and exhibit a relatively late and prolonged activation (Vogel et al. 1997). DDR1 seems to be preferentially expressed in luminal-like breast carcinoma, whereas the basal-like one expressed predominantly DDR2 (Saby et al. 2019; Takai et al. 2018). Moreover, the high level of DDR2 expression is associated with high BC grade (Toy et al. 2015). More recently, DDR1 mutations were strongly associated with poor prognosis in estrogen receptorpositive BC (Griffith et al. 2018). However, among the basal-like cell lines, MDA-MB-231 cells are the exception since they express weakly DDR1 and do not express DDR2 (Saby et al. 2019; Juin et al. 2014). It is important to note that as reported by Saby et al., mRNA analysis in silico using the Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) showed that 58 BC cell lines were separated into two distinct groups. The first one includes cells with a relatively high level of DDR1 and a low level of DDR2, and is essentially composed of cells with epithelial-like phenotype (E-cadherin) like the MCF-7 cells. The second group includes cells with a low level of DDR1. This group is composed by cells with basal-like phenotype (Vimentin) like the MDA-MB-231 cells which do not express DDR2. The other cell lines harboring basal-like phenotype like MDA-MB-157, MDA-MB-436, and others present an overexpression of DDR2 (Saby et al. 2019). Moreover, Toy et al. have shown for some of those basal-like BC cells, that the low level of DDR1 expression could be compensated by an increase in DDR2 expression (Toy et al. 2015). Maquoi group was the first to show the role of the collagen/DDR1 axis as a tumor suppressor in breast carcinoma. Indeed, this group showed that the 3D collagen matrix, by activating DDR1, inhibited the proliferation and induced apoptosis in luminal-like MCF-7 and ZR75-1 BC cells (Maquoi et al. 2012). In more recent works, DDR1 has been shown to activate an apoptotic signaling pathway by inducing BIK expression (Assent et al. 2015; Saby et al. 2018). While such phenotype was not observed in MDA-MB-231 cells (Maquoi et al. 2012), enforced expression of DDR1 in these cells restored cell proliferation suppression and apoptosis (Saby et al. 2019). Concerning involvement of DDR2 in BC progression, the first data have been reported by Longmore group, who demonstrated that this receptor was able to enhance invasion and metastasis by stabilizing SNAIL1 (Zhang et al. 2013). Another work has demonstrated that DDR2 not only in tumor cells, but

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also in cancer associated fibroblasts, is important for BC metastasis (Corsa et al. 2016). More recent data have shown that DDR2 controls breast tumor metastasis via the regulation of the matrix stiffness and integrin signal transduction in cancer associated fibroblasts. Thus, DDR2 has been proposed at a promising target for the treatment of metastatic BC (Grither and Longmore 2018).

2.1.2

Cytokines and Growth Factors

Among cytokines and growth factors, TGF-β and EGF are respectively important players in BC progression. TGF-β is secreted in the extracellular environment by several cell types, including macrophages, T cells, and monocytes. This factor is produced in a latent form until it is activated to interact with its receptors and this activation is highly controlled (Yu and Feng 2019). TGF-β has been associated with poor prognosis in patients with BC (de Kruijf et al. 2013). At the functional level, it has been shown recently that this factor plays a crucial role in induction of EMT and invasion in BC cells (Pang et al. 2016). Moreover, inhibition of TGF-β has been described to sensitize triple-negative breast carcinoma to chemotherapy (TNBC) (Bhola et al. 2013). EGF is expressed by several human tissues and promotes a variety of cell phenotypes in vivo and in vitro (Kajikawa et al. 1991). The paracrine signaling of epidermal growth factor (EGF) and its associated receptor EGFR has been shown to have an important role in driving BC progression and metastasis (Lo et al. 2007; Olsen et al. 2012). While it is known to promote cell proliferation (Wee and Wang 2017), EGF has also been described to have an important role in bone metastasis process (De Luca et al. 2008; Lu and Kang 2010). EGF has also been reported to promote EMT in BC (Kim et al. 2016). Therefore, overexpression of EGFR and its activation by EGF have been depicted to be predictive markers for poor clinical outcome in BC patients (Tischkowitz et al. 2007; Carey et al. 2010).

2.2

Impact of Hypoxia on Breast Carcinoma Behavior

Because of the weak vascular network associated with the exacerbated proliferation, solid tumors present often a very low oxygen level. Consequently, this generates hypoxia environment in the tumor (Semenza 2012) and particularly in breast carcinoma cells (Gilkes and Semenza 2013). In the context of breast cancer, it has been evaluated that partial pressure of oxygen is almost of 10 mm of mercury (Hg, range from 2.5 to 30 mmHg) compared to 65 mmHg in normal breast tissue. Transcriptomic studies on a large cohort of BC have shown the role of a family of transcription factors, HIF-1α and HIF-2α (HIF for hypoxia inducible factors), which are activated under hypoxia conditions, in the regulation of the expression of key genes encoding proteins involved in the various processes of tumor progression (The Cancer Genome Atlas Network 2012). Some of the first works have demonstrated

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that upregulation of HIF-1α was related to tumors and associated metastasis in human breast carcinoma and that this factor was a poor prognosis factor (Schindl et al. 2002; Zhong et al. 1999; Bos et al. 2003). Concerning the stroma matrix receptors which could be involved in metastasis process, a recent work has shown that the fibronectin receptor α5β1 receptor was overexpressed by activation of HIF-1α in hypoxic conditions and that this integrin heterodimer was responsible for BC metastasis to lymph nodes and lung (Ju et al. 2017). In other works, the level of HIF-1α expression has been associated with carcinogenesis process and an increase in proliferation rate of BC (Bos et al. 2001; Schwab et al. 2012). After demonstrating that hypoxia was able to induce vascular endothelial growth factor (VEGF) expression and to initiate angiogenesis (Shweiki et al. 1992), other works reported that HIF-1α expression in hypoxic conditions was responsible for this effect (Semenza 2000). Drug resistance has also been associated with HIF-1α expression in hypoxic conditions (Sullivan et al. 2008). Another work has demonstrated that HIF-1α expression was necessary for drug resistance in BC stem cells (Samanta et al. 2014). Xiang et al. have shown recently that HIF-1α was involved in the expression of TAZ, one of the matrix stroma sensors, and its recruitment into the nucleus to induced BC stem cell phenotype in hypoxic conditions (Xiang et al. 2014).

2.3

pH in Mammary Tissue

It has recently been well described how the acidic tumor microenvironment drives cancer progression (Boedtkjer and Pedersen 2020). The tightly regulated pH of cells is important to maintain a cellular homeostasis as chemical processes in the cytoplasm and in cell compartments which require an optimal pH (Andersen et al. 2014; White et al. 2017). The balance between the intracellular (pHi) and extracellular pH (pHe) is involved in regulating metabolic pathways via a fine-tuned balance between proton production and extrusion. The disruption of such balance in tumors is a consequence of the combination of high metabolic demands of cancer cells, in conjunction with poor perfusion and regional hypoxia. The low oxygen environment makes cells undergo a metabolic switch towards a more glycolytic phenotype, thus a higher production of protons (Warburg effect) (Gatenby and Gillies 2008). Excessive proton production induces intracellular acidification and apoptosis (Gottlieb et al. 1996; Damaghi et al. 2013). To compensate the high proton production, cells adapt by increasing the expression and activity of net acid extruders, keeping the intracellular pH normal or slightly alkaline. As a consequence, the microenvironment becomes acidic. A reversed pH gradient is associated with cancer progression, with acidic pHe stimulating invasion and migration (Damaghi et al. 2013; Webb et al. 2011; Hanahan and Weinberg 2011) and the slightly alkaline pHi promotes cell survival and increased proliferation (Damaghi et al. 2013; Flinck et al. 2018). This ability to sense pH changes in tumors is important for both normal stromal cells and cancer cells to survive. A study carried out by Hashim et al. has shown that BC cell

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lines MCF-7 and MDA-MB-231 showed a pHe as low as ~6.8 vs 7.4 in normal tissue, and a normal or slightly alkaline pHi, ~7.4–7.6 vs 7.2 in normal tissue (Hashim et al. 2011). The essential pH regulation in both normal tissue and tumors are maintained by plasma membrane transporters and enzymes, including Na+/H+ exchanger 1 (NHE1), Na+/HCO3
co-transporters, Na+ driven Cl
/HCO3
exchanger, the anion exchangers AE1 and AE2, monocarboxylate transporters (MCT1, MCT2, MCT3, and MCT4), and the V-ATPase (Andersen et al. 2014; Damaghi et al. 2013). Several of these transporters are involved in driving cancer proliferation, migration, and invasion (Boedtkjer and Pedersen 2020; Flinck et al. 2018; Andersen et al. 2016; Ma et al. 2019).

3 Dialogue Between Microenvironmental Elements and Ion Channels: Effect on Breast Cancer Hallmarks 3.1

Collagen Induces Breast Cancer Survival and Migration Through Potassium Channels

Although some studies have reported the effect of collagen type 1 or fibronectin on potassium and calcium channels in several cancers (Badaoui et al. 2018; Cherubini et al. 2005; Manoli et al. 2019; Toral et al. 2007), the relationship between matrix proteins and ion channels has been poorly studied in BC. Ouadid-Ahidouch’s team has demonstrated a role of a complex composed by Kv10.1 potassium channel, Orai1 channel, and SPCA2 (Golgi ATPase), in signal transduction induced by collagen 1 in BC cells’ survival. In non-invasive ER+ BC cell lines (MCF-7, T47-D), collagen 1, under free serum culture medium, promotes cell survival through the tyrosine kinase DDR1 receptor but not β1-integrin (Badaoui et al. 2018). Indeed, collagen 1, by activating DDR1, activates ERK1/2 that increases Kv10.1 and Orai1 expression and activity leading to an increase in the basal calcium entry independently of the reticular stores (store-independent calcium entry, SICE) that activates the ERK pathway that, in turn, promotes the expression of the oncogene c-Myc leading therefore to cell survival. Peretti et al. (2019) deeply demonstrated how collagen 1 favors the interaction of the complex Kv10.1/Orai1 and SPCA2. Collagen 1 increases the plasma membrane fraction of Kv10.1 and Orai1 channels and promotes their co-localization and interaction with SPCA2 in the lipid rafts. SPCA2 is indispensable to both Orai1 and Kv10.1 trafficking to plasma membrane in the presence of collagen 1. Silencing of SPCA2 induces Orai1 retention in the cytoplasmic compartment and in the Golgi for Kv10.1. Moreover, Kv10.1, Orai1, SPCA2, and DDR1 are highly expressed and co-localized in aggressive BC tissues, while in non-tumor samples, these proteins are less expressed at the plasma membrane and the expression of Kv10.1 is restricted to the Golgi (Peretti et al. 2019).

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Collagen 1 is also involved in BC aggressiveness. Collagen fiber alignment facilitates persistence by limiting cell protrusions, thus promoting cell migration and invasion (Riching et al. 2014), and redirect cell migration to move only in one direction (Ray et al. 2017). Basal-like BC MDA-MB-231 cells possess a high metastatic capacity and they also expressed Kv10.1 channel that regulates cell migration through two mechanisms: (1) by regulating calcium entry through Orai1 channels (Hammadi et al. 2012) and (2) by interacting with β1-integrin and focal adhesion kinase (Ouadid-Ahidouch et al. 2016). The extracellular matrix through fibronectin and collagen 1 also positively modulates Kv10.1-dependent cell migration. The MDA-MB-231 cell line adopts a more elongated morphology and increased migration rate when growing on double coating with fibronectin and collagen 1. Several studies have also shown that fibronectin is able to increase potassium Kv11.1 channel activity, which is part of the same subfamily as Kv10.1 in the neuroblastoma and colorectal cancers (Cherubini et al. 2005; Crociani et al. 2013). In BC, fibronectin could increase both the interaction and the co-localization of Kv10.1 with β1 integrin (unpublished data).

3.1.1

Stiffness, Mechanosensitive Ion Channels, and Breast Cancer

Malignant tumor extracellular matrix is often stiffer than the matrix surrounding adjacent non-malignant cells (Ingber 2008) and such pressures could stimulate mechanosensitive ion channels (Petho et al. 2019). Functional expression of Piezo channels has been described in BC cell lines (Li et al. 2015), and their relevance to BC has just been investigated recently. Piezo 1 is functional in MCF-7 BC cell line but not in MCF-10A normal mammary epithelial cell line. Pharmacological blockade of this channel reduced cellular motility of MCF-7 but not that of MCF-10A cells (Li et al. 2015). Moreover, BC patients with high Piezo1 mRNA levels showed a shorter overall survival when compared to those showing low Piezo1 expression levels (Li et al. 2015). Recently, in brain metastatic BC cell line MDA-MB-231BrM2, Valverde’s team has clearly reported that calcium influx via Piezo2 regulates cell migration by regulating the cytoskeleton organization through the RhoA-mDia pathway (Pardo-Pastor et al. 2018). Lou et al., by using the “Atlas database analysis,” identified a decreased Piezo2 expression in BC compared with normal control tissues (Lou et al. 2019). They also investigated the relation between Piezo2 expression level and the overall survival of patients, and they found that high expression of this channel is correlated to a favorable prognosis in BC. Moreover, the expression of Piezo2 is potentially targeted by five miRNAs and correlated with the downregulation of 109 genes enriched in Hedgehog signaling pathway, including regulated cell adhesion molecules downregulated by oncogenes (Lou et al. 2019). The mechanoreceptor TRPM7 has been shown to reduce the cytoskeletal tension through Myosin II activity in MDA-MB-231 cell line (Kuipers et al. 2018; Guilbert et al. 2013). Silencing of TRPM7 or its pharmacological inhibition, by waixenicin A, increased cytoskeletal tension likely through reducing SOX4 expression. Moreover,

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the increase of matrix stiffness (in a collagen coating model) decreased both the expression of TRPM7 and SOX4. They also found that both the mRNA expression of SOX4 and TRPM7 are positively correlated with primary breast tumor samples. The authors suggested SOX4 as a downstream transcriptional target of TRPM7 signaling in mesenchymal-type BC cell lines (Kuipers et al. 2018). To our knowledge, only one study has reported on the involvement of voltageactivated T-type calcium channels in MCF-7 BC cell proliferation (Basson et al. 2015) in relation with matrix density. The increase of extracellular pressure up to 40 mmHg activates T-type calcium channel (Cav3.3) leading to calcium influx and activation of PKC-b, which in turn activates NF-kB (Basson et al. 2015).

3.2

3.2.1

EGF and TGF-β Modulate EMT, Invasion, Migration, and Proliferation Through Potassium, Calcium, and Sodium Channels EGF

Abnormal expression and activity of EGF and EGFR promote EMT in cancer cells through ERK1/2 and PI3K/Akt pathways, which are involved in proliferation, metastasis, and invasion (Thiery 2002; Ellerbroek et al. 2001; Grunert et al. 2003). It has previously been shown that EGF, EGFR, and the phosphorylation of its tyrosine residues modulate the activity of ion channels (Levitan 1994), including potassium (Bowlby et al. 1997; Zhang et al. 2011; Peppelenbosch et al. 1991), calcium (Peppelenbosch et al. 1991, 1992), chloride (Jeulin et al. 2008), and voltagegated sodium channels (Fraser et al. 1638). Tyrosine kinases and phosphatases regulate the function ion channels activities that are involved in cancer proliferation, migration, invasion, and apoptosis (Davis et al. 2001; Azimi and Monteith 2016). These pathways are associated with EMT, induced by EGF and EGFR. Furthermore, several studies have identified that EMT induces changes in the expression and activity of different plasma membrane ion channels including potassium, calcium, and sodium, which will in turn regulate tumor invasion (Azimi and Monteith 2016). The calcium-activated potassium channel KCa3.1 (SK4) has been studied in several types of cancer including BC (Zhang et al. 2016). A blockage of SK4 has shown to inhibit proliferation and promote apoptosis in MDA-MB-231 cells. Furthermore, it has been shown that MDA-MB-231 and MDA-MB-468 cell lines can undergo EMT mediated by EGF/basis fibroblast growth factor (bFGF), whereas MCF-7 and T47D cells are not able to undergo EMT at all (Zhang et al. 2016). In addition, in MDA-MB-231 cells (harboring the most significant mesenchymal phenotype compared to other cell lines) the mRNA expression of SK4 is upregulated, and the decrease of SK4 channel expression downregulates the expression of the mesenchymal markers Vimentin and SNAIL1. The authors concluded that the expression of SK4 is associated with EGF/bFGF-induced EMT and that it might drive both the EMT and migration process in TNBC cells (Zhang et al. 2016).

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It is well studied that remodeling of calcium permeable channels, their expression, and Ca2+ signaling are linked to EMT, and that they promote the expression of several proteins associated with cells transforming to a more mesenchymal phenotype (Azimi and Monteith 2016). The Monteith’s team has deeply investigated the role of Ca2+ during the EMT process in BC cells (Davis et al. 2012, 2013, 2014). They have observed that treatment with EGF increases EMT markers as Twist, SNAIL1, and Vimentin in MDA-MB-468 cells and have identified specific channels involved in Ca2+ remodeling as regulators of EMT induced by EGF (Davis et al. 2012, 2014). TRPM7 is involved in EGF-mediated EMT by enhancing Vimentin protein expression. Furthermore, TRPM7 silencing results in a reduction of the EGF induced STAT-3 phosphorylation, but does not alter the cytosolic Ca2+ response induced by EGF (Davis et al. 2014). In another study, the same authors found not only a higher expression of EMT related markers, but also an increased expression of Orai1 and Ca2+ entry. In this study, they found that EGF-induced EMT in MDA-MB-468 cells is associated with reduced agonist-stimulated and storeoperated Ca2+ influx. It is known that both Orai1 and TRPC1 maintain the constitutive Ca2+ influx, but here it has been shown that only Orai1, and not TRPC1, is associated with EGF-mediated EMT (Davis et al. 2012). Orai1 silencing inhibited non-stimulated Ca2+ influx, agonist-stimulated, and store-operated Ca2+ influx, whereas the silencing of TRPC1 only inhibited non-stimulated Ca2+ influx, but in a manner dependent on Orai1 (Davis et al. 2012). This suggests that the altered activity of Orai1 and TRPC1 plays a role in EGF-mediated EMT. In addition, TRPC1 silencing has been shown to be associated with a significant reduction in ERK1/2 signaling function, showing that TRPC1 is involved in proliferation. Ouadid-Ahidouch’s team has also reported the involvement of TRPC1 in MCF-7 cell proliferation induced both by EGF and the activation of the calcium sensing receptor (CaSR). Indeed, CaSR stimulation by extracellular Ca2+ ([Ca2+]o) (1.4–5.0 mM) increases TRPC1 expression, via ERK1/2 activation, and calcium influx leading to cell proliferation (El Hiani et al. 2009a). Additionally, cell proliferation is also obtained through a subsequent EGFR transactivation consecutive to CaSR activation in these cells (El Hiani et al. 2009b). In fact, both inhibitors of EGFR kinase (AG1478) and MMP (GM6001) reduce ERK1/2 activation, TRPC1 overexpression, and cell proliferation induced by [Ca2+]o. These data indicate the role of the CaSR-EGFR and ERK axis in response to extracellular calcium concentration in tumor environment of BC (Kadio et al. 2016). Davis et al. have found that EMT in BC is also associated with the altered gene expression of specific endoplasmic reticular (ER) calcium channels and pumps (Davis et al. 2013). The expression of the ER channels inositol 1,4,5-triphosphate receptor IP3R1, IP3R3, and ryanodine receptor RYR2 has been shown to be upregulated in EGF-treated MDA-MB-468 cells when compared to the non-treated cells. Under the same conditions, the ER pump SERCA2 is significantly upregulated, whereas the SERCA3 is downregulated. This suggests that EGF-induced EMT in BC induces changes in the expression of ER channels and pumps and thereby storage and Ca2+ signaling (Davis et al. 2013).

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Voltage-gated sodium (Nav) channels are widely expressed in metastatic cells of different types of cancer, including BC (Roger et al. 2015; Onkal and Djamgoz 2009; Fraser et al. 2005). Nav1.5 is upregulated in BC, which promotes invasion and metastasis phenotype (Roger et al. 2015; Gonzalez-Gonzalez et al. 2019a; Brackenbury 2012). Recently, it has been shown that Nav1.5 channels are involved in EGF-induced EMT. EGF induces both the expression and activity of Nav1.5 in MDA-MB-231 cells (Gonzalez-Gonzalez et al. 2019a). Furthermore, the mobility of MDA-MB-231 cells is increased when induced with EGF through the functional expression of Nav1.5. It can be suggested that Nav1.5 channels are not acting alone during cell migration induced with EGF. As the activation of Nav1.5 depolarizes the plasma membrane, other ion transporters could be activated by this environmental modification such as NHE or chloride channels (Gonzalez-Gonzalez et al. 2019a). In addition, the influx of Na+ through Nav1.5 channels stimulates the activity of NHE1, resulting in a higher proton extrusion, acidifying the extracellular environment, and thus activating metalloproteinases, which can promote the invasive and migratory capacity of cells (Gonzalez-Gonzalez et al. 2019a; Brisson et al. 2011; Gillet et al. 2009). Disrupting the homeostasis of ions as Na+, Ca2+, and H+ could potentially activate protein kinases and downstream pathways that affect migration, invasion, or proliferation (Gonzalez-Gonzalez et al. 2019a). Rho family GTPase, Rac1 has been shown to be involved in migration by regulating cytoskeletal rearrangement and lamellipodia formation (Yang et al. 2019). Nav1.5-dependent plasma membrane depolarization leads to Rac1 co-localization with phosphatidylserine and thereby activation. The activation of Rac1 in MDA-MB-231 cells results in lamellipodial protrusion formation, migration, and thereby a more invasive phenotype (Yang et al. 2019). The sodium content has shown to be higher in mammary adenocarcinomas than in normal lactating mammary epithelium (Amara et al. 2016; Sparks et al. 1983), even though it is not clear if tumor functions are correlated with the extra- or intracellular sodium concentration (Amara et al. 2016). Recently, it has been shown that treatment with NaCl and pro-inflammatory interleukin 17 (IL-17) has a synergistic inflammatory effect on the growth in BC cell lines. This treatment also enhanced the production of reactive nitrogen and oxygen (RNS/ROS) species, which correlated with an upregulation of the epithelial sodium channel (ENaC) expression level in various BC (Amara et al. 2016; Blaug et al. 2001; Boyd and Naray-FejesToth 2007). Treatment with NaCl, IL-17, and knockdown of ENaC reduce RNS/ROS species production. Furthermore, the same treatment enhances expression and phosphorylation of ERK1/2 in MDA-MB-231 cells. These data suggest that ENaC plays a role in proliferation through downstream ERK1/2 signaling and in the inflammatory process in BC (Amara et al. 2016).

3.2.2

TGF-β

Transforming growth factor beta (TGF-β) is another EMT inducer via the canonical or the non-canonical pathways in epithelial cells (Dumont and Arteaga 2000;

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Muraoka et al. 2002). Cell calcium entry, especially upon store depletion, is also involved in TGF-β-induced EMT by promoting cellular migration and potentially leading to metastasis. TGF-β treatment is known to increases migration, calpain activity, expression of EMT markers (Vimentin, N-cadherin) and decreases expression of epithelial markers (E-cadherin) in NMuMG and MDA-MB-231 cells (Schaar et al. 2016). TGF-β-treatment increases store-mediated Ca2+ entry, via TRPC1 / STIM1 that activates calpain leading to migration, a loss of E-cadherin and MMP activation. Silencing of TRPC1 or STIM1, or using pharmacological inhibition of SOCE (SKF-96365) decreased TGF-β induced Ca2+ current, and inhibited calpain activation and cell migration (Schaar et al. 2016). Moreover, the overexpression of TRPC1 increases Ca2+ entry and promotes TGF-β-mediated cell migration. TGF-β affects more the activity of TRPC 1/STIM1 but neither the expression of STIM1 nor that of Orai1. TGF-β also suppresses cell proliferation of both MDA-MB-231 and MCF-7 cells by inducing cell cycle arrest at the G0/G1 phase by accumulating p21 and reducing cyclin E expression (Cheng et al. 2016). These effects are calcium dependent since they are altered by EGTA or by pharmacological inhibition of SOCE. Treatment of MDA-MB-231 cells with TGF-β decreases both STIM1 expression and thapsigargin-induced calcium entry. Moreover, stably STIM1 overexpressing in MDA-MB-231 cells suppresses the TGF-β-induced effects. TGF-β increases the expression of the transcriptional inhibitory factor of STIM1 (Wilms’ tumor suppressor 1, WT1). Silencing of WT1 restores the expression of STIM1 in the presence of TGF-β. Moreover, both TGF-β and thapsigargin increased ERK1/2 phosphorylation and pharmacological inhibition of SOCE reduces the TGF-β-induced ERK phosphorylation (Cheng et al. 2016). Hu et al. have found that TGF-β-induced EMT through downregulating of Oct4 that upregulates STIM1 and Orai1 expression leading to an increase in SOC entry (Hu et al. 2011). Recently, Figiel and co-workers have proposed a new mechanism involving three partners Zeb1 (EMT transcription factor), SK3 channel, and calcium influx, probably through SOC channels, in the regulation of prostate cancer cell migration stimulated by TGF-β (Figiel et al. 2019). They showed that TGF-β increases the expression of Zeb1 and SK3 channel, which lead to calcium influx and migration. The expression of Zeb1 by TGF-β is dependent on calcium influx and Zeb1 controls the transcriptional activity of the SK3 channel gene. Moreover, both linoleic acid and eicosapentaenoic acid inhibit the migration induced by TGF-β likely by disrupting lipid raft SK3-Ca2+ channels complexes.

3.2.3

ATP, via Purinergic Receptors, Regulates Proliferation, Invasion, Migration, and EMT

ATP is a nucleotide firstly known to provide energy to different biological processes in living cells. In physiological conditions, intracellular ATP rate (5–10 mM) is relatively high when compared to extracellular medium (10–100 nM) (Gilbert et al. 2019). However, this balance is totally changed in case of cancer. Indeed, real-time extracellular ATP concentration monitoring showed that it could reach hundreds of

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millimolar in the tumor microenvironment (Falzoni et al. 2013; Pellegatti et al. 2008). Cell damage as well as non-lytic pathways has been reported to explain the high extracellular ATP rate. Among these pathways, vesicular exocytosis and ATP efflux through ATP release channels and nucleotide transporters have been reported (Yegutkin 2008). Otherwise, the involved cells are both infiltrating inflammatory cells and tumor cells in response to inflammation, hypoxia, or to some therapies. Extracellular ATP is sensed at P2 purinergic receptors. Burnstock and Kennedy (Kennedy and Burnstock 1985) have proposed the distinction between P2X and P2Y receptors based on pharmacological criteria. Cloning and transduction mechanisms led to the nomenclature of P2X ionotropic ligand-gated ion channel receptors and P2Y metabotropic G protein-coupled receptors (Burnstock 1996). Seven subunits (named P2X1-7) assemble as homo- or hetero-trimers to form the channel of P2X receptors. ATP is the physiologic agonist of these receptors whose activation results in the alteration of cytosolic calcium concentration. On the other hand, there are eight isoforms of P2Y receptors named P2Y1 & 2; P2Y4 & 6; and P2Y11-14. They differ from each other by the nature of their agonists and by the signal transduction pathways that their activation triggers. Indeed, P2Y1 & 2; P2Y4 & 6 are coupled to a Gq protein that, in turn, activate a phospholipase Cβ, while P2Y12-14 is coupled to a Gi protein that inhibits the adenylyl cyclase. Among the Gq coupled subfamily, P2Y2 is the only ATP-active isoform. It is also considered UTP equally active. ADP, UTP, and UDP are respectively the preferred ligands of the P2Y1, P2Y4, and P2Y6 isoforms. Among the Gi coupled subfamily, ADP is the preferred ligand of P2Y12&13 while P2Y14 is activated by sugar nucleotides such as UDP-glucose and UDP-galactose. P2Y11 is a special case in that it is coupled to both a Gq and a Gs protein, thus when activated by ATP it results in an increase of intracellular calcium and cAMP concentrations (Di Virgilio 2012). The effect of ATP depends on its concentration in the extracellular medium and the panel of P2 receptors expressed in tumor and/or stromal cells. In MCF-7 BC cells, all P2Y receptors are expressed but not all the P2X isoforms. Indeed, P2X1 and P2X3 transcripts are not expressed. Moreover, the transcript profile shows a relative strong expression of P2X4 when compared to P2X2 & 5. P2X6 & 7 are not significantly expressed. When exposed to 30 μM [ATP]o, MCF-7 shows a 50 pA inward current, which seems to be a P2X-like current. Extracellular ATP treatment does not significantly affect cell death or proliferation. However, cell migration is increased. As assessed by specific siRNA and the use of different inhibitors, ATP-induced migration results in the activation of the nucleotide on P2Y2 receptor leading to an increase in [Ca2+]cyt and subsequent activation of MEK pathway (Chadet et al. 2014). Highly invasive MDA-MB-435s BC cell line expresses P2X4, P2X5, P2X6, and P2X7. However, P2X7 isoform is by far the most expressed and seems to be the only active form. Furthermore, in MDA-MB-435 cells, millimolar concentrations of ATP activate an inward current, leading to an increase in [Ca2+]cyt. P2X7R activation regulates MDA-MB-435s apoptosis, migration, and invasiveness. Indeed, ATP concentrations over 3 mM result in significant cell death that is inhibited both by KN62 and A740003 P2X7R inhibitors. Additionally, millimolar ATP exposition

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer. . .

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induces elongation of “Neurite-like” MDA-MB-435s prolongations, which are hallmarks of a migratory cell profile. The ATP induces regulation cell migration through activation of SK3 potassium channels by the calcium-induced influx. P2X7R activation is also involved in MDA-MB-435s cell invasiveness in a dose-dependent manner both in vitro and in vivo through regulating cathepsin B active forms (Jelassi et al. 2011). Recently, Maffey et al. (2017) reported that mesenchymal stem cells from tumor microenvironment promote BC stem cell proliferation, and metastasis through purinergic signaling. Such processes take place through exosomes and microvesicles that increase cytosolic calcium concentration. A significant increase in cell responsiveness is observed when exogenous ATP is added to the cells. In these cells, ATP acts through P2X ionotropic receptors as assessed by P2X inhibition experiments. Indeed, P2X7 inhibition by A438079 leads to a significant decrease in cell metabolism activity and cell growth. Moreover, ATP depletion in the extracellular medium leads to a significant decrease in BC cell invasiveness. ATP action is modulated by other factors present in tumor microenvironment such as EGF (Davis et al. 2011). Davis et al. have shown that EGF induces changes in response to ATP in MDA-MB-468 BC cells. Indeed, in the presence of ATP, EGF induces a significant change in the calcium profile and expression of EMT markers such as Vimentin. Analysis of purinergic receptors has shown that P2X5 isoform is upregulated (4.6-folds) in the presence of EGF. Upregulation of this isoform is confirmed (13-folds) in mesenchymal-like BC cells when compared to epitheliallike cells. Moreover, P2X5 knockdown leads to a decrease in Vimentin which remains significant despite its weak expression (Davis et al. 2011). A synthetic presentation of the different actors previously described is reported in Table 1 and in Figs. 1 and 2.

3.3 3.3.1

Involvement of Ion Channels in the Adaptation of Cells to Live in: Hypoxic Conditions

As depicted previously, hypoxia is an important feature of the tumor microenvironment, which promotes, e.g., BC adaptation, resistance, and aggressiveness. In addition, hypoxia regulates different parameters of the tumor microenvironment like angiogenesis, extracellular matrix composition, or stromal cells’ functions. However, underlying mechanisms are not yet clearly defined. Among the numerous tracks currently explored, ion channels could be good candidates due to their involvement in multiple tumor processes and their membrane localization. Indeed, a large information panel is already available regarding their role in the response to oxygen variations in the cardiovascular and neuronal system but few elements are evaluated in tumor context.

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Table 1 Ion channels involved in the dialogue with microenvironment: links to matrix, EGF, TGF-β, and ATP Channel family Potassium channels

Orai and TRP

Type/ name Kv10.1

Involved in cancer progression by Survival induced by collagen 1

Kv10.1

Migration induced by fibronectin and collagen 1 EMT induced by EGF/bFGF EMT induced by EGF

SK4, KCa3.1 Orai1 & TRPC1 TRPC1 TRPM7

TRPC1

PIEZO

Sodium channels

MDA-MB-468 cell proliferation Maintains BC mesenchymal phenotype/response to matrix rigidity TGF-β-induced EMT

Orai1 and STIM1

TGF-β-induced EMT

TRPM7

EGF-induced EMT

PIEZO1

Cellular motility

PIEZO2

Migration

Nav1.5

Increased migration induced by EGF

Nav1.5

Increased migration

Signaling pathway DDR1, ERK phosphorylation, increased expression and membrane fraction of Kv10.1 and Orai1, increased co-localization of Kv10.1 and Orai1 through SPCA2, increased SICE, increased [Ca2+]i, increased c-Myc expression and cell survival Increasing co-localization and interaction between Kv10.1 and β1-integrin Increased Vimentin and snail mRNA expression Reduced non-stimulated and agonist-stimulated, Ca2+ entry through Orai1 and TRPC1 ERK1/2 phosphorylation, cell proliferation Increased cytoskeletal tension through reducing SOX4 expression Increased store-mediated Ca2+ entry, activation of calpain, loss of E-cadherin, and MMP activation Inhibition of Oct4 expression that upregulates STIM1 and Orai1 expression leading to increase SOC Increased Vimentin expression along with STAT3 activation Silencing of PIEZO 1 reduces cell motility Regulating the cytoskeleton organization through the RhoA-mDia pathway EGF increased Nav1.5 expression Depolarization of the resting Vm (Na+-dependent) that increases Rac activation

References Badaoui et al. (2018), Peretti et al. (2019)

Unpublished Personal data Zhang et al. (2016) Davis et al. (2012) Davis et al. (2012) Kuipers et al. (2018)

Schaar et al. (2016)

Hu et al. (2011)

Davis et al. (2014) Li et al. (2015) Pardo-Pastor et al. (2018) GonzalezGonzalez et al. (2019b) Yang et al. (2019) (continued)

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Table 1 (continued) Channel family Others STIM

Type/ name

Involved in cancer progression by

STIM1

TGF-β inhibiting cell proliferation

ER intracellular calcium transporters

IP3R RYR SERCA

EMT induced by EGF

P2X ionotropic ligand-gated ion channel

P2X7

Growth Proliferation Mammosphere formation Spheroid size Invasion EMT

P2X5

Signaling pathway

References

Increased expression of Wilms’ tumor suppressor 1 (WT1), reduction of STIM1 expression, reduction of SOCE, reduction or ERK phosphorylation, increased P21expression and reduction of cyclin E expression, cell cycle arrest in G0-G1 phase A high increase of RYR2 expression A slight increase in IP3R1 and IP3R3 and SERCA2 expression A decrease of expression of SERCA3 Stimulate invasiveness through P2X7, enhancing Ca2+ and Na+ influx and K+ efflux

Cheng et al. (2016)

Potentiate the EGF-induced Vimentin protein expression and reduced E-cadherin expression

Davis et al. (2011)

Davis et al. (2013)

Maffey et al. (2017)

Some reports described the involvement of Ca2+ signaling in response of BC cells to hypoxia. It has been previously described that hypoxia could induce EMT (Gonzalez and Medici 2014). In fact, Davis et al. demonstrated that Ca2+ chelation reduces the hypoxia-induced EMT in MDA-MB-468 cells (Davis et al. 2014). By deciphering the putative molecular support, they analyzed the role of TRPM7 channel but they could not demonstrate that this channel is involved in the modulation of the [Ca2+]cyt even though it participates to the regulation of EMT markers. Works from the Monteith’s lab brought information about other calcium channels involved in the response of BC cells to hypoxia. In fact, TRPC1 seems to be involved in hypoxia-mediated events (Azimi et al. 2017). More precisely, hypoxia increases TRPC1 mRNA expression that regulates SNAIL and Claudin 4 expression and participates to the regulation of EGFR and STAT3 phosphorylation. In addition, TRPC1 is also involved in autophagy process through the EGFR pathway. In a recent study, the same group demonstrated that BC molecular subtypes present different calcium channel expression profile. Accurately, they showed that Orai3 channel is more specific to luminal cell type compared to Orai1, which is mostly

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H. Ouadid-Ahidouch et al.

A

B FibronecƟn Collagen

Collagen

b -integrin

P

Kv10.1

Orai1

Kv10.1

Orai1

SPCA2

FAK

Ca2+

P-ERK C-myc

MigraƟon

Survival

ProliferaƟon

Fig. 1 Schematic illustration of ion channels, involved in collagen 1-induced effects in breast cancer. (a) Effect of collagen and fibronectin on cell migration in the highly metastatic MDA-MB231 breast cancer cell line. (b) Effect of collagen on the survival and proliferation in the non-invasive MCF-7 breast cancer cells

expressed and active in the basal cell type (Azimi et al. 2019). They further analyzed Orai3’s involvements in hypoxia and they demonstrated that: (1) Orai3’s expression is increased in hypoxia through HIF-1α pathway; (2) this channel is not involved in the regulation of EMT markers’ expression; (3) Orai3 regulates EGFR autophosphorylation without any effect on migration; (4) it participates to the hypoxia regulation of migration and to the inflammatory/immune response gene profile. In a similar manner, Liu and collaborators demonstrated that Orai1 is also involved in the response to hypoxia (Liu et al. 2018). More precisely, they showed that Orai1 is involved in a Notch1 signaling pathway associated with a storeoperated Ca2+ entry and NFAT4 to participate to the aggressiveness of TNBC cells. Intracellular Ca2+ transporters could also be involved in the TNBC phenotype. Indeed, it has been shown that mitochondrial calcium uniporter (MCU) could regulate the HIF-1α pathway, and subsequent expressed genes, as well as the ROS production, participating to the metastatic processes (Tosatto et al. 2016). The results of this study suggest that MCU could be an actor in the response to hypoxia. It is now clearly established that hypoxia also promotes resistance to therapy (Yeldag et al. 2018). In this context, Lu et al. demonstrated that [Ca2+]cyt concentration is increased by carboplatin treatment in a TNBC model (Lu et al. 2017). More precisely, glutathione S-transferase omega 1 (GSTO1), which is regulated by

TRPC1

↑RYR2 ↑SERCA2 ↓SERCA3

↓ Non-stimulated Ca2+ influx ↓ Agonist-stimulated Ca2+ influx ↓ Store-operated Ca2+ entry

Migration

EMT

KCa3.1

ENaC(γ)

↑ERK phosphorylation Activation of RNS/ROS

Rac1 activation through Vm depolarization

NaV1.5

Proliferation

↑ Vimentin ↑ Snail

EGFR

↑Vimentin STAT3 activation

TRPM7

NaCl IL-17

Proteases

Migration

EMT

STIM1

Proliferation

↑Wilms tumor suppressor ↓Stim expression ↓SOCE ↓ERK activation Cell cycle arrest in G0-G1

Ca2+

TRPC1

Activation of Calpain Loss of E-Cadherin Activation of Oct4

TGF-βR

Stimulation with TGF-β

Fig. 2 Ion transporters regulation by EGF and TGF-B and conferring breast cancer invasion, migration, and proliferation. Black arrows indicate the sequence of events for each channel type. See text for details. Green color indicates SERCA2 and 3 and STIM1 that are located in the ER

Invasion

RYR2 SERCA2/3

Intracellular space

Extracellular space

ORAI1

Stimulation with EGF

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer. . . 19

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H. Ouadid-Ahidouch et al.

HIF-1α and HIF-2α and whose expression is increased by carboplatin, interacts with RyR1 and promotes Ca2+ release from the internal store. The Ca2+ raise activates the PYK2-SRC-STAT3 pathway promoting the BC stem cell phenotype and induces consequently chemoresistance. In a similar way, it has been shown that TRPC5, which is overexpressed in Adriamycin-treated MCF-7 cells, participates to the VEGF secretion regulation through a HIF-1α pathway suggesting an involvement of this channel in the cell response to hypoxia (Zhu et al. 2015). Regarding the potassium channels, some studies also described their involvement in BC properties in response to hypoxia. Firstly, Mu and collaborators highlighted the amplification of KCNN9 potassium channel gene (Mu et al. 2003). They then described an improvement of the hypoxia resistance of the cells by using in vitro and in vivo models, which is not affected by the p53 status. A second subclass of the potassium channel family has been described in the hypoxia context: the voltagegated potassium channels. Eag1 channel, also named Kv10.1, which was among the first Kv channels highlighted in oncogenic process, has been initially involved in the hypoxia homeostasis (Downie et al. 2008). By using Eag1-expressing CHO cells, authors demonstrated that Eag1 channel participates to the HIF-1α expression’s regulation and thereby VEGF secretion and vascularization. According to the involvement of Eag1 in the proliferation and in the motility of different BC cell models (Ouadid-Ahidouch et al. 2016), Lai et al. analyzed the putative expression relationship of this channel and HIF-1α in human samples (Lai et al. 2014). Through their observational study, they demonstrated that the co-expression of the 2 actors is positively correlated with node status, tumor stage, and tumor size suggesting an interest to use this association like a potential biomarker. In addition, recent data obtained in our laboratory demonstrated that Eag1 channel could participate to the regulation of MDA-MB-231 cells’ migration in hypoxia condition (unpublished data). To the best of our knowledge, only another study described the role of Kv3.1 and Kv3.4 in the control of BC cell migration and invasion (Song et al. 2018). Little information about other players of the BC cell’s transportome is available. However, it has been described an increase in aquaporin 1 in HIF-1α expression in BC tissues (Yin et al. 2008). In addition, P2X7 has been involved in the regulation of tumor cell invasion, in hypoxia context, through a signaling pathway involving RAGE, Akt, ERK1/2, NF-κB translocation, and MMP-2, -9 expression (Tafani et al. 2011). Despite the fact that NaV channels are already well described in the promotion of the BC cell aggressiveness and in the response to oxygen variations in myocytes and carotid bodies, there is no study about their involvement in hypoxic breast tumors. Ion channels and transportome actors, involved in the answer to hypoxia, are classified in Table 2 and Fig. 3. Finally, there is a very closed link between pH modification in tumor microenvironment and hypoxia. In this way, it is clear that acid-sensing ion channels and H+ transporters could be modulated in this context but the concept has still not been demonstrated.

