EFFECTS OF ESTROGEN ON VOLTAGE-GATED EXPRESSION AND IN HUMAN BREAST CANCER CELL LINES

ILEY OZERLAT

Thesis submitted to the University of London for the Degree of Doctor of Philosophy

January, 2009

Imperial College London Division of Cell and Molecular ABSTRACT

This PhD Thesis aimed to elucidate a possible functional interaction between estrogen receptor signaling and voltage-gated sodium channel (VGSC) expression/activity in human breast cancer (BCa) cell lines. In particular, a novel estrogen receptor mechanism (G- coupled receptor 30, GPR30) was evaluated in metastatic human BCa cells, and short-term (non-genomic) and long-term (genomic) mechanisms regulating the expression of 'neonatal' Nav1.5 (nNav1.5), the predominant isoform expressed in these cells, were investigated. The Introduction chapter gives general information about cancer, estrogen and its role in BCa, VGSCs and regulation of ion channels by steroid hormones. This is followed by the Materials and Methods chapter where detailed information is given on the methodologies, cell lines and pharmacological treatments, used. The Thesis includes 3 main Results chapters, presenting data as follows: (1) Short-term effects of 170-estradiol on MDA-MB-231 cell adhesion: Evaluating the role of GPR30: Acute (up to 10 minutes) and short-term (10-20 minutes) treatments of strongly metastatic human BCa cell line (MDA-MB-231) with 1713-estradiol (E2) reduced cellular adhesion and co-application of (i) VGSC blocker tetrodotoxin (TTX) or (ii) a protein kinase A (PICA) inhibitor inhibited this effect. A range of suggested that GPR30 was involved in the non-genomic effects of E2 on adhesion. (2) Long-term effects of E2 on MDA-MB-231 cells: VGSC expression and adhesion: Long-term (24 h) treatments of MDA-MB-231 cells with E2 increased nNav1.5 mRNA expression without affecting total protein expression. A VGSC-dependent reduction in adhesion was shown by use of TTX, and over-expression of GPR30 increased the effect of E2 on adhesion. (3) Long-term effects of E2 on VGSC expression and adhesion of ERa-expressing MDA-MB-231 cells: ERa transfection in MDA-MB-231 cells (giving MDA-ERa cells) reduced nNav1.5 mRNA expression. Long-term (24 h) treatment of MDA-MB-231 cells with E2 reduced nNav1.5 mRNA and protein expression, and decreased VGSC- dependent adhesion. Long-term (> 24 h) treatment of MDA-ERa cells with estrogen antagonist ICI-182,780 did not affect cell adhesion, but increased lateral motility and transverse migration.

2 The overall conclusion is that functional expression of nNav1.5 in MDA-MB-23 1 cells is controlled by estrogen and this includes a non-genomic receptor mechanism. The Thesis concludes with a General Discussion chapter in which the basic findings are discussed more broadly and as regards potential clinical significance.