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Table 2 Ion channels involved in the relation between hypoxia and pH and breast cancer cells Involved in Channel cancer family Type/name progression by Signaling pathway Relation with pH homeostasis in breast cancer tumor Voltage gated ion channels by: Sodium NaV1.5 Invasion Invasiveness through NHE1, Migration enhancing H+ efflux ! activating ECM degradation by cathepsin invasion and migration through Src/Y421 activation Proton Hv1 Invasion Invasion and migration ! reguMigration lating pHe ! secretion of cathepsin matrix metalloproteinase ! ECM degradation Other CalciumCLCA2 Proliferation Proliferation and apoptosis activated Apoptosis induced by p53 in response to chloride DNA damage channel Acid-sens- ASIC1 Proliferation Through ROS-AKT-NF-κB, ing ion Invasion ERK1/2, and Ca2+ channels Migration Relation with hypoxia in breast cancer tumor Calcium channels TRPC1 EMT Regulation of gene expression and of EGFR and STAT3 phosphorylation TRPC5 VEGF secretion Through HIF-1α pathway Orai3

Hypoxia response

Orai1

Migration Invasion Angiogenesis Aggressiveness

MCU RyR1

BCSC promotion Chemoresistance

References

Brisson et al. (2011, 2013), Gillet et al. (2009)

Wang et al. (2011, 2012)

Walia et al. (2009)

Gupta et al. (2014, 2016)

Azimi et al. (2017) Zhu et al. (2015) Azimi et al. (2019)

Regulation of EGFR autophosphorylation and participation to the control of migration and inflammatory/ immune gene profile Through Notch1/Orai1/SOCE/ NFAT4

Liu et al. (2018)

Through HIF-1α pathway and subsequent genes’ regulation Through GSTO1/RyR1/PYK2/ Src/STAT3

Tosatto et al. (2016) Lu et al. (2017) (continued)

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Table 2 (continued) Channel family Potassium channels

Type/name

Involved in cancer progression by

TASK-3 (KCNK9)

Hypoxia resistance

Eag1

Kv3.1/ Kv3.4

Migration Invasion

Signaling pathway

References

Genetic amplification promotes the resistance to drastic environment like hypoxia Co-expression with HIF-1α correlates with tumor size, node status, and tumor stage Increased expression in hypoxia

Mu et al. (2003) Lai et al. (2014) Song et al. (2018)

Other Aquaporin 1 P2X7

3.3.2

Invasion

Co-expression with HIF-1α in breast cancer tissues In association with RAGE and through a Akt/Erk1/2/NF-κB translocation

Yin et al. (2008) Tafani et al. (2011)

Acidic Conditions

The major regulators of pH in tumor cells are the transporters and carbonic anhydrases involved in the extrusion of H+ excess to maintain the alkaline pHi. Whereas these transporters have often been reported to be important in tumor progression, the roles of pH sensing ion channels are less described. Here, we describe the pH sensing ion channels, mediated primarily through their expression at the cell surface in BC. A synthetic presentation is available in Table 2 and in Fig. 4. A type of ion channels, being voltage independent but affected by pH, is the acidsensing ion channels (ASICs), where eight subunits encoded by five genes have been identified. ASICs are H+ cation-gated channels and are activated by extracellular acid. Some types (ASIC1) are both Na+ and Ca2+ permeable where other types are only Na+ permeable (Damaghi et al. 2013). ASICs are mainly expressed in the central and peripheral nervous system and belong to the degenerin/epithelial sodium channel (DEG/ENaC) superfamily. Despite being expressed in the nervous system, ASICs have shown to be expressed in glioma cells and BC (Berdiev et al. 2003; Gupta et al. 2016). As ASICs have been reported to play an important role in acidosis-associated physiological and pathophysiological conditions (Wu et al. 2017), they may be involved in cancer progression, due to the acidic extracellular environment. ASIC1 is highly expressed in malignant BC tissue, compared to normal breast tissue, and genetic alterations of ASIC1 expression correlate with the overall survival of patients (Gupta et al. 2016). Furthermore, downregulation and pharmacological inhibition of ASIC1, with amiloride or psalmotoxin, suppressed tumor growth in vitro and in vivo. In vivo studies have shown that ASIC1 also leads

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer. . .

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P2X7 Aggressiveness and metastatic potential (e.g. invasion, EMT, survival)

TRPC5

Kv10.1

+ Signaling pathways (e.g. HIF1α, ERK, Akt, Notch, EGFR…)

TRPC1

TASK-3

RYR1

ORAI3 MCU

Kv3.1/3.4

ORAI1

Fig. 3 Schematic representation of the different ion channels described in hypoxia context of breast cancer. Membrane or intracellular Ca2+ and K+ transporters are modulated by hypoxia or modulate hypoxia signaling to promote aggressiveness/metastatic potential of breast cancer cells. Function and expression modulation of the channels are involved in signaling pathways promoting angiogenesis, survival, chemoresistance, invasion, migration, and EMT. Integral descriptions are included in the main text

to metastatic activity for lung tumor nodules, compared to the control. Together, these studies show that ASIC1 is important for BC growth, invasion, and metastasis. ASIC1 is expressed in some BC cell lines (MCF-7 and LM-4142), and acidification of breast cancer cells (pHe 6.6) leads to a high production of reactive oxygen species (ROS) levels (Gupta et al. 2014, 2016). Indeed, ASIC1 activation regulates proliferation, invasiveness, migration, apoptosis, and angiogenesis through ROS-AKTNF-κB pathway (Gupta et al. 2014, 2016). Furthermore, the inhibition or silencing of ASIC1 suppressed acidosis-induced activation of ERK1/2, AKT, and NF-κB (Gupta et al. 2016). These findings show that ASIC1 is required for ROS production in BC cells, and ROS is a central molecule in regulating downstream pathways in an acidic environment. ASICs are also responsible for Ca2+ entry, and activation of ASIC1 leads to a rise in [Ca2+]cyt in neurons (Gupta et al. 2016). Ca2+ is involved in cancer as it regulates invasion and migration signaling (Davis et al. 2012; Gupta et al. 2016; Monteith et al. 2017). ROS production has been shown to be decreased by calcium chelators, indicating that ASIC1 regulation of Ca2+ is important for ROS

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H. Ouadid-Ahidouch et al.

Acidic pH (~6.8) ECM degradation (Migration/Invasion)

Extracellular space

NaV1.5

NHE1

ASIC1

Cathepsin

Hv1

hCLCA2

Proteases

Intracellular space

DNA Damage Src activation

ROS/AKT/NF-κB ERK1/2

p53

Downstream targets

Migration

Invasion

Proliferation

Apoptosis

Fig. 4 Schematic illustration of ion channels, involved in pH regulation and sensing in breast cancer

generation under acidic conditions (Gupta et al. 2016). Taken together, these suggest that there is a crosslink between ASICs and Ca2+ influx and that ASICs can be involved in the regulation of Ca2+ signaling pathway. Another type of ion channel involved in pH regulation is the voltage gated proton channel Hv1, which is highly selective for H+, and no other cations. Hv1 is specifically expressed in highly metastatic human BC and the downregulation of Hv1 inhibits the metastatic by reducing invasion, migration, and H+ secretion (Wang et al. 2011). As previously described, acidic pHe promotes degradation of ECM, which increases the secretion and activation of proteases. The proteases need the low pHe to have optimal activity. Among many proteases, the cathepsins and the MMPs are essentially involved in degradation and remodeling of ECM (Wang et al. 2011). The secretion and activation of some proteases are pH-regulated and MMP-9 showed reduced activity in MDA-MB-231 cells with suppressed Hv1. This indicates that secretion of protons by Hv1, ensuring the acidic pHe, promotes invasion and metastasis by activating and secreting proteases, such as MMP-9 (Wang et al. 2011). In addition, a knockdown of Hv1 in MDA-MB-231 cells decreases proliferation, invasiveness but also inhibited pH recovery and proton secretion, affecting cell capacity of acidifying pHe (Wang et al. 2012). Furthermore, the high expression of Hv1 in tumors from patients is correlated with tumor progression and patients were more likely to have a shorter overall survival. High expression of Hv1 is associated with a poor prognosis, thus making Hv1 a prognostic factor (Wang et al. 2012). The

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metastatic potential of MDA-MB-231 cells correlates with the high Hv1 expression in the plasma membrane. Taken together, the regulation of pH by Hv1 and the acidic pHe in cancer cells affect the secretion, activity, and cellular distribution of proteases, thus making the BC cells showing a more aggressive phenotype, with high proliferation, invasiveness, and migration. The knockdown of Hv1 showed inhibition of tumor progression, development, and metastasis, making Hv1 a molecular biomarker and target of BC therapy (Wang et al. 2012). NaV1.5 has been shown to interact with the predominant regulator of pHi NHE1, in the caveolae to enhance the H+ efflux, resulting in an acidification of the pericellular microenvironment (Brisson et al. 2011; Gillet et al. 2009). NaV1.5 and NHE1 co-localize in the plasma membrane of cancer cells and extracellular matrix assays suggest that they are both involved in the same pH-dependent invasiveness regulatory pathway (Brisson et al. 2011). The invasive properties of both channels in cancer cells have been shown to be activated through acidic extracellular cathepsins, mainly cathepsin B and S (Gillet et al. 2009). From high-grade BC biopsies and highly invasive BC cells lines, the overexpression of NaV1.5 has been associated with ECM remodeling and an increased risk of developing metastasis (Gillet et al. 2009; Brisson et al. 2013). In addition, it has been shown that NaV1.5 interacts with NHE1, allosterically increasing NHE1 activity in a pH range of 6.4–7.0, suggesting more proton extrusion at more acidic pHi. This interaction is supposed to occur in caveolae of the invadopodia compartment, hence responsible for increased ECM degradation and invasiveness (Brisson et al. 2013). A more aggressive phenotype of the BC cells could be explained by the enhanced Src kinase activity and the phosphorylation of Y421 cortactin, involved in migration and invasion (Brisson et al. 2013; Liu et al. 1999). These data suggest that NaV1.5 is regulated by pH and enhances NHE1 activity, promoting degradation of ECM and leads to invasion and migration in BC cells (Brisson et al. 2011, 2013). Some other ion channels sensitive to the pH are expressed in BC. Among the Ca2+ channels, one example is the transient receptor potential vanilloid 1 (TRPV1), which is proton sensitive. The modulation of these channels has been reported to play a functional role in TNBC, where they have been shown to be overexpressed (Weber et al. 2016) and associated with growth and progression (Weber et al. 2016; Wu et al. 2014). Furthermore, the chloride channel protein 2 (CLC-2) has shown to be opened by mild acidification but is completely inhibited by strong acidification (Arreola et al. 2002). CLC-2 is highly expressed in epithelial cells and in the colon where it has been suggested to have role in electroneutral salt absorption (Sandoval et al. 2011). CLC channels are expressed in BC cells and tissue and especially CLC-3 is over expressed (Zhou et al. 2018) and is related to invasion, migration, and cell cycle regulation (Peretti et al. 2015). Moreover, metastatic BC cells transfected with hCLCA2 presented a reduced pHi from 7.49 to 6.67, an acidic pHi known to activate apoptosis. The acidification of the cytosol by hCLCA2 could explain its inhibitory effect on proliferation and cell survival, as pH has profound effects on these events (Walia et al. 2009). In addition, mammary epithelial cells and lung fibroblast expressing cystic fibrosis conductance regulator (CFTR) have been found

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H. Ouadid-Ahidouch et al.

to induce a drop in pH to ~6.7 to initiate apoptosis, whereas the CFTR mutant did not (Barriere et al. 2001; Gottlieb and Dosanjh 1996). Concerning potassium channels, the two-pore domain potassium channel (K2P) family includes some members that are pH sensitive (Dookeran and Auer 2017). Members of the subfamily, the TWIK-related alkaline pH activated potassium channels including TASK-2, TALK-1, and TALK-2, are stimulated by an extracellular alkalinization (Dookeran and Auer 2017; Pei et al. 2003; Patel and Lazdunski 2004). These channels are of interest as their genes have been found to be either altered or upregulated in BC tissue, and in some cell types are found to be required for apoptosis (Dookeran and Auer 2017; Pei et al. 2003; Patel and Lazdunski 2004; Williams et al. 2013). These channels are inhibited by an extracellular acidification, which may contribute to cancer cells avoiding apoptosis through these channels (Andersen et al. 2014). Another subfamily of the K2P is the TWIK-related acid sensitive (TASK) family, which is inhibited by extracellular acidification. All the genes have been found upregulated in BC tissue and the gene coding for TASK-3 (KCNK9) is recognized as a proto-oncogene and its overexpression promotes tumorigenesis (Pei et al. 2003; Patel and Lazdunski 2004; Dookeran et al. 2017). Taken together, these channels (CLC and K2P) would be potential actors to regulate downstream signaling pathways of these cancer hallmarks through an acidification of the tumor environment.

4 Conclusion and Perspectives We have summarized here the modulation of ion channels expression and/or activity by the tumor microenvironment and how this involves changes in BC development and progression. To better understand the complex nature of BC, several cell lines were used to study the tumor microenvironment impact on BC progression: luminal-like, basallike, proliferative, invasive, and expressing “or not” different receptors for estrogen, progesterone, or HER-2. However, the results obtained remain fragmentary and represent only an approximation of how the processes take place in patient’s tumor. Moreover, tumor heterogeneity constitutes one of the major obstacles in cancer treatment leading to the recurrence of cancer. It is progressively becoming clear that there is significant response heterogeneity in drug responses within cancer cell populations. So far, most of the studies investigating the role of ion channels in cancer progression were dealing with cancer cells in vitro. Up to now their modulation by the microenvironment, which is crucial for tumor progression, has not been largely studied in BC and there is little knowledge about their expression profile and their role in clonal cell populations. Consequently, experimental approaches must be improved in order to get closer to the reality of the disease. For this purpose, it would be appropriate to investigate the role of ion channels by using different models including 3D cell culture, organoids, co-culture models, or microfluidic systems. Indeed, such approach could better enable to inform us about the interactions

Effects of the Tumor Environment on Ion Channels: Implication for Breast Cancer. . .

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between different cell types present in tumor environment and tumor cells and the role of ion channels in these interactions. Acknowledgments This work was supported by the UPJV “Université de Picardie Jules Verne,” the “Région Hauts-de-France,” the CNO (“Cancéropôle Nord-Ouest”), and the Marie SkłodowskaCurie Innovative Training Network (ITN), Grant Agreement number: 813834 – pHioniC – H2020MSCA-ITN-2018. Declaration of Competing Interest The authors declare that they have no conflict of interest.

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Rev Physiol Biochem Pharmacol (2021) 181: 39–56 https://doi.org/10.1007/112_2020_22 © Springer Nature Switzerland AG 2020 Published online: 1 August 2020

Ion Channel Profiling in Prostate Cancer: Toward Cell Population-Specific Screening Valerio Farfariello, Natalia Prevarskaya, and Dimitra Gkika

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stromal Cell Profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Endothelial Cell Profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neuronal and Neuroendocrine Tumor Cell Profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . New Methods for Cell Population Separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Cell Isolation Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Cell Characterization Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract In the last three decades, a growing number of studies have implicated ion channels in all essential processes of prostate carcinogenesis, including cell proliferation, apoptosis, migration, and angiogenesis. The changes in the expression of individual ion channels show a specific profile, making these proteins promising clinical biomarkers that may enable better molecular subtyping of the disease and lead to more rapid and accurate clinical decision-making. Expression profiles and channel function are mainly based on the tumoral tissue itself, in this case, the epithelial cancer cell population. To date, little data on the ion channel profile of the cancerous prostate stroma are available, even though tumor interactions with the microenvironment are crucial in carcinogenesis and each distinct population plays a specific role in tumor progression. In this review, we describe ion channel expression profiles specific for the distinct cell population of the tumor microenvironment (stromal, endothelial, neuronal, and neuroendocrine cell populations) and the technical approaches used for efficient separation and screening of these cell populations.

V. Farfariello, N. Prevarskaya, and D. Gkika (*) Université de Lille, Inserm, U1003 – PHYCEL – Physiologie Cellulaire, Lille, France Laboratory of Excellence, Ion Channels Science and Therapeutics, Université de Lille, Villeneuve d’Ascq, France e-mail: [email protected]

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Keywords Calcium · Cancer biomarkers · Chloride · Ion channels · Neuroendocrine cells · Potassium · Stroma cells · Transient receptor potential · Tumor-derived endothelial cells

1 Introduction One of the main challenges to Europe in 2020 is an investment in better health for all. In particular, the increasing life expectancy in the EU is expected to be accompanied by new ways of preventing diseases, development of more effective diagnostic tools and therapies, and invention of new technologies that promote health and wellbeing. The estimated total number of cancer deaths in Europe in 2018 was 1.93 million, of which 10% was due to prostate cancer (PCa) (Ferlay et al. 2018). PCa is one of the three most common noncutaneous human malignancies and the second most lethal tumor among men in Europe: in 2018 in the EU, 350,000 cases were diagnosed with the incidence rate increasing (Ferlay et al. 2018). The current diagnosis is based on a digital rectal exam and prostate-specific antigen (PSA) serum measurements (www.mayoclinic.org). However, the management of borderline PSA is not straightforward, and the PSA test shows poor sensitivity and specificity (Prensner et al. 2012). Thus, elevated PSA levels may be elevated not only in PCa but also in benign prostate cancer, resulting in overdiagnosis and occasional overtreatment (Ross et al. 2016). Therefore, further examination based on imaging techniques and histological analysis of prostate needle-core biopsies is needed for an accurate diagnosis. To prevent overdiagnosis, the combination of PSA testing with the detection of other biomarkers has significantly improved PCa detection, staging, and monitoring. Several novel blood-based biomarkers have been clinically introduced, including human glandular kallikrein 2 (hK2), transforming growth factor-beta 1 (TGF-β1), interleukin-6 (IL-6) and its receptor (IL-6R), and urokinase plasminogen activator (uPA) and its receptor (uPAR) (Shariat et al. 2009, 2011). The majority of PCa patients presents with low-grade PCa that can be successfully treated with surgery or radiation therapy. Approximately 10% of patients are diagnosed with high-grade PCa, which has a high chance of progressing after prostatectomy or radiation. These patients are treated by androgen-deprivation therapy, either by gonadotropin-releasing hormone (GnRH) agonists or by anti-androgen compounds and their combination, referred to as a maximal androgen blockade (MAB) (Ranieri 2012). Bicalutamide (commercially available as Casodex®, AstraZeneca) is a highly selective antagonist of the androgen receptor that was approved in 1995 as a combination treatment, with a GnRH analog, for the treatment of advanced PCa. Since its discovery, bicalutamide has been used as monotherapy for the treatment of early stages of PCa and as a combination treatment for advanced prostate cancer after prostatectomy (Wellington and Keam 2006). Chemical castration or androgen ablation therapy inhibits cancer progression,

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but PCa often progresses to the castration-resistant late stage of the tumor, often becoming incurable. Diagnosis has considerably improved in recent decades by intense research aimed at the identification of biomarkers for molecular imaging or as tools for ex vivo diagnosis (Ku et al. 2019; Koo et al. 2019). However, challenges for precision oncology remain due to high intertumoral and intratumoral heterogeneity as well as diverse mechanisms of resistance to treatment. Novel biomarkers would aid in better disease molecular subtyping and therefore more rapid and accurate clinical decision making. In this regard, ion channels are progressively emerging as novel potential biomarkers and therapeutic targets in several types of human cancers, including PCa (Lastraioli et al. 2015; Duranti and Arcangeli 2019) and await validation in the clinic. Accumulating evidence demonstrates that the development of PCa involves aberrant ion channel expression as well as altered functionality (Lastraioli et al. 2015; Pla and Gkika 2013; Gkika and Prevarskaya 2011; Prevarskaya et al. 2018), which are involved in nearly all the “hallmarks of cancer” as described by Hanahan and Weinberg (Hanahan and Weinberg 2011). Indeed, the acquisition of a malignant tumor phenotype is the result of enhanced cell proliferation and migration, aberrant differentiation, and increased cell survival that result in the expansion and invasion of the surrounding tissue. All these different hallmarks of tumorigenic stages have been associated with changes in gene expression in PCa and, as a consequence, with abnormal responses of all cellular ion channels conducting potassium (KCNA3, BKCa, KCNMA1) (Fraser et al. 2003; Bloch et al. 2007; Du et al. 2016), sodium (SCN9A, Nav1.8) (Suy et al. 2012; Rizaner et al. 2016), chloride (ANO7) (Kaikkonen et al. 2018), calcium (Cav3.2, ORAI) (Gackière et al. 2013; Dubois et al. 2014), and mostly cationic nonselective currents (Han et al. 2019; Wissenbach et al. 2001; Gkika et al. 2010, 2015; Bidaux et al. 2007; Monet et al. 2010; Oulidi et al. 2013; Bai et al. 2010; Sun et al. 2013, 2014; Holzmann et al. 2015; Sagredo et al. 2018). Several authors have therefore dedicated great effort to defining the role of the aforementioned channels in prostate carcinogenesis and to determining their value as possible biomarkers; however, it should be noted that, to date, most of the data concern epithelial cancer cells. In addition to cancer epithelial cells, a primary tumor consists of nonepithelial cellular components such as cancer-associated fibroblasts (CAFs), endothelial cells (ECs), immune cells, neurons, neuroendocrine cells (Hägglöf and Bergh 2012; Klein 2014), and cancer stem and progenitor cells (Leão et al. 2017; Moccia and Poletto 2015). The predominant cell population of the tumor stroma consists of CAFs, which create the structural foundation supporting most solid cancers and secrete several extracellular matrix (ECM) components important for tumor cell maintenance (Liao et al. 2019; Kalluri 2016). The tumor microenvironment also contains innate immune cells, including macrophages (TAMs, tumor-associated macrophages), neutrophils, mast cells, myeloid-derived suppressor cells (MDSCs), dendritic cells, natural killer cells, and adaptive immune cells (T and B lymphocytes). These cells release several cytokines and chemokines in the tumor microenvironment that can either promote or inhibit tumor development and progression (Lin and Karin 2007). The other two cell types, ECs and pericytes,

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play a central role in cancer progression. Under physiological conditions, pericytes reside near endothelial cell junctions and form an umbrella-like structure that covers gaps between endothelial cells and regulates barrier function (Carmeliet and Jain 2011). In contrast, in tumor vessels, pericytes are not associated with ECs, and as a result, cancer cell intravasation into the circulatory system is enabled (Hanahan and Weinberg 2011). In addition, neoangiogenesis, tumor growth, and dissemination are regulated by neurons, either directly through neurosignaling or by controlled angiogenesis (Faulkner et al. 2019). These nonepithelial components are often collectively referred to as the tumor stroma, and their interaction with the tumor epithelium plays a key role in promoting tumor growth and dissemination. For this reason, profiling the ion channels that characterize the PCa stroma is a promising approach for determining biomarkers that indicate disease progression and/or treatment failure (Staunton et al. 2017; Webber et al. 2016). In this review, we focus on the deregulation in expression and the consequent changes in cellular function of ion channels localized in the microenvironment of prostatic tumors, namely, in (1) stromal cells, which we consider here to be mainly myofibroblasts, CAFs, and inflammatory cells; (2) ECs; and (3) neurons and neuroendocrine cells. All ion channels described in the review are illustrated in Fig. 1. In addition, in the last paragraphs, we develop technical advances in separating cell populations and tumor tissue screening that could be used for more efficient global profiling of PCa stromal ion channels. The tumor microenvironment is composed of normal and neoplastic epithelial cells, stromal cells (CAFs), blood vessels, and nervous cells. Ion channels can participate to the regulation of the physiology of all these cell populations, thus contributing indirectly to tumor growth and progression. Here we the ion channels which expression is modulated in prostate cancer microenvironment, making them potential candidates for PCa profiling. Note that no data are currently available for immune and nervous cells.

2 Stromal Cell Profiling The tumor microenvironment mainly consists of myofibroblast cells, immune cells, and other supporting cells and structures. It is now clear that tumor microenvironment signaling is essential for cancer growth and progression (Cunha et al. 2002, 2003), and studies performed on prostate cancer were among the first to demonstrate an important role for the stroma in cancer progression. In this context, gene expression analyses performed on prostate stroma can provide precise information about any eventual role of the stromal transportome in prostate cancer progression. The main technique used to isolate prostate stroma from the whole tumor is laser capture microdissection followed by microarray gene expression analysis. As a result of this approach, many genes have been found to be different in tumor stroma than they are in normal tissues or to be specific to the

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Fig. 1 Ion channels and the tumor microenvironment. The tumor microenvironment is composed of normal and neoplastic epithelial cells, stromal cells (CAFs), blood vessels and nervous cells. Ion channels can participate to the regulation of the physiology of all these cell populations, thus contributing indirectly to tumor growth and progression. Here we show the ion channels which expression is modulated in prostate cancer microenvironment, making them potential candidates for PCa profiling. Note that no data are currently available for immune and nervous cells

reactive tumor stroma, and among these altered genes, some encoding ion channels have been described. One of the first studies showing altered expression of transportome components in prostate cancer stroma was published in 2009 by Dakhova et al. (2009). The goal of this study was to characterize reactive prostate stroma associated with poor outcome to understand the underlying biological processes and signaling mechanisms. To this end, they performed a microarray gene expression analysis of laser-

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captured reactive stromal cells and compared the resulting profile to that of normal stromal cells. A total of 544 and 606 genes were found to be upregulated and downregulated, respectively, in the reactive stroma cells. Of note, genes belonging to the gene ontology term “ion transport,” such as chloride channel 4 (CLCN4), chloride intracellular channel 5 (CLIC5), glycine receptor alpha 3 (GLRA3), and gamma-aminobutyric acid A receptor-gamma 2 (GABRG2), were upregulated in the reactive stroma. Another study conducted by Planche and colleagues (Planche et al. 2011), based on oligonucleotide-based Affymetrix microarrays on laser capture microdissection (LCM)-derived prostate normal and cancer stromal tissues, was aimed at characterizing gene expression changes during cancer progression. The results, which support an argument for two distinct sets of genes with significantly different clinical outcomes, revealed the upregulation of transient receptor potential cation channel subfamily M member 8 (TRPM8) and CLIC5 (as also found in the abovementioned study (Dakhova et al. 2009)) and the downregulation of potassium channel subfamily K member 3 (KCNK3) and ryanodine receptor type 2 (RYR2), which is specific to prostate cancer stroma. More importantly, another transportome member, glutamate receptor ionotropic AMPA 1 (GRIA 1), was found to be associated with a good prognosis. With the attempt to categorize the presence of tumors in patients when a prostate sample does not contain any recognizable tumor, Jia et al. (2011) identified a stromaspecific classifier for nearby tumors based on a gene selection procedure aimed at eliminating any potential bias derived from individual or tumor heterogeneity. Among the 146 genes identified, potassium inwardly rectifying channel, subfamily J, member 8 (KCNJ8), and transient receptor potential channel 3 (TRPC3) were found to be downregulated in tumor-adjacent stroma cells ( 0.42 and 0.75 logarithm fold change compared to the expression in normal stromal cells, respectively). Although the role of these channels was not investigated, this study provides evidence that ion channels (1) are preferentially expressed in prostate stroma, (2) are used as tools for early diagnosis, and (3) may play a role in prostate cancer progression mediated by stromal cells. In the prostate stroma, epithelial cells are highly responsive to androgens. During prostate development, stromal AR stimulates and sustains epithelial cell growth (Marker et al. 2003), and during prostate cancer development and progression, loss of stromal AR may play a role in cancer progression and the development of resistance to androgen ablation therapies (Olapade-Olaopa et al. 1999; Li et al. 2008). In a study published in 2011, Berry PA and colleagues (Berry et al. 2011) performed microarray gene expression profiling on isolated human prostate stromal cells treated or not with dihydrotestosterone, demonstrating that androgens regulate the expression of the ER-calcium sensor STIM1. Their results raised questions of whether the reduction of AR in prostate cancer stromal cells affects STIM1 expression, the associated store-operated Ca2+, and/or the development of androgen resistance.

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3 Endothelial Cell Profiling Tumor growth and dissemination are firmly dependent on tumor vascularization, which is promoted by tumor cells upon secretion of a number of growth factors. In addition to other highly vascularized solid tumors, PCa growth is dependent on neovascularization to allow local diffusion of oxygen and glucose. Interaction between PCa cells and the stromal compartment is essential for cell invasion, angiogenesis, and metastatic potential (Alphonso and Alahari 2009). Microvessel density, a measurement of PCa angiogenesis, has been shown to be a prognostic marker (Aragon-Ching et al. 2010; Hwang and Heath 2010). During vessel formation, “activated” ECs proliferate, migrate, differentiate, and become stabilized in a new circulatory network. Although these ECs are thought to be genetically stable compared to those in tumor cells, it was recently shown that tumor-derived ECs (TECs) differ significantly from their normal counterparts, as indicated by their high levels of survival, proliferation, and angiogenic properties, as well as their resistance to chemotherapeutics (Bussolati et al. 2011). As a result, TECs form irregular, leaky, and hemorrhagic tumor blood vessels (De Bock et al. 2011), resulting in different responses to antiangiogenic drugs than are exhibited by normal ECs. In our recent study (Fiorio Pla et al. 2014), we isolated TECs from PCa (PTECs) clinical samples, and we found resistance to specific anti-angiogenic drugs, such as sorafenib and sunitinib, compared to the resistance of normal ECs. These results are in line with those from other studies indicating TEC resistance of hepatocellular carcinoma cells to sorafenib (Xiong et al. 2009) or to NSK-01105, a novel sorafenib derivative (Yu et al. 2014). TECs comport quite differently than normal ECs at the cellular level, responding in a different manner to pro-angiogenic factors such as VEGF and bFGF, and their secondary response involves Ca2+, arachidonic acid, nitric oxide, and hydrogen sulfide (Fiorio Pla et al. 2008, 2010; Pupo et al. 2011). This altered intracellular signaling reflects ion flux through the cell membrane, suggesting an altered ion channel profile. Complete expression profiling for TRP channels was recently published by our group, identifying a specific signature for PCa compared to that of breast (BTEC) and renal (RTEC) carcinomas (Bernardini et al. 2019). TECs from the three tumor types showed deregulated transcription of trpm1, trpp2, and trpml1, which we qualified as TEC-associated genes. Furthermore, the transcription of five genes, namely, trpa1, trpv2, trpc3, trpc6, and trpm7, were deregulated only in prostate carcinoma and were therefore qualified as prostate-specific transcripts. Among the encoded proteins, TRPV2, TRPC3, and TRPA1 are contributors to the main properties of ECs during angiogenesis, such as EC proliferation, directed motility, sprout elongation, and morphogenesis regulation in vitro and in vivo (Bernardini et al. 2019). In the aforementioned study (Bernardini et al. 2019), TRPV2 was identified as a factor increasing tumor angiogenesis by acting on EC viability and proliferation. TRPV2 has been previously indirectly associated to altered angiogenesis in a mouse model of arthritis. In this model, activation of the channel by the O-1821 synthetic cannabinoid reduced synovial angiogenesis as well as infiltration of the

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inflammatory cells in the synovial tissues (Laragione et al. 2015). These studies reinforce the hypothesis of the TRPV2 pro-angiogenic role and are further supported by the previously positive correlation with tumor progression of the castrationresistant prostate (Monet et al. 2010) and bladder (Caprodossi et al. 2007) cancer. The second TRP channel identified to have a pro-angiogenic role was TRPC3, but following a different mechanism. EC overexpressing TRPC3 showed an increased ability in chemoattracting prostate cancer cells (Bernardini et al. 2019). In this respect more studies are needed in order to identify the exact Ca2+ signaling pathway used by tumor endothelial cells overexpressing TRPC3. Indeed, it is well established that Ca2+ signals are key players not only in EC but in the tumor microenvironment (Prevarskaya et al. 2018; Caprodossi et al. 2007; Savage et al. 2019). Further, the most profound effect on EC physiology was though due to the TRPA1 channel. Overexpression and/or activation of the TRPA1 channel promoted not only in vitro cell migration and tubulogenesis but also sprouting angiogenesis. Activation of the channel using allyl isothiocyanate (AITC) increased angiogenesis in the mouse retina, while its inhibition using the chemical compound HC030031 decreased the number of retinal tip-like cells (Bernardini et al. 2019). Here again as for TRPC3, this pro-angiogenic role was related to Ca2+ signaling since AITC increased intracellular calcium levels in tumor prostate endothelial cells as compared to their healthy counterpart (Bernardini et al. 2019). In accordance with these results, increased Ca2+ signals were associated with sprouting angiogenesis in an elegant study of Yokota et al. (2015). In this study, the authors succeed to record at the cellular level Ca2+ signals in the ECs of genetically modified zebrafish during sprouting angiogenesis. They therefore demonstrated that VEGF initiates Ca2+ oscillations in ECs and is critical for the choice and the migration of tip cells (Yokota et al. 2015). Ca2+ signaling of TRPA1 was also associated with tumor progression in prostate via the activation of the channel by triclosan. Triclosan, a common preservative factor largely used for its antimicrobial action and known as an endocrine disruptor, activated TRPA1 in stromal cells resulting in an increased secretion VEGF, putting in evidence the multifaceted role of TRPA1 in prostate tumor microenvironment (Derouiche et al. 2017). Taken together, the PCa TRP channel profile should be further validated and extended to other ion channel families for possible diagnostic and eventual therapeutic use. The TEC ion channel signature could thus be used in combination with other already known molecular targets known to regulate tumor angiogenesis. VEGF and its receptor VEGFR2 constitute common markers of tumor vascularization that are often overexpressed in tumors (Kerbel and Folkman 2002).

4 Neuronal and Neuroendocrine Tumor Cell Profiling The role of ion channels expressed in neuronal and neuroendocrine cells is one of the least studied in the PCa microenvironment. The prostate stroma is abundantly innervated by the sympathetic (adrenergic) and parasympathetic (cholinergic)

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nerves, which control the growth and maintenance of the prostate gland. A recent study demonstrated increased nerve infiltration in the tumor microenvironment in high-grade cancers versus low-grade cancers or benign prostatic hyperplasia (Magnon et al. 2013). Catecholamines secreted by sympathetic nerves activate adrenergic signaling and therefore stimulate tumor growth. On the other hand, when parasympathetic nerves activate cholinergic signaling, tumor dissemination is stimulated (Magnon et al. 2013). Taking into account that ion channels are the main component of both the adrenergic and cholinergic components, it would be interesting to screen them in the context of prostate carcinogenesis. In addition to neoneurogenesis, neuroendocrine differentiation is also correlated with poor prognosis. Neuroendocrine cells represent a small population of 1% in the prostatic epithelial tissue which is dispersed in the whole benign prostatic gland. However, neuroendocrine differentiation is positively associated with hormonerefractory prostate cancer and correlates with poor prognosis (Grobholz et al. 2005). As this population is dispersed in prostate, specific markers such as chromogranin A (CgA) identifying the neuroendocrine cell population are valuable in order to evaluate prostate cancer dedifferentiation and aggressiveness (Theodoropoulos et al. 2005). The main hypothesis concerning the molecular mechanism underlying the action on dedifferentiation is based on the neurosecretory action of these latter. Indeed, neuroendocrine cells release a variety of neuropeptides, such as the parathyroid hormone-related peptide, neurotensin, calcitonin, or gastrinrelated peptides, which act on the normal development of the prostate gland, while an increase of this cell population would promote the progression of the tumoral prostatic tissue. Interestingly, neuroendocrine differentiation of epithelial prostate cells modulates as well Ca2+ signaling. The modulation of Ca2+ signaling is due to the downregulation of SERCA 2b Ca2+ ATPase and the luminal Ca2+ binding/ storage chaperone calreticulin, which in combination with low store-operated channel current result to a reduction in filling the ER stores (Vanoverberghe et al. 2004). Ca2+ signaling is modulated not only at the level of the intracellular Ca2+ stores but also at the plasma membrane since neuroendocrine cells overexpress voltage-gated Ca2+ channels and in particular the CaV3.2 (α1H) pore subunit (Mariot et al. 2002). The increase in Cav3.2 at the transcriptional level is the result of the upregulation of early growth response 1 (Egr-1) and downregulation of repressor element (RE)-1silencing transcription factor (REST) (Fukami et al. 2015). This upregulation of CaV3.2 (α1H) promotes morphological differentiation and survival of neuroendocrine-differentiated cells (Weaver et al. 2015; Hall et al. 2018), which results in further secretion of prostatic acid phosphatase (PAP). Indeed, CaV3.2 (α1H) favors the synthesis and secretion of PAP, as well as serotonin, and is thus critical for the enhanced autocrine/paracrine secretion in neuroendocrine prostate cancer. This phenomenon has been suggested to be, in turn, crucial for the progression of prostate cancer toward an androgen-independent stage (Gackière et al. 2008). To date, systematic ion channel screening is not available for the cell populations in the PCa microenvironment, including neuronal and neuroendocrine cells. One of the limiting factors of screening is the efficient separation and sufficient purity of the different cell populations acquired from clinical samples. In the next paragraph, we

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explain some of the technical approaches that could be useful in separating and characterizing these cell populations to better identify their distinct ion channel profiles.

5 New Methods for Cell Population Separation High-throughput technologies for tumor tissue screening have generated a substantial amount of data, which has been exploited for many years, to find, sometimes successfully, cancer biomarkers and/or targets for therapy. However, these data have been obtained from whole tissues, thus lacking cell specificity with the consequent underestimation of potential genes involved in key pathways related to cancer initiation and progression. In recent decades, new technologies have been implemented to better isolate cell populations and single cells within tumor tissues, leading to new perspectives in cancer research. The following paragraphs recapitulate the main techniques used to isolate or characterize cell populations, from the most known to the latest ones emerging.

5.1 5.1.1

Cell Isolation Techniques Explant Culture or Enzymatic Separation

The methods used for explant culture and enzymatic separation are among the oldest and simplest isolation techniques. In the explant method, the tissue is excised into small pieces and placed in specific culture dishes (usually bearing a modified polystyrene surface incorporating a mixture of anionic and cationic functional groups to increase adherence of primary cells) (Hendijani 2017). In this case, the extracellular matrix, the secretome, and other cellular components facilitate cell adhesion and growth (Brizzi et al. 2012), and the cells migrate out of the tissue and adhere to the culture surface, depending on the selectivity of the culture medium being used. In enzymatic methods, several proteolytic enzymes are used to separate cells from tissues; the single cell suspension is then cultured in medium appropriate for facilitating the proliferation of a particular cell population (Uysal et al. 2018). In both cases, the presence of other cell types can be problematic, especially when the medium used is unable to strictly select a single population. However, medium renewal and cell passage can reduce the amount of “contamination” due to the adherence properties of different cells.

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Laser Capture Microdissection (LCM)

LCM technology emerged in the late 1990s as a tool to directly select cell types from heterogeneous tissues. LCM is a versatile technology that enables the preparation of homogeneous isolates of specific subpopulations of cells from which RNA/DNA or protein can be extracted for RT-polymerase chain reaction (PCR), quantitative PCR, Western blot analyses, and/or mass spectrophotometry. The general features of LCM are (Ferlay et al. 2018) visualization of the cells/tissues via wide-field microscopy (bright field, contrast, or fluorescence), (Prensner et al. 2012) laser energy transfer to the region of interest (ROI), and (Ross et al. 2016) removal of the selected area from the tissue section and transfer to an adequate support system (Emmert-Buck et al. 1996), mainly via propulsion (from a tissue mounted on special slides to the collection tube, DIRECTOR technology), laser-assisted catapulting (PALM technology), or gravity-assisted microdissection (ION LMD technology). The main advantages of LCM are the speed by which samples are processed and the precision of the outcomes. This technique can be used for a variety of biological preparations, including living cells and tissues (frozen or FFPE), and, depending on the accuracy of the manipulations, can yield highly pure DNA, RNA, and/or proteins for genomic and/or proteomic analysis. Limitations of this technique are mainly related to the need of a pathologist capable of identifying morphological characteristics of the cells. Although some immunohistochemical protocols can be helpful in this regard, these procedures are prone to degrading RNA and proteins with the consequent loss of quality of the biological preparation (Domazet et al. 2008).

5.1.3

Antibody-Based Cell Sorting

The antibody-based cell sorting method refers to the known techniques named fluorescence-activated cell sorting (FACS) and magnetic-activated cell sorting (MACS). Both approaches are based on the presence of cell membrane antigens that are targeted by functionalized antibodies to achieve cell separation. In FACS separation, the antibody is bound to a fluorophore that, once excited by lasers, enables cell sorting based on a previously fixed fluorescence threshold. In MACS separation, antibodies are bound to iron-bearing nanoparticles: the entire cell population is then placed in a magnetic field, which retains the labeled cells and allows the elution of the unlabeled ones. Both methodologies can be used alternatively for positive or negative selection protocols since users can label either wanted or unwanted cells. Although FACS and MACS share common principles, some differences include population purity and timing of the procedures. In fact, FACS allows a more precise selection of cells in that multiple and simultaneous labeling can be used. However, analysis and sorting times are often slower for FACS than they are for MACS (Tomlinson et al. 2012).

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Cell Characterization Techniques Digital Spatial Profiling

Digital spatial profiling (DSP), developed by NanoString Technologies, Inc., combines imaging and tissue sampling with standard IHC methodologies. DSP can simultaneously characterize regional and quantitative protein expression of several immune or cancer markers (currently as many as 40) on a single FFPE tissue section (Merritt et al. 2020). Tissue preparation for DSP is the same as it is for standard IHC but is followed by incubation with a mix of visualization markers (VMs include stained tissue-specific regions and ROI selection) and DSP probes (a panel of antibodies linked to DNA barcodes). An imaging step is then necessary to choose the ROI, and ultraviolet exposure allows oligo collection and quantification using the proprietary system (Van and Blank 2019). One of the advantages of DSP is that tissues can be preserved after analysis for further IHC staining. However, the system is based on the use of antibodies, and there is a small risk of false positivity due to unspecific binding and background signals.

5.2.2

Single-Cell RNA Sequencing

Even though the abovementioned methods enable the precise identification, collection, and/or characterization of specific cell populations, the heterogeneity at the single-cell level presents obstacles to research. To overcome this problem, singlecell RNA sequencing (scRNA-seq) has emerged as one of the most powerful tools available. In the first step, the transcriptome is obtained from an individual cell by single-cell isolation, usually achieved through FACS and serial dilutions of the sorted cells, LCM, or microfluidic technologies. To generate scRNA-seq libraries, cell lysis, reverse transcription into first-strand cDNA, second-strand synthesis, and cDNA amplification are required. After cell lysis, messenger RNAs are selected using poly(dT) primers (poly(A)+ selection), and first-strand cDNA is produced using Moloney murine leukemia virus reverse transcriptase (Hwang et al. 2018). The second strands are usually produced using poly(A) tailing. Because poly(A) selection provides small amounts of mRNAs and low amounts of subsequently attained cDNAs, the latter is typically amplified by PCR. The sequencing step is then performed on a platform, such as that from Illumina, to obtain raw data for analysis. Raw data are then first submitted to quality control analysis and normalization, followed by read alignment and quantification using proprietary or Cloud-based tools (Islam et al. 2011).

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Cell Painting

Gene expression profiling is one of the most powerful tools available to date to characterize cells, but it fails to provide information about the morphological profiles of a cell phenotype. One of the most recent methodologies to overcome this problem is cell painting (Bray et al. 2016), which relies on the use of several concomitant fluorescent markers to identify changes in cell morphology phenotypes, including not only fluorescence distribution and intensity but also cell size, shape, and texture. This technique is particularly useful for categorizing small molecules by phenotypic similarity (e.g., to screen phenotypic changes induced by compounds) or to identify phenotypic signatures associated with disease (e.g., normal vs. cancer cells). The main steps necessary to achieve the protocol are essentially (1) cell culture and, ultimately, treatment with compounds or siRNAs, (2) staining with nonantibody-based fluorescence-labeled markers (such as Hoechst 33342 for nuclei, concanavalin A for endoplasmic reticulum, SYTO for nucleoli, wheat germ agglutinin for the Golgi apparatus and plasma membrane, phalloidin for F-actin, and MitoTracker for mitochondria), and (3) image analysis performed with the dedicated software CellProfiler™. The last step enables the identification of individual cells and characterization of approximately 1,500 morphological features, with the possibility of clustering image-based profiles to obtain distinct hierarchical groupings (Gustafsdottir et al. 2013). One of the main advantages of this technique is the possible use of several palettes of markers to extend cellular phenotyping. However, given the experimental setup necessary to obtain data, the results could be biased, since the cell culture itself (2D culture, plastic support, or seeding properties) or staining procedures can introduce artifacts.

6 Conclusions As described above, many isolation and characterization methods are now available for more accurate and cell population-specific profiling. Depending on the type of analysis and cell phenotype to be analyzed, researchers have many choices among several tools that can achieve useful results with high-quality samples specifically representing several components of tumor tissues. These technical advances must be integrated and fully exploited to define the full ion profiles of the tumor environment cell populations, such as CAFs, ECs, and, especially, immune cells, neurons, and neuroendocrine cells, for which few or no data are currently available. The results of such screening could be used in combination with the existing ion channel profiles of cancer epithelial cells to provide a more accurate ion channel signature of PCa and contribute to better diagnoses and prognoses of the disease.

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Acknowledgments English language, grammar, punctuation, spelling, and overall style by the highly qualified native English-speaking editors at American Journal Experts (certificate number EDCC-3B24-C703-F3F2-FDE9). Conflict of Interest The authors declare no conflict of interest in the manuscript. Funding All authors were supported by grants from the Ministère de l’Education Nationale, the Institut National de la Santé et de la Recherche Medicale (INSERM), and La Ligue contre le cancer. DG was supported by the Institut Universitaire de France (IUF). VF was supported by Institut National du Cancer (INCA).

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Ion Channels in Lung Cancer Etmar Bulk, Luca Matteo Todesca, and Albrecht Schwab

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Ion Channels in Lung Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Transient Receptor Potential (TRP) Channels in Lung Cancer . . . . . . . . . . . . . . . . . . . . . . . 2.2 Voltage-Gated Ion Channels in Lung Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 K2P Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Ca2+-Activated Potassium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Chloride Channels in Lung Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Nicotine Acetylcholine Receptors (nAChRs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract Ion channels are a major class of membrane proteins that play central roles in signaling within and among cells, as well as in the coupling of extracellular events with cellular responses. Dysregulated ion channel activity plays a causative role in many diseases including cancer. Here, we will review their role in lung cancer. Lung cancer is one of the most frequently diagnosed cancers, and it causes the highest number of deaths of all cancer types. The overall 5-year survival rate of lung cancer patients is only 19% and decreases to 5% when patients are diagnosed with stage IV. Thus, new therapeutical strategies are urgently needed. The important contribution of ion channels to the progression of various types of cancer has been firmly established so that ion channel-based therapeutic concepts are currently developed. Thus far, the knowledge on ion channel function in lung cancer is still relatively limited. However, the published studies clearly show the impact of ion channel inhibitors on a number of cellular mechanisms underlying lung cancer cell aggressiveness such as proliferation, migration, invasion, cell cycle progression, or adhesion. Additionally, in vivo experiments reveal that ion channel inhibitors diminish tumor growth in mice. Furthermore, some studies give evidence that ion

E. Bulk (*), L. M. Todesca, and A. Schwab Institute of Physiology II, University of Münster, Münster, Germany e-mail: [email protected]

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channel inhibitors can have an influence on the resistance or sensitivity of lung cancer cells to common chemotherapeutics such as paclitaxel or cisplatin. Keywords Ion channels · Lung cancer

1 Introduction Lung cancer is one of the leading causes of cancer related death worldwide. Overall, its 5-year survival rate amounts to 19% (Siegel et al. 2019). The 1-year survival rate of non-small lung cancer (NSCLC) patients in stage IV, however, is only 15–19%. The 5-year survival rate of these patients is even as low as 5%. The prognosis of small cell lung cancer (SCLC) patients is even worse (Blandin Knight et al. 2017). Unfortunately, about 70% of lung cancer patients are in an advanced stage of the disease at the time of diagnosis (Travis 2011; Lemjabbar-Alaoui et al. 2015; Bittner et al. 2014). At this stage, tumors are often unresectable, since the patients already developed multiple distant metastases (Goldstraw et al. 2016). Historically, lung cancer was classified into the subtype small cell (SCLC) and the major subtype non-small cell lung cancer (NSCLC), the latter approximately accounting for 85% of all lung cancers (Goodwin et al. 2017). Other difference between these two subtypes is that SCLC cells are microscopically smaller in comparison to NSCLC cells. SCLC metastasizes to other organs much faster as NSCLC. Thus, SCLC patients die earlier, sometimes within a few weeks when untreated. SCLC has only two stages: the extensive stage (ED-SCLC), with around 70% of cases and the limited stage (LS-SCLC), with the remaining 30% of patients (Calles et al. 2019). The staging in NSCLC is based on the TNM classification (T ¼ primary tumor, N ¼ lymph nodes, M ¼ metastasis) and is subdivided into stage IA until IVB (Goldstraw et al. 2016). In 2015, the World Health Organization (WHO) changed the classification of lung tumors and defined subtypes on the basis of their histological appearance (Travis et al. 2015). The histological types are divided into adenocarcinoma, squamous cell carcinoma, neuroendocrine tumors (including SCLC), large cell carcinoma, sarcomatoid carcinoma, and other and unclassified tumors (including nuclear protein in testis (NUT) carcinoma). The histological classification is refined by a molecular classification which also considers the mutational status of the patients because it offers the potential for targeted therapy. With the discovery of somatic mutations in the epidermal growth factor receptor (EGFR) gene, the therapeutic impact of tyrosine kinase inhibitors (TKI) came into focus. EGFR is overexpressed in more than 60% of all NSCLCs (Da Cunha et al. 2011; Hsu et al. 2019). EGFR is involved in several cellular processes that are relevant for tumor progression. Examples include the modulation of cell proliferation, apoptosis, cell motility, and neovascularization (Cheng et al.

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2012). Since many EGFR mutations are responsible for the constitutive activation of the tyrosine kinase receptor, these mutations are also associated with either sensitivity or resistance to EGFR TKIs like gefitinib or erlotinib (Pao et al. 2004; Riely et al. 2006; Cheng et al. 2012; Lemjabbar-Alaoui et al. 2015). In addition to EGFR, other driver mutations have been identified to underly lung adenocarcinoma progression such as mutations in KRAS, EML4-ALK, BRAF, PIK3CA, MET, ERBB2, MAP2K1, and NRAS (Pao and Girard 2011; Cheng et al. 2012). In part, these mutated signaling molecules are also exploited therapeutically. Recently, immune checkpoint inhibitors against programmed death 1 (PD-1) and programmed death ligand 1 (PD-L1) were shown to be effective in KRASmutant NSCLC so that they are now used as standard care in second-line treatment of NSCLC (Jeanson et al. 2019). Another strategy aims at disrupting the angiogenic pathway by using antibodies against the endothelial growth factor VEGF as bevacizumab or sorafenib that targets VEGF-2/3, PDGFR-β, c-Kit, Raf, and Flt-3 (Lemjabbar-Alaoui et al. 2015). However, the resistance with treatment of antiVEGF agents eventually occurs in all patients (Lemjabbar-Alaoui et al. 2015). In general, not only the resistance but also the ineffectivity of most inhibitors or agents in advanced stages are still big challenges in treating NSCLC patients. This calls for a better understanding of lung cancer pathophysiology which should lead to the development of innovative alternative therapeutic strategies. Such a promising novel approach is emerging by targeting ion channels in cancer. They are a major class of membrane proteins that play central roles in signaling within and among cells as well as in the coupling of extracellular events with cellular responses (Prevarskaya et al. 2018). Moreover, ion channels offer the potential of being promising cancer biomarkers (Lastraioli et al. 2015b).

2 Ion Channels in Lung Cancer During the last decade, the focus on ion channels and their impact in cancer became more and more evident. This is due in part to the increasing availability of ion channel modulators. Hence, targeting of ion channels could be a potentially useful therapeutical approach in the treatment of cancer. Thus, first clinical trials are already evaluating the therapeutic potential of ion channel targeting in cancer patients. For example, the TRPV6 inhibitor SOR-C13 is evaluated in the treatment of solid tumors of epithelial origin (ClinicalTrials.gov Identifier: NCT03784677, Fu et al. 2017), and in case of breast cancer patients, a randomized controlled trial assesses the blockage of voltage-gated sodium channels (ClinicalTrials.gov Identifier: NCT01916317, Martin et al. 2015; Fairhurst et al. 2015). So far, there is no such approach to the best of our knowledge for the treatment of lung cancer patients. In the following, we will give an overview about the current knowledge of ion channels and their contribution to lung cancer. A complete list of all ion channels contributing to lung cancer is summarized in Table 1.

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Table 1 Ion channels and their impact in lung cancer Channel TRPA1

Histology SCLC AC/SCC NSCLC LLC

TRPC1

NSCLC AD/SCC

TRPC3

NSCLC AC/SCC AC NSCLC AC/SCC NSCLC AC/SCC NSCLC AC/SCC

TRPC4 TRPC6 TRPM2

TRPM7

NSCLC

TRPV1

NSCLC AC/SCC NSCLC AC/SCC NSCLC

TRPV4 KV1.1

Cell line/ tissue SCLC cell lines/tissue Lung tissue NSCLC/ SCC cells Lewis lung cancer cells A549, lung tissue

Function/phenotype Expression, apoptosis, tumor growth Invasion

Ref. Schaefer et al. (2013), Park et al. (2016), Takahashi et al. (2018), Du et al. (2014)

Expression, differentiation, proliferation

A549, lung tissue Lung tissue A549, lung tissue A549, lung tissue A549, H1299, lung tissue A549

Expression, differentiation, proliferation Expression, good prognosis Expression, differentiation, proliferation Expression, differentiation, proliferation Upregulation, apoptosis, proliferation, tumor growth, invasion Expression, migration

Heilig et al. (2006), Tajeddine and Gailly (2012), Jiang et al. (2013) Jiang et al. (2013), Saito et al. (2011)

A549, lung tissue Lung tissue

Upregulation Upregulation

KV1.3 KV7.1

NSCLC NSCLC AC

KV9.3 KV10.1 (EAG1)

NSCLC SCLC NSCLC

A549, NCI-H460 A549 A549, NCI-H460, lung tissue A549 Lung tissue, A549

Cell viability, tumor growth

KV10.2 KV11.1 (HERG1)

NSCLC SCLC

Lung tissue SCLC cells

Expression Functional expression, proliferation

NaV1.7

NSCLC

H23, NCI-H460, Calu-1

Upregulation, functional expression, invasion

Tumor growth Migration, proliferation, overexpression Expression, tumor growth Expression, EMT

Jiang et al. (2013) Jiang et al. (2013) Park et al. (2016), Masumoto et al. (2013), Almasi et al. (2019) Heilig et al. (2006), Gao et al. (2011) Park et al. (2016), Masumoto et al. (2013) Park et al. (2016) Jeon et al. (2012), Jang et al. (2011a) Jang et al. (2011b) Girault et al. (2014)

Lee et al. (2015) Hemmerlein et al. (2006), Díaz et al. (2009), RestrepoAngulo et al. (2011) Feng et al. (2008) Bianchi et al. (1998), Hemmerlein et al. (2006), Glassmeier et al. (2012) Roger et al. (2007), Campbell et al. (2013) (continued)

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Table 1 (continued) Cell line/ tissue A549, NCI-H460, H358, MOR Lung tissue Ben lung carcinoma cells, lung tissue A549, lung tissue

Channel K2P3.1

Histology NSCLC

K2P9.1

SCC

KCa3.1

NSCLC

VSOR

NSCLC

ClC-3

NSCLC

VRCC

SCLC

ANO1

NSCLC

GLC82, NCI-H520, lung tissue

CFTR

NSCLC

A549, lung tissue

Kir2.3

NSCLC AC NSCLC AD

A549, lung tissue A549, H1299, lung tissue A549, H1299, H1975, lung tissue A549

α5nAChR α7nAChR

NSCLC

α9nAChR dupα7

NSCLC NSCLC

A549, A549/ CDDP A549, A549/PTX NCI-H209

A549, SK-MES-1

Function/phenotype Expression, functional expression, apoptosis, proliferation, migration, EMT

Ref. Leithner et al. (2016), Wang et al. (2018)

Overexpression, cell viability, tumor growth, lung colonization

Mu et al. (2003), Sun et al. (2016)

Overexpression, functional expression, proliferation, migration, invasion, adhesion, tumor growth Apoptosis, apoptotic volume decrease, functional activation, cell sensitivity Overexpression, resistance, sensitivity Channel inhibition, cell cycle progression Upregulation, proliferation, migration, invasion, tumor growth, expression in advanced lung tumors Downregulation, good prognosis, migration, invasion, metastasis, enhanced methylation Overexpression, reduced survival, migration Expression, proliferation, migration, invasion, tumor growth Upregulation, proliferation, migration, invasion, EMT, tumor growth

Bulk et al. (2015, 2017)

He et al. (2010), Min et al. (2011) Chen et al. (2019) Renaudo et al. (2007) Jia et al. (2015), He et al. (2017)

Li et al. (2015, 2018a, b, 2010), Son et al. (2011)

Wu and Yu (2019) Zhang et al. (2017a, b), Sun and Ma (2015), Sun et al. (2017) Ma et al. (2019), Zhang et al. (2016, 2017a, b), Mucchietto et al. (2018)

Expression, proliferation

Mucchietto et al. (2018)

Properties of a tumor suppressor

Cedillo et al. (2019)

SCLC small cell lung cancer, NSCLC non-small cell lung cancer, SCC squamous cell carcinoma, AC adenocarcinoma

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Transient Receptor Potential (TRP) Channels in Lung Cancer

The family of TRP channels comprises a multitude of ion channels that are composed of six transmembrane domains. Since most TRP channels are permeable for Ca2+, they are crucial for the cellular Ca2+ homeostasis and for Ca2+ signaling, which is often altered in cancer cells (Prevarskaya et al. 2014; Cui et al. 2017). Being a second messenger, Ca2+ is involved in many cellular processes including migration, invasion, proliferation, and adhesion, which are relevant for cancer progression (Pierro et al. 2018; Cui et al. 2017). Based on their sequence homology, TRP channels can be grouped into six subfamilies which are TRPA (ankyrin), TRPC (canonical), TRPM (melastatin), TRPML (mucolipin), TRPP (polycystin), and TRPV (vanilloid). So far, the understanding of the role of TRP channels in lung cancer progression is far from being fully understood. A summary of the current knowledge about TRP channels in lung cancer will be discussed in the following. The transient receptor potential ankyrin 1 (TRPA1) is a Ca2+ permeable non-selective cation channel that is activated by cold and mechanical stimuli, as well as by almost all oxidizing and electrophilic chemicals, including chlorine, acrolein, tear gas agents, and methyl isocyanate (Story et al. 2003; Bessac and Jordt 2010). Originally, TRPA1 was found in sensory neurons but it has become clear that it is also expressed in other cell types including lung cancer cells. Its expression has been described in a panel of human small cell lung cancer (SCLC) cell lines (Schaefer et al. 2013). TRPA1 mRNA expression is significantly higher in tumor samples from SCLC patients than in NSCLC tumor samples or non-malignant lung tissues. An altered TRP channel expression (including that of TRPA1) was also detected by Park et al. (2016) in NSCLC (adenocarcinoma and squamous cell carcinoma). Quite recently, Takahashi et al. observed TRPA1 expression and its functionality in several non-small cell lung cancer cells (NSCLC) and squamous cell lung cancer cells (Takahashi et al. 2018). The authors showed that TRPA1 enhances chemosensitivity and promotes an oxidative stress defense in response to reactive oxygen species (ROS) in cancer cells through an upregulation of Ca2+ dependent anti-apoptotic signaling pathways. By the use of H2O2 in TRPA1-enriched cancer cell lines, the authors showed that the increase in the [Ca2+]i is suppressed by TRPA1 inhibition and that TRPA1 is the major channel responsible for Ca2+ entry in response to ROS. In TRPA1-enriched HCC1569 and H1792 spheroids, TRPA1 inhibition leads to a decrease of the [Ca2+]i and increased apoptosis in cells localized in the inner region of the spheroids. Furthermore, the authors demonstrate that inhibition of TRPA1 reduces tumor growth in xenografted mice. Expression of TRPA1 was also found in Lewis lung cancer cells, where it promotes, in combination with TRPM8 channels, an invasive phenotype (Du et al. 2014). TRPM8 is also activated by cold temperatures, by cooling compounds (menthol, icilin), and by pressure (González-Muñiz et al. 2019). Its expression and upregulation were detected in lung cancer specimen, too (Tsavaler et al. 2001; Park et al. 2016). Two other TRPM channels are connected to lung cancer cells.

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TRPM2 channels are upregulated in lung adenocarcinoma and squamous cell carcinoma. They are also expressed in A549 and H1299 NSCLC cells, which are commonly used NSCLC cell lines (Park et al. 2016; Masumoto et al. 2013; Almasi et al. 2019). TRPM2 channels are involved in apoptosis, proliferation, migration, and invasion of lung cancer cells (Almasi et al. 2019). Silencing of TRPM2 increases intracellular levels of ROS and reactive nitrogen species (RNS) which in turn causes DNA damage and cell death. TRPM2 silencing reduces proliferation, cell migration, and invasion and suppresses the expression of EMT markers. Furthermore, silencing of TRPM2 in A549 cells transplanted into SCID mice reduces tumor growth. A549 cells also express TRPM7 channels (Heilig et al. 2006). Silencing of TRPM7 channels decreases EGF-enhanced migration of A549 cells (Gao et al. 2011). Two members of the vanilloid TRP channels, TRPV1 and TRPV4 were suggested as diagnostic markers in lung cancer, since they are upregulated in adenocarcinoma and squamous cell carcinoma of the lung (Park et al. 2016). Moreover, TRPV1 channels are activated in A549 cells after irradiation (Masumoto et al. 2013). The authors assume that TRPV1 is involved in DNA damage response, since downregulation of TRPV1 or pharmacological treatment with the inhibitor capsazepine suppresses the activation of the DNA repair markers γH2AX (phosphorylated histone variant H2AX) and ATM (ataxia-telangiectasia mutated kinase). In contrast, the TRPV1 agonist capsaicin induces γH2AX in γ-irradiated cells. Members of the TRPC (canonical) family are also expressed in lung cancer cells (Heilig et al. 2006; Tajeddine and Gailly 2012; Jiang et al. 2013). Inhibition of TRPC channels decreases the proliferation of A549 cells, while it is increased by their overexpression. Interestingly, expression of TRPC1, 3, 4, and 6 strongly correlates with a well-moderately differentiation grade of NSCLC in patients (Jiang et al. 2013). A more detailed mechanistic study with a focus on TRPC1 channels showed that silencing of TRPC1 channels induces the G(0)/G(1) cell cycle arrest of A549 cells which in turn results in a dramatic decrease of cell proliferation (Tajeddine and Gailly 2012). This study also revealed that TRPC1 is involved in EGF-induced Ca2+ signaling and therefore, the authors suggest TRPC1 as a major regulator of the epidermal growth factor receptor (EGFR) signaling. This suggestion is supported by the fact that stimulation of EGFR by EGF induced Ca2+ entry via TRPC1 channels. Ca2+ entry through TRPC1 constitutes an amplification loop, which is triggered by EGFR stimulation and then enhances EGFR autophosphorylation and activity. One study describes a better outcome for lung cancer patients, when TRPC3 channel expression is elevated (Saito et al. 2011). This better outcome is in accordance to the findings of Jiang et al. (2013), because TRPC3 expression was found at lower levels in lung cancer tissues than in normal lung tissue and also at lower levels in A549 cells than the expression of TRPC1, 4, or 6 (Jiang et al. 2013). All in all, the current findings indicate that TRP channels have an impact in lung cancer and could be a useful diagnostic marker or therapeutic target, as already suggested by several authors.

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Voltage-Gated Ion Channels in Lung Cancer

Voltage-gated ion channels are gated by changes of the membrane potential. The traditional view is that they are predominantly active in excitable cells such as in neuronal and muscle cells. This view, however, has been largely refined by showing that voltage-gated ion channels are not only functional in excitable cells, they are widely expressed in many non-excitable cells as well. Thus, they are also functional in many cancer cells including lung cancer cells (Rao et al. 2015; Lastraioli et al. 2015a, b). Depending on the charge carrying ions, voltage-gated ion channels are classified into the subfamilies of voltage-gated Na+ channels (VGSC, NaV), voltagegated K+ channels (VGKC, KV), and voltage-gated Ca2+ channels (VGCaC, CaV). One of the first demonstrations that voltage-dependent ion channels are present in lung cancers was published in 1989 (Pancrazio et al. 1989). Here, the authors described voltage-dependent currents carried by K+ and Na+ ions in three human small-cell lung cancer cell lines (NCI-HI28, NCI-H69, and NCI-HI46) which were inhibited by the respective blockers (4-aminopyridine and tetraethylammonium for KV channels, tetrodotoxin for NaV channels). In addition, the authors could also identify the activity of CaV channels. KV Channels Using a pharmacological approach, it was shown that KV channels are linked to the proliferation of SCLC cells (Li et al. 2005) and NSCLC cells (Pancrazio et al. 1993; Wang et al. 2002; Li et al. 2005). Proliferation of these cells is inhibited in the presence of 4-aminopyridine or tetraethylammonium. In a further study, proliferation of a cisplatin-resistant lung cancer cell line (A549/CDDP) is inhibited by 4-aminopyridine in vitro and in vivo in xenografted nude mice. Additionally, the authors demonstrate that 4-aminopyridine induces cell apoptosis and enhances the sensitivity of cisplatin-resistant A549/CDDP cells to cisplatin (DDP) (Luo et al. 2018). Tetraethylammonium or 4-aminopyridine in combination with the epidermal growth factor receptor tyrosine kinase inhibitor gefitinib also decreases the cell viability of side populations of gefitinib-resistant NCI-H460 cells (Choi et al. 2017). The authors found a similar effect when using the voltage-gated KV7 opener flupirtine. Decreased expression levels of phosphorylated EGFR, phosphorylated ERK, and total Ras protein in cells indicate that the combination treatment reduces the viability of gefitinib-resistant NCI-H460 cells through inhibition of the EGFRRas-Raf-ERK pathway. A reduced cell viability of NCI-H460 cells could also be observed in the presence of the KV1.1 blocker dendrotoxin-κ (DTX-κ). Injection of DTX-κ directly into the tumor tissue of xenografted nude mice reduces the tumor volume (Jeon et al. 2012). As shown by the same group, DTX-κ also reduces the tumor growth in nude mice, when transplanted with A549 lung cancer cells (Jang et al. 2011a). The authors obtained a similar inhibitory effect in xenografted mice transplanted with A549 cells, when applying margatoxin (MgTX), a blocker of KV1.3 (Jang et al. 2011b). Viability of A549 cells is similarly reduced when they are treated with shRNA against KV1.3 channels. A549 cells also express KV9.3

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channels which appear not to be functional as a homomer, but form heteromers with KV2.1 channels (Lee et al. 2015). Knockdown of the KV9.3 channel protein in A549 lung cancer cells as well as in HCT15 colon carcinoma cells reduces tumor growth in xenografted SCID mice. siRNA against KV9.3 modulates the expression of cell cycle regulatory proteins and reduces the cell viability of A549 and HCT15 cells. While it is claimed that the expression of KV2.1 is not altered by these maneuvers, it did not become entirely clear whether the observed effects are due to non-conducting properties of KV9.3 itself or due to an altered formation of heteromeric KV2.1/KV9.3 channels. KV10.1 (EAG) and KV11.1 (HERG1) channels are among the best studied KV channels in cancer (Ouadid-Ahidouch et al. 2016; Duranti and Arcangeli 2019). They have also been identified in SCLC cells (Bianchi et al. 1998; Hemmerlein et al. 2006). KV10.1 expression in A549 cells is upregulated by antiestrogens (Díaz et al. 2009). This was interpreted as a potential cross talk between EGFR and the estrogen receptor (ER) pathways: Phospho-EGFR and phospho-p44/p42 MAPK are rapidly activated by estrogen and EGF; in vitro experiments show that EGFR ligands are released upon estrogen stimulation and estrogen, and EGF can mutually modulate the levels of the mutual receptors. Moreover, the combination of fulvestrant and gefitinib inhibits proliferation and apoptosis in vitro and downstream signaling molecules, including phospho-p44/p42 MAPK (Stabile et al. 2005). Upregulation of KV10.1 has also been linked to epithelial-to-mesenchymal transition (EMT), which is a phenomenon associated with tumor malignancy (Restrepo-Angulo et al. 2011). The KCNH5 gene coding for KV10.2 is more frequently methylated in NSCLC tissues compared with matched noncancerous tissues (Feng et al. 2008). However, this study drew no conclusion with respect to the expression of the channel protein and the resulting functional impact of the methylation pattern. Silencing KV11.1 channels reduces proliferation of SCLC cells by about 50% (Glassmeier et al. 2012). While the KV channels discussed so far have been shown to regulate lung cancer growth and proliferation, other KV channels have also been linked to migration and invasion. The KV7.1 (KVLQT1) channel has been identified as a regulator of NSCLC cell proliferation and migration (Girault et al. 2014). Silencing of KV7.1 channels or pharmacological inhibition with clofilium or chromanol reduces cell growth and migration of A549 and NCI-H460 cells. Additionally, the authors found an overexpression of the KV7.1 channels in 17 of 26 tissue samples from lung adenocarcinoma patients. NaV Channels NaV channels are abundantly expressed in many cancers including lung cancer and contribute to cellular behaviors associated with metastasis (Nelson et al. 2014; Fraser et al. 2014; Djamgoz et al. 2019; Haworth and Brackenbury 2019). Two studies also demonstrate the inhibitory effect of the NaV blocker tetrodotoxin to reduce the invasion capacity of several NSCLC cells with a strong metastatic phenotype (Roger et al. 2007; Campbell et al. 2013). Furthermore, upregulation of NaV1.7 induced by EGF increased the invasiveness of NSCLC cells, suggesting that EGF/EGFR signaling controls the transcriptional regulation

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of NaV1.7 (Campbell et al. 2013). The authors show how the use of the EGFR blocker gefitinib impacts on NaV1.7 mRNA, protein, and INa, suggesting that EGF/EGFR signaling controls transcriptional regulation of Nav1.7 and numbers of functional channels at the cell surface via ERK1/2. In this context, it is interesting to note that there are many NaV targeting drugs in clinical use (Mantegazza et al. 2010). Examples include antiepileptic and antiarrhythmic drugs. Yet, so far it is not known with certainty whether these drugs have any impact on cancer patient overall survival (Fairhurst et al. 2015). To answer this question, a study was launched that searches the Clinical Practice Research Datalink (CPRD) for a potential correlation between exposure to NaV-inhibiting drugs and altered survival of patients with cancer (Fairhurst et al. 2016). In conclusion, voltage-gated ion channels are widely expressed in lung cancer. For several channels, it has been shown that they are involved in cellular processes underlying tumor progression such as proliferation, migration, or apoptosis. Some studies have already tested the therapeutic potential of combining channel blockers with chemotherapeutic drugs in NSCLC cells, to overcome the resistance or to make cells more sensitive to specific drugs (Luo et al. 2018; Choi et al. 2017). Thus, targeting voltage-gated ion channels might be a useful approach in the treatment of lung cancer.

2.3

K2P Channels

Two-pore-domain K+ (K2P) channels play an important role in controlling the negative resting potential of eukaryotic cells (Miller and Long 2012). Based on this very general function, they are involved in many physiological and pathophysiological processes ranging from development to neuronal excitability and cancer (Feliciangeli et al. 2015; Wiedmann et al. 2016). In fact, the expression of almost all K2P channels is dysregulated in cancer (Williams et al. 2013). K2P channels are activated by a variety of chemical and physical stimuli including pH, lipids, oxygen tension, and mechanical stretch. They are also molecular targets for neurotransmitters, G protein-coupled receptors, and volatile or local anesthetics (Goldstein et al. 2005). A detailed analysis of K2P channel expression in various cancer entities revealed dysregulated expression of several K2P channels in lung cancer (Williams et al. 2013). However, up to date there are only few studies examining the function of K2P channels in lung cancer cells. KCNK9, which encodes the K2P9.1 channel (TASK3) is overexpressed in 35% of tissues from lung cancer patients (Mu et al. 2003). For squamous lung cancer patients, overexpression of KCNK9 significantly correlates with a lower survival (Sun et al. 2016). Targeting K2P9.1 with a monoclonal antibody (Y4) decreases the cell viability and increases cell death of K2P9.1expressing Ben lung carcinoma and breast cancer cells (Sun et al. 2016). Administration of this antibody to mice also diminishes tumor growth of subcutaneous

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engraftments of Ben lung carcinoma cells and reduces lung colonization of intravenously injected breast carcinoma cells in mice. The acid- and oxygen-sensitive channel K2P3.1 (TASK-1) is expressed in some NSCLC cell lines, including A549 cells (Leithner et al. 2016). The authors reveal the functional relevance of this channel, by using hypoxia or the K2P3.1 inhibitor anandamide which induce the depolarization of A549 cells. Treating cells with siRNA against K2P3.1 leads to an increased apoptosis and reduced proliferation of A549 cells. An additional study shows that K2P3.1 is involved in the migration of A549 cells and promotes their epithelial mesenchymal transition, accompanied by increased expression of MMP-2, MMP-9, and vimentin as well as a loss of E-cadherin (Wang et al. 2018). All in all, the two K2P channels K2P3.1 or K2P9.1 are expressed and involved in the progression of lung cancer cells. Targeting K2P9.1 with an antibody obviously affects the progression of lung cancer cells and breast cancer cells in vitro and in vivo. Thus, the targeted use of antibodies could be a useful approach against cancer.

2.4

Ca2+-Activated Potassium Channels

Ca2+-activated K+ channels (KCa) are widely expressed in nearly all cell types, where they couple membrane potential and the intracellular Ca2+ concentration ([Ca2+]i). They are classified into three subfamilies, the large conductance KCa1.1 (BKCa), and the small conductance KCa2.1-3 (SK) as well as the intermediate conductance KCa3.1 (IK) (Berkefeld et al. 2010). In particular, KCa3.1 channels have been studied intensively in the context of cancer (reviewed in Mohr et al. 2019). KCa3.1 channels belong to a “10 K+ channel set,” comprising 5 upregulated and 5 downregulated K+ channel genes, which has predictive power with respect to the prognosis of patients with lung cancer (Ko et al. 2019).To the best of our knowledge, our group has been the only one to show the functional impact of the elevated KCa3.1 channel expression to NSCLC progression (Bulk et al. 2015, 2017). We observed that the increased KCa3.1 channel expression is due to a hypomethylated promoter of its KCNN4 gene. This hypomethylation strongly correlates with a poor survival of lung cancer patients and an aggressive phenotype of A549 NSCLC cells. In in vitro and in vivo experiments, we also observed that KCa3.1 silencing or inhibition with the KCa3.1 blockers senicapoc or TRAM-34 impacts several cellular processes such as adhesion, migration, invasion, proliferation, and tumor growth in xenografted mice. In conclusion, functional expression of KCa3.1 influences the cellular behavior of NSCLC cells. Furthermore, high expression of KCa3.1 correlates with the aggressiveness of NSCLC cells and with a poor prognosis of NSCLC patients and thereby, KCa3.1 could be a useful prognostic marker in NSCLC.

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Chloride Channels in Lung Cancer

Chloride channels are a functionally and structurally diverse group of membrane proteins. Several of them have been identified on a molecular level only quite recently (Jentsch and Pusch 2018). Chloride channels are permeable for various anions, including iodide, bromide, nitrates, phosphates and also negatively charged amino acids. They are crucial for the transepithelial transport and the control of water flow. According to their gating mechanisms, Cl channels can be classified as members of the voltage-dependent/gated CIC subfamily, Ca2+-activated Cl channels (CaCC), volume-regulated channels (LRRC8A/VRAC/VSOR), the cystic fibrosis transmembrane conductance regulator (CFTR), and the transmitter-gated GABA and glycine receptors. Since Cl channels are ubiquitously expressed in all eukaryotic cells, they are also connected to cancer cells including lung cancer cells. Application of the chemotherapeutic substance carboplatin or the protein kinase inhibitor staurosporine has been used to enhance apoptosis or the apoptotic volume decrease (AVD) in A549 cells (He et al. 2010). Apoptosis or AVD could be blocked with the chloride channel blockers, 4,40 -diisothiocyanostilbene-2,20 -disulfonic acid (DIDS), and 5-nitro-2-(3-phenyl propylamino)-benzoate (NPPB). Furthermore, the authors observed Cl currents with similar properties as hypotonicity-induced volume-sensitive Cl currents in A549 cells, when treated with carboplatin and staurosporine. This was seen as an indication that volume-sensitive chloride channels (VSOR) could be responsible for the carboplatin-induced apoptosis in A549 cells that causes the AVD process. Cisplatin was shown to have a similar effect in A549 cells (Min et al. 2011). Interestingly, the cisplatin-resistant A549/CDDP cells do not undergo AVD and have no VSOR currents, when treated with cisplatin. Using the histone deacetylase inhibitor trichostatin A, VSOR currents and an increased cisplatin-induced apoptosis can be partially restored, suggesting that an impaired activity of VSOR channels may be responsible for the cisplatin resistance in A549/CDDP cells. CIC-3 is described to be involved in the resistance of tumor cells to doxorubicin (DOX) and paclitaxel (PTX). Altered expression of ClC-3 results in an increased drug resistance to paclitaxel accompanied with an upregulation of the P-glycoprotein (P-gp) in drug-sensitive A549 or MCF-7 cells (Chen et al. 2019). Moreover, the authors demonstrate that ClC-3 is highly expressed in drug resistant A549/PTX and MCF-7/DOX cells. In addition to the VSOR channels, one more publication should be referred to which demonstrates that ligands of the sigma-1 receptor, an intracellular transmembrane protein of the endoplasmatic reticulum that has been characterized as a tumor biomarker, inhibit volume-regulated chloride channels in small cell lung cancer and T-leukemia cells (Renaudo et al. 2007). Sigma-1 receptor ligands inhibit the respective currents and cell cycle progression in SCLC cells. Some CaCC channels are connected to lung cancer. The anoctamin 1 channel (ANO1) is upregulated in different human lung cancer cell lines and also in tissues of lung cancer patients (Jia et al. 2015). This study also shows that silencing of ANO1 by small hairpin RNA decreases the proliferation, migration, and invasion of

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GLC82 and NCI-H520 lung cancer cells and reduces the tumor growth in xenografted mice. A recent study demonstrates that expression of ANO1 correlates with advanced tumor stage in NSCLC patients and predicts the recurrence after surgery (He et al. 2017). The cystic fibrosis transmembrane conductance regulator (CFTR) has been suggested to be a biomarker in NSCLC, since its expression is downregulated in NSCLC (Li et al. 2015). Additionally, the authors demonstrate that low CFTR expression correlates with advanced stage and lymph node metastasis and with a poor prognosis of NSCLC patients. Furthermore, the knockdown of CFTR in A549 NSCLC cells induces migration and invasion in vitro, and the number of metastatic foci and their size increases in the lungs of transplanted mice. Conversely, overexpression of CFTR suppresses the migration and invasion of A549 cells. A similar result was obtained by another group (Li et al. 2018a). This group also found that nicotine-induced cancer cell progression of A549 cells is accompanied by inhibiting CFTR, suggesting that CFTR may function as a tumor suppressor (Li et al. 2018b). Genetic variations in the CFTR gene are also suspected to modulate the risk of lung cancer (Li et al. 2010). Thus, genetic alterations in the CFTR gene may play a protective role in lung carcinogenesis. The methylation status in the CFTR gene was studied in one report. Here, the authors found that methylation of the CFTR gene is significantly enhanced in tissues of NSCLC patients and accompanied by low CFTR expression (Son et al. 2011). In their analysis, they also observed that methylation of the CFTR gene correlates with a poorer survival of younger patients (62 years), but not with that of older patients. An earlier classification of the chloride channel family contained several other proteins, which include the CLIC or the CLCA proteins. However, it has been shown that these are zinc-dependent metalloproteases with autoproteolytic activity and therefore not ion channels (Bothe et al. 2011; Gibson et al. 2005; Jentsch and Pusch 2018). CLIC proteins have been identified to play a role in Rho-regulated cortical actin dynamics as well as in vesicular trafficking and integrin recycling (Argenzio and Moolenaar 2016). Some of these proteins are linked to lung cancer. However, we will not discuss this any further because they are no Cl channels. In conclusion, several chloride channels are connected to lung cancer and play a role in the resistance to chemotherapeutics such as paclitaxel or doxorubicin. CFTR is suggested to act as tumor suppressor, since it is downregulated in lung cancer cells and its low expression correlates with a poor prognosis of NSCLC patients.