3 ACKNOWLEDGEMENTS

First of all, I would like to express my gratitude to Professor Mustafa Djamgoz who has given me the chance to pursue this degree of Doctor of Philosophy in his laboratory and who has been my supervisor for the past four years. He has been extremely helpful during the construction of my project as well as throughout the whole process. His wisdom and grand experience has guided me till the end. Especially for his patience to read the whole Thesis several times and to discuss it in depth, I am extremely thankful! I can not express how thankful I am to Dr. Scott Fraser for being such a wonderful person he is and for helping me with any problem I had during my time in the lab. He has been a great supervisor and a friend throughout these four years. I have benefited immensely from his technical and practical experiences in the laboratory, and I would like to thank him for his time and patience in helping me and answering my (sometimes endless) questions. I have enjoyed working with him a lot. Another wonderful person I can not thank enough is Dr. James Diss. I really appreciate his time and patience. He spent one summer to teach me everything about RNA extraction and real-time PCR and he spent much more time answering all my questions about primers and molecular techniques very patiently! He has been a great teacher and a great friend. I would like to also express my appreciation to Dr. Dongmin Shao for all his time and help with plasmid extractions, transfections and siRNA experiments, as well as with my Thesis. Also many thanks to Dr. Martin Spitaler and Dr. Peter Clark for their help with confocal microscopy. I have to say that I find myself extremely lucky for having many more great people to help me and befriend me throughout the four years I spent in the laboratory. For their support, guidance and friendship I would like to thank to Dr. Chris Palmer, Dr. Ebru Aydar, Dr. Emma Williams, Dr. Myrto Chioni and Dr. Pinar Uysal-Onganer. I would like to thank to my advisors Dr. Kenji Okuse and Prof. Simak Ali for their help and time during the first years of the project. Also many thanks to Prof. Eric Prossnitz for providing the GPR30 , to Prof. Ronald Weigel, Prof. Edward Filardo and Prof. Martin Allday, for providing the plasmids and to Prof. Craig Jordan for providing the MDA-ERa, VC5 and MDA-10A cell lines. I would like to also thank to my lovely friends here in UK: Adil Seytanoglu for his friendship and also helping me with EndNote, Fatma Mokhtar, Mine Guzel, Nahit

4 Rizaner, Rustem Onkal, Seden Cigizoglu Grippon and Sophie Pageon for their friendship and constant support. Also many thanks to my friends Dr. Banu Isbilen and Dr. Umut Fahrioglu, and my family in Cyprus: my aunt Hatice, uncle Sener, cousins Nazan and Hasan Yorgozlu, my grandmother Ismet Ozerlat, my mother- father- and sister-in-law Mebruke, Sonmez and Meryem Gunduz, my dear English teacher Gulten Fettahoglu and dear Hulya Bingollu for their love and support. There are many people without whom this PhD would not have been possible. My uncle, Prof. Ihsan Gursel has always been an inspiration for me since when I first chose to study biology and later when I decided to do a PhD. I can not express how thankful I am to him for his help during my initial communication with Prof. Djamgoz and his support throughout this journey. I would like to also thank to my aunt Dr. Mayda Gursel and my cousin Devrim Gursel for their love and support. I would like to thank to my uncle, Zeki Gursel, for his constant support and love. His wisdom and love of education has always inspired me and I have always admired and been proud of his level of knowledge and intelligence. This has given me a way of guidance and self-confidence since my childhood. My dear aunt Neslihan and my cousins Arda and Deha Gursel: Thank you very much for your love and support! I would like to express my love and thanks to my beloved grandmother Faize Gursel. Thank you for your deepest love and prayers that helped me throughout my PhD! My parents, Imren and Dervis Ozerlat, and my beloved sisters, Idil and Ilke: Without you I could not have done any of this! Mom and dad, thank you very much for your love, and financial and psychological support during this rollercoaster-like journey. Idil and Ilke, your love and support kept me going, thank you! One important person I saved for the last but definitely not the least is my beloved, other-half, Asim Gunduz. He has been the best throughout these four years. He was the one whom I shared my laughter with when I got a nice result, the shoulder I cried on when the experiments did not work, whom I discussed my project with and got constructive criticism, who cooked for me and looked after me when I was in the lab till late or at home working on my Thesis. He is the one without whom none of this would have been possible. For all of this and his love, I am very grateful! Finally, I would like to thank to Pro-Cancer Research Fund (PCRF) for supporting this project; and Kanser Arastirma Vakfi (KAV) and North Cyprus Ministry of Education for the financial aid they have provided.