2.6

Nicotine Acetylcholine Receptors (nAChRs)

Cigarette smoking and the use of tobacco products is the cause of about 90% of lung cancer cases (Lemjabbar-Alaoui et al. 2015; Hecht 2003). One of the major components of tobacco is nicotine that activates nicotinic acetylcholine receptors (nAChRs). Beside nicotine, the nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)1-butanone (NNK) and N´-nitrosonornicotine (NNN) are also agonists of nAChRs

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(Grando 2014). nAChRs form a heterogeneous family of ion channels comprising different types of subunits (α and β). They can be found not only in neuronal, but also in non-neuronal cells such as bronchial epithelium and keratinocytes (Egleton et al. 2008). In combination to nicotine, nAChRs are connected to several diseases, specifically to cardiovascular diseases and to several cancer types including lung cancer. In the following, we will refer only to some recent studies about nAChRs and its implications to lung cancer, because this topic has been extensively reviewed in the past (Friedman et al. 2019; Grando 2014). Several studies reveal that nicotine induces several cellular processes of lung cancer cells. Through activation of α5-nAChR with nicotine, the migration and invasion capability of A549 cells is increased (Sun and Ma 2015). In contrast, silencing of α5-nAChR blocks the stimulatory effect of nicotine and suppresses migration and invasion of A549 cells. The inducible effect of nicotine on cell proliferation of A549 cells could also be inhibited by silencing of α5-nAChR (Zhang et al. 2017a, b). The authors also observed the same effect in H1299 NSCLC cells. Furthermore, the authors demonstrate that nicotine increased the expression levels of α5-nAChR, which correlates with the activation of the JAK2/ STAT3 signaling cascade. Silencing of α5-nAChR also inhibits the tumor growth in mice when they are exposed to nicotine (Sun et al. 2017). Furthermore, the authors demonstrate that high expression of α5-nAChR in NSCLC patients correlates with a shorter survival time. In addition to α5-nAChR, several other subunits of nAChR are related to lung cancer, especially the subunit α7-nAChR which is upregulated in tissue samples of NSCLC patients (Ma et al. 2019). Analysis from a data set of the Cancer Genome Atlas (TCGA) reveals that this upregulation of α7-nAChR correlates with an unfavorable prognosis for these NSCLC patients. Similar to studies with α5-nAChR, knockdown experiments or the pharmacological treatment with inhibitors for α7nAChR, such as α-bungarotoxin (α-BTX) suppresses proliferation, tumor growth in nude mice, migration, invasion, and EMT of NSCLC cells induced by nicotine (Zhang et al. 2016, 2017a, b). These responses are mediated by the MEK/ERK signaling pathway. Nicotine-induced proliferation of A549 cells also correlates with the activation of the AKT pathway (Mucchietto et al. 2018). Inhibition of either α7nAChR or α9-nAChR results in a suppression of AKT and ERK in nicotine-induced A549 cells, accompanied with a reduction in proliferation of these cells. In contrast to the above-mentioned tumor promoting effects of the α7-nAChR subunit, the truncated α7-nAChR form dupα7 elicits different effects. Nicotine or the nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) does not stimulate proliferation of A549 or SK-MES-1 cells stably expressing dupα7 (Cedillo et al. 2019). Nicotine and NNK also have no effect on the migration of these dupα7 overexpressing NSCLC cells and the tumor growth in mice of dupα7 overexpressing A549 cells is suppressed. In conclusion, nAChRs are also important players in the cellular processes underlying lung cancer progression and for the prognosis for lung cancer patients.

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3 Outlook Taken together, the work cited in this brief review leaves no doubt that ion channels are linked to lung cancer progression, and to steps of the metastatic cascade (Fig. 1). Most of these studies suggest that ion channels could serve as potential markers in lung cancer (Park et al. 2016; Li et al. 2015; Liu et al. 2018; Wu and Yu 2019) and several studies demonstrate that overexpression of some ion channels correlates with a lower survival rate of lung cancer patients (Wu and Yu 2019; Bulk et al. 2015). Furthermore, some authors found a correlation between channel expression and tumor stages in NSCLC (Li et al. 2015; He et al. 2017). All these studies by and large address diagnostic and predictive aspects of ion channels in lung cancer. Thus, it should be considered to exploit the altered channel expression for diagnostic purposes and utilize them as targets for non-invasive imaging approaches. First proof-of-principle studies have already been published (Lastraioli et al. 2015a, b; Brömmel et al. 2020). However, there is still a large gap of knowledge concerning the underlying mechanisms by which ion channels contribute to lung cancer progression. A few studies, for example, indicate that some ion channels are associated with lung cancer metastasis (Brackenbury 2012; Bulk et al. 2015, 2017). Thus, despite being the most frequent cause of cancer-related death, lung cancer falls short with respect to the knowledge on ion channels in its pathophysiology when compared with other tumor entities. A lot of further research is required to fully understand the role of ion channels in lung cancer.

Intravasation Primary tumor Proliferation/tumor growth TRPA1, TRPC1, TRPC3, TRPC4, TRPC6, TRPM2, Kv1.1, Kv1.3, Kv7.1, Kv9.3, Kv11.1, K2P3.1, K2P9.1, KCa3.1, ANO1, α5-nACHR, α7-nACHR, α9-nACHR

Adhesion

Metastasis K2P9.1

KCa3.1

CFTR

Extravasation Invasion TRPA1, TRPM2, Nav1.7, KCa3.1, ANO1, Kir2.3, α5-nACHR, α7-nACHR CFTR

KCa3.1

Migration TRPM7, K2P3.1, KCa3.1, ANO1, Kir2.3, α5-nACHR, α7-nACHR CFTR

Fig. 1 Ion channels involved in the steps of the metastatic cascade of lung cancer

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Today, the treatment options of lung cancer patients are manifold and became more effective, due to the molecular targeting. The side effects are generally better tolerated by patients with the application of monoclonal antibodies and small molecule tyrosine kinase inhibitors than those of conventional chemotherapy (Bittner et al. 2014). Yet, they are still significant. The contribution of ion channels to lung cancer has become evident so that the targeting of ion channels should be considered as an important therapeutic option, too. A great advantage in targeting ion channels is that numerous inhibitors already exist. Moreover, some inhibitors of particularly cancer-relevant channels have already been tested in clinical trials (for other indications) such as the KCa3.1 channel blocker senicapoc (ICA-17043 (2,2-bis (4-fluorophenyl)-2-phenylacetamide). It has a similar chemical structure as TRAM34, but has a higher affinity for KCa3.1 (Ataga et al. 2006; Stocker et al. 2003). Senicapoc went successfully into phase III clinical trials as a possible drug in sickle cell anemia treatment, but due to lack of clinical efficacy the study was terminated (Ataga et al. 2011). Beside this, senicapoc has also been proven as an effective KCa3.1 inhibitor in experimental cancer research, as shown by our own study. Here, we observed that tumor growth in xenografted mice transplanted with A549 NSCLC cells is significantly reduced when mice are treated with senicapoc (Bulk et al. 2015). Another group was able to find a similar result, but with the KV1.1 voltage-gated channel blocker dendrotoxin-κ (Jeon et al. 2012; Jang et al. 2011a). Currently, the TRPV6 inhibitor SOR-C13 is in the clinical trial of a phase I study and finds its usage in the treatment of advanced solid tumors. The best response was a 27% reduction in a pancreatic tumor (ClinicalTrials.gov Identifier: NCT03784677). Its usage is safe and well tolerated (Fu et al. 2017). A further interesting approach is a combined therapy of a chemotherapeutic agent together with an ion channel inhibitor, as already performed to induce apoptosis in A549 NSCLC cells using a T-type Ca2+ channel blocker for CaV3.1 in combination with a chemotherapeutic agent (Byun et al. 2016). A combined therapy might also be interesting to overcome the resistance of tyrosine kinase inhibitors as gefitinib (Jeon et al. 2012), or to reduce side effects of chemotherapeutics because the combination with channel modulators could allow a dose reduction. The therapeutic potential of combining chemotherapeutic drugs with ion channel modulators is supported by bioinformatic meta-analyses of microarray experiments obtained from ArrayExpress and Gene Expression Omnibus (GEO) databases. It is well known that such meta-analyses allow to summarize multiple individual estimates, typically obtained from different studies, weighing them by a key factor (Lee 2018; Ahn and Kang 2018). Using this approach, we compared the expression of ion channels in erlotinib-resistant lung cancer cells and sensitive ones and detected several differentially expressed ion channels (Balko et al. 2006; Zhang et al. 2012). Of course, the functional relevance of such results has to be verified by wet lab experiments. Nonetheless, they lend further support to our firm expectation that ion channel targeting will evolve as a novel therapeutic strategy in the treatment of lung cancer.

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Acknowledgements The authors would like to thank past and present members of our research group who all contributed to revealing the importance of ion channels in cancer. Lung cancer related work from our laboratory was supported by the Deutsche Krebshilfe (Grant number: 110261) and the Deutsche Forschungsgemeinschaft (GRK 2515/1, Chembion).

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Rev Physiol Biochem Pharmacol (2021) 181: 81–104 https://doi.org/10.1007/112_2020_34 © Springer Nature Switzerland AG 2020 Published online: 10 August 2020

Contribution and Expression of Organic Cation Transporters and Aquaporin Water Channels in Renal Cancer Giuliano Ciarimboli, Gerit Theil, Joanna Bialek, and Bayram Edemir Contents 1 Renal Cell Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Epidemiology and Risk Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Genetic Factors Associated with RCC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 RCC Subtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Grading of Renal Cell Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Diagnosis and Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Renal Transport Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Kidneys Function as a Filtration and Reabsorption Organ . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Transporters in Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Aquaporin Protein Family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Aquaporins in Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 AQP1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 AQP2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 AQP3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 AQP4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract The body homeostasis is maintained mainly by the function of the kidneys, which regulate salt and water balance and excretion of metabolism waste products and xenobiotics. This important renal function is determined by the action of many transport systems, which are specifically expressed in the different parts of G. Ciarimboli Medicine Clinic D, Experimental Nephrology, University Hospital of Münster, Münster, Germany G. Theil and J. Bialek Clinic of Urology, University Hospital, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany B. Edemir (*) Department of Medicine, Hematology and Oncology, Martin Luther University HalleWittenberg, Halle (Saale), Germany e-mail: [email protected]

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the nephron, the functional unit of the kidneys. These transport systems are involved, for example, in the reabsorption of sodium, glucose, and other important solutes and peptides from the primary urine. They are also important in the reabsorption of water and thereby production of a concentrated urine. However, several studies have shown the importance of transport systems for different tumor entities. Transport systems, for example, contributed to the proliferation and migration of cancer cells and thereby on tumor progression. They could also serve as drug transporters that could enable drug resistance by outward transport of, for example, chemotherapeutic agents and other drugs. Although many renal transporters have been characterized in detail with respect to the significance for proper kidney function, their role in renal cancer progression is less known. Here, we describe the types of renal cancer and review the studies that analyzed the role of organic cation transporters of the SLC22family and of the aquaporin water channel family in kidney tumors. Keywords Aquaporin · Organic cation transporter · Renal cancer

1 Renal Cell Tumors 1.1

Epidemiology and Risk Factors

Worldwide renal cancer was the 14th common cancer with more than 403,000 new cases in 2018 and accounted for 2.2% of all newly diagnosed cancer (Bray et al. 2018). Renal cell carcinoma (RCC) was associated with more than 175,000 deaths per year and remains one of the most lethal urological malignancies. By initial presentation around 15% of the patients have already metastases. Different factors influence cancer incidence and mortality. For example, the incidence rate of RCC is 4.5-fold higher in high/very-high developed regions, based on Human Development Index (HDI) versus low/medium HDI regions. The causes of RCC are not sufficiently understood, but lifestyle plays an important role. For example, around 30% smokers have increased risk to develop RCC compared to 15% for non-smokers; 6% of RCC deaths are associated with smoking (Cumberbatch et al. 2016; Dy et al. 2017). Obesity is another major risk for RCC development. Worldwide 26% of all kidney cancer cases are associated with a high BMI (Arnold et al. 2015). Each 1 kg/m2 gain in body mass index (BMI) corresponded with a 4% increase and a 5 kg/m2 gain in BMI with a 25% increase risk for RCC development (Wang and Xu 2014). Beside obesity, hypertension is also a risk factor for RCC. Individuals with a history of hypertension were associated with 67% increased risk of developing RCC (Hidayat et al. 2017). Surprisingly, alcohol consumption may reduce the risk for development of RCC (Koppes et al. 2005; Lee et al. 2007).

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1.2

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Genetic Factors Associated with RCC

Von Hippel-Lindau Syndrome (VHL syndrome) is an inherited disease caused by mutations of VHL gene. In about 70% of all clear cell RCC (ccRCC) mutations in the VHL gene can be detected (Maher 2018). Inactivation of VHL leads to stabilization of hypoxia factor 1 a (HIF1a) which induces the expression, for example, of proangiogenic proteins, like Vascular Endothelial Growth Factor (VEGF) and angiogenesis (Tsang and Sharma 2018). The Birt-Hogg-Dubé syndrome (BHD syndrome) occurs as a consequence of folliculin (FLCN) gene mutation. BHD-associated renal carcinoma occurs in different subtypes like chromophobe RCC, ccRCC, or oncocytomas (Schmidt and Linehan 2016). Hereditary papillary renal carcinoma (pRCC) appears as rare, bilateral, multifocal papillary type 1 renal tumor that is related with mutations in the hepatocyte growth factor receptor (MET) gene. The type 2 pRCC is a hereditary leiomyomatosis, which is characterized by mutation in the fumarate hydratase (FH) gene. Other gene mutations associated mostly with pRCC are related to Phosphatase and Tensin homolog 1 (PTEN1) gene (Maher 2018). Chromosome 3 translocations and hereditary BRCA1 associated protein-1 (BAP1) tumor syndrome are usually correlated with ccRCC and succinate dehydrogenase subunit-related loss of function mutations are associated with various types of renal carcinoma (Maher 2018).

1.3

RCC Subtypes

The most common form with up to 75% of all RCCs is ccRCC. Originally, it arises from the proximal tubule epithelial cells and is highly vascularized (Makhov et al. 2018). The cytoplasm of these neoplastic cells is lipid- and glycogen-rich, it appears microscopic clear; however, the lesion may also contain cells with eosinophil granular cytoplasm (Muglia and Prando 2015). Typical for the ccRCC are loss of VHL protein expression due to loss of function mutation within the VHL gene or due to methylation of its promoter. Also Loss of Heterozygosity (LOH) at 3p25 is associated with ccRCC. Around 15% of patients with ccRCC develop metastases within the lung, liver, bones as well as lymph nodes (Muglia and Prando 2015). Patients with ccRCC have worse prognosis than patients with papillary and chromophobe RCC. The second most common variant of the RCC, with about 10% of all RCC, is papillary RCC (pRCC). It is divided into two subtypes (subtype 1 and 2) that differ in morphological characteristics and clinical prognosis (Muglia and Prando 2015). Subtype 1 pRCC is characterized by a single layer of basophilic cells with scanty cytoplasm and hyperchromatic low nuclear grade. In the subtype 2 the cells are arranged as pseudostratified layer and show an eosinophilic cytoplasm and higher nuclear grade (Muglia and Prando 2015; Warren and Harrison 2018). Typically

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pRCC appears as hypovascular tumor compared to the surrounding parenchyma. Subtype 1 has a better prognosis compared to subtype 2 (Muglia and Prando 2015). Chromophobe RCC (chRCC) with around 5% is the third common subtype of RCC and has a very good prognosis (Peyromaure et al. 2004). Pathohistologically, chRCC displays large cells with pale reticulated cytoplasm, perinuclear halos, and hypovascularization of the tumor. ChRCC is associated with BHD syndrome (Schmidt and Linehan 2016). The prognosis gets worse in the presence of poor prognostic factors like sarcomatoid transformations (Muglia and Prando 2015). Other rare RCC subtypes include multilocular cystic renal neoplasm with a very good prognosis (Warren and Harrison 2018; Muglia and Prando 2015). Hereditary leiomyomatosis RCC (hlRCC) is a very aggressive form which is related to nonrenal-leiomyomatosis (Moch et al. 2016; Schmidt and Linehan 2016). The collecting duct RCC (cdRCC) also known as Bellini duct carcinoma is a very aggressive form with poor prognosis (Muglia and Prando 2015; Sui et al. 2017). Renal medullary RCC, a rare and aggressive form which originates from collecting duct cells, is frequently observed in Afro-Americans and is usually associated with sickle cell trait (Sigauke et al. 2006; Cheng et al. 2008; Ohe et al. 2018; Msaouel et al. 2019). Other RCC forms include microphthalmia transcription factor translocation RCC, succinate dehydrogenase deficient RCC, mucinous tubular and spindle cell RCC or tubulocystic RCC (Schmidt and Linehan 2016; Moch et al. 2016; Wang and Rao 2018; Muglia and Prando 2015; Sarungbam et al. 2019). However, not all RCC (up to 6%) can be classified and therefore, they are categorized as RCC unclassified. Patients bearing unclassified tumors have poor prognoses, as this category includes several histologically heterogeneous RCC subtypes with high mortality rates (Muglia and Prando 2015).

1.4

Grading of Renal Cell Carcinoma

The validation of prognostic factors for each type of RCC is of major importance (Moch et al. 2016). The WHO and the International Society of Urological Pathology introduced a new grading system based on Fuhrman classification distinguishing the unique RCC subtypes; however, the investigations were only performed for ccRCC, pRCC, and chRCC (Delahunt et al. 2019) (Table 1). The analysis determined that for ccRCCs and pRCC focal nucleolar grade is related to 5-year survival rate and the nuclear size is prognostic only for ccRCC. For chRCC none of the parameters correlated with clinical outcome (Moch et al. 2016).

1.5

Diagnosis and Therapy

Early stage RCC is mainly asymptomatic and only in more advanced stages the RCC may display clinical symptoms. The “classic triad” of symptoms like hematuria,

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Table 1 The World Health Organization/International Society of Urological Pathology grading system for clear cell and papillary renal cell carcinoma (Delahunt et al. 2019) Grade 1 Grade 2 Grade 3 Grade 4

Cell nucleoli absent or inconspicuous and basophilic at 400
magnification Cell nucleoli conspicuous and eosinophilic at 400
magnification and visible but not prominent at 100
magnification Cell nucleoli conspicuous and eosinophilic at 100
magnification Tumors showing extreme nuclear pleomorphism, giant tumor cells and/or the presence of any proportion of tumor with sarcomatoid and/or rhabdoid dedifferentiation

flank pain, and abdominal mass correlate with a locally advanced or metastatic RCC. Since physical check-ups has a limited role in diagnosis of RCC, palpable abdominal mass, varicocele, or bilateral lower extremity edema should always be followed by imaging for retroperitoneal neoplasia (Capitanio and Montorsi 2016). Routine diagnostic blood test (serum creatinine, glomerular filtration rate (GFR), complete cell blood count, erythrocyte sedimentation rate, liver function, alkaline phosphatase, lactate dehydrogenase, serum corrected calcium) might be altered by RCC. So far unfortunately a key biomarker detectable in blood is still not available. RCC are frequently diagnosed by means of non-invasive radiological techniques such as ultrasonography, computed tomography (CT). The CT imaging techniques apply for detecting and characterizing renal masses, tumor extension, and condition of the adrenal glands and other solid organs. Since the accuracy and safety of renal biopsy is low, its current role has been limited in decision on treatment of renal cancer. The use of 11C-choline-positron emission tomography (PET)/CT has been found to be useful for staging and restaging of renal cell carcinoma patients and useful in diagnosis and follow-up (Nakanishi et al. 2018). PET analysis performed with 18F fluorocholine, the fluorinated analogue of 11C-choline, suggested that the level of 18F fluorocholine transporter (organic cation transporter 2- OCT2) expression influences the renal tissue accumulation of this marker. Since OCT2 expression can vary depending on the presence or not of renal cancer, 18F fluorocholine PET may be useful for renal cancer detection (Visentin et al. 2018). Currently no recommendation exists as standard imaging in the diagnosis and staging of RCC (Escudier et al. 2019). The major treatment of localized renal tumors remains surgery. The Partial nephrectomy (PN), also called nephron sparing surgery, is recommended for tumors in the size up to 10%, cBioPortal, Table 1).

2.1.3

ABCGs

Since the detection of BRAFV600E mutation in 40–60% of melanomas, the clinical treatment with BRAF-inhibitors as vemurafenib (PLX-4032) or dabrafenib has emerged as a successful strategy (Hauschild et al. 2018). Expression of ABCG2 transporter in intestinal epithelial cells was found to reduce the early intestinal uptake of vemurafenib. Furthermore, the expression of both ABCB1 and ABCG2 at the blood-brain barrier limited the penetration of vemurafenib into the brain (Durmus et al. 2012). Further in vivo experiments showed that inhibition of

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ABCB1a/1b and ABCG2 elevated plasma levels and accumulation of vemurafenib in brain tissue of wild-type mice to the levels of Abc1a/1b/ Abcg2/ knockout mice (Durmus et al. 2012). Thus, the bioavailability and the accumulation of vemurafenib in brain tissue of metastatic melanoma were reduced (Wu and Ambudkar 2014). ABCG2 was furthermore shown to mediate resistance to vemurafenib in BRAFV600E melanoma cells (Wu et al. 2013; Wu and Ambudkar 2014).

2.2

ANOs (Anoctamins)

The TMEM16 family of membrane proteins comprises ten members in the human genome, but only the first two (ANO1, ANO2) were unambiguously shown to conduct calcium-activated chloride currents. Anion conductance and a predicted topology of eight transmembrane segments inspired the family name, but all other members seem to lack channel function and rather have lipid scramblase activity (Whitlock and Hartzell 2017). Here, we focus exclusively on the channel-forming proteins ANO1 and ANO2. Recent cryo-electron microscopy analysis showed ten transmembrane segments in ANO1/2 (Paulino et al. 2017). Expression of ANO1 (DOG-1, ORAOV2) channel protein is tightly linked to various cancer types (Wanitchakool et al. 2014). Thus, before elucidation of the channel function, the protein was already known as being overexpressed in gastrointestinal stromaderived tumors (GIST), pancreatic cancer, oral cancer, and head and neck squamous cell carcinoma (HNSCC), but does not seem to have a role in melanoma. Synonym names like DOG-1 (discovered on GIST-1) and ORAOV2 (oral cancer overexpressed 2) refer to this expression in cancer. While monoclonal ANO1 antibodies were described as valuable tool for the differential diagnosis of GIST, no immunostaining was detectable in 67 melanoma samples (Miettinen et al. 2009). Reduction of ANO1 expression in melanoma was also observed by in silico expression analysis, revealing about fourfold lower mRNA expression in melanoma samples compared to nevi (D’Arcangelo et al. 2019). No publications focusing on ANO2 in melanoma are available today; however a high mutation rate (>10%) was observed analyzing public data for melanoma (Table 1, cBioPortal). For both ANO1 and ANO2, mRNA expression was found to correlate negatively with patient prognosis analyzing available public data (Table 1).

2.3

AQPs (Aquaporins)

Aquaporins (AQPs) are integral membrane proteins, which mainly facilitate the transport of water across the plasma membrane. They are characterized by six membrane-spanning alpha-helical segments with both carboxylic and amino

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terminals on the cytoplasmic side. The superfamily of aquaporins comprises 17 genes (AQP0–AQP16) in vertebrates (Finn et al. 2014). Aquaporins are expressed in high-grade tumor cells of different tissue origins and may contribute to angiogenesis and cell migration. In melanoma cells, expression of AQP-1, AQP-3, AQP-4, AQP-5, AQP-7, AQP-8, AQP-9, and AQP-11 was reported (Gao et al. 2012). AQP1 (CHIP28) protein expression in melanoma was found associated with BRAFV600 mutation and with adverse prognosis (Imredi et al. 2016). Its expression in primary melanomas was also suggested as a predictive marker for cerebral melanoma progression (Imredi et al. 2018). In B16 mouse melanoma models, AQP1 expression increased lung metastases (Hu and Verkman 2006), and intratumoral injections of AQP1 siRNA resulted in reduced tumor size, associated with reduced angiogenesis (Nicchia et al. 2013). Finally, lung metastasis was inhibited by AQP1 siRNA, which was related to induced apoptosis in course of hypoxic conditions in tumors due to prevented angiogenesis (Simone et al. 2018). On the contrary, a recent in silico analysis suggested an almost fourfold downregulation of AQP1 in melanoma compared to nevi (D’Arcangelo et al. 2019). AQP3 expression was reported in melanocytes and melanoma cells (Bakry et al. 2016). In a meta-analysis for different progression markers, AQP3 has been suggested for a melanoma metastasis signature (Timar et al. 2010). Both overexpression of AQP3 and AQP9 resulted in increased chemoresistance in melanoma cells, as shown for arsenite. Thus, AQP3 and AQP9 inhibited apoptosis, which was partly explained by downregulation of p53 and upregulation of anti-apoptotic Bcl-2 and XIAP (Gao et al. 2012). Analyzing available public data, expression of AQP1 and AQP9 was found to correlate with bad patient prognosis (Table 1). On the other hand, reduced mRNA expression of AQP3 (tenfold) and of AQP9 (twofold) in melanoma samples as compared to nevi was suggested by a recent in silico analysis (D’Arcangelo et al. 2019). Also in a gene expression profile analysis of primary and metastatic melanoma, downregulation of AQP3 was found in some metastases (Riker et al. 2008).

2.4

ASICs (Acid-Sensing Ion Channels)

The degenerin/epithelial sodium ion channel superfamily (DEG/ENaC) includes the amiloride-sensitive epithelial sodium channel (ENaC), described in the chapter on SCNN1s, as well as acid sensitive ionic channels (ASIC). ENaC and ASICs mediate Na+ influx, which supports typical cancer cell characteristics, such as cell proliferation, migration, and invasion (Xu et al. 2016b). Thus, ASIC1-5 are upregulated in various cancer types (Zhu et al. 2017). Expression of ASIC1, 2, and 5 was reported in some melanomas (Table 1), whereas normal melanocytes lack ASIC expression. So far, no correlation of expression and prognosis has been suggested. Mutation rates of ASIC proteins in melanoma appear as rather low (4 mm thickness), strong immunostaining for KCNH2 was found, which was significantly weaker in thin melanomas and in nevi (Arcangeli et al. 2013). Thus, KCNH2 appears as a candidate biomarker for aggressive melanoma. The functional relevance of KCNH2 for melanoma progression waits to be

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elucidated, but any pharmacologic intervention with this channel as putative therapy seems excluded, given the crucial relevance of KCNH2 for cardiac repolarization. KCNH7 (KV11.3, HERG3) was reported to be expressed in melanoma cells. Interestingly, stimulation of KCNH7 with a small-molecule activator induced autophagy and senescence in A375 melanoma cells (Perez-Neut et al. 2016). According to public databases, information on other members of the KCNH family is available. Thus, KCNH5 and KCNH7 were shown to have a high mutation rate (15.5% and 12.5%, respectively), and the expression of KCNH2, KCNH3, and KCNH8 were correlated with a better prognosis, whereas expression of KCNH6 was linked to worse prognosis (Table 1).

2.12.3

KCNJs

The KCNJ subfamily (KCNJ1-18) encodes so-called inward rectifier K+ channels (Kir) and comprises structurally relatively simple channels with just two transmembrane segments per subunit. Accessory subunits, e.g., the sulfonylurea receptors in KCNJ8 (Kir6.1) and in KCNJ11 (Kir6.2), can allow for a more complex regulation, such as adaption to the cytosolic ATP/ADP balance. Recent studies showed differential gene expression of KCNJ1, KCNJ10–KNCJ16, and KCNJ18 in melanoma versus nevi. Whereas KCNJ13, 15, 18, and 12 are downregulated, KCNJ2 is upregulated in melanomas versus benign nevi (D’Arcangelo et al. 2019). KCNJ channels were determined as functionally relevant in cervical cancer (VazquezSanchez et al. 2018) and in glioma (Huang et al. 2009), where they may target cell proliferation via ERK signaling. In melanoma, however, no significant roles of KCNJ channels were reported so far. According to public databases, expression of KCNJ3, J8, J12, and J13 was correlated with worse prognosis. Most family members reveal a relatively low mutation rate in melanoma; only KCNJ8 mutations may correlate with a better prognosis (Table 1). Of note, 17% of the KCNJ8 mutations were G417E/R.

2.12.4

KCNKs

The subfamily KCNK comprises 15 channel-forming proteins, characterized by 4 transmembrane segments forming two pore-lining elements per subunit. Assembly of just two of these subunits is sufficient to form a K+ channel with the typical fourfold symmetry. This unique structure inspired the names “two-pore” or “tandem-pore” channels (K2P). Several members of this subfamily have already been implicated in tumor formation, e.g., genomic amplification of KCNK9 (K2P9.1, TASK3) was found in breast cancer, resulting in its overexpression and promotion of cancer cell survival (Mu et al. 2003). This oncogenic potential of KCNK9 in breast cancer was experimentally shown to require the formation of functional channels (Pei et al. 2003). An in silico analysis of microarray expression data for KCNK genes in cancer versus their corresponding normal tissues implied that

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KCNK9 overexpression is not very common in human cancers, including melanoma (Williams et al. 2013). A recent study has indicated downregulation of KCNK1, KCNK2, and in particular KCNK7 (K2p7.1) in melanoma in comparison to melanocytes (D’Arcangelo et al. 2019). In contrast, KCNK1 (K2P1.1) was overexpressed in 12 of 20 other cancer types (Williams et al. 2013). This in silico expression study did not identify any KCNK gene to be overexpressed in melanoma, while four genes (KCNK1, KCNK5, KCNK6, KCNK7) were found underexpressed as compared to nevus cells. Even when KCNK channels are not upregulated in melanoma, they may be of functional relevance. Thus, knockdown studies suggested a pro-oncogenic and pro-survival role of KCNK9 in melanoma (Kosztka et al. 2011). Immunostaining has shown its intracellular locations around the nucleus in melanoma cells in contrast to normal melanocytes (Pocsai et al. 2006). In WM35 melanoma cell line, KCNK9 was located in mitochondria (Kosztka et al. 2011; Nagy et al. 2014), and its knockdown resulted in caspase-dependent as well as in caspase-independent apoptosis induction (Nagy et al. 2014). Given that KCNK9 is also expressed in normal melanocytes, it remains in question whether pharmacologic intervention may offer a realistic therapeutic strategy. According to public databases, increased expression of KCNK2 and KCNK12 in melanoma was correlated with worse prognosis (Table 1). Mutations in KCNK family members were relatively rare. However, mutations in KCNK5, KCNK9, and KCNK13 were linked to a better prognosis of melanoma patients (Table 1). Particular mutations observed were D104N in KNCK9 (18%) and G123E in KCNK13 (13.5%).

2.12.5

KCNMs

KCNMA1 (KCa1.1, BK, SLO) encodes a K+ channel that combines voltagedependent and Ca2+-dependent activation. At resting cytosolic Ca2+ levels, extreme depolarization would be needed to open the channel, but upon a rise in intracellular Ca2+ concentration, the threshold for activation shifts to more negative voltages. As a unique structural feature, the typical 6TM topology is extended by a unique seventh transmembrane helix, the S0 segment, preceding the transmembrane helices S1–S6. The unusual large single channel conductance of KCNMA1 channels inspired the synonym name BK, for “big conductance.” Beyond known physiological functions, such as the regulation of smooth muscle tone, KCNMA1 channels were commonly detected in several human cancers, e.g., in renal carcinoma and breast cancer, where they have been suggested to be of functional and predictive relevance (Rabjerg et al. 2015; Schickling et al. 2015). Functional relevance of KCNMA1 (KCa1.1) was also described for melanoma. Thus, KCNMA1 mRNA is a target of miRNA miR-211, and ectopical expression of miR-211 in melanoma cells reduced KCNMA1 expression associated with decreased cell proliferation and invasiveness (Mazar et al. 2010). Comparable effects were seen after shRNAmediated knockdown of KCNMA1.

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Strong expression of KCNMB3 was correlated with poor prognosis of melanoma patients (Table 1), whereas the only rarely found mutations in KCNMB3 (0.9%) were linked to a better prognosis. The most frequent mutation in KCNMB1 was E143K (18%).

2.12.6

KCNNs

The KCNN subfamily of K+ channels comprises four members with a 6TM subunit topology. In contrast to voltage-gated 6TM channels, all four are largely insensitive to membrane voltage, but activated by cytosolic Ca2+, sensed by calmodulin at the cytosolic side of the channels. Functional expression of KCNN1 (KCa2.1), KCNN2 (KCa2.2), and KCNN4 (KCa3.1) was earlier described in IGR1 melanoma cells (Meyer et al. 1999), and the recent in silico analysis of ion channel expression in melanoma revealed overexpression of KCNN2 and KCNN4 in melanomas versus nevi and melanocytes (D’Arcangelo et al. 2019). ROC (receiver operating characteristic) analysis indicated a diagnostic ability of KCNN2 expression to discriminate melanoma from nevi (AUC ¼ 0.91). KCNN2 (KCa2.1) appears as promising therapeutic target for melanoma (D’Arcangelo et al. 2019). Thus, siRNA-mediated silencing of KCNN2 strongly increased the anti-proliferative effects of the antifungal drug miconazole in A375 melanoma cells (D’Arcangelo et al. 2019). Even higher relevance may be suggested for KCNN2 in a hypoxic tumor environment, due to the finding that KCNN2 mRNA levels and KCNN2 (KCa2.1) currents were increased in IGR1 melanoma cells under hypoxic growth conditions (Tajima et al. 2006). Functional and possibly therapeutic relevance in melanoma cells was implicated for KCNN4 (KCa3.1) channels. Expression of KCNN4 in melanoma cells was described in mitochondria, and its inhibition resulted in mitochondrial membrane hyperpolarization and early activation of the pro-apoptotic Bcl-2 protein Bax. The selective inhibitor TRAM-34 did not induce apoptosis by itself, but synergistically enhanced sensitivity to TNF-related apoptosis-inducing ligand (TRAIL) and overrode TRAIL resistance in a large panel of melanoma cell lines (Quast et al. 2012). The death ligand TRAIL represents a promising antitumor strategy providing the overcoming of the problem of inducible resistance (Eberle 2019). Combination of TRAM-34 and TRAIL resulted in massive activation of mitochondrial pro-apoptotic pathways, as seen by loss of mitochondrial membrane potential and release of the mitochondrial factors cytochrome c, AIF (apoptosis-inducing factor) and Smac (second mitochondria-derived activator of caspase). Apoptosis induced by TRAIL/ TRAM-34 overrode two apoptosis rheostats, consisted of (1) Bax and Bcl-2 as well as of (2) Smac and XIAP (X-linked inhibitor of apoptosis protein). Thus, apoptosis was strongly diminished by Bax or Smac knockdown as well as by Bcl-2 or XIAP overexpression (Quast et al. 2012). As both TRAIL and KCNN4 inhibitors have shown only minor side effects in clinical trials, the application of this combination in melanoma therapy appears as conceivable.

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Selective BRAF inhibition as by the inhibitors vemurafenib and dabrafenib represents a highly successful targeted therapy in BRAF-mutated melanoma. However, tumor relapse and therapy resistance have remained as major problems, which may be addressed by combination with other pathway inhibitors (Flaherty et al. 2014). Of particular interest was that combination with TRAM-34 was highly effective in melanoma cell lines in combination with vemurafenib. Thus, apoptosis was significantly enhanced, and cell viability was decreased, and also acquired resistance in vitro was overcome. The combination resulted in enhancement of mitochondrial pro-apoptotic pathways and caspase-3 activation (Bauer et al. 2017). In addition to regulation of apoptosis, proliferation assays in A-375 melanoma cells revealed that the combination of TRAM-34 with PI3K-pathway inhibitors (LY294002, ZSTK474) had an even stronger synergistic potential than combination of TRAM-34 with MAPK pathway inhibitors (PLX4720, PD98059; Buttstädt, N. and Schönherr, R., unpublished). Thus, the inhibition of KCNN channels appears as a suitable combination for different therapeutic strategies in melanoma, and KCNN4 may only be one example. According to public databases, KCNN3 expression was linked to worse prognosis. On the other hand, it remains puzzling that the databases also suggest a correlation between KCNN2 and KCNN4 expression in melanoma and improved prognosis (Table 1). More work is needed to clearly define the roles of KCNN channels in melanoma.

2.12.7

Further KCN Channels

Due to in silico analysis, also downregulation of KCND3 and KCNS3 in melanoma as compared to melanocytes was suggested (D’Arcangelo et al. 2019). Concerning the possible, additional roles of KCNBs, KCNGs, KCNIs, KCNQs, KCNTs, KCNUs, and KCNVs, no information on melanoma was found in the literature.

2.13

MAGT1 (Magnesium Transporter 1)

MAGT1 is a magnesium cation transporter protein localizing in the cell membrane, which serves an additional putative function in N-glycosylation based on its association with N-oligosaccharyl transferase (Cherepanova et al. 2014; Kelleher et al. 2003). According to public databases, strong overexpression of MAGT1 is reported in melanoma, and high expression further correlated with poor prognosis ( p ¼ 0.0009; Table 1).

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MCUs (Mitochondrial Calcium Uniporters)

MCUs serve as mitochondrial calcium uniporters. An important mechanism for maintaining intracellular Ca2+ homeostasis is based on the uptake of accumulating Ca2+ into the mitochondrial matrix. Ca2+ uptake into mitochondria is driven by the negative potential inside the mitochondrial membrane, according to the chemiosmotic hypothesis (Mitchell and Moyle 1967). Initially, Ca2+ ions pass the outer mitochondrial membrane via voltage-dependent, anion-selective channels (VDACs; please see there) into the intermembrane space (Colombini 2016). Secondly, Ca2+ is imported to the matrix via the mitochondrial calcium uniporter complex (MCUC). This complex is composed of the pentameric pore-forming subunit (MCUa) (Baughman et al. 2011), the negative MCU regulator β-subunit (MCUB) (Kamer and Mootha 2015), an essential MCU regulator (EMRE), the regulatory subunit of the mitochondrial Ca2+ uptake 1 (MICU1 and 2) (Plovanich et al. 2013), mitochondrial calcium uniporter regulator 1 (MCUR1), and the regulator SLC25A23 (Mallilankaraman et al. 2012). Taken-up Ca2+ activates dehydrogenases of the tricarboxylic acid (TCA) cycle, maintaining the adequate ATP-level and allowing cell proliferation (Bustos et al. 2017). MICU1 is expressed in most malignant tissues as well as in melanoma (proteinatlas.org 2019), and MICU1 mutations are frequent in melanoma (Vultur et al. 2018). Knockdown of the ribosomal protein S3 (RpS3) led to reduced expression of MICU1 and decreased localization of MICU1 in the mitochondrial membrane. Further, RpS3 knockdown promoted the opening of mitochondrial transition pore and the flooding of Ca2+ into the mitochondria, resulting in apoptosis induction in A375 melanoma cell line (Bustos et al. 2017; Tian et al. 2015). However, Ca2+ may exert a dual (pro-death and pro-survival) function in tumor cells depending on the experimental conditions. Thus, Ca2+ chelators as well as the MCU inhibitor ruthenium 360 decreased mitochondrial Ca2+ levels and sensitized tumor cells for TRAIL-induced cell death (Takata et al. 2017). MCU, MICU1, and MICU2 were found to be strongly expressed in melanoma samples based on public databases (Table 1). Here, expression of MICU1 is correlating with better and expression of MICU2 with worse survival of melanoma patients.

2.15

MPCs (Mitochondrial Pyruvate Carriers)

MPCs (MPC1 and MPC2) are located in the inner mitochondrial membrane. MPCs are critical for cellular homeostasis, as the transport of pyruvate from the cytosol into the mitochondrial matrix is central for further processing of pyruvate in the tricarboxylic acid cycle. As MCPs were shown to be involved in several human diseases, they are thought to be attractive druggable molecules. MCP1 and 2 were speculated to form large protein complexes for active function; however, recent studies in yeast support the formation of heterodimers as active systems, whereas homodimers

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appeared as inactive (Tavoulari et al. 2019). Based on Warburg effects and on known metabolic changes in melanoma, alterations in MPC expression could be of high relevance for melanoma progression. Based on human proteinatlas data, expression of both MCP genes is upregulated in melanomas compared to melanocytes (Table 1, proteinatlas.org). Interestingly, although acting as heterodimers, MPC2 mRNA is less expressed in relation to MPC1. No correlation of gene expression and survival of melanoma patients were found so far, and both genes are only rarely mutated in melanoma (Table 1). Transcriptional repression of both MPC1 and MPC2 promoters seems to depend on C-terminal binding protein 1 (CtBP1) (Deng et al. 2018). Downregulation of MPC1 and 2 resulted in proliferation and migration of melanoma cells supported by enhanced cytoplasmic NADH level. This is in agreement with findings in other kinds of tumors, where low expression of MPC1 and 2 was correlated to enhanced cell proliferation and migration (Takaoka et al. 2019; Tang et al. 2019; Zhou et al. 2017). However, downregulation of CtBP1 was described and linked to melanoma progression (Winklmeier et al. 2009). Due to these partly contrary findings, more studies on MPC1 and 2 are necessary to finally understand their function and significance in melanoma. Recently, another MPC1-like protein (MPC1L) was described, which shares high homology and functional equivalence with MPC1. In contrast to MPC1, its expression pattern is highly tissue-specific, only found in testis and sperm cells (Vanderperre et al. 2016). There is so far no data available showing MPC1L expression in melanoma.

2.16

MRS2

The human magnesium transporter MRS2 is located in the inner mitochondrial membrane. In yeast, MRS2 was identified as an essential component of the mitochondrial Mg2+ influx system, whereas the physiological role of human MRS2 still remains unclear. An association with multidrug resistance was suggested for gastric cancer (Chen et al. 2009a). No publications on melanoma are available until today, although TCGA data suggests a negative prognostic role of MRS2 ( p < 0.05; Table 1).

2.17

MTCH1s (Mitochondrial Carrier)

The genes of the mitochondrial carrier homologs (MTCH1, MTCH2; also named SLC25A49, SLC25A50) encode members of a mitochondrial carrier family. MTCH1 is an outer mitochondrial membrane protein, which can mediate mitochondrial depolarization and apoptosis induction upon its overexpression, as suggested by activation of the permeability transition pore. Whereas most mitochondrial

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pro-apoptotic pathways are controlled by the family of pro- and anti-apoptotic Bcl-2 proteins and are finally mediated through the pro-apoptotic family members Bax or Bak, MTCH1-induced apoptosis appeared as an independent pathway and not mediated by these two central apoptosis agonists (Lamarca et al. 2008). Also MTCH2 was localized in the outer mitochondrial membrane, where it may function as a receptor of the truncated (activated) form of the pro-apoptotic BH3-only protein Bid, which represents a crosslink between extrinsic, death ligand-induced and intrinsic, mitochondria-driven, pro-apoptotic pathways (Raemy et al. 2016). Significant MTCH1 expression was reported in melanomas, where it correlated to bad prognosis (Table 1). However, no detailed studies on the role of MTCH1 and MTCH2 are so far available for melanoma.

2.18

ORAIs (Calcium Release-Activated Calcium Modulator, ORAI1-3)

Store-operated Ca2+ entry (SOCE) is a well-studied example of the functional interplay between endoplasmic reticulum (ER) and plasma membrane. Release of Ca2+ ions from the ER into the cytosol typically causes a moderate and transient rise of cytosolic Ca2+. In 1992, a Ca2+ current across the plasma membrane was identified that followed Ca2+ release from the ER and allowed a larger and more sustained response (Hoth and Penner 1992). It is now known that this interplay between the two cellular compartments requires the complex physical interaction between channel proteins (ORAI) in the plasma membrane and a transmembrane Ca2+ sensor protein in the ER (STIM) (Fahrner et al. 2017). Three ORAI genes (ORAI1-3, TMEM142A-C) and two STIM (STIM1, STIM2) genes in the human genome show a wide expression across most tissues, reflecting their physiological relevance, e.g., in the cardiovascular system, in muscle cells, or in immune cells. The expression and functional relevance of the Orai-STIM interaction is now also well established in many cancer types (Chalmers and Monteith 2018; Fiorio Pla et al. 2016). SOCE is also an important step in normal and malignant melanocytes, but the contribution of the individual ORAI and STIM genes seems to vary with the studied system. Thus, high expression of the subunits Orai1 and STIM2 was found in melanocytes (Stanisz et al. 2012) as well as in melanoma cells (Stanisz et al. 2014), while other reports described mainly Orai1 and STIM1-dependent SOCE in melanoma (Sun et al. 2014; Umemura et al. 2014). The functional consequences of SOCE channels in melanoma are diverse, but most studies agree on a promoting effect of SOCE on cell proliferation as well as on migration and invasion (Stanisz et al. 2014, 2016; Sun et al. 2014; Umemura et al. 2014). However, the correlation between the amplitude of SOCE and a downstream effect is not necessarily simple and linear. The SOCE-dependent support of invadopodium formation that promotes the invasive phenotype of melanoma cells was found to rely on oscillating cytosolic

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Ca2+ concentrations (Sun et al. 2014). As may be expected for a second messenger like Ca2+, having multiple connections to cellular signaling pathways, various downstream effectors can be relevant in tumor cells. A common characteristic in melanoma as well as in other cancer cells is the activation of transcription factor NFAT as a major downstream effector of SOCE (Chalmers and Monteith 2018). Orai2, Orai3, STIM1, and STIM2 proteins were found expressed in the majority of melanomas. Orai1 was found in about half of analyzed melanoma samples, which correlated with better prognosis (Table 1).

2.19

Piezo1 and 2

The two genes Piezo1 and Piezo2 in the human genome encode unique mechanosensitive cation channels with high physiological relevance. Well-studied functions include cutaneous touch sensation and sensing of blood pressure and shear stress in blood vessels. Unlike other mechanogated channels, e.g., the TMC channels in cochlear hair cells, Piezo channels do not require a complex network of accessory proteins to allow full mechanogating. Thus, aberrant expression of Piezo genes in unusual cell types or heterologous expression in HEK293 cells will allow functionality without further proteins. The functional unit required to sense mechanical forces resides in three large propeller-like structures on the extracellular side of the trimeric channel complex (Zhao et al. 2019). Studies on Piezo channels in human cancer are still at their beginnings, but first findings indicate a possible relevance of both channel types. Piezo2 downregulation predicts poor prognosis in breast cancer (Lou et al. 2019). While this implies a tumor-suppressive function of Piezo2, Piezo1 was found to promote typical oncogenic properties. Thus, in osteosarcoma models, shRNA-mediated knockdown of Piezo1 inhibited cell invasion (Jiang et al. 2017), and in prostate cancer, Piezo1 accelerated cell cycle and promoted cancer development (Han et al. 2019). Thus far, no evidence for any functional relevance of Piezo genes in melanoma or melanocytes has been stated. Nevertheless, it is interesting to mention that skin melanocytes can influence gene expression of Piezo2 in neighboring primary sensory neurons. This is dependent on dopamine released from skin melanocytes, which activated dopamine receptors on the sensory neurons, leading to lower Piezo2 expression and thereby reducing mechanical sensitivity of darker pigmented skin (Ono et al. 2017).

2.20

PKD2

Please see TRPPs.

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P2X (Purinergic Receptors)

Purinergic receptors are widely expressed in many human cell types contributing to several functions, e.g., in the brain. In neural stem cells, they may also be involved in the regulation of cell proliferation, migration, and inhibition of apoptosis (Burnstock 2016; Ulrich et al. 2012). Purinergic receptors subdivide in three major classes: while P1 and P2Y receptors represent typical G protein-coupled receptors, P2X receptors are ligand-gated ion channels and thus of particular interest for this review. Of the P2X receptors, the ATP-gated receptor P2X7 is highly expressed in various cancers, including melanoma (White et al. 2005). Its expression is frequently associated with enhanced cancer cell survival, proliferation, and metastatic potential, and P2X7 thus was discussed as a new target for melanoma (Mantel and Harvey 2015). Several agonists and antagonists have been described that modulate P2X7 activity (Fischer et al. 2014). Treatment of mouse B16 melanoma cells with an irreversible antagonist (oxidized ATP) resulted in decreased melanoma cell proliferation in vitro as well as inhibited tumor growth in B16 melanoma-bearing mice (Hattori et al. 2012). Also, pharmacologic inhibition of P2X7 in mouse B16 tumors through intratumoral injection of the selective blocker AZ10606120 resulted in reduced tumor growth (Adinolfi et al. 2012). Furthermore, radiation-induced cytotoxicity in B16 melanoma cells was enhanced by the P2X7 receptor antagonist Brilliant Blue G, both in vitro and in vivo (Tanamachi et al. 2017). On the other hand, P2X7 may also exert a key role in inflammation and immunity. In the B16 melanoma model, host P2X7 expression was critical to support an antitumor immune response and to restrict tumor growth and metastatic diffusion, thus possibly limiting the use of P2X7 blockers for anticancer therapy (Adinolfi et al. 2015). According to human proteinatlas data, P2X7 is overexpressed in melanoma, and high expression is statistically linked to poor prognosis (Table 1, proteinatlas. org).

2.22

RYRs (Ryanodine Receptors)

Ryanodine receptors (RyR1, RyR2, RyR3) are involved in the regulation of intracellular Ca2+ concentration. Many cellular processes are regulated by Ca2+ signaling, including cell proliferation, motility, gene expression, and apoptosis (Bootman et al. 2001). In melanoma, Ca2+ signaling has come into particular focus also since the identification of the role of WNT in melanomagenesis (Weeraratna 2005). Expression of RyR1 and its involvement in Ca2+ signaling was described in normal human melanocytes (Kang et al. 2000). Increased expression of RyR2 was found in melanoma cells and tissue, as compared to melanocytes (Deli et al. 2007). On the other hand, the RyR1 inhibitor dantrolene suppressed the antitumor effects of the metabolite Euplotin C in melanoma cells (Carpi et al. 2018). Possibly further underlining

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the role of RyRs in melanoma, a single-nucleotide polymorphism was recently identified for RyR3, which correlated with improved survival of melanoma patients (Wang et al. 2019). Interestingly, all three genes (RyR1, RyR2, RyR3) are frequently mutated in melanoma (Table 1).

2.23

SCNs (Voltage-Gated Sodium Channels)

The SCN family of voltage-gated sodium channels consists of nine genes encoding α-subunits, namely, SCN1A–SCN5A (NaV1.1–NaV1.9) and SCN8A–SCN11A, as well as four genes that encode the auxiliary β-subunits SCN1B–SCN4B (NaVβ1– NaVβ4). The classical function of voltage-gated sodium channels is the initiation of action potentials in neurons and muscle cells, but expression of all listed α- and β-subunits was also found in cancer cells, and functional relevance for cell proliferation and migration has been reported (Biasiotta et al. 2016; Patel and Brackenbury 2015). Expression analyses did not reveal abnormal regulation of SCN sodium channel subunits in melanoma versus nevi (Biasiotta et al. 2016; D’Arcangelo et al. 2019). Also, mRNA expression and functional activity of the α-subunits SCN5A (NaV1.5) and SCN8A (NaV1.6) have been reported for melanoma cell lines as well as for normal melanocytes (Xie et al. 2018; Yang et al. 2017). A possible role of voltagegated sodium channels in melanoma development and progression waits to be elucidated. While SCN7A (NaX or NaV2.1) shows significant sequence similarity to the group of SCN α subunits, it does not respond to changes in membrane potential but to changes in the extracellular Na+ concentration (Noda and Hiyama 2015). Thus far, no expression or functional relevance of SCN7A in melanoma has been reported. For all family members of the SCNxA group, high mutation rates were found, ranging from 7% to 22% (Table 1), whereas the B proteins are only rarely mutated. According to human proteinatlas, the SCN genes show low mRNA expression in melanoma, but for three genes of this family (SCN1B, SCN4B, SCN11A) a relatively higher expression was found statistically linked to shorter overall-survival of melanoma patients.

2.24

SCNN1s (Sodium Channel Epithelial 1s)

ENaC channels or SCNN1s (sodium channel epithelial 1) are non-voltage-gated, amiloride-sensitive sodium channels, which are described to control fluid and electrolyte transport across epithelia in the kidney, lung, and other organs. Functional channels are formed as heterotrimers composed of α-, β-, and γ-subunits; the role of a fourth paralog (δ) is less clear (Hanukoglu and Hanukoglu 2016). All four paralog subunits (SCNN1A, SCNN1B, SCNN1C, SCNN1D) were found expressed

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in G-361 human melanoma cell line, with high abundance of the δ subunit (SCNN1D) (Yamamura et al. 2008a). However, mRNA expression data revealed downregulation of SCNN1B and even more of SCNN1A in melanomas versus melanocytes (D’Arcangelo et al. 2019). SCNN1A is a target of microRNA-125b (Zhang et al. 2014), which has been shown to control melanoma progression (Kappelmann et al. 2013). A possible role of SCNN proteins as tumor suppressors has been reported for gastric cancer, where SCNN1B suppressed cancer growth and metastasis (Qian et al. 2017). Relations were also seen between SCNN proteins and MAPK inhibition. Thus, MAPK inhibition by combined BRAF and MEK inhibitors (dabrafenib plus trametinib) in melanoma patients can lead to hyponatremia as adverse effect, which has been related to activation and stabilization of SCNN channels (Assan et al. 2019). Mutations in SCNN1A and B, although not very common, were associated with better prognosis, while strong expression of SCNN1D and G correlated to worse overall survival of melanoma patients (Table 1).

2.25

SLCs (Solute Carrier Family)

The solute carrier family (SLC) members are important membrane transport proteins, mediating transport of inorganic ions, amino acids, lipids, as well as neurotransmitters across membranes, and they also play an important role in drug disposition. Human SLCs are classified into 65 families. Most SLCs function as cotransporters using gradients as driving force for substrate import into cells, whereas only few SLCs show channel-like properties (Bai et al. 2017; Fredriksson et al. 2008). A comprehensive expression analysis of 29 SLC transporters revealed no expression of 12 SLCs and no differential expression of 14 SLCs in melanoma cells. Only SLC29A2 (ENT2), SLC21A3 (OATP1A2), and SLCO1B1 (OATP1B1) showed significantly higher expression in melanoma cell lines as compared to normal melanocytes (Grottker 2019).

2.25.1

SLC1As

Certain amino acids, e.g., leucine and glutamine, are essential for growth and survival of tumor cells, including melanoma. The leucine transporter LAT1 (SLC7A5; please see SLC7As) is associated with the alanine-serine-cysteine (and glutamine) transporter ASCT2 (SLC1A5) for uptake of amino acids. Both LAT1 and SLC1A5 show increased expression in melanoma samples as well as in melanoma cell lines. Thus, SLC1A5 was suggested as drug target with potentially high pharmacological importance. Inhibition of SLC1A5, as well as its shRNA-mediated knockdown, reduced amino acid transport into melanoma cells, leading to inhibition of mTORC1 signaling and reduction of melanoma cell proliferation (Colas et al.

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2015; Wang et al. 2014). A relation between SLC1A5 and ferroptosis was further established based on miR-137, which targets SLC1A5 and suppressed drug-induced ferroptosis in melanoma cells (Luo et al. 2018).

2.25.2

SLC2As (Glucose Transporter)

The SLC2A family is composed of the so-called glucose transporters (GLUT1-14), which catalyze the uptake of sugars (Rogers et al. 2002). This family of transporters is characterized by a conserved topology comprising 12 transmembrane helices. By sequence homology, SLC2As are grouped into three classes: Class I comprises SLC2A1–4 and 14; Class II SLC2A5, SLC2A7, SLC2A9, and SLC2A11; Class III SLC2A6, SLC2A8, SLC2A10, SLC2A12, and SLC2A13. Transporter function is explained by a model of alternate conformation (Oka et al. 1990). A single substrate binding site is exposed toward the outside or the inside of the cell, respectively. Binding of glucose (or other hexoses) induces a conformational change associated with transport and release to the other side of the membrane, so-called facilitated diffusion. Based on their important role in glucose transport, this family is widely studied in physiology and pathophysiology. In addition to classical SLC2A-associated pathophysiological conditions like changes in fructose uptake, glucose transfer, or regulation of insulin secretion, the roles of SLC2As also became of importance in cancer and for the metabolic changes in cancer cells. SLC2A1 expression in melanoma has been observed in several studies. Thus, positive membrane staining for SLC2A1 was seen in 69 of 225 melanomas, whereas no expression was observed in nevi (Dura et al. 2019). The number of SLC2A1positive cells and staining intensity correlated with Breslow thickness. This is in agreement with other data including these from human proteinatlas. SLC2A1 expression was revealed to enhance proliferation, apoptosis resistance, and migratory activity and in vivo metastasis in melanoma by modulating JNK activity (Koch et al. 2015). Further, SLC2A1 expression correlated with poor survival of melanoma patients (Dura et al. 2019; Koch et al. 2015). SLC2A family members are only rarely mutated in melanomas (0.6–4.5%), and no correlation between mutation and prognosis was observed (Table 1). Expression of SLC2A9 and A12 showed a link to unfavorably prognosis (Table 1).

2.25.3

SLC3As (L-Type Amino Acid Transporter)

SLC3A2 (CD98, 4F2) and SLC7A5 (LAT1, L-type amino acid transporter 1; please also see SLC7As) constitute a heterodimeric transmembrane protein complex, which mediates the cellular uptake of branched and aromatic amino acids, essentially needed for cell proliferation (Napolitano et al. 2015). SLC3A2 is expressed on human melanoma cells (Dixon et al. 1990) as well as in different tumor types, and

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it has also been suggested as prognostic marker and as possible therapeutic target for melanoma (Theodosakis et al. 2016).

2.25.4

SLC4As (Bicarbonate Transporter)

The SLCA4 family members (SLC4A1–A12) are HCO3 transporters in the plasma membrane, which maintain pH homoeostasis in several cell types (Parker and Boron 2013; Romero et al. 2013). SLC4A1–A3 serve as cotransporters of Cl and HCO3 and are Na+-independent. Whereas SLC4A1–A3 function as cellular acid loaders, SLC4A4 (NBCe1), SLC4A5 (NBCe2), SLC4A7 (NBCn1), SLC4A8 (NDCBE), and SLC4A10 (NCBE/NBCn2) are Na+-coupled HCO3 transporters (Na+-driven bicarbonate transporters (NDBT)) and function as acid extruders, as reviewed in Gorbatenko et al. (2014). Studies reported that SLC4A9 can mediate an intracellular pH recovery due to CO2-induced acidosis (McIntyre et al. 2016). SLC4A1 is mainly expressed in erythrocytes to mediate CO2 transport from tissues to the lung as well as to regulate glycolytic enzyme activity in erythrocytes (Barneaud-Rocca et al. 2011). SLC4A1 is upregulated in gastric cancer cells and in colorectal cancer cells as reviewed in Gorbatenko et al. (2014), where it interacts with the cell cycle inhibitor p16 (INK4a) (Shen et al. 2007). Studies showed a HIF1-dependent induction of SLC4A4 under hypoxic conditions in a colon cancer cell line and described the important role of SLC4A4 in cell proliferation, intracellular pH regulation, and migration in breast and colon cancer cells (Parks and Pouyssegur 2015). Several studies reported upregulated expression of SLC4A transporters in various cancer cell types, such as SLC4A7 (NBCn1) and SLC4A4 (Boedtkjer et al. 2013; Parks and Pouyssegur 2015). Although public protein expression data showed a partially high expression of SLC4A2 and SLC4A9 in melanoma (proteinatlas.org 2019), not much is known about the particular roles of SLC4As in melanoma progression.

2.25.5

SLC5As (Sodium/Glucose Transporter Family)

SLC5As are members of the so-called sodium/glucose transporter family. Based on sequence homology, this family was grouped into two subfamilies: cotransporters of sugars, e.g., SLC5A1 (SGLT1; glucose), and transporters of molecules such as ascorbate, choline, iodide, lipoate, monocarboxylates, and pantothenate, e.g., SLC5A5 (iodide). SLC5A1 and 2 exert important roles in systemic glucose metabolism, being responsible for the uptake of glucose in the intestine or reabsorption in the kidney, respectively. Several of the transporters as SLCA1 (SGLT1), SLC5A7 (CHT1), SLC5A8 (AIT), and SLC5A10 (SGLT5) are not expressed in melanoma cells nor in normal melanocytes, based on the human proteinatlas data (Table 1, proteinatlas.org) as well as confirmed by own cDNA array analysis (Bosserhoff group, unpublished data).

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Despite its lack of expression, mutations in SLC5A10 were suggested to correlate with unfavorable prognosis (cBIOPortal, Table 1). SLC5A2 (SGLT2) was reported as expressed in roughly 10% of melanoma samples, and weak expression was observed in melanoma cell lines but not in melanocytes (proteinatlas.org 2019). Some clinical observations suggested an increase in melanoma risk in type 2 diabetes patients using SGLT2 inhibitors, which was, however, rejected by a meta-analysis of 21 randomized controlled trials (Tang et al. 2018). On the other hand, the meta-analysis also revealed that the use of SGLT2 inhibitors was not protective, suggesting that SLC5A2 may not play an important role in melanoma development. Also SCL5A3 (SMIT) is expressed in melanoma (Mallee et al. 1997). This is further supported by the human proteinatlas and by unpublished cDNA array data. Its expression was linked to unfavorable prognosis (Table 1, proteinatlas.org). This also applies to SLC5A4 (SGLT3), SLCA9 (SGLT4), and SLCA12 (SMCT2), for which induced expression in melanoma as compared to normal melanocytes and an unfavorable link to overall survival was seen (Table 1). For SLC5A4, mutations, which occurred in 2.4% of melanoma samples, were correlated to unfavorable survival (Table 1). Both SLC5A5 (NIS) and SLC5A11 are expressed in melanoma, but not in melanocytes; no link to survival was observed. SLC5A6 (SMVT) seems to be expressed in melanoma and melanocytes; however its regulation is controversial between different data sets.

2.25.6

SLC7As (Cystine-Glutamate Antiporter)

The SLC7A family comprises 13 members (SLC7A1–SLC7A12, SLC7A14), which can be divided into the cationic amino acid transporters (CATs) and glycoproteinassociated amino acid transporters (gpaATs). The CAT members are 14 TM proteins, which mediate as exchanger pH- and Na+-independent transport of cationic amino acids (system y+). The gpaAT subgroup contains 12 TM proteins, which heterodimerize with SLC3 (CD98; please see SLC3As) family members and function as amino acid exchangers at the cell surface (Etoga et al. 2010; Oda et al. 2010; Wolf et al. 2002). Whereas heterodimers between SLC3A2 and SLC7A5 (LAT1) and SLC7A8 (LAT2) function as Na+-independent L-transporters, heterodimers between SLC3A2 and SLC7A7 (y+LAT1) or SLC7A6 (y+LAT2) transport Na+independent cationic amino acids as well as Na+-dependent neutral amino acids. SLC7A10 (Asc-1) heterodimerizes with SLC3A2 to transport small neutral amino acids (Alexander et al. 2017). The cystine-glutamate antiporter comprises the proteins SLC7A11 (xCT) and SLC3A2. It plays an important role in cellular uptake of the glutathione precursor cystine, a key step in glutathione synthesis. In hair and skin melanocytes, SLC7A11 serves as an important regulator of pheomelanin synthesis (Chintala et al. 2005). Interestingly, disruption of SLC7A11 also inhibited the growth of a variety of cancers, including lymphoma, glioma, prostate, and breast cancer (Chen et al. 2009c). Pharmacological inhibition of SLC7A11 by sulfasalazine was shown to sensitize B16F10 melanoma cells for

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radiation therapy (Nagane et al. 2018). In melanomas, SLC7A11 is overexpressed, and its expression further correlated with tumor stage and tumor progression. Exogenous SLC7A11 overexpression promoted cell proliferation in vitro and enhanced tumor growth in xenograft melanoma models. SLC7A11 was also suggested as the molecular target of riluzole, which reduced melanoma cell proliferation in vitro and tumor progression in vivo (Shin et al. 2018). Regarding the relations of SLC7A11 and cell death induction, deficiency of SLC7A11 resulted in autophagy and endoplasmic reticulum stress in melanocytes (Zheng et al. 2016). As cystine is the precursor of the major antioxidant glutathione, SLC7A11 suppression may result in enhanced reactive oxygen species (ROS) levels, further leading to ROS-induced cell death, as shown in melanoma cells treated with the HDAC inhibitor vorinostat (Wang et al. 2018). Expression of SLC7A11 was related to therapy resistance and has been suggested as prognostic marker (Theodosakis et al. 2016). Further, SLC7A5 (LAT1) is upregulated in a variety of human tumors, including melanoma whereas expressed at low-level in normal tissues (Fukumoto et al. 2013; Yanagida et al. 2001). Even higher expression correlated with melanoma metastasis, and SLC7A5 inhibitors resulted in enhanced response of melanoma cells to chemotherapy (Fukumoto et al. 2013).

2.25.7

SLC9As (Sodium/Hydrogen Exchangers 9)

Sodium/hydrogen exchangers 9 (or solute carrier family 9, SLC9As) are a family of transporters that regulate intracellular pH and cell volume by utilizing the sodium gradient across the plasma membrane to extrude protons from the cytosol to the extracellular space in a ratio of 1 Na+ (in) to 1 H+ (out). Whereas the isoforms SLC9A1 (NHE1), SLC9A2 (NHE2), SLC9A3 (NHE3), SLC9A4 (NHE4), SLC9A5 (NHE5), SLC9A8 (NHE8), and SLC9A9 (NHE9) seem to be involved in intracellular pH homeostasis and cell volume regulation, isoforms SLC9A6 (NHE6) and SLC9A7 (NHE7) are located on intracellular membranes, such as on endosomes and the trans-Golgi network (Miyazaki et al. 2001; Nakamura et al. 2005; Numata and Orlowski 2001). Especially, the SLC9A1 (Na+/H+ Exchanger 1, NHE1) isoform is expressed in keratinocytes, melanocytes, and melanoma cells (Sarangarajan et al. 2001). Here, NHE1 expression in keratinocytes contributes to the physiological acidification of the upper skin layer (Behne et al. 2002). SLC9A1 plays a central role in regulating pH homeostasis and may contribute to extracellular acidification in melanoma (Stüwe et al. 2007). It interacts via the translocated hydrogen protons with integrins on the cell surface and thus may influence migration, morphology, and adhesion of human melanoma cells (Stock et al. 2005; Stüwe et al. 2007). Additionally, SLC9A1 generates pH nanodomains at focal adhesions, modulating adhesion in migrating melanoma cells (Ludwig et al. 2013). Studies showed that NHE1 overexpression and extracellular acidification reduce cell-cell adhesion of melanoma cells while promoting cell-matrix interaction. In this way, the cell detachment from the primary

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tumor and the invasion of the cells into the surrounding tissue is promoted (Hofschröer et al. 2017). For SLC9A2-9, no studies on melanoma are published.

2.25.8

SLC10A-13As

The solute carrier SLC10 family (SLC10A1–SLC10A7) transports bile acids, sulfated solutes, and xenobiotics in a sodium-dependent manner. Especially, SLC10A1 (NTCP) and SLC10A2 (ASBT) are involved in enterohepatic circulation of bile acids (Dawson et al. 2009; Klaassen and Aleksunes 2010). Expression of most SLC10As seems to be low or undetectable in most melanomas, with the exception of SLC10A3 showing medium to strong protein expression in all analyzed samples (Table 1, proteinatlas.org). Mutations in SLC10A3 correlate with better patient prognosis (Table 1). A single study described SLC10A6 as regulated in irinotecan-resistant melanoma cell clones (Gao et al. 2008). However, its possible role in drug resistance needs further investigations. The SLC11 family (SLC11A1 and SLC11A2) mediates a proton-coupled metal ion transport (Fe2+ and Mn2+) across the cytoplasmic membrane (SLC11A2/DMT1) and across endosomal (SLC11A2/DMT1) or lysosomal/phagosomal membranes (SLC11A1/NRAMP1). SLC11A1 increases concentrations of free radicals in phagosomes to damage pathogens and to contribute to the antimicrobial activity of macrophages. No data on its expression or its possible role in melanoma cells are available. Expression of SLC11A2 was suggested to correlate with worse prognosis (Table 1). The most frequent mutations observed in SLC11A1 were F199 frameshifts. The chloride transporter family SLC12 (SLC12A1–SLC12A9) mediates the transport of ions in various tissues, particularly in the kidney and choroid plexus of the brain. Whereas SLC12A5 exerts an oncogenic function by inhibiting apoptosis and promoting metastasis in colorectal cancer (Xu et al. 2016a), no data are available on possible roles of SLC family members in melanoma. Based on public databases, several family members are strongly expressed in melanoma at the protein level (SLC12A4, A7, A8, A9; Table 1). Here, strong expression of SLC12A7 correlated with worse prognosis ( p < 0.05, Table 1). The most frequent mutations in SLC12A5 were G322R/E (8.6%) and in SLC12A7 G843W/V (11% of mutated samples). The transporter family SLC13 (SLC13A1–SLC13A5) can be divided into two groups. Group 1 comprises NaS1 and NaS2, which transport sulfate, particularly in the intestine, kidney, and placenta; group 2 comprises NaC1, NaC2, and NaC3, which convey carboxylates in the kidney and liver (IUPHAR 2019). Expression of SLC13A3 and A4 was linked to worse overall survival of melanoma patients (Table 1).

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SLC16As

The members of the SLC16A family (SLC16A1- SLC16A9) can be differentiated based on the transported substrates. The proton-coupled monocarboxylate transporters (MCT1-4; SLC16A1, SLC16A7, SLC16A3, SLC16A4) mediate the transport of monocarboxylates, in particular lactate and pyruvic acid. The affinity for lactate and pyruvate varies between the different MCTs (Draoui and Feron 2011). SLC16A1 (MCT1) is most widely expressed and mediates the uptake of lactate in skeletal muscle, heart muscle, liver, and red blood cells (Halestrap and Meredith 2004). SLC16A7 (MCT2) expression is limited especially to the retinal pigment epithelium and choroid plexus epithelia (Halestrap and Meredith 2004). SLC16A4 (MCT4) expression is increased in response to hypoxia and occurs in highly glycolytic cells, e.g., in white muscle cells (Ullah et al. 2006). SLC16A1 (MCT1) and SLC16A4 (MCT4) are the two MCTs mainly expressed in tumor cells. Most solid tumors reprogram their metabolism, independently of oxygen availability toward aerobic glycolysis (a phenomenon well-known as Warburg effect) resulting in high production of protons and lactate (Gatenby and Gillies 2004; Warburg 1956). Especially SLC16A1 (MCT1) and SLC16A4 (MCT4) play essential roles by mediating lactate and proton efflux to the extracellular milieu (Chiche et al. 2010) and contribute to an acidification of the extracellular milieu. In this way, the acidic microenvironment leads to a selection of cancer cells with increased metastatic potential. Moreover, tumor acidosis may result in an evasion to immune response and in resistance to radio- and chemotherapy (Hirschhaeuser et al. 2011). Studies have shown that in tumors a metabolic symbiosis between tumor cells with a glycolytic phenotype and tumor cells with an oxidative phenotype is found. Thus, glycolytic tumor cells generate lactate under hypoxic conditions, which is predominantly exported by SLC16A4 (MCT4) and is imported into oxidative tumor cells under oxygen-rich conditions via SLC16A1 (MCT1), to be further metabolized in oxidative metabolism (Spugnini et al. 2015). In response to acidic extracellular pH, human melanoma cells have shown an increased activity of SLC16A1 and SLC16A4 (Wahl et al. 2002). SLC16A4 expression is elevated in advanced melanomas, and SLC16A1 and SLC16A4 are associated with shorter overall survival of melanoma patients (Chiche et al. 2010; Pinheiro et al. 2016), possibly underlining the importance of SLC16A1 and SLC16A4 during melanoma progression. For the SLC16A4 gene, an intron retention process was revealed with a retention of parts of intron 2/3 (265 bp) potentially leading to frameshift of SLC16A4 (Giannopoulou et al. 2019). The proteins basigin (CD147) and embigin are integral plasma membrane glycoproteins (Kanekura et al. 1991) with extracellular immunoglobulin domains, which mediate the SLC16A1 and SLC16A4 protein localization at the plasma membrane (Kirk et al. 2000). Basigin expression is enhanced in melanoma and facilitates as chaperone of the surface localization of SLC16A1 and SLC16A4 and their catalytic activity (Kirk et al. 2000; Su et al. 2009).

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A preclinical study with the multi-kinase inhibitor RAF265 for treatment of metastatic melanoma showed that RAF265-responsive melanomas with wild-type BRAF had a 15-fold lower level of SLC16A6 mRNA-expression (Su et al. 2012). Suppression of SLC16A6 was also seen by microarray analysis in GNAQ/BRAFmutant uveal melanoma cell line UM, following treatment with the MEK inhibitor selumetinib (Ambrosini et al. 2012). Another study on melanocyte differentiation in uveal melanoma, using suppressive subtractive hybridization (SSH) technique, identified SLC16A6 as the strongest repressed gene in UM in comparison to normal uveal melanocytes (Bergeron et al. 2012). The reduced expression of SLC16A6 might result in the reduction of lactate-fueled ATP production, affecting tumor cell survival in a tumor microenvironment with low glucose concentrations (Draoui and Feron 2011). In contrast, SLC16A7 was identified as upregulated in chemosensitive melanoma cell subclones versus non-responders (Willmes et al. 2016). SLC16A12 was found upregulated in a study comparing melanocytes derived from dark and light skinned individuals under basal conditions (López et al. 2015). SLC16A14 was identified as downregulated target gene of NFIB in Nfib-cKO hair follicle stem cells using RNA-seq analysis (Chang et al. 2013).

2.25.10

SLC17As

The SLC17A (SLC17A1–SLC17A9) family can be divided in the following subgroups according to the transported products: sodium-phosphate cotransporters (SLC17A1–A4) are expressed in the kidney and in the intestine, but are only rarely found in melanomas. SLC17A5 is found on lysosomes and synaptic vesicles and mediates the export of sialic acid and the accumulation of acidic amino acids driven by a proton gradient (Alexander et al. 2011). The degradation of glycoproteins in lysosomes results in the formation of amino acids and sugar residues, which are further exported via SLC17A5 from lysosomes for subsequent metabolization (Miyaji et al. 2011). The subgroup of vesicular glutamate transporters (VGLUTs; SLC17A7, SLC17A6, SLC17A8) mediates the uptake of glutamate into synaptic vesicles and secretory vesicles (Bellocchio et al. 2000). Finally, SLC17A9 represents a vesicular nucleotide transporter that allows ATP uptake, dependent on Cl and membrane potential (Sawada et al. 2008). For the SLC17A transporters, no studies in melanoma are published. Public databases report a mutation in SLC17A8 (S89F, 12%) (Table 1). Furthermore, expression of SLC17A5 correlated with better prognosis, whereas expression of A9 correlated with worse prognosis for melanoma patients.

2.25.11

SLC18s

Members of the SLC18A family (SLC18A1, SLC18A2, SLC18A3, SLC18B1) function as amine/proton antiporters, using the proton gradient established by a vacuolar ATPase that acidifies secretory vesicles. The SLC18A antiporter transports

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positively charged amine neurotransmitters, such as serotonin, and hormones from the cytoplasm into secretory vesicles (Alexander et al. 2011). No studies on melanoma can be found to date. Expression of SLC18A1 correlated with better prognosis based on TCGA data (Table 1).

2.25.12

SLC19As

The SLC19 family members (SLC19A1–SLC19A3) function as transporters of folic acid and thiamine, which are transported across the plasma membrane particularly in the intestine, kidneys, and placenta. The transport is driven by pH difference. Whereas SLC19A2 and SLC19A3 mediate the transport of thiamine (Dutta et al. 1999; Rajgopal et al. 2001), SLCA3 transports mono- and pyrophosphate derivatives of thiamine and folate (Lu’o’ng and Nguyen 2013). In a study using a two-step DNA microarray technique, SLC19A2 was identified as MITF target, suggesting that MITF is also involved in the regulation of amino acid and lipid metabolism (Hoek et al. 2008). Expression of SLC19A1 and of SLC19A2 were correlated with worse melanoma patients’ prognosis (Table 1).

2.25.13

SLC21As

Please see SLCOs.

2.25.14

SLC22As

The family members of SLC22 (OCT, organic cation transporter) function as organic cation as well as carnitine transporters, and they also mediate the uptake of many anticancer drugs. The SLC22 transporters mostly function as antiporters that exchange organic ions. The six main cation transporters are SLC22A1 (OCT1), SLC22A2 (OCT2), SLC22A3 (OCT3), SLC22A4 (OCTN1), SLC22A5 (OCTN2), and SLC22A16 (OCT6). Moreover, SLC22A4, SLC22A5, and SLC22A16 can also transport the zwitterion carnitine (Hagenbuch and Meier 2004; Koepsell and Endou 2004). SLC22 proteins are mainly expressed in the kidney, intestine, and liver, where they mediate the absorption and elimination of drugs and metabolites. In addition, SLC22s are expressed in diverse tissues, such as heart, brain, lung, placenta, salivary gland, and testis (Klaassen and Aleksunes 2010). SLC22A1 was found only weakly expressed in the melanoma cell line SK-MEL3 (Huber et al. 2015). SLC22 gene expression was profiled in 60 human cancer cell lines represented in the NCI-60 panel of the National Cancer Institute (NCI), to identify relevant drug uptake transporters. Expression of SLC22A4 (organic cation/carnitine transporter 1) was found in a variety of cancer cell lines as well as in nine melanoma cell lines (Okabe et al. 2008). Overexpression of SLC22A4 in a cervix carcinoma cell line

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(KB-3-1) was shown to result in increased cellular uptake and increased sensitivity to the chemotherapeutic drugs mitoxantrone and doxorubicin (Okabe et al. 2008). Interestingly, SLC22A4 (35%) and A7 (9%) are frequently mutated in melanoma. Expression of SLC22A18 was correlated to better prognosis, while expression of SLC22A2, 11, 16, and 17 correlated with worse prognosis (Table 1).

2.25.15

SLC25As

Please see MTCH.

2.25.16

SLC45A

The SLC45 family (SLCA1–SLC45A) mediates the transport of sugar molecules across the plasma membrane (Vitavska and Wieczorek 2013). It is thought that SLC45A2 (MATP, melanin-associated transporter protein) is needed for the transport of substances required for melanin biosynthesis. It is localized in the melanosome membrane and is involved in processing and trafficking of tyrosinase to the melanosome. Furthermore, SLC45A2 is linked to the maintenance of pH homeostasis in melanosomes (Bin et al. 2015). Mutations of SLC45A2 were correlated with type IV oculocutaneous albinism (Newton et al. 2001), and gene polymorphisms lead to skin and hair color alterations (Graf et al. 2005). Thus, single-nucleotide polymorphisms of the SLC45A2 gene (E272K and F374L) are associated with dark eyes, hair, and skin in Caucasian populations (Newton et al. 2001; Yuasa et al. 2004). The mutation F374L was further correlated to a reduced risk to develop melanoma. Thus, SLC45A2 may be considered as a melanoma susceptibility gene (Fernandez et al. 2008). Studies suggested that SLC45A2 gene expression is regulated via a cAMP signaling pathway and the downstream transcription factor MITF (Du and Fisher 2002). Additional studies revealed that melanosome alkalization caused by the adenylate cyclase activator forskolin resulted in elevated expression of SLC45A2 and increased melanin synthesis in mouse melanoma cells (Cheli et al. 2009). According to the Human Protein Atlas, SLC45A2 is expressed in cutaneous melanomas, and gene variants are associated with an increased risk for melanoma (Guedj et al. 2008; Harada et al. 2001). Using tandem mass spectrometry, a number of HLA class I–bound peptides have been identified that derived from SLC45A2. CTLs generated against these epitopes recognized and eliminated cutaneous, uveal, and mucosal melanoma cell lines (Park et al. 2017). Expression of SLC45A2 correlated with better patient outcome (Table 1). In SLC45A3 the mutation R245L/W was observed in 15% of all mutated samples, which was linked to a better survival (Table 1).

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SLCOs (Solute Carrier Organic Anion Transporter Family)

The solute carrier organic anion-transporter family members (SLCOs, SLC21As, or OATPs) handle a broad variety of substrates, including bile acids, bromosulphophthalein, some steroidal compounds, as well as drugs such as HMG-CoA reductase inhibitors (e.g., pravastatin), cytotoxic drugs, and antibiotics (Seithel et al. 2008). Expression of the family members is mainly found in the intestine, liver, brain, and kidney, e.g., SLCO1B1 and SLCO1B3 are liver-specific proteins, while SLCO2B1 and SLCO1A2 are expressed on the apical membrane of intestinal enterocytes. Data on expression in melanoma are hardly available. According to the human proteinatlas, normal melanocytes do not express any of these transporters. In melanoma cells, some SLCO family members were only weakly expressed (SLCO1A2, SLCO1C1, SLCO2A1, SLCO4A1, SLCO5A1, SLCO6A1) (Table 1, proteinatlas. org). Interestingly, links to survival were observed for SLCO1A2 (expression is unfavorable) and to SLCO4A1 and SLCO5A1 (expression is favorable). Further astonishing is that mutations in SLCO1B1, although not found to be expressed by immunohistochemistry, were linked to unfavorable survival (Table 1). One study revealed expression of SLCO3A1 (OATP-D) in melanoma cells but without any characterization of its function (Adachi et al. 2003). In a profiling analysis of mRNA expression of SLCO family members in a 60 cancer cell line panel of NCI, SLCO5A1 exhibited high expression in melanoma cell lines (Okabe et al. 2008). In summary, hardly any confirmed data are available, preventing reliable estimations about the role of SLCO family members in melanoma. However, the analysis of these transporters in melanoma may be of further interest, based on their role in drug transport and with regard to therapeutic intervention.

2.27

STEAPs (Six-Transmembrane Epithelial Antigen of the Prostate)

The STEAP protein family (six-transmembrane epithelial antigen of the prostate) encloses at least four proteins (STEAP 1–4). These are metalloreductases, which can convert iron from insoluble Fe3+ to soluble Fe2+ and copper from Cu2+ to Cu1+, thus stimulating the cellular uptake of both iron and copper. The protein structures are predicted to contain six transmembrane domains, and the proteins were found predominantly expressed in prostate tissue, but are also upregulated in multiple cancer cell lines (Grunewald et al. 2012). In melanoma, STEAP1 protein is strongly expressed and is presented by HLA-A2 in sufficient amounts to allow recognition by CTLs (Rodeberg et al. 2005). A specific STEAP1 antigen was discussed as candidate for T cell-based immunotherapy (Kobayashi et al. 2007). Thus, a fusion protein of heat shock protein 65 and an immunogenic STEAP1 epitope, applied as tumor

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vaccine, inhibited the growth of B16F10 melanomas in an immunocompetent mouse model (Chen et al. 2019). For STEAP2, 3, and 4, so far no information on melanoma is available in PubMed, and according the human proteinatlas, STEAP2–4 and are not or only weakly expressed in melanoma (Table 1, proteinatlas.org).

2.28

STIMs (Stromal Interaction Molecules)

Please see ORAIs.

2.29

TPCNs (Two-Pore Channel Proteins)

The TPCN genes encode the two-pore channel proteins (TPCNs). Changes in TPCN1 were described in breast cancer and in bladder cancer, whereas no changes were observed in melanoma (Biasiotta et al. 2016). TPCN2 is a cation channel expressed in melanocytes, localized in the melanosome membrane. Knockout as well as knockdown experiments resulted in a substantial accumulation of melanin in melanocytes, which was explained by a regulating effect on melanosomal pH and intracellular Ca2+ signaling (Ambrosio et al. 2016). TPCN2 inhibition, e.g., by the natural flavonoid naringenin, was discussed as a therapeutic strategy for different pathological conditions including the targeting of progression and metastatic potential of melanoma (Pafumi et al. 2017).

2.30

TRPs (Transient Receptor Potential Cation Channel Subfamilies)

The phenotypic impact of a mutation in Drosophila, namely, an atypical light response of the membrane potential in photoreceptor cells, stimulated a family name that encloses 27 members in the human genome. All TRP members share a tetrameric channel structure and a 6TM-topology of the subunits, very similar to voltage-gated K+ channels. Most TRPs are permeable to Ca2+ ions, but often with rather low selectivity. Just like the TRP channel in Drosophila photoreceptors, many of the mammalian TRPs are involved in sensory functions, including taste, temperature sensation, and pain signaling. Beyond these established physiological functions, compelling evidence has accumulated for the expression and functional impact of selected TRP channels in human cancer (Deliot and Constantin 2015; Park et al. 2016). The expression and therapeutic application of TRPs and other ion channels in cancer has been reviewed by Brackenbury (2016) and Fraser and Pardo (2008).