5 Dedicated to my mom (imren), dad (Dervi), sisters (idil & ilke) and fiancée (Asian).

6 TABLE OF CONTENTS

ABSTRACT 2

ACKNOWLEDGEMENTS 4

TABLE OF CONTENTS 7

LIST OF FIGURES AND TABLES 12

ABBREVIATIONS 18

Chapter 1 GENERAL INTRODUCTION 26 1.1 Cancer basics 27 1.1.1 MicroRNAs 28 1.2 Metastasis 29 1.2.1 Epithelial-to-mesenchymal transition and invasion 31 1.2.2 Angiogenesis and tumour cell dissemination 34 1.2.3 Adhesion and extravasation 35 1.3 Breast cancer (BCa) 36 1.4 Estrogen 38 1.4.1 Genomic pathway 38 1.4.2 Non-genomic pathway 41 1.4.2.1 Classical ERs 41 1.4.2.2 Non-classical ERs and other receptors 42 1.4.3 Role of estrogen in BCa 45 1.5 Voltage-gated sodium channels (VGSCs) 47 1.5.1 Regulation of VGSCs 49 1.5.1.1 Transcriptional regulation 49 1.5.1.2 Post-transcriptional regulation 50 1.5.1.3 Post-translational regulation 51 1.6 Steroid hormone regulation of ion channels 53 1.6.1 Regulation of VGSCs 53 1.7 Ion channels and disease 54 1.7.1 Role of VGSCs in metastatic cell behaviours 55 1.8 Aims and scope of the Thesis 57

Chapter 2 MATERIALS AND METHODS 58 2.1 Cell culture 59 2.1.1 Cell lines 59 2.1.2 Culture conditions 59 2.1.3 Passaging and trypsinizing the cells 60 2.1.4 Freezing and thawing cells 60 2.2 Pharmacological agents and treatments 61 2.2.1 1713-estradiol 61

7 2.2.2 BSA-conjugated E2 61 2.2.3 G1 compound 63 2.2.4 ICI-182,780 63 2.2.5 Tetrodotoxin treatment 63 2.2.6 PKA inhibitor treatment 63 2.3 In vitro functional assays 64 2.3.1 Single-cell adhesion measurement apparatus (SCAMA) 64 2.3.2 Cell motility 64 2.3.3 Cell migration 66 2.3.4 MTT 66 2.3.5 Data analysis 68 2.4 Molecular biology 68 2.4.1 Total RNA extraction and purification 68 2.4.2 Determination of RNA quality 69 2.4.3 Quantification of total RNA 69 2.4.4 Synthesis of single-stranded complementary DNA (cDNA) 69 2.4.5 Polymerase chain reaction (PCR) 71 2.4.5.1 Analyzing the quality of PCR products 75 2.4.5.2 Data analysis 75 2.5. Protein-level studies 75 2.5.1 Whole-cell protein extraction 75 2.5.2 Protein concentration determination 76 2.5.3 Western blotting 76 2.5.4 Immunocytochemistry and digital imaging 79 2.5.4.1 Confocal microscopy 81 2.6 Plasmid transfection of GPR30 into MDA-MB-231 cells 82 2.7 RNA interference 85

Chapter 3 SHORT-TERM EFFECTS OF 17P-ESTRADIOL ON MDA-MB-231 CELL ADHESION: EVALUATING THE ROLE OF GPR30 88 3.1 Introduction 89 3.2 Aims and scope 90 3.3 Results 91 3.3.1 Adhesion 91 3.3.1.1 Control experiments 91 3.3.1.2 Acute treatments with estrogen 94 3.3.1.3 Short-term treatments with estrogen 94 3.3.2 Tests of VGSC involvement in the effect of estrogen on MDA-MB-231 cell adhesion. 97 3.3.2.1 Effect of blocking VGSC activity with tetrodotoxin 97 3.3.2.2 Short-term effects of estrogen and TTX co-treatments 97 3.3.3 Studies on the estrogen receptor expressed in MDA-MB-231 cells: Evaluation of GPR30 as a candidate mechanism 100 3.3.3.1 Expression of GPR30 and absence of ERa mRNA in MDA-MB-231 cells 100 3.3.3.2 Expression of GPR30 protein in MDA-MB-231 cells 100 3.3.3.3 Effect of BSA-conjugated E2 on MDA-MB-231 cell adhesion 104

8 3.3.3.4 Effect of GPR30-specific ligand, G1 compound, on MDA-MB-231 cell adhesion 104 3.3.3.5 Over-expression of GPR30 in MDA-MB-231 cells 107 3.3.3.5.1 Basal adhesion of GPR30-14 cells 107 3.3.3.5.2 Effect of short-term estrogen treatment on GPR30-14 cells 107 3.3.3.5.3 Subcellular distribution of GPR30 protein in GPR30-14 cells 111 3.3.3.6 Effect of GPR30 siRNA on MDA-MB-231 cells 111 3.3.3.6.1 mRNA studies 111 3.3.3.6.2 Protein studies 116 3.3.3.6.3 Single-cell adhesion studies 123 (i) Block of estrogen's effect on adhesion 123 (ii) Block of G1 compound's effect on adhesion 123 3.3.3.7 Effect of GPR30 siRNA and overexpression on VGSC mRNA expression in MDA-MB-231 cells 123 3.3.3.7.1 nNav1.5 123 3.3.3.7.2 VGSCI3 subunits 127 3.3.4 Possible role of PKA in short-term effect of estrogen on MDA-MB-231 cell adhesion 127 3.4 Discussion 133 3.4.1 Short-term effect of estrogen on MDA-MB-231 cell adhesion: Involvement of VGSCs 134 3.4.2 Identity of the receptor responsible for the non-genomic estrogen regulation in MDA-MB-231 cells: Pharmacological evidence 135 3.4.3 Effects of GPR30 over-expression on MDA-MB-231 cells 137 3.4.4 Silencing GPR30 in MDA-MB-231 cells 138 3.4.5 A model for GPR30 involvement in non-genomic estradiol signaling and metastatic cell behaviour 139 3.4.6 Concluding remarks 142

Chapter 4 LONG-TERM EFFECTS OF 1713-ESTRADIOL ON MDA-MB-231 CELLS: VOLTAGE-GATED SODIUM CHANNEL EXPRESSION AND ADHESION 143 4.1 Introduction 144 4.2 Aims and scope 145 4.3 Results 145 4.3.1 Long-term effects of estrogen on nNav1.5 mRNA expression in MDA-MB-231 cells 145 4.3.1.1 Control experiments 145 4.3.1.2 Dose dependence 147 4.3.1.3 Time dependence 147 4.3.2 Long-term effects of estrogen on nNav1.5 protein expression in MDA-MB-231 cells 151 4.3.3 Long-term effects of estrogen on MDA-MB-231 cell adhesion 151 4.3.3.1 Control experiments 151 4.3.3.2 E2 treatment 151 4.3.4 Possible involvement of VGSC activity in the long-term effect of E2 on adhesion 151 4.3.5 Possible involvement of GPR30 in the long-term effects of estrogen on MDA- MB-231 cells 155

9 4.3.5.1 Long-term effects of G1 treatment on nNav1.5 mRNA expression in MDA-MB-231 cells 155 4.3.5.2 Long-term effects of G1 treatment on cell adhesion 155 (i) MDA-MB-231 cells 155 (ii) GPR30-14 cells 155 4.3.6 Long-term effects of estrogen on VGSCI31 mRNA expression in MDA-MB- 231 cells 159 4.4 Discussion 167 4.4.1 Effects of long-term estrogen treatment on VGSC expression in MDA-MB-231 cells 167 4.4.1.1 mRNA studies 167 4.4.1.2 Protein-level studies 170 4.4.1.3 Functional aspects: Adhesion 170 4.4.1.3.1 Why does the short-term effect of G1 compound disappear in long- term treatment? 172 4.4.2 A model for long-term effects of estrogen in MDA-MB-231 cells 173