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TRPA1

TRPA1, named “A” after the 14 ankyrin repeats in the cytosolic amino terminus, was found upregulated in several human cancers including breast carcinoma, where TRPA1 appeared as important for oxidative-stress defense (Takahashi et al. 2018). Functional TRPA1 channels were also proven in various melanoma cell lines as well as in normal melanocytes (Oehler et al. 2012). In normal melanocytes, TRPA1 seems to play a crucial role in the phototransduction cascade that links melanin synthesis to UV light exposure (Bellono et al. 2014).

2.30.2

TRPCs

The group of “canonical” TRPC channels comprises six members in humans, and several of them seem to be involved in carcinogenesis. Of particular interest appears the functional coupling of TRPC channels in the plasma membrane to calcium sensor proteins (STIM/ORAI; see also there) in the endoplasmic reticulum membrane, allowing the coupling of calcium store release and calcium entry from the extracellular space (store-operated calcium entry, SOCE). A recent study showed differential gene expression of TRPC1, TRPC4, TRPC6, and TRPC7 in melanoma versus nevi. While TRPC1 is downregulated, TRPC7 and TRPC4 are upregulated (D’Arcangelo et al. 2019). TRPC1-dependent SOCE was recently identified as crucial step in epithelial-to-mesenchymal transition (EMT) in breast cancer cells, which was accompanied by N-cadherin upregulation (Schaar et al. 2016). Thus, EMT as a critical step in metastasis of cancer cells may be promoted by TRPC channel activity. Similar mechanisms may be relevant in melanoma cells. In co-culture with keratinocytes, A375 human melanoma cells lose expression of N-cadherin, a process requiring contact-mediated Ca2+ influx via TRPC channels (TRPC1, 3, and 6) (Chung et al. 2018). The possible impact of TRPC channels in melanoma cells is, however, not limited to the control of cadherin expression. Thus, knockdown of TRPC3 with shRNA, as well as pharmacologic channel blockade, reduced proliferation and migration properties in human melanoma cell lines (Oda et al. 2017). Recently, increased levels of a long noncoding RNA (lncRNA), encoded by the gene SNHG5, were reported in melanoma tissue and cell lines (Gao et al. 2019). This lncRNA acts as microRNA sponge and indirectly increases TRPC3 expression. In consequence, experimental downregulation of SNHG5 led to lower TRPC3 expression, reduced proliferation, and induced apoptosis in melanoma cells (Gao et al. 2019). Thus, TRPC3 and its regulatory network may offer interesting new therapeutic target sites. Also the channels TRPC5 and TRPC6 are frequently implicated in cancer promotion, e.g., TRPC5 in colorectal cancer (Wang et al. 2017) and TRPC6 in hepatocellular carcinoma (Xu et al. 2018), but both canonical TRPs have not yet been described to be relevant in melanoma.

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TRPMs

The melastatin subfamily of TRP channels (TRPMs) comprises eight members in humans and was named after melastatin. TRPM1is highly expressed in melanocytes of the skin and in the pigment epithelium of the retina. TRPM1 (melastatin) is transcriptionally regulated by MITF, and its expression levels are inversely correlated to tumor thickness and aggressive melanoma growth (Duncan et al. 1998). This finding implied a tumor-suppressive function of this unselective, Ca2+-permeable cation channel. However, later work challenged this hypothesis and brought an unexpected new hypothesis explaining TRPM1-related tumor suppression. A microRNA (miR-211), encoded in intron 6 of the TRPM1 gene, was identified as the tumor-suppressive agent in this regulatory system (Levy et al. 2010). Expression of miR-211in metastatic melanoma cells, but not expression of the TRPM1 alone, reduced migration and invasiveness of the cells. The tumorsuppressive function of miR-211 relied on the downregulation of three genes: IGF2R, TGFBR2, and NFAT5 (Levy et al. 2010). In normal epidermal melanocytes, TRPM1 channels seem to be required for melanin synthesis. The TRPM1 mRNA abundance correlated with melanin concentrations in melanocytes, and knockdown of TRPM1 reduced melanin production (Oancea et al. 2009). Also TRPM2 was implicated in tumor formation in breast, gastric, and pancreatic carcinoma as well as in melanoma (Almasi et al. 2019; Miller 2019). The detailed analysis of TRPM2 transcripts in melanoma revealed a number of alternative protein products, including TRPM2-TE (tumor-enriched) comprising only the protein’s C-terminus as well as TRPM2-AS, a melanoma-enriched antisense transcript (Orfanelli et al. 2008). Functional knockout of TRPM2-TE sensitized melanoma cells for apoptosis induction (Orfanelli et al. 2008). For TRPM3 no relevant role in melanoma has been reported yet, and expression analyses did not reveal any aberrant gene regulation in melanoma (Biasiotta et al. 2016; D’Arcangelo et al. 2019). Unlike other TRP channels, TRPM4 and TRPM5 do not conduct Ca2+ ions but form monovalent cation-selective channels. Expression of TRPM4 and TRPM5 has been reported in certain cancer types as prostate and lung carcinoma (Gao and Liao 2019; Hantute-Ghesquier et al. 2018), but no role was so far identified in melanoma. TRPM6 and TRPM7 are permeable for Mg2+ and Ca2+ ions and may particularly contribute to intracellular Mg2+ homeostasis. For TRPM7, a channel with an additional cytosolic serine/threonine kinase activity, a protective role against oxidative stress was suggested in melanocytes (Decker et al. 2014), but also for these channels, no particular role in melanoma has been defined thus far. TRPM8 stands out of the subfamily, as it is physiologically activated by cold temperatures and serves as cold sensor in human cells (Bautista et al. 2007). It was firstly detected as upregulated in prostate cancer (Noyer et al. 2018; Tsavaler et al. 2001). TRPM8 overexpression was also found in melanoma cells, and menthol, a natural activator of this channel, was found to reduce the viability of TRPM8expressing melanoma cells (Yamamura et al. 2008b). Thus, menthol and related

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natural products with low toxicity have been discussed as possible new agents for melanoma therapy (Slominski 2008).

2.30.4

TRPMLs

The three members of the TRPML family (TRPML1-3, MCOLN1-3) were named after mucolipidosis type IV, a severe disease with defective lysosomal biogenesis, caused by mutated TRPML1. The channels of this subfamily are still lacking a reliable characterization with respect to ion conduction and selectivity, due to their typical intracellular localization in endosomes and lysosomes. TRPML1 (MCOLN1) was found upregulated in many HRAS-driven cancers, such as cancers of bladder or head and neck. These types of cancer cells were explicitly vulnerable to TRPML1 inhibition (Jung et al. 2019), suggesting a functional relevance of the channels for cell survival. Similar roles of TRPML channels in melanoma have not been reported, but TRPML3 was shown to be highly expressed in healthy melanocytes of the mouse, and gain-of-function mutations in this channel led to a loss of melanocytes and loss of fur color in mice (Xu et al. 2007).

2.30.5

TRPP

The TRPP subfamily was named after polycystin 2 (PKD2, TRPP1, previously TRPP2), a protein involved in autosomal dominant polycystic kidney disease. TRPP1 contains six transmembrane segments and forms heterotetramers with the non-channel protein PKD1 (polycystin 1, previously TRPP1) (Su et al. 2018). This complex contributes to cell cycle regulation in kidney cells, e.g., through interaction with the transcription factor Id2 (Li et al. 2005). TRPP1 (PKD2) alone forms nonselective cation channels, mainly localized in the ER membrane. Two further members of the TRPP subfamily with 6-TM topology are known: PKKD2L1 (polycystin 2-like 1, TRPP2) and PKD2L2 (polycystin 2-like 2, TRPP3). While PKD2L1 forms nonselective cation channels in the primary cilium and in the plasma membrane (Ng et al. 2019), the function of PDK2L2 is less well established. Thus far, no experimental or clinical data on the involvement of TRPP (PKD) channels in melanoma progression have been reported, but a possible link between TRPP1 (PKD2) and cell adhesion of melanoma cells has been observed. Thus, in B16 mouse melanoma cells, the siRNA-mediated knockdown of PKD2 (polycystin 2) led to reduced cell-cell adhesion, which was coupled to downregulation of E-cadherin (Bian et al. 2010). Expression of TRPP3 was linked to worse prognosis in melanoma (Table 1).

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351

TRPVs

The six members of the TRPV subfamily are named after the chemical group of vanilloids, such as the spicy pepper ingredient capsaicin that was identified as natural activator of TRPV1. Four members of this subfamily are activated by heat (TRPV1–4), and all six members form Ca2+-permeable channels, with TRPV5 and TRPV6 as the most selective Ca2+ channels of the family. TRPV1 is expressed in various cancer types including breast cancer (Weber et al. 2016), where activation by capsaicin can induce cell death (Wu et al. 2014). In melanoma tissues as well as cell lines, significant downregulation of TRPV1 was observed as compared to normal melanocytes and nevus tissue (Yang et al. 2018). A tumor suppressor function has been proposed for TRPV1 in melanoma, with NFAT2, ATF3, and p53 as downstream effectors of a TRPV1-mediated Ca2+ influx into the cell (Yang et al. 2018). As for TRPV4 channels, a growing body of evidence suggests a biological function in several cancer types including colon carcinoma and gastric cancer (Liu et al. 2019; Xie et al. 2017). Most studies reported a positive effect of TRPV4 channel activity on cell survival, while its inhibition reduced cell growth, e.g., via the phosphatase PTEN (Liu et al. 2019). A pro-survival role of TRPV4 in melanoma is not established; rather a recent study suggests that TRPV4 channel activity may even support cell death in melanoma (Zheng et al. 2019). Also the calcium-selective channel TRPV6 is overexpressed in several cancer types, including tumors of prostate, breast, pancreas, and colon (Haustrate et al. 2019; Lehen’kyi et al. 2012). This understanding resulted in a phase I clinical study for TRPV6 inhibition in patients with advanced tumors of epithelial origin, which revealed stable disease in approximately 50% of patients for up to 12 months (Fu et al. 2017). By contrast, TRPV6 does not seem to be regulated in melanoma versus normal melanocytes (D’Arcangelo et al. 2019), and no experimental studies implied any functional role of TRPV6 in melanoma cells. TRPV1–TRPV6 are included in a recent study presenting differential gene expression in nevi versus melanoma (D’Arcangelo et al. 2019). Here, slight opposite regulations were found for TRPV5 (1.2-fold up in melanoma) and TRPV6 (0.58-fold).

2.31

VDACs (Voltage-Dependent Anion Channels)

Voltage-dependent anion channels (VDAC1-3) are key mitochondrial proteins, driving cellular energy metabolism by controlling the influx and efflux of metabolites and ions through the mitochondrial membrane. They are expressed in three isoforms, which share common channeling properties, but play different roles in cell survival. While VDAC1 serves pro-apoptotic functions, VDAC2 can suppress the effects of different pro-apoptotic stimuli (de Stefani et al. 2012). VDAC1 appeared as necessary for apoptosis induced by myostatin, a member of the transforming growth factor-β superfamily. Thus, knockdown of VDAC1 inhibited myostatin-

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induced Bax translocation and apoptosis induction in cancer cells. Myostatin also inhibited tumorigenesis of B16F10 melanomas and induced apoptosis in melanoma cells (Liu et al. 2013). A further role of VDAC1 was suggested in melanoma cell apoptosis regulated by the pro-apoptotic Bcl-2-related protein Bim (Gao et al. 2015). In a recent in silico analysis of melanoma versus melanocytes, VDAC1 was found upregulated with high statistical significance (D’Arcangelo et al. 2019). A possible antagonistic role of VDAC2 in apoptosis regulation is based on its interaction with the pro-apoptotic, multidomain Bcl-2-related protein Bak (Cheng et al. 2003). In melanoma cells, the pro-apoptotic activity of the Bcl-2-related protein Bcl-xS was explained by the binding of Bcl-xS to VDAC2 resulting in a release of Bak for pro-apoptotic functions (Plotz et al. 2012). No data are available in PubMed on VDAC3 and melanoma, and according to the human proteinatlas, VDAC3 is not or only weakly expressed in melanoma with expression linked to unfavorable prognosis ( p ¼ 0.014, Table 1).

2.32

Other Transporter Proteins Expressed on Melanoma

For several other families of transport proteins, we could not detect relevant literature in PubMed. As some of these factors were, however, already characterized as important for tumor progression of other cancers, there are still important gaps to close in the characterization of the transport mechanisms in melanoma.

3 Conclusion and Perspectives Melanoma of the skin remained a deadly disease, despite the significant advances in the last years, achieved by targeted therapy as well as by the use of immune checkpoint inhibitors. Further improvement of melanoma therapy is urgently needed to finally defeat this aggressive cancer. Improvements may be particularly expected from combination therapies. Thus, the identification and characterization of new therapeutic targets in melanoma cells is highly important and promising. Cellular homeostasis is critically controlled in particular by a multitude of membrane and channel proteins. Thus, also malignant cell proliferation and apoptosis deficiency of cancer cells strongly depend on a suitable regulation and dysregulation of the large orchestra of channel proteins. A striking lesson of this “transportome” overview in melanoma is that the role of defined channels and even more their interaction in tumor development needs to be further defined experimentally for each single molecule. For example, while the Ca2
-permeable TRPV1 channel may act as a tumor suppressor with negative correlation of its expression and metastasis, overexpression of KCNN4 K+ channels may support melanoma cell proliferation and chemotherapy resistance. For other channels, such as for KCNH2 K+ channels, the expression level might serve as

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Table 2 Expression correlated to overall survival in melanoma

Gene ABCA12 ABCB6 CACNA1G CACNB3 KCNA3 KCNN4 SLC4A8 SLC7A7 SLC9A7 SLC16A9 SLC16A12 SLC18A1 SLC20A1 VDAC3

Prognostic pvalue by mRNA expression (proteinatlas. org) p ¼ 0.0037 p ¼ 0.036 p ¼ 0.0001 p ¼ 0.033 p ¼ 0.015 p ¼ 0.0025 p ¼ 0.031 p ¼ 0.029 p ¼ 0.013 p ¼ 0.05 p ¼ 0.018 p ¼ 0.034 p ¼ 0.023 p ¼ 0.014

Prognostic pvalue by mRNA expression (oncolng.org) p ¼ 0.036 p ¼ 0.0064 p ¼ 0.0021 p ¼ 0.024 p ¼ 0.00011 p ¼ 0.0025 p ¼ 0.0029 p ¼ 0.000003 p ¼ 0.0032 p ¼ 0.035 p ¼ 0.019 p ¼ 0.0067 p ¼ 0.025 p ¼ 0.0064

PROGgene No p ¼ 0.0064 No No p ¼ 0.013 p ¼ 0.0017 No p ¼ 0.0055 p ¼ 0.000095 No p ¼ 0.033 No p ¼ 0.044 No

XENA p ¼ 0.00051 p ¼ 0.0098 p ¼ 0.0021 p ¼ 0.0182 p ¼ 0.000063 p ¼ 0.011 p ¼ 0.0275 p ¼ 0.000008 p ¼ 0.0029 p ¼ 0.039 p ¼ 0.0091 p ¼ 0.045 No p ¼ 0.0093

Prognostic marker Negative Negative Negative Negative Positive Positive Positive Positive Positive Negative Negative Positive Positive Negative

Information of the most important channels and transporters in melanoma based on the correlation of expression data and overall survival. The list contains genes for which at least three independent analyses with cBioPortal (cbioportal.org/), proteinatlas (proteinatlas.org), OncoLnc (Anaya 2016), PROGgeneV2 (genomics.jefferson.edu/proggene/), and UCSC Xena (Goldman et al. 2018) have shown a significant correlation ( p  0.05) (19th of December 2019)

useful progression marker, while thus far no clear causative link between channel expression and melanoma formation has been described (Table 2). This somewhat disappointing picture at this time point is not really surprising, given the huge variety of channel and transporter functions as well as the broad functional complexity of the transportome in the cell. Furthermore, the important interaction between tumor cells and the tumor microenvironment is strongly regulated and modulated by transporters and channels. Several examples of this large collection of molecules that characterize melanoma cells are summarized in this review. However, these represent only the few, so far investigated factors, whereas many other factors have not been characterized until now. Additional suitable candidates for therapy may be expected from thorough investigation of this highly important level of cellular regulation. In this review, we aimed at giving a detailed overview on the knowledge of channels and transporters playing a role in melanoma. The field is continuously developing, and new information about this big and heterogeneous group of molecules is continuously generated. By the thorough and systematic evaluation of the individual roles of all channel proteins in melanoma, which should be managed in the next years, we may await also the identification of new, targeted strategies. These need to selectively kill melanoma cells either alone or in combination with already established therapies. Development of new strategies will also be based on the tight

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molecular characterization of the tumors and on individualized therapy. Different melanomas may also differ in their dysregulated sets of channel proteins. In this respect, a thorough analysis of possibly synergistic effects between channel blockers and established targeted therapies or immunotherapies will be needed for those channels and transporters with relevance in melanoma. As indicated by our experiments on KCNN4 channels, new combinations of a channel blocker (TRAM-34) with pathway inhibitors (MAPK, PI3K) may show synergistic effects on cell proliferation and apoptosis. Also, T-type channel (Cav3) CACN is overexpressed in melanoma versus normal melanocytes. Studies showed that an inhibition and gene silencing reduced cell proliferation and melanoma cell viability. Thus, therapeutic inhibition of T-type CACN could be an attractive anticancer strategy. Additionally, KCNA3 potassium channels are overexpressed in several tumor types, including melanoma. It was shown that KCNA-specific inhibitors reduced tumor size by 90%, suggesting KCNA3 inhibition as promising therapeutically approach. Thus, after identifying so many promising transport proteins, systematic combination trials – in vitro and in vivo – are required as next steps to bring channels and transporters to the stage of therapeutic melanoma targets of the future. Finally, and hopefully in not so far future, we may have established therapies for all the different molecular variants of melanoma, and according to the present understanding, channel proteins can be expected to be within the first row of these new therapeutic options. Acknowledgments The work of AKB is supported by the DFG (BO1573), the German Cancer Aid, and the Wilhelm-Sander foundation. JE presently receives support from the German Cancer Aid (7011 2382).

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Ion Channel Dysregulation in Head and Neck Cancers: Perspectives for Clinical Application Nagore Del-Río-Ibisate, Rocío Granda-Díaz, Juan P. Rodrigo, Sofía T. Menéndez, and Juana M. García-Pedrero Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Head and Neck Cancer Characteristics and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Ion Channels and Channelopathies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Dysregulation of Potassium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Voltage-Gated Potassium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Calcium-Activated Potassium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Dysregulation of Sodium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Pathobiological Role . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Clinical Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Dysregulation of Calcium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Voltage-Gated Calcium Channel Subunits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Other Calcium Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Dysregulation of Transient Receptor Potential Cation Channels . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Pathobiological Role . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Clinical Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Dysregulation of Chloride Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Voltage-Gated Chloride Channels (ClCs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Calcium-Activated Chloride Channels (CaCCs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Chloride Intracellular Channels (CLIC) Family Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Other Chloride Channels (ATP-Gated CFTR or Volume-Regulated Anion Channel Subunits) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Dysregulation of Ligand-Gated Ion Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Nicotinic Acetylcholine Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Zinc-Activated Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 P2X Purinergic Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Inositol Triphosphate Receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Dysregulation of Porins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Aquaporins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. Del-Río-Ibisate, R. Granda-Díaz, J. P. Rodrigo, S. T. Menéndez (*), and J. M. García-Pedrero (*) Department of Otolaryngology, Hospital Universitario Central de Asturias and Instituto de Investigación Sanitaria del Principado de Asturias, IUOPA, Universidad de Oviedo, Oviedo, Spain Ciber de Cáncer, CIBERONC, Madrid, Spain

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8.2 Voltage-Dependent Anion-Selective Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Dysregulation of Gap Junction Proteins (Connexins) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Closing Remarks and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract Head and neck cancers are a highly complex and heterogeneous group of malignancies that involve very diverse anatomical structures and distinct aetiological factors, treatments and clinical outcomes. Among them, head and neck squamous cell carcinomas (HNSCC) are predominant and the sixth most common cancer worldwide with still low survival rates. Omic technologies have unravelled the intricacies of tumour biology, harbouring a large diversity of genetic and molecular changes to drive the carcinogenesis process. Nonetheless, this remarkable heterogeneity of molecular alterations opens up an immense opportunity to discover novel biomarkers and develop molecular-targeted therapies. Increasing evidence demonstrates that dysregulation of ion channel expression and/or function is frequently and commonly observed in a variety of cancers from different origin. As a consequence, the concept of ion channels as potential membrane therapeutic targets and/or biomarkers for cancer diagnosis and prognosis has attracted growing attention. This chapter intends to comprehensively and critically review the current state-of-art ion channel dysregulation specifically focusing on head and neck cancers and to formulate the major challenges and research needs to translate this knowledge into clinical application. Based on current reported data, various voltage-gated potassium (Kv) channels (i.e. Kv3.4, Kv10.1 and Kv11.1) have been found frequently aberrantly expressed in HNSCC as well as precancerous lesions and are highlighted as clinically and biologically relevant features in both early stages of tumourigenesis and late stages of disease progression. More importantly, they also emerge as promising candidates as cancer risk markers, tumour markers and potential anti-proliferative and anti-metastatic targets for therapeutic interventions; however, the oncogenic properties seem to be independent of their ion-conducting function. Keywords Cancer risk marker · Head and neck cancers · Ion channel · Prognostic marker · Squamous cell carcinoma · Therapeutic target

1 Introduction 1.1

Head and Neck Cancer Characteristics and Treatment

Head and neck cancers comprise a group of anatomically diverse and molecularly heterogeneous malignancies with differences in aetiology, treatment and prognosis (Chow 2020). Approximately 95% of head and neck tumours are squamous cell carcinomas (HNSCC) that primarily originate from the upper aerodigestive

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epithelium of the oral cavity, pharynx and larynx. HNSCC represents the sixth leading cancer by incidence worldwide, with approximately 600,000 new cases diagnosed each year and over 300,000 estimated deaths (Haddad and Shin 2008). Tobacco and alcohol have long been recognised as leading risk factors for head and neck cancers, which usually coexist causing multiplicative combined effects (Zhang et al. 2000; Hashibe et al. 2009). There is a wide geographical variation in the incidence and anatomic distribution of HNSCC worldwide, predominately attributed to demographic differences in the habits of tobacco and alcohol consumption (Argiris et al. 2008). Besides, infection by the human papillomavirus (HPV) has also emerged as a major aetiological factor for a subset of oropharyngeal carcinomas (Gillison et al. 2000) and Epstein-Barr virus (EBV) for nasopharyngeal carcinomas (Yu and Yuan 2006). Overall HNSCC incidence has been decreasing in the last three decades due to prevention programmes to reduce tobacco consumption, while the incidence of oropharyngeal cancer associated with HPV infection has been progressively increasing among individuals under 45 years of age, particularly among non-smokers (Marur et al. 2010). HNSCC usually develops from leukoplakia, erythroplakia or apparently normal epithelium, where premalignant lesions with abnormal DNA content are more prone to undergo malignant transformation (Leemans et al. 2011). HNSCCs are often diagnosed late because of the scarcity of symptoms; however, they are usually easy to view. The median age for diagnosis is in the early 60s, with a male predominance. They are highly lymphophilic, tend to loco-regional infiltration and are characterised by a high incidence of relapses and second primary carcinomas (Chow 2020). The detection of lymph node metastasis is extremely important; as being the most adverse independent prognostic factor, it conditions patients’ treatment and management (Forastiere et al. 2001). The incidence of distant metastasis in HNSCC is relatively low compared to other malignancies, ranging from 9 to 20% depending on the tumour site. Nevertheless, it still remains a major determinant for treatment decision-making since distant metastases also adversely impact patients’ survival. The mortality of HNSCC patients is mainly due to failure of the loco-regional control of the disease. There is an increased risk of developing multiple aerodigestive tract tumours as high as 27% (Leemans et al. 2011). Within the first 2 years of follow-up, recurrences are the most common cause of treatment failure. After the third year, second primary tumours occurring in upper aerodigestive tract, lung and oesophagus become the main threat for patient long-term survival (Priante et al. 2011). This could be explained by the term “field cancerization”, initially described in 1953 by Slaughter et al. (1953). Long-term exposure to tobacco carcinogens affects large areas of the aerodigestive tract mucosa with an increased risk of developing malignancies (Califano et al. 2000). This histologically normal mucosa may harbour macroscopically undetectable genetic and epigenetic abnormalities that trigger the development of an invasive carcinoma (Califano et al. 2000; Leemans et al. 2011). Braakhuis et al. 2003 defined a precancerous field as a group of epithelial cells showing cancer-associated DNA changes, although incapable of invasive growth. Additional epigenetic or genetic events are necessary to acquire an

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invasive potential. Typical genetic changes are losses of chromosome 3p, 9p21 and 17p13 and somatic mutations in TP53, detected in approximately 80% of HNSCC. These alterations tend to occur in early stages of HNSCC tumorigenesis which may suggest a crucial role in the formation of the preneoplastic field. After the field is formed, cells must acquire additional alterations in order to complete the malignant transformation and to turn the field into a carcinoma showing invasive growth. Although the temporal order of genetic alteration is not the same for each tumour, they usually share genetic alterations, and their accumulation is critical for tumour development and progression (Leemans et al. 2011). Common chromosomal gains in HNSCC include 7p and 3q. A further characteristic of head and neck cancers is the amplification of chromosomal region 11q13. This occurs in approximately 40% of HNSCCs and has been associated with the presence of lymph node metastasis and poor prognosis. Well-established oncogenes and tumour suppressor genes in HNSCC are EGFR, PIK3CA, CCND1, TP53, CDNK2A, PTEN and SMAD4. Early stage HNSCC (stages I and II) is curable in 80% to 95% of patients, depending on the tumour size and location. By contrast, overall 5-year survival remains around 50% for advanced stage III and IV tumours (Argiris et al. 2008). Unfortunately, most patients typically present with advanced cancer and lymph node metastases. Treatment options include surgery plus radiation therapy (RT), concomitant chemotherapy and RT or RT alone for patients with poor functional status. For patients with resectable advanced tumours, combined modality treatment can be offered to preserve organ function and improve outcome as two major goals. Patients with metastatic disease or loco-regionally recurrent, unresectable disease already irradiated are generally treated for palliation. Despite continuous advancements in local control and overall quality of life achieved with the use of combined modality therapies, the survival rates for HNSCC patients have barely increased over the last decades (Haddad and Shin 2008). Enormous efforts have been devoted to improve cancer detection and prognostication. Recent advances in genomic and basic research have increased our understanding of the molecular processes governing tumour formation and progression (Agrawal et al. 2011; Fanjul-Fernández et al. 2013). HNSCC is a heterogeneous disease involving deregulation of multiple pathways linked to cellular differentiation, cell cycle control, apoptosis, angiogenesis and metastasis (Leemans et al. 2011, 2018). Intense work is still focused on the identification of novel biomarkers that reliably predict aggressive tumour behaviour beyond current clinical and histopathological markers. These molecular markers may represent useful diagnostic or prognostic markers, as well as new targets for therapy (Leemans et al. 2018). At present, there are only a few therapeutic strategies available targeting aberrantly expressed pathways for HNSCC patients (Moreira et al. 2017; Leemans et al. 2018), such as the anti-EGFR antibody cetuximab, which has been increasingly used in the treatment of HNSCC patients, mainly in combination with RT (Bonner et al. 2006). In addition, two immune-checkpoint inhibitors, nivolumab and pembrolizumab (anti-PD-1/PD-L1 antibodies), have recently been approved by the Food and Drug Administration (FDA) for the treatment of recurrent or metastatic HNSCC (Alfieri et al. 2018).

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Ion Channels and Channelopathies

Ion channels are membrane-spanning proteins that selectively conduct ions across the cellular membranes. Ion channels possess a series of structural characteristics that include a water-filled permeation pathway, termed pore, which allows ions to flow across the cell membrane and a selectivity filter that specifies the permeant ion species. Besides, ion channels have a gating mechanism that serves to switch between the open and closed conformations. On this basis, ion channels can be divided into voltage-gated ion channels, which are regulated by changes in membrane potential, and ligand-gated ion channels, modulated by the binding of a ligand such as a hormone or a neurotransmitter. Ion channels are present in virtually every cell, thereby participating in many and highly diverse physiological events such as excitability, contraction, cell cycle progression and metabolism. Accordingly, defects in ion channel function can disrupt important biological processes and lead to a wide range of diseases (Niemeyer et al. 2001). Not surprisingly, the number of diseases associated to ion channel malfunction, termed “channelopathies”, has increased exponentially over the years (Niemeyer et al. 2001; Kass 2005; Wulff et al. 2009). Increasing evidence indicates that ion channels are involved in tumour cell biology and the concept of ion channels as membrane therapeutic targets and diagnostic/prognostic biomarkers has attracted growing attention (Wulff et al. 2009; Prevarskaya et al. 2010; Arcangeli et al. 2009). Ion channels are regulated during cell cycle and induce plasma membrane hyperpolarisation, which is necessary for pH and cell volume regulation, both factors closely related to cell proliferation (Arcangeli et al. 2009; Kunzelmann 2005). Moreover, numerous studies have demonstrated the implication of ion channels in the proliferation of a variety of tumour cell lines (Kunzelmann 2005; Wang 2004; Becchetti 2011). Hence, the oncogenic properties of ion channels together with their extracellular accessibility and functional modulation make them excellent targets for pharmacological and therapeutic interventions (Wulff et al. 2009; Asher et al. 2010; Pardo and Stühmer 2008). This chapter is focused on current knowledge and reported data concerning ion channel dysregulation in the specific context of head and neck cancers. An overview of both voltage-gated and ligand-gated ion channels found to be altered in head and neck cancers is shown in Fig. 1. The clinical and pathobiological relevance of each channel family will also be thoroughly reviewed and critically discussed in the following subsections.

2 Dysregulation of Potassium Channels Potassium (K+) channels are the largest and most diverse group of ion channels. They are widely distributed and participate in key cellular processes, such as cell cycle and proliferation, cell migration, invasion and apoptosis (Pardo and Stühmer

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Fig. 1 Overview of ion channels found to be dysregulated in head and neck cancers. Ion channels are classified by families and listed according to the IUPHAR nomenclature

2014). Therefore it is easy to understand how alterations in K+ channel expression may support tumour growth, progression and spreading. In particular, two members of the ether-à-go-go (EAG) potassium channel family, Kv10.1 (also known as hEAG1 or KCNH1) and Kv11.1 (HERG1 or KCNH2), have extensively been

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investigated. Notoriously, while under physiological conditions the expression pattern and function of Kv10.1 and Kv11.1 are almost exclusively restricted to the brain and heart, respectively, both channel subunits have been found frequently aberrantly expressed in multiple human cancers of diverse origin (Asher et al. 2010; Arcangeli 2005) and directly implicated in carcinogenesis and tumour progression (Asher et al. 2010; Arcangeli 2005; Pardo et al. 1999; Camacho 2006).

2.1

Voltage-Gated Potassium Channels

Among K+ channels, voltage-gated potassium (Kv) channels concentrate the majority of studies in head and neck cancers. Kv3.4 (also known as KCNC4 or HKSHII IC), Kv10.1 and Kv11.1 channel subunits have been found frequently abnormally expressed in HNSCC, although with marked differences in their timing, frequency and clinical significance. Abnormal expression of Kv3.4 and Kv11.1 has been detected by immunohistochemistry (IHC) in a high percentage of HNSCC tissue specimens (from larynx/ pharynx) and HNSCC-derived cell lines, whereas patient-matched normal epithelia exhibited negligible expression (Table 1) (Menéndez et al. 2010, 2012a). Positive Kv11.1 expression was thus found in 108 (87%) out of 124 primary HNSCC (Menéndez et al. 2012a) and Kv3.4 expression in over 40% HNSCC samples at both mRNA and protein levels (Menéndez et al. 2010). Similarly, increased expression of both Kv channel subunits has also been frequently observed in oral squamous cell carcinomas (OSCC) (Chang et al. 2003; Fernández-Valle et al. 2016a, b). Expression of Kv3.4 and Kv11.1 is also frequently detected in early stages of HNSCC tumourigenesis (Table 1). Immunohistochemical analysis of Kv3.4 protein has been performed in both laryngeal and oral precancerous lesions, and results consistently revealed positive Kv3.4 expression in 35 (52%) out of 67 laryngeal dysplasias (Menéndez et al. 2010), 50% of oral dysplasias and 16% of hyperplastic lesions (Fernández-Valle et al. 2016a), while staining was negligible in stromal cells and normal adjacent epithelium. Likewise, positive Kv11.1 immunostaining was also frequently observed in 31 (41%) of 75 laryngeal dysplasias (Menéndez et al. 2012a) and 22 (36%) of 62 oral leukoplakias (Fernández-Valle et al. 2016b). Two alternatively spliced variants have been described for Kv11.1 (London et al. 1997), and the two corresponding proteins, the full-length variant Kv11.1a (HERG1A) and the N-terminal splice variant Kv11.1b (HERG1B), have been detected in tumour cell lines (Crociani et al. 2003). Both subunits can assemble to form heteromeric channels that produce currents with unique, intermediate deactivation properties (London et al. 1997). The Kv11.1a/1b ratio changes during the cell cycle and has been postulated to be determinant for the proliferation of tumour cells (Crociani et al. 2003). Physiologically, Kv11.1a is expressed at higher levels in heart tissue compared to Kv11.1b (Guasti et al. 2008); however, it has been recently demonstrated that Kv11.1b is functionally present in induced pluripotent stem cellderived cardiomyocytes (iPSC-Cms) (Goversen et al. 2019). Kv11.1b has been

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Table 1 Dysregulation of potassium (K+) channels in head and neck cancers Channel Kv3.4

HGNC symbol KCNC4

Kv10.1

KCNH1

Kv11.1

KCNH2

KCa3.1

KCNN4

Kv1.3

KCNA3

Dysregulation status " HNSCC tissue samples " OSCC tissue samples " HNSCC cell lines " Precancerous lesions " HNSCC tissue samples " HNSCC cell lines

Biological processes affected Proliferation, invasion (non-canonical properties)

Clinical relevance Cancer risk marker, therapeutic target

Proliferation, invasion (non-canonical properties)

" HNSCC tissue samples " OSCC tissue samples " HNSCC cell lines " Precancerous lesions Detected in HNSCC cell lines # CD8+ TILs # CD8+ TILs

Proliferation, invasion (non-canonical properties)

Early diagnostic marker, tumour marker, poor prognosis, therapeutic target Cancer risk marker, tumour marker, poor prognosis, therapeutic target

Chemotaxis of CD8+ TILs, immunosuppression

Potential target for immunotherapy

T-cell activation

Marker of T-cell competence

References Menéndez et al. (2010), Chang et al. (2003), FernándezValle et al. (2016a), Lew et al. (2004) Menéndez et al. (2012b)

Menéndez et al. (2012a), FernándezValle et al. (2016b)

Yin et al. (2016), Chimote et al. (2013) Chimote et al. (2017)

Evidence of K+ channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. HNSCC head and neck squamous cell carcinoma, OSCC oral squamous cell carcinoma, TILs tumour-infiltrating lymphocytes

pointed as the prevalent isoform in cancer cells (Crociani et al. 2003) particularly in leukaemia (Pillozzi et al. 2007, 2014; Erdem et al. 2015). Contrasting this, the analysis of Kv11.1a and Kv11.1b expression by real-time RT-PCR in a panel of 10 HNSCC-derived cell lines showed that Kv11.1a was the most abundant isoform (Menéndez et al. 2016). Moreover, immunohistochemical evaluation of 133 HNSCC tissue specimens using a Kv11.1a-specific antibody (anti-HERG1A-NT) further evidenced that Kv11.1a expression was highly predominant in 90% of tumours (Menéndez et al. 2016). Expression of Kv11.2 (also known as HERG2 or KCNH6) and Kv11.3 (HERG3 or KCNH7) has also been reported in HNSCC cell

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lines by real-time RT-PCR (Menéndez et al. 2016), although not yet confirmed in tissue samples. Similar to Kv11.1, another member of the EAG channel family, Kv10.1 is also frequently expressed in over 80% of primary tumours and HNSCC-derived cell lines (Table 1), as shown by real-time RT-PCR (Menéndez et al. 2012b). Noteworthy, Kv10.1 expression was also detected in 39% of patient-matched normal mucosa samples, while normal epithelia from non-oncologic patients without exposure to tobacco carcinogens (i.e. children tonsillectomy) showed negative expression (Menéndez et al. 2012b). This observation may reflect the early occurrence of aberrant Kv10.1 expression during HNSCC tumourigenesis, although it remains unclear whether this change is driven by carcinogen exposure and/or directly involved in malignant transformation. In this respect, various studies have demonstrated a link between Kv10.1 expression and different cancer risk factors (CázaresOrdoñez and Pardo 2017). It has also been shown that Kv10.1 expression is early and rapidly upregulated by chemical carcinogens (dimethylhydrazine and N-methyl-Nnitrosourea) in colon cancer models, which suggests an active role in carcinogenesis (Ousingsawat et al. 2007). The study of the mechanisms that underlay Kv channel dysregulation in HNSCC demonstrated that the expression of the aforementioned ion channels (Kv3.4, Kv10.1, Kv11.1, Kv11.2 and Kv11.3) is controlled by epigenetic transcriptional regulation (Menéndez et al. 2012b, 2016). Thus, Kv mRNA levels were widely and highly induced by treatment with the inhibitor of histone deacetylase (HDAC) suberoylanilide hydroxamic acid (SAHA) in the HNSCC-derived cell lines SCC38 (from larynx) and SCC40 (tongue) (Menéndez et al. 2012b, 2016). Specifically, Kv3.4 expression only showed a slight increase in SCC40 cells upon SAHA treatment (Menéndez et al. 2016), which suggests that additional mechanisms may contribute to the aberrant Kv3.4 expression in HNSCC. Subsequent analysis of the acetylation status at each Kv gene promoter using chromatin immunoprecipitation (ChIP) assays revealed enrichment of histone activating marks such as H3Ac and H4K16Ac, which concomitantly accompanied increased Kv mRNA levels in HNSCC cells (Menéndez et al. 2012b, 2016). The effects of the demethylating agent 5-aza-20 -deoxycytidine (5-AZA) on Kv10.1 and Kv11.1 expression were also investigated in SCC38 and SCC40 cells; however, no significant changes were observed (Menéndez et al. 2012b, 2016). Furthermore, methylation analysis of KCNH1 gene promoter (Kv10.1) in HNSCC cells showed less than 10% of methylated CpG islands (Menéndez et al. 2012b). Together these findings support the importance of histone acetylation, but not methylation, to modulate Kv10.1 and Kv11.1 levels in HNSCC. In light of these findings, it is advisable to be cautious when suggesting the use of HDAC inhibitors for cancer treatment, as these agents may enhance the expression and oncogenic properties of Kv10.1 and Kv11.1 in HNSCC and perhaps in other cancers. KCNH1 gene, encoding human Kv10.1 channel subunit, maps to chromosomal region 1q32, which is commonly amplified in HNSCC and other cancers. This fact prompted the analysis of KCNH1 gene copy number in 88 primary HNSCC samples, paired normal epithelia and 32 precancerous lesions by real-time PCR (Menéndez

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et al. 2012b). KCNH1 gene copy gains (ranging from two- to threefold) were detected in 13 (15%) tumours and also 4 patient-matched normal mucosa. This low frequency clearly indicates that this is not the primary mechanism responsible for the aberrant Kv10.1 expression observed in 83% of primary tumours. Moreover, none of the precancerous lesions harboured KCNH1 copy number alterations, which jointly reflects that KCNH1 gene copy gain/amplification is a rare and late event in HNSCC tumorigenesis (Menéndez et al. 2012b).

2.1.1

Pathobiological Role

In vitro functional studies in HNSCC-derived cell lines have contributed to clarify the pathobiological role of Kv3.4, Kv10.1 and Kv11.1, demonstrating their contribution to cell proliferation and invasion, although independently of their ion-conducting function (non-canonical) (Table 1; Fig. 2) (Menéndez et al. 2010, 2012a, b). Non-canonical properties have been described for each of the major classes of ion channels involved in cell excitability, including sodium, calcium and potassium channels (Kaczmarek 2006). It has been demonstrated that mutant non-conducting subunits lacking a functional pore have the same effect as the functional channel and that ion channels can directly activate enzymes linked to cellular signalling pathways, serve as cell adhesion molecules or even cytoskeleton components (Kaczmarek 2006). Moreover, functional Kv10.1 channel has been detected in the inner nuclear membrane of NIH3T3, CHO, HEK293 and HeLa cells through immunofluorescence staining and confirmed by patch-clamp in HEK293 cells ectopically expressing Kv10.1 subunit (Chen et al. 2011). Even though the function that Kv10.1 channel may exert at the inner nuclear membrane is unknown, quite remarkably the presence of Kv10.1 at this location has been related to heterochromatin enriched areas, and as a consequence, a plausible role in gene expression regulation has been proposed perhaps by indirect interaction with heterochromatin (Chen et al. 2011). Various selective current blockers were used to investigate the role of Kv3.4, Kv10.1 and Kv11.1 on the proliferation of HNSCC cells: BDS-I (peptide toxin isolated from Anemonia sulcata that specifically blocks Kv3.4 currents (Diochot et al. 1998)), imipramine (tricyclic antidepressant that acts as a low specificity channel blocker known to inhibit Kv10.1 and Kv11.1 currents at micromolar level (Gavrilova-Ruch et al. 2002)), astemizole (second-generation antihistamine used in the treatment of allergy symptoms that cause acquired long QT syndrome by blocking Kv11.1 activity (Zhou et al. 1999)), E-4031 (class III antiarrhythmic drug that selectively blocks Kv11.1 (hERG) channels (Herzberg et al. 1998)) or mAb56 (Kv10.1-specific blocking antibody (Gomez-Varela et al. 2007)). None of these specific blockers showed any effect on the growth of SCC38, SCC40 and SCC42B cells (Menéndez et al. 2010, 2012a, b); however, specific knockdown of each Kv channel expression by siRNA transfection specifically and significantly reduced cell growth (Table 1; Fig. 2) (Menéndez et al. 2010, 2012a, b). The A-type

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Fig. 2 Biological processes affected by altered expression/activity of ion channels in the specific context of head and neck cancer. Ion channels are listed according to the IUPHAR nomenclature. EMT epithelial-mesenchymal transition. CaCC specifically refers to anoctamin 1 functions (ANO1)

K+ channel blocker 4-aminopyridine (4-AP) was found to inhibit the proliferation of OECM-1 cells (derived from oral carcinoma) (Lew et al. 2004) and also SCC38 and SCC42B cells (from laryngeal carcinomas) (unpublished data). Matrigel invasion assays showed that the invasive properties of HNSCC cells were dramatically impaired by specific siRNA-mediated channel knockdown (Table 1; Fig. 2) (Menéndez et al. 2010, 2012a, b).