Chapter 5 LONG-TERM EFFECTS OF 17D-ESTRADIOL ON VOLTAGE-GATED SODIUM CHANNEL EXPRESSION AND ADHESION OF ERa-EXPRESSING MDA-MB- 231 CELLS 176 5.1 Introduction 177 5.2 Aims and scope 178 5.3 Results 178 5.3.1 Initial investigations 178 5.3.1.1 Morphological observations 178 5.3.1.2 Studies of basal mRNA expression 180 (i) ERa 180 (ii) GPR30 180 (iii) nNav1.5 180 (iv) Nav1.7 184 5.3.1.3 Basal nNav1.5 protein expression 184 5.3.1.4 Basal adhesion studies 184 5.3.1.5 Basal cell motility studies 184 5.3.2 Effect of CS-FBS medium in MDA-ERa cells 188 5.3.2.1 pS2 mRNA expression 188 5.3.2.2 nNav1.5 mRNA expression 188 5.3.3 Long-term effect of E2 on nNav1.5 mRNA expression in MDA-ERa cells 192 5.3.3.1 Dose-dependence 192 5.3.3.2 Time-dependence 192 5.3.4 Long-term effect of E2 on MDA-ERa cell adhesion 192 5.3.5 Long-term effect of E2 on nNav1.5 mRNA expression in VC5 cells 196 5.3.6 Long-term effects of anti-estrogen, ICI-182,780 on MDA-ERa cells 196 5.3.6.1 nNav1.5 mRNA expression 196 5.3.6.2 Adhesion 200 5.3.6.3 Cell motility and migration 200 5.4 Discussion 200 5.4.1 Lack of effects of ERa transfection on GPR30 mRNA expression 203 5.4.2 Effects of ERa transfection on nNav1.5 mRNA and protein expression 204

10 5.4.3 Effects of ERa transfection on cellular behaviours 206 5.4.4 Effects of CS-FBS medium 207 5.4.5 Effects of DMSO 208 5.4.6 Effects of long-term E2 and ICI treatments 209 5.4.6.1 nNav1.5 mRNA expression 209 5.4.6.2 Cellular behaviours 212

Chapter 6 GENERAL DISCUSSION 214 6.1 Problems in the therapy of breast cancer 216 6.2 Role of estrogen and its multiple receptors in BCa 217 6.3 Role of VGSCs in cancer 219 6.4 Estrogen regulation of VGSCs and its role in BCa 220 6.5 Clinical implications 223 6.6 Future perspectives 225

APPENDIX I 227

APPENDIX II 228

APPENDIX III 229

APPENDIX IV 230

REFERENCES 231

MANUSCRIPT PREPARATIONS 267

PRESENATIONS AND ABSTRACTS 267

11 LIST OF FIGURES AND TABLES

Chapter 1 General Introduction

Figure 1.1 Stages of the metastatic cascade 30

Figure 1.2 Adhesion mechanisms in epithelial cells 32

Figure 1.3 ERa and ER13 tissue expression and functional domains 39

Figure 1.4 ER, GPCR and EGFR cross-talk signalling mechanisms also 43 showing possible integration of genomic and non-genomic pathways activated by estrogen

Figure 1.5 Schematic diagram of the voltage-gated sodium channels 48

Figure 1.6 Electrophysiological recordings showing voltage-gated membrane 56 currents from human breast epithelial and human BCa cell lines

Chapter 2 Materials and Methods

Table 2.1 Pharmacological agents used in the experiments 62

Figure 2.1 Schematic representation of the Single Cell Adhesion Measuring 65 Apparatus (SCAMA)

Figure 2.2 A typical standard curve for MDA-ERa cell number in relation to 67 absorbance at 570 nm as determined by MTT assay