2.1.2

Clinical Relevance

Mounting evidence convincingly demonstrates that Kv3.4, Kv10.1 and Kv11.1 dysregulation is biologically and clinically relevant in HNSCC development and/or disease progression, making these channels promising candidates as cancer

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risk markers, tumour markers, as well as potential membrane therapeutic targets (Table 1). Aberrant Kv expression frequently and commonly occurs in early stages of HNSCC tumourigenesis. More importantly, analysis of Kv3.4 and Kv11.1 expression in large series of laryngeal precancerous lesions uncovered a potential application as powerful predictors of cancer risk beyond histopathological evaluation that, despite its limited predictability, remains the current gold standard in routine clinical practice (Table 1) (Menéndez et al. 2010, 2012a). Similarly, patients harbouring oral leukoplakias with positive expression of Kv3.4 or Kv11.1 also showed a higher OSCC incidence than patients with negative expression (Fernández-Valle et al. 2016a, b); however, these differences did not reach statistical significance, probably due to the limited number of dysplastic lesions in these cohorts. Nonetheless, results also showed that Kv3.4 and Kv11.1 expression may not be sufficient to promote tumourigenesis, since approximately 20% of tumours were subsequently developed from lesions with negative expression. Alternatively, it is plausible these tumours could have originated over time from distinct lesions to those initially biopsied and evaluated. The role of Kv3.4, Kv10.1 and Kv11.1 in tumour progression has also been meticulously investigated in large cohorts of HNSCC patients and correlated with clinicopathological characteristics and disease outcome. Kv10.1 expression was found to increase during HNSCC progression, and it was more frequent in larger (pT4) and poorly differentiated tumours, advanced IV stage and the presence of regional lymph node metastasis (Menéndez et al. 2012b). Analogous findings demonstrated that Kv11.1 expression also increased during tumour progression and was significantly associated with advanced disease stages, tumour recurrence and reduced disease-specific survival in HNSCC (Table 1) (Menéndez et al. 2012a) and OSCC (Fernández-Valle et al. 2016b). Kv11.1 expression was significantly correlated with regional lymph node infiltration and distant metastasis (Menéndez et al. 2012a). Of note, Kv11.1-positive expression was detected in 96% of patients who developed distant metastasis and 100% of cases with regional recurrence (Menéndez et al. 2012a). By contrast, Kv3.4 expression diminished in advanced stage tumours and did not show any correlation with aggressive tumour phenotypes or prognosis in HNSCC and OSCC patients (Menéndez et al. 2010; Fernández-Valle et al. 2016a). Quite consistently, these findings support a role for Kv3.4 channel in the development of HNSCC and OSCC rather than in late stages of disease progression. Quite remarkably, aberrant expression of Kv10.1 and Kv11.1 was observed in an overwhelmingly high percentage of HNSCC tissue samples and derived cell lines (ranging between 80 and 90%), while both were absent in the corresponding normal counterparts. Similarly, frequent expression of these Kv channels has also been reported in other types of solid and soft tumours, and so being both proposed as tumour markers (Table 1) (Pardo and Stühmer 2014). Moreover, since the specific abrogation of Kv expression into HNSCC cell lines using siRNAs showed a major impact on cell proliferation and invasion, both Kv channels have been pointed as very promising therapeutic targets (Table 1). It is worth noticing that the possible

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strategies must be designed to tackle their non-canonical properties in order to be successful. According to these findings, Kv expression may enhance tumour growth and invasive capacity to favour tumour progression and metastatic spread, hence postulating these Kv channels as useful anti-proliferative and anti-metastatic targets for cancer therapy.

2.2

Calcium-Activated Potassium Channels

Potassium (K+) channels can be classified by their topology based on the primary amino acid sequence of the pore-containing subunit, thus distinguishing three groups with six, four or two putative transmembrane (TM) segments. Calcium-activated K+ channels present 6TM, and they share this topology with Kv channels and cyclicnucleotide gated channels, among others. Yin et al. (2016) reported the expression of KCa3.1 channel (also known as KCNN4, hSK4, hKCa4, hIKCa1 or IK) in two HNSCC-derived cell lines, SNU-1076 originated from a laryngeal carcinoma and OSC-19 from OSCC (Table 1). KCa3.1 channel was completely functional, as demonstrated by patchclamp analysis, and the current was abrogated by TRAM-34, a specific inhibitor of KCa3.1 channels (Yin et al. 2016). KCa2.1 channel (also hSK1 or KCNN1) was also detected at mRNA level in these HNSCC cell lines; however, patch-clamp experiments suggested that the corresponding protein was not functional. KCa3.1 mRNA and currents were not observed in the OSCC cell line HN5 (Yin et al. 2016). Once the expression and clinical impact of KCa3.1 channel is confirmed in tumour samples, its possible role as therapeutic target may gain value since its activation can prevent cancer cell death induced by ionomycin (Yin et al. 2016) and its inhibition has been related to reduced cell proliferation in other types of cancers (Jäger et al. 2004; Ouadid-Ahidouch et al. 2004; Parihar et al. 2003).

2.2.1

Pathobiological Role

KCa3.1 channel and the Shaker-related voltage-gated Kv1.3 (KCNA3, MK3, HLK3 or HPCN3) channel have been involved in tumour immunosurveillance (Table 1; Fig. 2). These two K+ channels are predominant in human T cells (Cahalan and Chandy 2009), thereby playing a key role in T-cell activation as they control Ca2+ influx upon antigen presentation to T-cell receptors (TCR) (Cahalan and Chandy 2009; Wang and Xiang 2013; Feske et al. 2012, 2015). The presence of tumour immune infiltrates has been associated with a good response to treatment in different malignancies (Fridman et al. 2012), although the efficacy of the response can be attenuated by factors such as the location and functional state of the tumourinfiltrating lymphocytes (TILs) (Wallis et al. 2015). Recently, Kv1.3 channel has been suggested as a marker for functionally competent TILs in HNSCC (Table 1) (Chimote et al. 2013). The expression of Kv1.3 was

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suppressed in CD8+ but not CD4+ TILs from HNSCC patients, leading to the suppression of Ca2+ signalling and compromising their effector functions as evidenced by reduced Ki67 staining and decreased granzyme B production in TILs that displayed lower Kv1.3 expression levels (Chimote et al. 2013). Interestingly, CD8+ TILs with weak Kv1.3 expression preferentially infiltrated within the tumour, while stromal CD8+ TILs showed significantly higher Kv1.3 levels (Chimote et al. 2013). Therefore, defects in Kv1.3 expression might hinder immunosurveillance in HNSCC patients, although the results should be further verified in a larger cohort. The same authors demonstrated that KCa3.1 channel activity is attenuated in circulating CD8+ T cells from HNSCC patients (Table 1) (Chimote et al. 2017). This attenuation is mediated by adenosine, which tends to accumulate in the tumour microenvironment where it exerts immunosuppressive actions (Whiteside 2017). The chemotaxis of CD8+ T cells is impaired in the presence of adenosine and can be recovered when cells are treated with agonists of the adenosine A2A receptor (Chimote et al. 2017). In an attempt to elucidate the mechanisms of KCa3.1 dysfunction and impaired chemotaxis in HNSCC CD8+ T cells, the same authors demonstrated that Ca2+/Calmodulin (CaM) expression is reduced in HNSCC T cells compared to healthy donors (Chimote et al. 2020). Since CaM controls KCa3.1 activation, this localised reduction of membrane-proximal CaM resulted in decreased CaM-KCa3.1 association and suppressed KCa3.1 activity in HNSCC T cells, subsequently limiting their ability to infiltrate adenosine-rich tumour microenvironments (Chimote et al. 2018). According to these data, KCa3.1 activators could be used as positive modulators of CD8+ T-cell function in cancers.

2.2.2

Clinical Relevance

The clinical relevance of KCa3.1 channel remains to be elucidated. Nonetheless, considering that the activation of KCa3.1 channel with 1-EBIO is able to revert the abovementioned inhibitory effects of adenosine in CD8+ cells, it has been suggested that drugs aimed at increasing KCa3.1 activity may help to improve immunotherapy response in cancer patients through an augmented penetration of CD8+ T cells into the tumour (Table 1) (Chimote et al. 2017). Evidences by Chimote et al. (2018, 2020) strengthen the therapeutic potential of KCa3.1 activators, as a promising strategy to restore cytotoxic T-cell functionality, to increase tumour infiltration and to ultimately enhance anti-tumour immune response. However, more research is needed to further confirm this. KCa3.1 channel has also been pointed as a potential therapeutic target. It is advisable to check the expression and the clinical correlations of KCa3.1 channel in HNSCC patients before drawing any conclusion.

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3 Dysregulation of Sodium Channels Despite the essential role that sodium channels exert in physiology, very little is known about their involvement in HNSCC development or progression. At the present, the only member of this large family that has been studied in HNSCC is Nav1.5, also referred to as SCN5A, LQT3, HB1, HBBD, PFHB1 or IVF. The expression of Nav1.5 has been analysed at both mRNA and protein level in 26 OSCC samples and 10 samples of normal mucosa (Table 2) (Liu et al. 2017). Although sample size was small, Nav1.5 expression was significantly higher in tumours than controls (Liu et al. 2017). In addition, Nav1.5 expression significantly increased in those patients displaying lymph node metastasis when compared with the non-metastatic group (Liu et al. 2017). A complementary study demonstrated that Nav1.5 channel is overexpressed in four different OSCC-derived cell lines, while its expression was barely detectable in human normal oral HOK cells (Zhang et al. 2019). Concordant with the previous data on OSCC tissue specimens, Nav1.5 expression levels were higher in the metastatic cell line HSC-3 than in SCC-4/15 and CAL-27 cells exhibiting low or non-invasive capabilities, respectively.

3.1

Pathobiological Role

It has recently been demonstrated that pharmacological and transcriptional inhibition of Nav1.5 channel function impaired the proliferation, migration and invasion of HSC-3 cells (Table 2; Fig. 2) (Zhang et al. 2019). Nav1.5 expression in HSC-3 cells was controlled by EGF and accompanied by an increase in cell proliferation, migration and invasion that was successfully diminished by treatment with either the specific inhibitor tetrodotoxin or specific siRNA (Zhang et al. 2019). Table 2 Dysregulation of sodium (Na+) channels in head and neck cancers

Channel Nav1.5

HGNC symbol SCN5A

Dysregulation status "OSCC tissue samples "OSCC cell lines "OSCC lymph node metastasis

Biological processes affected Proliferation, migration, invasion

Clinical relevance Metastatic marker, therapeutic target

References Liu et al. (2017), Zhang et al. (2019)

Evidence of Na+ channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. OSCC oral squamous cell carcinoma

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Clinical Relevance

Even though the role of Nav1.5 channel dysregulation has been scarcely investigated in the context of HNSCC, consistent results from the studies published so far support a possible role for Nav1.5 as a biomarker for metastatic cancer and an emerging therapeutic target (Table 2). It is also worth to highlight the first evidence for a link between Nav1.5 channel activity and EGFR signalling, which nowadays constitute the most important molecular target used for the treatment of HNSCC patients.

4 Dysregulation of Calcium Channels 4.1

Voltage-Gated Calcium Channel Subunits

Voltage-dependent calcium channels (VDCC) are voltage-gated channels permeable to Ca2+ that, under physiological conditions, are usually closed. They can be activated by depolarised membrane potentials. Only a few of the subunits that compose calcium channels have so far been found altered in the context of HNSCC. The expression of the Cavα2δ-1 subunit, also known as CACNA2D1, has been detected in 13 out of 16 laryngeal squamous cell carcinoma (LSCC) samples but only 2 of 16 normal tissue samples (Table 3) (Huang et al. 2019). Cav3.1 subunit, encoded by the CACNA1G gene, was also found highly expressed in both LSCC tissue samples and cell lines (Yu et al. 2014). By contrast, the expression of CACNA2D3 transcript, which codes for the Cavα2δ-3 subunit, was downregulated in 12 of the 13 nasopharyngeal carcinoma (NPC) samples compared to the corresponding adjacent tissue (Wong et al. 2013). It was further shown that CACNA2D3 downregulation was due to both loss of heterozygosity (LOH) and epigenetic silencing, i.e. methylation of the promoter region CpG island.

4.1.1

Pathobiological Role

Inhibition of Cav3.1 function by either siRNA or channel blocker mibefradil impaired the proliferation of Hep-2 cells, thereby inducing cell cycle progression arrest (Table 3; Fig. 2) (Yu et al. 2014). Contrary to this, overexpression of Cavα2δ-3 subunit in two different NPC cell lines with low endogenous levels (C666 and SUNE1) diminished cell growth in vitro and in vivo (Wong et al. 2013). Mechanistically, Cavα2δ-3 was proved to mediate increased intracellular levels of Ca2+, caspase 9 and caspase 3 expressions and annexin V to ultimately induce apoptosis. In addition, Cavα2δ-3 antagonised Wnt signalling by upregulating Nlk, which resulted in a decrease of β-catenin levels. Subsequently, the expression of multiple Wnt-mediated oncogenes known to regulate proliferation, invasion and epithelial to mesenchymal transition (EMT) such as MYC, CCND1, MMP7 and SNAIL also

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Table 3 Dysregulation of calcium (Ca2+) channels in head and neck cancers Channel Cav3.1

HGNC Symbol CACNA1G

Dysregulation status " LSCC tissue samples " LSCC cell lines " LSCC tissue samples

Biological processes affected Proliferation

Clinical relevance Therapeutic target

Cavα2δ-1

CACNA2D1

Migration, invasion, stemness, chemoresistance

Huang et al. (2019)

CACNA2D3

# NPC tissue samples

ORAI1

"OSCC tissue samples " Precancerous lesions

Cell growth, apoptosis, invasion, metastasis, EMT, in vivo tumour growth and metastasis Proliferation, migration, invasion, stemness, in vivo tumorigenesis

Stem cell marker, treatment resistance Tumour suppressor gene

Cavα2δ-3

Orai1

Therapeutic target

Lee et al. (2016)

References Yu et al. (2014)

Wong et al. (2013)

Evidence of Ca2+ channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. LSCC laryngeal squamous cell carcinoma, NPC nasopharyngeal carcinoma, OSCC oral squamous cell carcinoma, EMT epithelialmesenchymal transition

decreased at both transcriptional and translational level. Consistent with these data, Cavα2δ-3-overexpressing cells diminished metastasis in vivo, thereby causing E-cadherin upregulation and downregulation of both vimentin and fibronectin, which reflects that Cavα2δ-3 impairs EMT (Wong et al. 2013). According to these findings, Cavα2δ-3 has been postulated as a tumour suppressor gene in NPC. Huang et al. (2019) separated Cavα2δ-1+ cells from Cavα2δ-1- cells in two LSCC cell lines, TU686 and TU212, and found that cells expressing the channel subunit performed better in both migration and invasion assays (Table 3; Fig. 2). In addition, these authors studied the impact of Cavα2δ-1 on stemness and self-renewal capacity by using sphere formation assays. Results showed that Cavα2δ-1+ cells exhibited increased ability to form tumourspheres than the Cavα2δ-1- cells and also a higher tumorigenic ability in vivo. Together these findings demonstrate that Cavα2δ-1+ cells have higher self-renewal and tumour-initiating capacity (Table 3; Fig. 2). Furthermore, chemoresistance to cisplatin and paclitaxel was tested, and according to the data obtained by flow cytometry, the percentage of Cavα2δ-1+ cells increased after treatment with both drugs, indicating that Cavα2δ-1-expressing cells seem to be indeed more resistant to chemotherapy.

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Clinical Relevance

In light of the current reported data for the three calcium channel subunits dysregulated in HNSCC, Cav3.1 has been proposed as a novel therapeutic target in HNSCC (Table 3) (Yu et al. 2014). Conversely, Cavα2δ-3 emerges a candidate as tumour suppressor gene for NPC. Although Cavα2δ-3 is obviously not a candidate for direct targeting, it has been suggested that demethylating agents might be useful to increase CACNA2D3 expression and potentially for NPC treatment (Wong et al. 2013). Cavα2δ-1 has been suggested as a new stem cell marker in LSCC, and this channel could also play a role in chemoresistance (Table 3) (Huang et al. 2019).

4.2

Other Calcium Channels

Orai1 is one of the subunits of the calcium release-activated channel (CRAC), a calcium channel commonly present in non-excitable cells. Its expression has been reported to be upregulated in HNSCC tissue samples (from oral cavity and oropharynx) and also precancerous lesions (dysplasia) compared to normal epithelia (Table 3) (Lee et al. 2016).

4.2.1

Pathobiological Role

In order to investigate the biological role of Orai1 in OSCC, Lee et al. (2016) generated a dominant negative mutant form (E106Q), which can block functionally wild-type (wt) Orai1 channel. SCC4 cells (derived from an OSCC) expressing this mutant form showed impaired proliferation, migration and invasion, as compared to cells expressing wt Orai1 (Table 3; Fig. 2). Moreover, Orai1 channel was also found to promote stemness and the tumour-initiating potential of OSCC cells (Table 3; Fig. 2). Accordingly, SCC4/E106Q mutant cells formed significantly less colonies in soft agar than parental SCC4 cells in vitro, and they were also non-tumorigenic in vivo, whereas wt Orai1 cells caused tumours in three out of five inoculated mice (Lee et al. 2016). Moreover, NFAT signalling was found to be essential for Orai1 regulation of cancer stem cell (CSC) phenotype in OSCC, and NFATc3 was pointed as a major downstream effector. Furthermore, the NFAT antagonist cyclosporine A (CsA) significantly reduced both tumour sphere formation and cell migration.

4.2.2

Clinical Relevance

Lee et al. (2016) demonstrated that Orai1 expression increases at both mRNA and protein levels during oral/oropharyngeal carcinogenesis, thereby suggesting an important role of Orai1 in tumour progression. The same authors provided original

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evidence showing that inhibition of the Orai1-NFAT axis efficiently abrogated tumourigenicity and stemness, and as such it has been proposed as a potential molecular-targeted therapy for OSCC (Table 3).

5 Dysregulation of Transient Receptor Potential Cation Channels The transient receptor potential (TRP) family consists of 28 channels permeable to cations. Six subfamilies have been defined in humans based on homology: TRPA (ankyrin), TRPC (canonical), TRPM (melastatin), TRPML (mucolipin), TRPP (polycystin) and TRPV (vanilloid) (Li 2017). Since TRP channels control the flux of important ions like Ca2+ and Mg2+ that regulate many biological functions, alterations of these channels are frequent in all types of cancer, including HNSCC. An in silico analysis done by Park et al. (2016) with data from the International Cancer Genome Consortium from 353 HNSCC patients revealed altered expression of 12 of the 21 TRP genes. Expression of TRPC4, TRPC6, TRPV2, TRPV3, TRPM2, TRPML3, TRPP1 and TRPA1 was thus found to be upregulated, whereas expression of TRPV6, TRPM3, TRPM6 and TRPM8 was downregulated (Table 4). Only few of these targets have been confirmed experimentally by other groups. Bernaldo de Quirós et al. (2013) found increased levels of TRPC6 mRNA in 13 out of 24 HNSCC tissue samples compared to patient-matched normal mucosa and normal mucosa from healthy donors (Table 4). Furthermore, TRPC6 overexpression was concomitantly accompanying by TRPC6 gene amplification in 11 of 13 tumours, suggesting this is the primary underlying mechanism for the overexpression of this gene. Overexpression of TRPV2 and TRPV3 has been detected by IHC and mRNA quantification in 37 OSCC patients, when compared to normal tissue (Sakakibara et al. 2017). This study also assessed the expression of TRPV1 and TRPV4 channels, both found to be upregulated (Table 4). Gonzales et al. (2014) also reported TRPV1 overexpression in OSCC patients. In addition, TRPM2 overexpression has been demonstrated in 22 of the 23 tongue carcinomas by IHC, while TRPM2 expression was negligible in any of the 9 control tissues analysed (Table 4) (Zhao et al. 2016). Other TRP channels have been found dysregulated in HNSCC beyond those mentioned in the study by Park et al. (2016). Thus, Wu et al. (2016) reported TRPP2 overexpression by IHC in LSCC samples compared to patient-matched normal tissue (Table 4). Similarly, TRPM7 overexpression was also detected in nine HNSCC tissue samples, as compared to the corresponding normal counterpart (Qiao et al. 2019).

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Table 4 Dysregulation of transient receptor potential (TRP) cation channels in head and neck cancers Dysregulation status " HNSCC tissue samples NA " HNSCC tissue samples

Biological processes affected NA

Channel TRPA1

HGNC symbol TRPA1

TRPC1 TRPC4

TRPC1 TRPC4

TRPC6

TRPC6

" HNSCC tissue samples

Invasion, migration

TRPM2

TRPM2

Migration, apoptosis, xerostomia

TRPM3

TRPM3

TRPM6

TRPM6

TRPM7

TRPM7

" HNSCC tissue samples " Tongue carcinoma samples # HNSCC tissue samples # HNSCC tissue samples " HNSCC tissue samples

TRPM8

TRPM8

TRPML1

Invasion NA

Clinical relevance Cancer biomarker Therapeutic target Cancer biomarker, diagnostic marker Therapeutic target, cancer biomarker

NA

Therapeutic target, cancer biomarker, xerostomia treatment NA

NA

NA

Proliferation, invasion, migration

Therapeutic target

# HNSCC tissue samples

Invasion, migration

Therapeutic target

TRPML1

NA

Proliferation

TRPML3

TRPML3

NA

TRPP1

TRPP1

NA

NA

TRPP2

TRPP2

" HNSCC tissue samples " HNSCC tissue samples " LSCC tissue samples

Therapeutic target, cancer biomarker NA

Therapeutic target

TRPV1

TRPV1

Proliferation, invasion, migration, EMT NA

" OSCC tissue samples

Therapeutic target

References Park et al. (2016) He et al. (2012) Park et al. (2016) Park et al. (2016), Bernaldo de Quirós et al. (2013) Park et al. (2016), Zhao et al. (2016), Liu et al. (2013) Park et al. (2016) Park et al. (2016) Qiao et al. (2019), Jiang et al. (2007), Dou et al. (2013) Park et al. (2016), Okamoto et al. (2012) Jung et al. (2019) Park et al. (2016) Park et al. (2016) Wu et al. (2016), (2017)

Sakakibara et al. (2017), Gonzales et al. (2014) (continued)

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Table 4 (continued)

Channel TRPV2

HGNC symbol TRPV2

TRPV3

TRPV3

TRPV4

TRPV4

TRPV6

TRPV6

Dysregulation status " HNSCC tissue samples " OSCC tissue samples " HNSCC tissue samples " OSCC tissue samples "OSCC tissue samples # HNSCC Tissue samples

Biological processes affected NA

Clinical relevance Therapeutic target, cancer biomarker

NA

Therapeutic target

NA

Therapeutic target

NA

Cancer biomarker

References Park et al. (2016), Sakakibara et al. (2017) Park et al. (2016), Sakakibara et al. (2017) Sakakibara et al. (2017) Park et al. (2016)

Evidence of TRP channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. Xerostomia refers to the damage of salivary gland secretion caused by radiotherapy treatment. HNSCC head and neck squamous cell carcinoma, LSCC laryngeal squamous cell carcinoma, OSCC oral squamous cell carcinoma, EMT epithelial-mesenchymal transition, NA not available information

5.1

Pathobiological Role

Most of the TRP channels are involved in maintaining the homeostasis of cations like Na2+, Ca2+, K+, Mg2+ or Zn2+, which play a crucial role in multiple biological processes such as cell proliferation, cell cycle regulation and invasion, among others. The effects of TRPM7 channel on cell proliferation have been extensively studied (Table 4; Fig. 2). Different mechanisms have been proposed to explain how TRPM7 inhibition, either pharmacologically or by siRNA, impairs cell proliferation. In this sense, its function as a Ca2+ channel seems to have a major contribution. Jiang et al. (2007) showed that decreasing the extracellular concentration of Ca2+ reduced the proliferation of FaDu cells derived from a hypopharyngeal carcinoma. Analogous effect was observed when using two non-specific inhibitors of TRPM7, namely, Gd3 + and 2-Aminoethoxydiphenyl borate (2-APB). A lower, although still significant, effect was observed when using siRNA targeting TRPM7, which has been related to low transfection efficiency or the fact that these two blockers may target other members of the TRP channel family. It has also been demonstrated that the TRPM7-dependent effect on cell proliferation was inhibited by midazolam, a benzodiazepine that acts in a benzodiazepine receptor-independent manner to decrease TRPM7 expression in FaDu cells (Dou et al. 2013). Moreover, this inhibitory effect was restored by treatment with the TRPM7 agonist bradykinin. Another mechanism by which TRPM7 can regulate cell growth is the flux of Mg2+. According to the

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results presented by Qiao et al. (2019), the proliferation rate of two different HNSCC cell lines (FaDu and CAL27) was induced by adding Mg2+, which also caused TRPM7 overexpression. Targeting TRPM7 channel activity and/or expression with either the inhibitor FTY720 or siRNA reduced the proliferation of these cells. This effect was mechanistically linked to mTOR, which was upregulated when adding Mg2+ and inhibited by FTY720. Another channel related to proliferation is TRPML1. Jung et al. (2019) found that inhibition of TRPML1 channel specifically reduced the proliferation of cells harbouring the HRAS mutation G12V but had no effect in HRASWT cells (Table 4; Fig. 2). Furthermore, in HRASG12V cells, TRPML1 expression was necessary for the growth advantage characteristic of cells carrying HRAS mutations. On the other hand, it has been shown that TRPP2 inhibits cell proliferation (Wu et al. 2017). The proliferation of Hep-2 cells from laryngeal cancer was induced upon tumour necrosis factor α (TNF-α) treatment, and this effect was related to TRPP2 inhibition (Table 4; Fig. 2). The involvement of TRPP2 channel was further confirmed by siRNA silencing, which led to increased proliferation independent of TNF-α. There are also evidences for the contribution of various TRP channels to cell migration and invasion in HNSCC (Table 4; Fig. 2). The study by Qiao et al. (2019) proved the effect of Mg2+ through TRPM7 in cell migration and invasion, which were impaired by TRPM7 channel blockade using FTY720 or siRNA. However, this study did not assess whether the effect on migration and invasion occurs through the mTOR pathway, as proved for cell proliferation. Similarly, TRPP2 silencing using specific siRNA significantly impaired both invasion and migration in Hep-2 cells (Wu et al. 2016), and siRNA against TRPC6 was also able to reduce the migration and invasion of SCC42B cells, derived from LSCC (Bernaldo de Quirós et al. 2013). TRPM8 channel was also found to promote the invasion and migration of two different OSCC cell lines by using the agonist menthol and antagonist RQ-00203078 (Table 4; Fig. 2) (Okamoto et al. 2012). Transfection of a tongue carcinoma cell line with shRNA against TRPM2 significantly reduced its ability to migrate, as shown by Zhao et al. (2016). Another TRP channel involved in cell invasion is TRPC1 (Table 4; Fig. 2). Treatment with the inhibitor 2-APB or TRPC1 gene silencing with siRNA reduced cell adhesion and invasion in the CNE2 cell line derived from NPC (He et al. 2012). In all the studies herein presented, except for TRPM7, Ca2+ ion flux is proposed as the mechanism underlying the changes in cell motility. Various studies investigating the role of TRP channels on migration and invasion also suggested their participation in EMT (Table 4; Fig. 2); however, only Wu et al. (2016) actually tried to prove it. Transfection of Hep-2 cells with TRPP2 siRNA caused E-cadherin upregulation and vimentin downregulation. Since E-cadherin loss and vimentin upregulation are well-established characteristics of EMT, these results led to the interpretation that TRPP2 channel induces EMT. Other EMT markers found to be downregulated by TRPP2 silencing were Smad4, STAT3, SNAIL, SLUG and TWIST.

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Given that TRPM2 is known to be activated by reactive oxygen species (ROS), particularly H2O2, Zhao et al. (2016) analysed the effect of TRPM2 channel in ROS-induced cell death (Table 4; Fig. 2). Gene silencing with shRNA increased the number of apoptotic cells in the tongue carcinoma cell line SCC-9, as measured by flow cytometry staining for annexin V, thereby indicating that TRPM2 channel promotes cell survival.

5.2

Clinical Relevance

Most of the herein-reviewed studies on TRP channels altered in HNSCC suggest a potential role as novel therapeutic targets for TRPC6 (Table 4) (Bernaldo de Quirós et al. 2013), TRPV1-4 (Sakakibara et al. 2017), TRPM2 (Zhao et al. 2016), TRPP2 (Wu et al. 2016), TRPM7 (Qiao et al. 2019; Dou et al. 2013), TRPML1 (Jung et al. 2019), TRPM8 (Okamoto et al. 2012) and TRPC1 (He et al. 2012). The in silico analysis by Park et al. (2016) not only provided information on numerous TRP channels dysregulated in HNSCC but also estimated their potential use as biomarkers. Thus, elevated expression of various genes TRPC4, TRPC6, TRPV2, TRPM2, TRPML1 and TRPA1 as well as a low expression of TRPV6 could be cancer incidence markers. The best diagnostic marker was TRPC4, with a specificity of 79.49% and a sensitivity of 86.12% (Table 4; Fig. 2). On the other hand, an interesting study by Liu et al. (2013) provided the first evidence of a link between TRPM2 activation and xerostomia, which is the damage of salivary gland secretion after radiotherapy treatment of HNSCC patients (Table 4; Fig. 2). TRPM2 function was activated by irradiation treatment, through poly-ADPribose polymerase (PARP) activation. Moreover, salivary damage caused by irradiation in TRPM2+/+ mice was irreversible, while TRPM2-/- mice recovered around 60% of salivary fluid secretion in 30 days. Interestingly, treatment of TRPM2+/+ mice with 3-aminobenzamide an inhibitor of PARP1, which is a downstream target of TRPM2, also induced a significant recovery of salivary gland function. Therefore, blockade of TRPM2 activation (e.g. PARP1 inhibitors) may emerge as an effective treatment to protect and restore salivary gland function, thereby reducing this common side effect of radiotherapy in cancer patients (Table 4; Fig. 2).

6 Dysregulation of Chloride Channels Chloride channels are a family of anion-selective channels with a pore-forming structure implicated in a wide variety of biological and cellular processes including pH and cell volume regulation, neuron excitability, transepithelial transport, acidification of intra- and extracellular compartments and cell proliferation and differentiation. Chloride channels have been functionally classified according to the gating (opening) mechanism as voltage-gated chloride channels (CIC channels), calcium-

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activated chloride channels (CaCC channels), ATP-gated CFTR, ligand-gated glycine or γ-aminobutyric acid (GABA)-activated chloride channels and volumeregulated chloride channels. Given their important physiological roles, chloride channel dysfunction has been associated with several human diseases (reviewed by Puljak and Kilic 2006; Verkman and Galietta 2009).

6.1

Voltage-Gated Chloride Channels (ClCs)

Voltage-gated chloride channel ClC or CLCN family proteins are localised in the plasma membrane and intracellular vesicles, with nine different genes identified in mammals (reviewed by Poroca et al. 2017). ClC-1, ClC-2, ClC-Ka and ClC-Kb are expressed on the plasma membrane, where they function as bona fide chloride channels. ClC-3 to ClC-7 are primarily expressed in intracellular membranes, showing compartment specificity in endosomal and lysosomal membranes as intracellular exchangers. It has been suggested that ClC-3 to ClC-5 are also expressed in the plasma membrane and produce chloride currents (Friedrich et al. 1999). ClCs play a fundamental role in different physiological processes, such as regulation of resting potential in skeletal muscle, transepithelial Cl reabsorption in kidneys and pH control and Cl concentration in intracellular compartments. In fact, mutations/ dysfunctions of ClC chloride channels and ClC intracellular exchangers have been directly linked to various human-inherited diseases, including myotonia congenita, retinal degeneration, leukodystrophy, Bartter’s syndromes III and IV, Dent’s disease, osteopetrosis and lysosomal storage disease (Poroca et al. 2017). Among the voltage-activated chloride channels, ClC-3 and ClC-7 have been found to be highly expressed in poorly differentiated NPC cells (CNE-2Z) (Table 5) (Wang et al. 2012). However, knockdown of ClC-3 expression by siRNA but not ClC-7 blocked chloride currents, hence indicating that CIC-3 mainly contributes to acid-activated chloride currents in CNE-2Z cells (Wang et al. 2012). ClC-3 has been considered a major component of background chloride channels activated by autocrine/paracrine ATP via purinergic pathways, which is involved in cell volume maintenance (Yang et al. 2011). In addition, investigations by Zhang et al. (2014) revealed that ClC-3 modulates the expression of AQP-3 to form complexes in NPC cells (CNE-1 and CNE-2Z) implicated in cell volume regulation. ClC-3 expression was found to be cell cycle-dependent with low levels in G1 and high levels in S phase (Wang L-W et al. 2004), thereby playing an essential role in cell cycle progression and proliferation of CNE-2Z cells (Xu et al. 2010).

6.1.1

Pathobiological Role

Xu et al. (2010) demonstrated that ClC-3 channel regulates cell proliferation and cell cycle progression in the poorly differentiated NPC cell line CNE-2Z (Table 5; Fig. 2). Thus, targeting ClC-3 by specific antisense oligonucleotide led to the

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Table 5 Dysregulation of chloride (Cl) channels in head and neck cancers Biological processes affected Proliferation, cell cycle regulation, migration

Clinical relevance Therapeutic target, tumour marker

" NPC cell lines

NA

NA

ANO1

" HNSCC tissue samples " HNSCC cell lines " OSCC tissue samples " Precancerous lesions

Proliferation, migration, invasion, metastasis, apoptosis, in vivo tumour growth, EMT and chemoresistance

Therapeutic target, tumour marker, prognostic marker, metastasis risk marker, treatment response/ resistance

CLIC1

CLIC1

NA

Tumour marker

CLIC3

CLIC3

NA

NA

CLIC4

CLIC4

" OSCC tissue samples " NPC tissue samples and plasma "Mucoepidermoid carcinomas " OSCC tissue samples

Apoptosis

Therapeutic target

Channel ClC-3

HGNC symbol CLCN3

Dysregulation status " NPC cell lines

ClC-7

CLCN7

CaCC

References Wang et al. (2012), Xu et al. (2010), Ye et al. (2016), Zhang et al. (2013), Yu et al. (2009), Mao et al. (2007), (2008), Zhu et al. (2012), Zhou et al. (2018) Wang et al. (2012) Ruiz et al. (2012), Dixit et al. (2015), Rodrigo et al. (2015), Li et al. (2014), Wanitchakool et al. (2014), Duvvuri et al. (2012), Ayoub et al. (2010), Shiwarski et al. (2014), Godse et al. (2017), Bill et al. (2015), Guo et al. (2019), Reddy et al. (2016), Kulkarni et al. (2017) Cristofaro et al. (2014), Chang et al. (2009) Wang et al. (2015) Xue et al. (2016)

Evidence of Cl channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. CaCC specifically refers to Anoctamin 1 (ANO1). NPC nasopharyngeal carcinoma, HNSCC head and neck squamous cell carcinoma, OSCC oral squamous cell carcinoma, NA not available information

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inhibition of cell proliferation and S-phase arrest (Xu et al. 2010). Results by Ye et al. (2016) further revealed that ClC-3 regulates cell cycle progression from G0/G1 to S by upregulation of Cyclin D1-CDK4/6 through inhibition of p21 and p27 expression in CNE-2Z cells. Moreover, ClC-3 has been found to be a downstream target of Cyclin D1 (Zhang et al. 2013). As such, Cyclin D1 via CDK4/6 may functionally modulate chloride channel activity in these cells. Similarly, Yu et al. (2009) investigated the effect of ClC blockade with 5-nitro-2(3-phenylpropylamino) benzoic acid (NPPB) in the laryngeal cancer cell line Hep-2. NPPB treatment of Hep-2 cells inhibited cell proliferation, suppressed ERK1/2 and AKT1 phosphorylation and caused cell cycle arrest (Yu et al. 2009). Moreover, inhibition of ClC-3 expression reduced migration of CNE-2Z cells by modulating cell volume through regulation of volume-activated chloride currents (Mao et al. 2008). Blockade of volume-activated chloride channels with NPPB also inhibited migration of CNE-2Z cells (Mao et al. 2007). Volume-activated chloride channel currents were higher in migrating CNE-2Z cells than non-migrating cells and more sensitive to the blockers NPPB and tamoxifen, which reflects their involvement in cell migration.

6.1.2

Clinical Relevance

Observations by Zhu et al. (2012) proved increased ClC-3 expression and higher volume-activated chloride currents in cancerous CNE-2Z cells compared to normal nasopharyngeal epithelial cells (NP69-SV40T). They also demonstrated that CNE-2Z cells are more sensitive and dependent on chloride current activation to proliferate than the normal counterpart. In light of these data, ClC-3 has been proposed as a tumour biomarker and a therapeutic target for NPC (Table 5) (Zhu et al. 2012). It has also been shown that ClC-3 expression and activation contributes to the dihydroartemisinin (DHA)-induced apoptosis in CNE-2Z cells (Zhou et al. 2018), indicating that ClC-3 channel activity may play a critical role in the selective action of this anti-tumour agent in NPC (Zhou et al. 2018).

6.2

Calcium-Activated Chloride Channels (CaCCs)

Ca2+-activated Cl channel (CaCC) activity is widely observed in a variety of cell types where they play different physiological functions (reviewed by Hartzell et al. 2005; Tian et al. 2012). Anoctamins have recently emerged as a CaCC family that comprises ten different proteins (named ANO1 to ANO10). It has been demonstrated that ANO1 (also known as TMEM16A or DOG1) forms active CaCC channels at the plasma membrane, as does its closest relative ANO2 (TMEM16B) in olfactory receptors (Tian et al. 2012). These channels are essential to regulate airway fluid secretion, secretory gland functions, gut motility, renal function, smooth muscle contraction and olfactory signal transduction (Tian et al. 2012; Bill and Alex

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Gaither 2017). They have also been associated to various inherited diseases and cancer (Tian et al. 2012; Wanitchakool et al. 2014; Bill and Alex Gaither 2017). The role of other anoctamin paralogs remains largely unknown. A dual role has been described for ANO6 (TMEM16F) as a Fas ligand-activated Cl channel and phospholipid scramblase, while other anoctamins are mainly detected as intracellular proteins (Wanitchakool et al. 2014; Tian et al. 2012). ANO1 has been found frequently abnormally expressed in HNSCC (Table 5) and other cancers, such as breast, prostate, oesophageal, lung and gastrointestinal cancers (Wanitchakool et al. 2014; Bill and Alex Gaither 2017). Ruiz et al. (2012) analysed ANO1 protein expression in over 4,000 samples from 80 different cancer types and 76 normal tissue counterparts and found that ANO1 is highly expressed in HNSCC and gastrointestinal stromal tumours (GIST) compared to the normal tissues and other tumour types. In the context of HNSCC, ANO1 is predominantly overexpressed in HPV-negative HNSCC compared to HPV-positive HNSCC at RNA and protein levels in both tissue samples and HNSCC-derived cell lines (Table 5) (Dixit et al. 2015; Rodrigo et al. 2015). ANO1 gene amplification occurs frequently in over 50% HNSCCs (Rodrigo et al. 2015) and, similar to other genes mapping within 11q13 amplicon, is differentially associated to HPV-negative HNSCC (Hermida-Prado et al. 2018). In addition, ANO1 expression in HNSCC can also be epigenetically regulated by promoter methylation (Finegersh et al. 2017; Dixit et al. 2015). ANO1 gene amplification has also been frequently observed in laryngeal precancerous lesions (63%), whereas concomitant ANO1 protein expression was detected at a lower frequency (20%) (Table 5) (Rodrigo et al. 2015). Li et al. (2014) reported ANO1 protein expression in over 80% OSCC specimens. ANO1 expression was significantly higher in OSCC versus normal tissue and also in metastatic compared to non-metastatic tumours (Table 5) (Li et al. 2014).

6.2.1

Pathobiological Role

It has been shown that ANO1 may exert different roles in cell proliferation and migration depending on cell-specific protein networks and signalling pathways (Table 5; Fig. 2) (reviewed by Wang et al. 2017; Bill and Alex Gaither 2017). ANO6 has been linked to apoptosis rather than cell proliferation (Wanitchakool et al. 2014). Duvvuri et al. (2012) demonstrated that ANO1 knockdown in UM-SCC1 cells (derived from OSCC harbouring ANO1 gene amplification) inhibited tumour growth in vitro and in xenografted mice, which was concomitantly accompanied by reduced levels of ERK1/2 phosphorylation/activation. Moreover, ANO1 overexpression in HNSCC cells led to a robust activation of Ras-Raf-MEK-ERK1/ 2 pathway that was prevented by the dominant-negative mutant of H-Ras H-RasN17 (Duvvuri et al. 2012). In marked contrast, ANO1 overexpression in Hep-2 cells did not affect cell proliferation and growth in soft agar but induced cell migration and invasion altering cell adhesion, lamellipodia formation, detachment and cell spreading (Table 5; Fig. 2) (Ayoub et al. 2010). The effects of ANO1 on cell motility were dependent

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on its activity as a CaCC channel, and hence specifically targeted by CaCC blockers such as DIDS and fluoxetine, but unaffected by other Cl channel blockers such as DCPIB and CFTRinh172 (Ayoub et al. 2010). ANO1 expression and CaCC currents were also critical for cell migration in the oral carcinoma cell line SCC-25 (Li et al. 2014). Consistent with this, ANO1 gene amplification and overexpression, as well as other relevant genes within the 11q13 amplicon, were significantly associated with the development of distant metastasis in HPV-negative HNSCC (Ayoub et al. 2010). Similarly, Ruiz et al. (2012) showed that ANO1 contributes to cell volume regulation thereby favouring cell migration but not proliferation of BHY oral carcinoma cells (harbouring ANO1 gene amplification and overexpression). Inhibition of ANO1 currents by AO1 impaired cell migration, whereas proliferation remained unchanged (Ruiz et al. 2012). Accordingly, ANO1 protein expression and gene amplification was more frequent in HNSCC patients with lymph node metastasis (Ruiz et al. 2012). ANO1 expression has also been correlated with metastasis in OSCC patients (Li et al. 2014). By contrast, Shiwarski et al. (2014) found that ANO1 expression diminished in nodal metastasis compared to patient-matched primary tumours. They also proved experimentally using orthotopic mouse models that ANO1 expression dynamically drives tumour growth and metastasis formation (“grow or go” model). UM-SCC1 cells with stable ANO1 shRNA knockdown were implanted in the mouth floor of nude mice, which resulted in reduced tumour growth/size when compared to control cells. However, ANO1-shRNA tumours formed more nodal metastases than the ANO1-expressing tumours (Table 5; Fig. 2) (Shiwarski et al. 2014). Mechanistically, TMEM16A expression was regulated by DNA promoter methylation to drive progression from primary tumour to lymph node metastasis, thus promoting changes in cell motility and morphology and regulation of EMT, which involved direct interaction between ANO1 S970 residue and the actin-associated protein radixin. Godse et al. (2017) reported that ANO1 expression was correlated with tumour size and decreased apoptosis by examining a panel of 11 HNSCC samples. ANO1 overexpression was thus found to contribute to tumour progression by blocking apoptosis in FaDu cells and also in in vivo UM-SCC1 xenografts. Mechanistically, Bim expression was reduced and ERK1/2 activation increased (Godse et al. 2017). ANO1 overexpression also blocked cisplatin-induced apoptosis in HNSCC models both in vitro and in vivo (Godse et al. 2017), indicating a link between ANO1 and chemoresistance (Table 5; Fig. 2). Bill et al. (2015) demonstrated that ANO1 and EGFR form a functional complex in HNSCC cells that modulate EGFR signalling. The interaction between ANO1 and EGFR requires the trans-/juxtamembrane domain of EGFR and was found to be independent of the ANO1/CaCC channel activity and EGFR kinase activity. Moreover, a bidirectional interplay was demonstrated between both proteins. ANO1 expression regulates EGFR stability, and in turn, EGFR activation increased ANO1 protein levels. HNSCC cells harbouring ANO1 gene amplification and overexpression exhibited higher sensitivity to antiEGFR agents such as gefitinib, and cell proliferation was robustly inhibited by co-targeting ANO1 and EGFR (Bill et al. 2015). These observations suggest that

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combined treatment with ANO1 inhibitors could potentiate the clinical efficacy of EGFR-targeted therapies and overcome resistance to single anti-EGFR agents. Investigations by Guo et al. (2019) proved that matrine, a potent inhibitor of ANO1, currents with anti-tumour activity in lung adenocarcinoma cells LA795, effectively blocking cell proliferation and migration. Pharmacologic ANO1 targeting of HNSCC cells with the small inhibitor T16A-inh01 reduced cell viability in a dose-dependent manner (Duvvuri et al. 2012).

6.2.2

Clinical Relevance

Before ANO1/DOG1 was identified as a CaCC, it was established as a cancer biomarker for gastrointestinal stromal tumours (GIST) (Espinosa et al. 2008; Wanitchakool et al. 2014). Similarly, ANO1 has been proposed as a diagnostic marker for salivary acinic cell carcinoma (Table 5) (Chênevert et al. 2012). Mounting evidence indicates that ANO1 expression contributes to tumour progression in HNSCC, although with clear differences depending on the HNSCC subtype and HPV status (Dixit et al. 2015; Rodrigo et al. 2015). ANO1 has shown a major impact on patient prognosis in HPV-negative HNSCC (Dixit et al. 2015). It has also been correlated with poor prognosis in laryngeal and oral carcinomas (Table 5) (Rodrigo et al. 2015; Li et al. 2014). Accordingly, targeting ANO1 could be potentially useful for the treatment of some subsets of HNSCC patients. ANO1 has also been associated with more aggressive phenotypes, tumour recurrence and cisplatin resistance (Table 5) (Godse et al. 2017). Analysis of data from The Cancer Genome Atlas (TCGA) revealed that a significantly higher proportion of patients harbouring ANO1-overexpressing tumours recurred compared to the non-recurrent group (71% vs 26%) (Godse et al. 2017). A meta-analysis also identified ANO1 as the highest predictor of recurrence and disease failure (Reddy et al. 2016). ANO1 gene amplification and expression have also emerged as predictors of distant metastasis in HPV-negative HNSCC, thus being proposed as potential markers for distant metastasis risk (Table 5) (Ayoub et al. 2010). Moreover, it has been demonstrated that ANO1 overexpression contributes to various properties linked to metastasis, such as cell migration, invasion, cell adhesion, spreading and detachment (Ayoub et al. 2010). Conversely, it has also been reported that ANO1 knockdown promotes cell migration and metastasis formation (Shiwarski et al. 2014). Therefore, the functional consequences of ANO1 inhibition need further investigation and clarification before it can be safely and effectively applied as a potential therapeutic option for HNSCC patients. ANO1 expression has been found to correlate with response to the anti-EGFR agent gefitinib in HNSCC cells (Bill et al. 2015), and targeting ANO1 led to improve response to anti-EGFR therapies with cetuximab in HNSCC (Table 5) and also antiHER2 therapies with trastuzumab in breast cancer (Kulkarni et al. 2017). Therefore, ANO1 emerges as a predictor of response to EGFR/HER2-targeted therapies, and hence, combinational treatments with ANO1 inhibitors could enhance response to

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biological therapies and plausibly circumvent the development of ANO1-mediated resistance mechanisms.

6.3

Chloride Intracellular Channels (CLIC) Family Proteins

The chloride intracellular channel (CLIC) family represents a subgroup of the glutathione S-transferase (GSTs) superfamily, predominantly localised in intracellular membranes (Edwards and Kahl 2010). CLIC proteins are very distinct from other ion channels in terms of structural plasticity. These proteins may exist as soluble globular proteins and integral membrane proteins with ion channel function (Berry and Hobert 2006). CLIC proteins are highly conserved with six distinct paralogues in mammals (CLIC1–CLIC6). They are multifunctional proteins that participate in a wide variety of signalling activities (reviewed by Gururaja Rao et al. 2018). CLIC4 expression levels have been found to increase in OSCC tissue samples compared to healthy oral mucosa (Table 5) (Xue et al. 2016). Cristofaro et al. (2014) performed a proteomic analysis using 2D gel electrophoresis coupled to mass spectrometry (2D-PAGE/MS) to detect proteins differentially expressed in OSCC compared to normal tissue. In addition to POSTN, annexin A2 or ezrin, CLIC1 also emerged among the differentially expressed proteins (Cristofaro et al. 2014). CLIC1 expression has been detected in over 75% NPC tissue specimens by IHC (Table 5) (Chang et al. 2009). Moreover, increased CLIC1 levels were also detected by ELISA in plasma from NPC patients compared to healthy controls (Table 5) (Chang et al. 2009). In addition, CLIC3 has been found overexpressed in mucoepidermoid carcinomas compared to the normal counterpart (Table 5), and CLIC3 expression was correlated with promoter hypomethylation (Wang et al. 2015). Nevertheless, the functional consequences of CLIC1 and CLIC3 dysregulation remain unexplored.

6.3.1

Pathobiological Role

The pathobiological role of CLIC4 was investigated in the HNSCC-derived cell line (HN4) by transfection with specific siRNAs. CLIC4 knockdown in HN4 cells increased the expression of Bax, active caspase 3 and CHOP, while suppressing Bcl-2 expression, ultimately leading to apoptosis induction (Table 5; Fig. 2) (Xue et al. 2016).

6.3.2

Clinical Relevance

Information is rather limited on the possible clinical significance of CLIC dysregulation in HNSCC. CLIC1 has been pointed as a tumour biomarker in NPC

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based on its frequent overexpression (>75%) detectable in both tissue samples and plasma (Table 5) (Chang et al. 2009). However, CLIC1 expression has not been reported in other HNSCC subtypes, which merits further investigation. It has also been suggested that CLIC4 could be a potential therapeutic target (Table 5) (Xue et al. 2016), although evidence is so far limited to the functional consequences of CLIC4 expression abrogation on apoptosis in the HN4 cell line (Xue et al. 2016).

6.4

Other Chloride Channels (ATP-Gated CFTR or Volume-Regulated Anion Channel Subunits)

Volume-sensitive outwardly rectifying chloride (VSOR Cl) currents have been detected by patch clamp in the NPC cell line CNE-2Z (Su et al. 2019), which can be activated by gambogenic acid (GNA) and blocked by various chloride channel blockers such as DIDS and DCPIB. Moreover, VSOR Cl activation by GNA led to endoplasmic reticulum (ER) stress, induction of apoptosis and diminished proliferation of CNE-2Z cells (Fig. 2). It has also been demonstrated that chloride channels are major targets of anti-tumour drugs. Thus, emodin increased chloride channel expression and activity in CNE-2Z cells, thereby decreasing cell growth by inducing apoptosis and cell cycle arrest (Ma et al. 2017). In addition, the chloride channel blocker NPPB prevented emodin-induced apoptosis in CNE-2Z cells (Ma et al. 2017). On the other hand, it has been reported that ethanol activates chloride currents to promote cell migration in CNE-2Z cells, but not in normal nasopharyngeal epithelial cells (NP69-SV40T) (Wei et al. 2015). Chloride currents and cell migration of CNE-2Z cells were inhibited by NPPB and tamoxifen (Wei et al. 2015; Mao et al. 2005). These observations suggest that long-term alcohol exposure/consumption could favour tumour spreading. It has been shown that cisplatin, a major chemotherapeutic agent in HNSCC treatment, preferentially binds to mitochondrial membrane proteins, in particular voltage-dependent anion channels (Yang et al. 2006). Moreover, Yang et al. (2015) demonstrated that cisplatin induced chloride currents in CNE-2Z cells by activating volume-sensitive like chloride channels via the P2Y purinoceptor pathway. P2Y receptor expression was detected in CNE-2Z cells, and cisplatin-induced chloride currents were blocked by the purinergic antagonist suramin and the selective P2Y inhibitor RB2 (Yang et al. 2015). Ursolic acid has also been found to activate chloride currents thus decreasing cell volume in CNE-2Z cells (Li et al. 2012). This effect was targeted by the chloride channel blockers NPPB and tamoxifen. In addition, it has been demonstrated that the volume-regulated anion channel VRAC (also known as VSOR or VSOAC) plays a crucial role in tumour responsiveness to platinum-based drugs (Planells-Cases et al. 2015). It has been recently uncovered that VRACs are composed of heteromers of leucine-rich repeat-containing 8 (LRRC8) proteins, which comprise five members (LRRC8A–LRRC8E) (Jentsch et al. 2016). LRRC8A was identified as an indispensable subunit to form functional

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VRAC, together with at least one of the other four exchangeable partners (LRRC8B/ C/D/E). LRRC8 subunit composition modulates substrate selectivity, and these proteins probably constitute the channel pore. Notably, the study by PlanellsCases et al. 2015 further revealed that VRAC, through LRRC8A and LRRC8D subunits, plays a dual role tumour drug response by mediating cisplatin transport and uptake and independently facilitating drug-induced apoptosis.

7 Dysregulation of Ligand-Gated Ion Channels 7.1

Nicotinic Acetylcholine Receptors

Nicotinic acetylcholine receptors (nAChR) are cholinergic receptors that naturally bind the neurotransmitter acetylcholine in neurons. They are the receptors to which nicotine binds, forming either homomeric or heteromeric pentamers. More than ten different subunits have been identified, which can be classified into the alpha (CHRNA) or beta (CHRNB) groups. Despite nicotinic receptor subunits usually being located in neurons and muscle cells, they can be detected in epithelia and have also been found altered in some cancers. Scherl et al. (2016) studied the expression of the subunits α1, α3, α5 and α7 by real-time RT-PCR, immunoblotting and IHC in different HNSCC tissue samples from different subsites, i.e. the oropharynx, hypopharynx and larynx. Major expression changes were observed in the subset of laryngeal carcinomas by comparing tumour tissues and normal counterparts. Thus, α1 subunit was found upregulated, while α3 and α7 were downregulated, as confirmed at both mRNA and protein level (Table 6). The α1 subunit was also overexpressed in hypopharyngeal carcinomas; and it appeared to be downregulated in oropharyngeal carcinoma at protein level, but not at mRNA level. In addition, the α5 mRNA was found to be upregulated in all three HNSCC subsites.

7.1.1

Pathobiological Role

Since nicotine is an important and potentially carcinogenic tobacco component, its effect on the upper aerodigestive tract has been of particular interest in the cancer research field. Various groups have demonstrated that nicotine promotes cell proliferation by activating EGFR signalling in different HNSCC-derived cell lines from the oral cavity and hypopharynx (Shimizu et al. 2019; Chernyavsky et al. 2015; Nieh et al. 2015). This proliferative effect has been linked to the α7 subunit, since it was reverted by various α7-selective inhibitors (Table 6; Fig. 2). Similarly, nicotine also increased cell migration and invasion, and these effects were inhibited by compounds targeting α7 (Table 6; Fig. 2) (Shimizu et al. 2019; Nieh et al. 2015). In line with this, Nieh et al. (2015) reported increased expression of the EMT markers fibronectin, MMP-9, Twist and Snail, as well as decreased

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Table 6 Dysregulation of ligand-gated ion channels in head and neck cancers

Channel nAChRα1 subunit

nAChRα3 subunit nAChRα5 subunit nAChRα7 subunit

HGNC symbol CHRNA1

CHRNA3 CHRNA5 CHRNA7

ZAC

ZACN

P2X7

P2RX7

IP3R2

ITPR2

Dysregulation status " LSCC tissue samples " HPSCC tissue samples # LSCC tissue samples " HNSCC tissue samples # LSCC tissue samples

" HPSCC tissue samples " HNSCC tissue samples

# LSCC tissue samples

Biological processes affected NA

Clinical relevance NA

References Scherl et al. (2016)

NA

NA

Scherl et al. (2016)

NA

NA

Scherl et al. (2016)

Proliferation, migration, invasion, EMT

Therapeutic target

NA

Early diagnostic marker Therapeutic target, prognosis marker, xerostomia treatment NA

Scherl et al. (2016), Shimizu et al. (2019), Chernyavsky et al. (2015), Nieh et al. (2015) Li et al. (2018)

Invasion, apoptosis, xerostomia

NA

Bae et al. (2017), Gilman et al. (2019)

Janiszewska et al. (2015)

Evidence of ligand-gated channel expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. Xerostomia refers to the damage of salivary gland secretion caused by radiotherapy treatment. nAChR nicotinic acetylcholine receptor, ZAC zinc-activated channel, P2RX P2X purinergic receptor, IP3R inositol triphosphate receptor, LSCC laryngeal squamous cell carcinoma, HPSCC hypopharyngeal squamous cell carcinoma, HNSCC head and neck squamous cell carcinoma, EMT epithelial-mesenchymal transition, NA not available information

expression levels of E-cadherin in cells exposed to nicotine. These effects were also related to α7 and reverted by treatment with a α7 inhibitor. Using a mouse metastasis model, Shimizu et al. (2019) found that nicotine enhanced metastasis formation, and this action was abrogated by a nAChR inhibitor. Evidence indicates that nicotine also attenuates apoptosis (Table 6; Fig. 2). Decreased annexin V was measured by flow cytometry, and downregulation of the apoptotic proteins caspase-3, cleaved PARP and Bax was also observed in cells exposed to nicotine (Nieh et al. 2015). In addition, Chernyavsky et al. (2015) also reported decreased cytochrome C release, which is another well-known marker of apoptosis.

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According to the study by Nieh et al. (2015), cells could only form spheroids when exposed to nicotine (Table 6; Fig. 2). This was accompanied by increased protein expression of CSC markers ALDH1, OCT4 and NANOG. Noteworthy, nicotine was found to increase chemoresistance to cetuximab and cisplatin (Shimizu et al. 2019; Nieh et al. 2015), and it also increased radioresistance (Shimizu et al. 2019; Nieh et al. 2015).

7.1.2

Clinical Relevance

All the authors who have investigated the carcinogenic effects of nicotine suggest the use of nAChR inhibitors as a novel therapeutic strategy (Table 6) (Shimizu et al. 2019; Nieh et al. 2015; Chernyavsky et al. 2015). Moreover, nAChR inhibitors could also be effective to counteract nicotine-induced stemness and radio/ chemoresistance, which merits further investigation.

7.2

Zinc-Activated Channels

The zinc-activated channel ZAC, encoded by ZACN gene, is a cation channel activated by zinc. Li et al. (2018) performed an RNA-seq screening aimed at identifying key genes and pathways in the pathogenesis of hypopharyngeal squamous cell carcinoma (HPSCC). ZACN was found to be the most upregulated gene in HPSCC patients compared to controls (Table 6). This preliminary work suggests ZAC could be considered as a biomarker candidate for early diagnosis. Nevertheless, the clinical and biological significance of ZAC channel in HNSCC should be deeper investigated.

7.3

P2X Purinergic Receptors

These cation channels open when stimulated by high concentrations of extracellular ATP, which are usually indication of tissue disease, inflammation or injury. Studies about these proteins in HNSCC have to date been focused on the P2X7 receptor. Expression of P2X7 was found to be upregulated in 6 HNSCC patients when compared to controls (Table 6) (Bae et al. 2017). Functionally, this receptor has been implicated in cell viability. P2X7 inhibition impaired the growth of a cell line obtained from submandibular gland carcinoma by increasing apoptosis (Table 6; Fig. 2). Additionally, blocking P2X7 caused a reduction of cell invasion (Table 6; Fig. 2). Based on these data showing the oncogenic properties of P2X7, it has been proposed as a potential prognosis biomarker, as well as a novel therapeutic target (Table 6). In addition, another study by Gilman et al. (2019) suggested a possible clinical application of P2X7 inhibitors for the treatment of radiotherapy-related

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xerostomia (Table 6), since injections of a P2X7 antagonist A438079 demonstrated efficacy to prevent radiation-induced salivary gland damage in mice.

7.4

Inositol Triphosphate Receptor

Inositol triphosphate (IP3) receptors, coded by ITPR genes, are cation channels that open when bound to IP3. Little is known about their role in the context of HNSCC. A miRNA screening performed by Janiszewska et al. (2015) in LSCC samples revealed ITPR2 (encoding IP3R2) as a target gene for miR-1290, which was overexpressed in LSCC. Further validation by real-time RT-PCR showed that IP3R2 was significantly downregulated in the tumour samples, compared to normal tissue (Table 6; Fig. 2). However, the significance of IP3R2 expression dysregulation in HNSCC remains to be elucidated.

8 Dysregulation of Porins 8.1

Aquaporins

Aquaporins (AQPs) are a group of transmembrane proteins of approximately 270 amino acids. Currently, 13 members have been identified in humans (AQP0 to AQP12) (Delporte and Steinfeld 2006), which can be classified into two groups, depending on their ability to transport only water (AQP1, AQP2, AQP4, AQP5 and AQP8) or both water and glycerol (AQP3, AQP7, AQP9 and AQP10) (Reddy and Dony 2017). In addition, AQP1 has been suggested to act as an O2 transport channel (Echevarría et al. 2007). AQPs have been widely studied in diverse human diseases. Evidence indicates that dysregulation of AQP1, AQP3 and AQP5 could play a role in HNSCC pathogenesis (Table 7). Ishimoto et al. (2012) analysed the expression of AQP3 and AQP5 by IHC in OSCC and adenoid cystic carcinomas (ACC). Expression of AQP3 and AQP5 was found to differentially increase in OSCC, compared to the corresponding normal counterparts (Table 7). Kusayama et al. (2011) also detected high AQP3 levels in OSCC samples and lymph node metastasis, but not in normal tissues. In marked contrast, AQP3 and AQP5 expression significantly decreased in ACC samples compared to normal tissue (Ishimoto et al. 2012). AQP1 expression was assessed by IHC in 107 oro/hypopharyngeal squamous cell carcinomas (OPSCC). AQP1 expression was exclusively detected in a subset of patients with an aggressive form of basaloid-like squamous cell carcinomas and suggested as a potential biomarker (Table 7) (Lehnerdt et al. 2015). AQP5 expression was also found to increase in OPSCC and significantly correlated with absence of p16 and Bcl-2 expression in this tumour subtype (Lehnerdt et al. 2015).

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Table 7 Dysregulation of porins in head and neck cancers

Channel AQP1

HGNC symbol AQP1

Dysregulation status "ACC tissue samples "NPC tissue samples " Basaloidlike SCC

AQP3

AQP3

AQP5

AQP5

"OSCC tissue samples "OSCC cell lines # ACC tissue samples "OPSCC tissue samples "OSCC cell lines # ACC tissue samples

Biological processes affected Anchoragedependent and anchorageindependent cell growth, O2 transporter

Clinical relevance Risk stratification, poor prognostic marker

Proliferation, cell adhesion

Therapeutic target

Proliferation, cell adhesion

Risk stratification, poor prognostic marker

References Lehnerdt et al. (2015), Li and Zhang (2010), Tan et al. (2014), Shao et al. (2011), Echevarría et al. (2007) Ishimoto et al. (2012), Kusayama et al. (2011)

Ishimoto et al. (2012), Lehnerdt et al. (2015)

Evidence of porin expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. ACC adenoid cystic carcinoma, NPC nasopharyngeal carcinoma, OPSCC oro/hypopharyngeal squamous cell carcinoma, SCC squamous cell carcinoma

AQP1 expression was also examined in 30 NPC samples by both IHC and realtime RT-PCR. Results consistently showed AQP1 overexpression in tumours compared to normal tissues; in particular higher AQP1 levels were observed in migrated tumours (Table 7) (Li and Zhang 2010). AQP1 promoter methylation and expression was explored in 77 primary ACC samples and 30 normal salivary gland tissues from non-oncologic patients. AQP1 hypomethylation and increased expression were frequently observed in this tumour type (Table 7). Moreover, AQP1 hypermethylation was found to significantly associate with increased overall survival (Tan et al. 2014).

8.1.1

Pathobiological Role

The role of altered expression of AQP1, AQP3 and AQP5 has been investigated and related to cell proliferation and survival. It has been proved that AQP1 promotes both anchorage-dependent and independent cell growth (Table 7; Fig. 2). Thus, AQP1 overexpression induced cell proliferation and soft agar colony formation in

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the ACC-derived cell line SACC83 with low endogenous levels of AQP1 (Shao et al. 2011). In addition, Tan et al. (2014) reported that AQP1 overexpression in SACC83 cells had no effect on migration and invasion assays. Besides, AQP1 function has also been related to O2 transport (Echevarría et al. 2007). Accordingly, AQP1 could facilitate O2 loss in the cytoplasm, causing stabilisation of O2-dependent hypoxia-inducible transcription factor (HIF) and subsequent upregulation of HIF-mediated pro-angiogenic factors. Ishimoto et al. (2012) provided evidence for the role of AQP3 and AQP5 as regulators of cell growth and survival in OSCC (Table 7; Fig. 2). In vitro blockade using the pan-AQP inhibitor CuSO4 or specific siRNAs for AQP3 and AQP5 significantly decreased the proliferation of various OSCC cell lines (SAS, SCCKN and Ca9-22), and it also affected cytoskeletal organisation, as observed by means of F-actin staining. Mechanistically, it was demonstrated that AQP5 knockdown inhibited the expression of integrins α5 and β1, focal adhesion kinase (FAK) and ERK in SAS cells. Collectively, these findings suggest that AQP5 may enhance tumour growth through the integrin-initiated FAK/MAPK signalling pathway. Similarly, Kusayama et al. (2011) revealed AQP3 function to be critical for oral and oesophageal tumour growth. Treatment of oral cancer SAS cells with the pan-AQP inhibitor CuSO4 or AQP3 knockdown by specific siRNAs effectively blocked cell growth. AQP3-siRNA inhibited the expression of integrinsα5 and β1, and cell adhesion was in turn dramatically impaired in SAS cells (Table 7; Fig. 2), but not in the adenocarcinoma-derived cell lines (HT-29 and Caco2) and normal cells (fibroblasts). Furthermore, AQP3-siRNA was also found to target FAK/MAPK signalling pathway specifically in SCC – but not adenocarcinoma-derived cells; hence the phosphorylation levels of FAK, MAPK and MEK were markedly reduced.

8.1.2

Clinical Relevance

Based on current data, AQP1 and AQP5 have been proposed as biomarkers for risk stratification of specific HNSCC subtypes (Table 7). AQP1 was thus found to identify a subset of patients with aggressive basaloid-like squamous cell carcinomas and AQP5 a subset of OPSCC patients with Bcl-2-negative and p16-negative tumours and poor clinical outcome (Lehnerdt et al. 2015). AQP1 hypermethylation has been pointed as a predictor of good prognosis in ACC (Tan et al. 2014). Targeting AQP3 and AQP5 expression or function has been found to effectively and specifically suppress tumour cell growth and integrin-mediated cell adhesion in SCC, while no effect was observed in adenocarcinomas and normal cells. Moreover, AQP3 and AQP5 function has been linked to FAK activation, which is a key regulator of cell growth, migration, invasion and metastatic spreading and correlated with aggressive phenotypes in HNSCC and other cancers (McLean et al. 2005; Canel et al. 2006, 2008). Therefore, AQP3 and AQP5 emerge as promising therapeutic targets for SCC (Table 7). High levels of AQP3 are detected in both primary OSCC and lymph node metastasis (Kusayama et al. 2011). The combination of AQP3 inhibition with some chemotherapeutic drugs such as cisplatin or

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5-fluorouracil has demonstrated a potential application (Kusayama et al. 2011). Combined treatment of low doses of AQP3-siRNA and cisplatin potently inhibited tumour cell growth compared to single treatment, suggesting that AQP3 inhibition may sensitise to chemotherapeutic drugs (Kusayama et al. 2011).

8.2

Voltage-Dependent Anion-Selective Channels

The voltage-dependent anion-selective channels (VDACs) or mitochondrial porins are a class of mitochondrial transmembrane proteins which allow the exchange of metabolites and ions across the outer membrane. To date, the role of VDAC channels in HNSCC has been scarcely investigated. Cisplatin is a well-known alkylating agent used in the treatment of a wide variety of solid tumours, including HNSCC. Even though the mechanism of action has been related almost exclusively to its nuclear and mitochondrial DNA-binding capacity, cisplatin may also bind to cysteine, methionine and histidine residues in proteins. It has been shown that cisplatin binding to VDAC may alter its structure and function, inducing cytochrome C release and apoptosis in HNSCC (Yang et al. 2006). Fenofibrate has demonstrated therapeutic efficacy in mouse models of oral tumorigenesis by reducing tumour size and incidence and decreasing VDAC protein expression and mTOR activity (Jan et al. 2016). It has also been shown that fenofibrate alters the expression levels of VDAC, hexokinase II (HK II), pyruvate kinase and pyruvate dehydrogenase, which was associated with the Warburg effect (Fig. 2). Furthermore, fenofibrate reprogrammed metabolic pathways by disrupting the binding of HK II to VDAC. In addition, it has recently been demonstrated that E6 oncoproteins from the high-risk HPV16 and HPV18 act as inducers of mitochondrial metabolism in HNSCC HPV-positive cells, also increasing VDAC protein levels (Cruz-Gregorio et al. 2019). Nonetheless, the relevance of VDAC expression changes in HNSCC remains to be elucidated.

9 Dysregulation of Gap Junction Proteins (Connexins) Gap junctions are a plethora of intercellular transmembrane channels that allow the exchange of ions and low-weight molecules between cells. This type of channels communicates the cytoplasm from adjacent cells through connexins (Cx), the structural components of these channels. Twenty-one connexins have been described in humans, being Cx43 (or GJA1) the prevalent and most studied in large cohorts of HNSCC patients (Table 8) (Puzzo et al. 2016; Dános et al. 2016). Cx26 and Cx30 have also been investigated in HNSCC pathogenesis. The expression of Cx26 and Cx30 was analysed by IHC in 13 patients with primary HNSCC (Ozawa et al. 2007). Cx30 expression was markedly reduced in tumours compared to normal mucosa (Table 8), whereas Cx26 levels remained unchanged. Ectopic Cx30 expression led to

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Table 8 Dysregulation of gap junction proteins in head and neck cancers Channel Cx26

HGNC symbol GJB2

Cx30

GJB6

Cx43

GJA1

Cx45

GJC1

Dysregulation status "OSCC tissue samples " Lymph node metastasis # HNSCC tissue samples "LSCC tissue samples " OSCC tissue samples "OSCC lymph node metastasis

Biological processes affected NA

Clinical relevance NA

Proliferation

NA

Apoptosis, chemosensitisation

Tumour suppressor gene, prognostic marker NA

NA

References Brockmeyer et al. (2014)

Ozawa et al. (2007), (2009) Puzzo et al. (2016), Dános et al. (2016), Brockmeyer et al. (2014), Gurbi et al. (2019) Brockmeyer et al. (2014)

Evidence of gap junction protein expression dysregulation (either " upregulation or # downregulation) in head and neck cancer samples/cells are summarised, together with the reported biological impact and clinical relevance proposed Ion channels are listed according to the IUPHAR nomenclature. HNSCC head and neck squamous cell carcinoma, LSCC laryngeal squamous cell carcinoma, OSCC oral squamous cell carcinoma, NA not available information

increased proliferation in HSC-4 cells (Table 8; Fig. 2) (Ozawa et al. 2009). These data suggest a possible role for Cx30 in HNSCC tumorigenesis. Cx26 has also been studied in OSCC samples, where it was found overexpressed when compared to normal oral mucosa. Cx26 expression was even higher in lymph node metastasis, where Cx45 expression was also detected. Interestingly, Cx45 expression was not observed either in normal tissue or in primary tumours (Table 8) (Brockmeyer et al. 2014). Various studies have evaluated the prognostic significance of Cx43 in HNSCC. Puzzo et al. (2016) assessed the expression of Cx43 in 87 patients with LSCC and found a positive correlation between Cx43 expression and overall survival. Patients with Cx43-positive expression showed an increased survival compared with those with negative expression (Table 8) (59.6% vs 37.1%). Similarly, Dános et al. (2016) reported a significant positive correlation between Cx43 expression and diseasespecific survival by analysing a large cohort of 90 pharyngeal, laryngeal and oral cancers. Accordingly, low Cx43 levels were associated with poorer outcomes, which led to the hypothesis that Cx43 may act as a tumour suppressor gene (Puzzo et al. 2016; Dános et al. 2016). By contrast, Brockmeyer et al. (2014) found that Cx43 was an independent marker of poor prognosis by analysing a series of 35 OSCC. Specifically, membrane Cx43 expression was the only significant independent predictor of short overall survival. It has also been recently demonstrated that ectopic Cx43 expression reduced the levels of the anti-apoptotic protein Bcl-2 in FaDu cells and increased sensitivity to paclitaxel (Table 8) (Gurbi et al. 2019). Concordantly, an inverse correlation

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between Cx43 and Bcl-2 protein expression has also been observed in HNSCC tissue samples (Gurbi et al. 2019). Future studies are therefore needed to fully depict the contribution of Cx43 expression to HNSCC progression and/or chemosensitisation.

10

Closing Remarks and Future Perspectives

In light of the herein reviewed data, it becomes clear that dysregulation of ion channel expression and function is frequent in all the stages of head and neck malignancies, thereby contributing to various key cellular processes for tumour biology and cancer hallmarks. Overall, ion channels are predominantly upregulated in head and neck cancers, although Cavα2δ-3 and Cx43 have been found downregulated and postulated as tumour suppressors. It is therefore reasonable to consider that ion channels could be exploited as promising therapeutic targets primarily at the plasma membrane, a very convenient location for drug targeting, as well as biomarkers for cancer diagnosis and prognosis. This possibility should be of great interest in head and neck cancers that are particularly devoid of biomarkers and molecular-targeted therapies approved for clinical use. Nevertheless, despite current findings looking very promising, further substantial work is still needed and encouraged to facilitate rapid translation into clinical application. In this respect, it seems fundamental to fully establish the clinical and biological relevance of ion channel dysregulation. Studies aiming at this should cover considerable validation on various disease-relevant preclinical models as well as analysis of large collections of patient samples. Taking this into consideration and based on current reported data, Kv3.4, Kv10.1 and Kv11.1 channels are highlighted as clinically and biologically relevant in both early stages of head and neck tumourigenesis and late stages of HNSCC progression. In fact, the role of these Kv channels has been comprehensively investigated using large cohorts of HNSCC and OSCC patients, laryngeal and oral precancerous lesions and panels of HNSCC-derived cell lines. Noteworthy, Kv10.1 and Kv11.1 expression was detected in an extraordinarily high percentage of tumours (>80%) but not in the normal counterparts, postulating these channels as potential tumour markers and poor prognostic markers. In addition, Kv3.4 and Kv11.1 emerge as powerful biomarkers for cancer risk assessment in patients with precancerous lesions, which could be extremely useful for early detection of cancer and/or its prevention. Importantly, Kv3.4 and Kv11.1 expression demonstrated superior predictability beyond histopathological grading, current gold standard, reinforcing the benefits and feasibility of incorporating the immunohistochemical detection of these proteins, which is relatively simple and easy to interpret, into the clinical routine jointly with histopathological diagnosis. Regarding the pathobiological role of Kv3.4, Kv10.1 and Kv11.1 in HNSCC, it has been proved that these Kv channels play an active role in cell proliferation and invasion, although independently of their ion-conducting function. Together these

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findings suggest that abnormal Kv channel expression could confer a proliferative advantage to the cells carrying this alteration and the acquisition of invasive potential. This would favour the progression of precancerous lesions into invasive carcinoma in early stages of HNSCC tumourigenesis, while contributing to the acquisition of truly invasive and metastatic phenotypes in advanced disease stages. Therefore, Kv expression may favour tumour progression and metastatic spread through an enhancement of cell proliferation and invasiveness, postulating these Kv channel subunits as useful anti-proliferative and anti-metastatic targets for cancer therapy. According to the available data, pharmacological blockade of Kv channel activity does not seem to be an adequate approach to effectively target Kv function on HNSCC growth and progression. Plasmid vector-mediated Kv11.1 RNA interference has been successfully used in mice (Zhao et al. 2008) and might have potential therapeutic utility in human cancers where the conducting properties of Kv11.1 are not a major determinant. There is also growing interest in developing novel strategies for antibody-based therapies, such as the generation of bifunctional antibodies through the fusion to an effector molecule. Following this strategy, the tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) attached to an antiKv10.1 antibody was able to selectively induce apoptosis in prostate tumour cells, while normal cells were not affected (Hartung et al. 2011). It has been reported that Kv11.1 channels form complexes with β1 integrin subunit specifically in cancer cells but not in cardiomyocytes (Pillozzi et al. 2007; Becchetti et al. 2017). Kv11.1/β1 integrin interaction is required for the activation of FAK, and it mediates tumour progression and metastasis (Becchetti et al. 2017). Likewise, it has been demonstrated that the actin-interacting protein cortactin directly interacts with Kv10.1 and controls Kv10.1 channel expression and function (Herrmann et al. 2012). Notably, cortactin and FAK have been recognised as key regulators of tumour progression and metastatic dissemination and poor prognostic markers in HNSCC (Rodrigo et al. 2009; Canel et al. 2006, 2013). Furthermore, cortactin and FAK expression plays an important role in early stages of tumourigenesis, and both have emerged as powerful predictors of cancer risk in patients with laryngeal and oral precancerous lesions (de Vicente et al. 2012; Villaronga et al. 2018). Hence, it is tempting to speculate that cortactin and FAK could be critical players and regulators of Kv10.1 and Kv11.1 oncogenic functions; however, this possibility requires confirmation in HNSCC. It has also been pointed that AQP3 and AQP5 may enhance HNSCC growth through integrin-initiated FAK signalling specifically in SCC but not adenocarcinoma-derived cells or normal cells (Ishimoto et al. 2012; Kusayama et al. 2011), thus emerging as a central regulatory node in this type of tumours. Intense research has also been devoted to the calcium-activated chloride channel ANO1. Its potential as biomarker for diagnosis of specific cancer subtypes (i.e. ACC) or poor prognosis in HPV-negative HNSCC seems unquestionable. However, ANO1 targeting has led to pleiotropic functional effects and varying outputs depending on cell/tissue specificity, which may limit a possible therapeutic application until the subsets of patients who could safely and effectively be benefited

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are adequately stratified. Even though TRP channels are frequently altered in HNSCC, the clinical and biological impact of these changes has been scarcely investigated. It is also worth to mention that the chloride channel CLIC1 has been proposed as an effective tissue and plasma biomarker for NPC, which should be further explored in other HNSCC subtypes. Moreover, blockade of TRPM2 activation as well as P2X7 inhibitors have proved efficacy for xerostomia in mice, which represent plausible treatments to prevent or restore radiation-induced salivary gland damage, a common side effect of RT in cancer patients. Interestingly, it has also been demonstrated that ion channels may contribute to HNSCC progression by modulating the tumour microenvironment. Thus, defects in Kv1.3 and KCa3.1 channels have been related to immunosuppression, and strategies aimed at increasing channel activity have consequently been suggested to improve immunotherapy response in HNSCC patients by increasing TIL recruitment (Chimote et al. 2017), which undoubtedly merits further investigation. KCa3.1 could also play a role in the tumour cells themselves, since KCa3.1 channel is expressed and functional in HNSCC cells although not yet confirmed in tumour samples. Acknowledgements This work was supported by grants from the Plan Nacional de I+D+I 20132016 from ISCIII (PI16/00280 and PI19/00560) and CIBERONC (CB16/12/00390), the Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Ayudas a Grupos PCTI Principado de Asturias (IDI2018/155) and the FEDER Funding Program from the European Union. NRI is recipient of a FPU predoctoral fellowship (FPU17/01985) from the Spanish Ministry of Education, RGD is recipient of a Severo Ochoa predoctoral fellowship (BP19-063) from the Principado de Asturias, and STM is recipient of a Sara Borrell postdoctoral fellowship from the Instituto de Salud Carlos III (CD16/00103). The authors declare no conflict of interests. All authors read and approved the final version of the manuscript.

Glossary 2-APB 2-Aminoethoxydiphenyl borate 2D-PAGE/MS 2D Gel electrophoresis coupled to mass spectrometry 4-AP 4-Aminopyridine 5-AZA 5-Aza-20 -deoxycytidine ACC Adenoid cystic carcinoma AQPs Aquaporins CaCC Calcium-activated chloride channel ChIP Chromatin immunoprecipitation ClC Voltage-gated chloride channel CLIC Chloride intracellular channel CRAC Calcium release-activated channel

Ion Channel Dysregulation in Head and Neck Cancers: Perspectives for Clinical. . .

CsA Cyclosporine A CSC Cancer stem cell Cx Connexin DHA Dihydroartemisinin EAG Ether-à-go-go EBV Epstein-Barr virus EMT Epithelial to mesenchymal transition ER Endoplasmic reticulum FAK Focal adhesion kinase FDA Food and Drug Administration GABA γ-Aminobutyric acid GIST Gastrointestinal stromal tumours GNA Gambogenic acid GST Glutathione S-transferase HDAC Histone deacetylase HGNC HUGO Gene Nomenclature Committee HIF Hypoxia-inducible factor HKII Hexokinase II HNSCC Head and neck squamous cell carcinoma HPSCC Hypopharyngeal squamous cell carcinoma HPV Human papilloma virus IP3 Inositol triphosphate iPSC-Cm Induced pluripotent stem cell-derived cardiomyocytes LOH Loss of heterozygosity LSCC Laryngeal squamous cell carcinoma nAChR Nicotinic acetylcholine receptor NPC Nasopharyngeal carcinoma NPPB 5-Nitro-2-(3-phenylpropylamino) benzoic acid OPSCC Oro/hypopharyngeal squamous cell carcinoma OSCC Oral squamous cell carcinoma ROS Reactive oxygen species RT Radiotherapy RT-PCR Reverse transcription-polymerase chain reaction SAHA Suberoylanilide hydroxamic acid TCGA The Cancer Genome Atlas TCR T-cell receptors TIL Tumour-infiltrating lymphocytes TM Transmembrane segment TRP Transient receptor potential VDAC Voltage-dependent anion-selective channel VDCC Voltage-dependent calcium channels VSOR Cl2 Volume-sensitive outwardly rectifying chloride WT Wild type ZAC Zinc-activated channel

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