Figure 2.3 RNA quality determination by agarose 70

Table 2.2 PCR primer sequences and related details 72

Figure 2.4 Typical real-time PCR amplification and melting curves 73

Figure 2.5 An example of calibration curve for real-time PCR 74

Figure 2.6 Typical BSA standard curve for Bio-Rad protein assay 77

Table 2.3 Primary 78

Table 2.4 Secondary antibodies 78

Figure 2.7 Antibody standard curves used for densitometry analyses 80

12 Figure 2.8 Agarose gel electrophoresis picture of the two plasmids 84

Figure 2.9 Transfection efficiency of siRNA in MDA-MB-231 cells 87

Chapter 3 Short-term effects of 1713-estradiol on MDA-MB-231 cell adhesion: Evaluating the role of GPR30

Figure 3.1 Incubation in MPS increased MDA-MB-231 cell adhesion time- 92 dependently

Figure 3.2 Incubation in DMSO decreased MDA-MB-231 cell adhesion 93 dose-dependently

Figure 3.3 Acute effects of estrogen on MDA-MB-231 cell adhesion were 95 dose-dependent and reversible

Figure 3.4 Short-term effects of estrogen on MDA-MB-231 cell adhesion 96 were reversible

Figure 3.5 Short-term tetrodotoxin treatment increased MDA-MB-231 cell 98 adhesion and the effect was reversible

Figure 3.6 Short-term TTX treatment blocked the effect of E2 on MDA-MB- 99 231 cell adhesion

Figure 3.7 ERa mRNA was absent; GPR30 mRNA was present at low levels 101 in MDA-MB-231 cells

Figure 3.8 Western blotting showed GPR30 protein expression in MDA-MB- 102 231 cells

Figure 3.9 Immunocytochemistry confirmed GPR30 protein expression in 103 MDA-MB-231 cells

Figure 3.10 GPR30 protein localization in MDA-MB-231 and MCF-7 cells 105

Figure 3.11 Short-term effect of E2-BSA treatment on MDA-MB-231 cells 106 adhesion was dose-dependent

Figure 3.12 Real-time PCR confirmed over-expression of GPR30 mRNA in 108 transfected colonies

Figure 3.13 Over expression of GPR30 protein in transfected colonies 109

Figure 3.14 GPR30 over-expression did not affect basal adhesion 110

Figure 3.15 Short-term effect of estrogen treatment on GPR30-14 cell 112 adhesion was reversible

13 Figure 3.16 Over-expression increased intracellular immunoreactivity of 113 GPR30 protein

Figure 3.17 Over-expression increased intracellular GPR30 protein 114

Figure 3.18 Over-expression increased relative proportion of intracellular 115 GPR30 protein without changing plasma membrane expression

Figure 3.19 siControl (non-targeting siRNA) and mock (no siRNA) did not 117 affect GPR30 mRNA levels in MDA-MB-231 cells

Figure 3.20 GPR30 siRNA reduced GPR30 mRNA levels significantly in 118 MDA-MB-231 cells

Figure 3.21 GPR30 siRNA reduced GPR30 protein levels significantly in 119 MDA-MB-231 cells

Figure 3.22 siRNA decreased intracellular immunoreactivity of GPR30 120 protein

Figure 3.23 siRNA decreased intracellular GPR30 protein expression 121

Figure 3.24 siRNA decreased relative proportion of intracellular GPR30 122 protein without changing plasma membrane expression

Figure 3.25 siControl (non-targeting siRNA) and GPR30 siRNA did not affect 124 MDA-MB-231 cell adhesion

Figure 3.26 GPR30 siRNA inhibited the short-term effect of E2 treatment of 125 MDA-MB-231 cell adhesion

Figure 3.27 GPR30 siRNA inhibited the effect of G1 compound on MDA- 126 MB-231 cell adhesion

Figure 3.28 siControl (non-targeting siRNA) and GPR30 siRNA did not 128 change nNav1.5 mRNA levels in MDA-MB-231 cells

Figure 3.29 VGSCI3 subunit expression in MDA-MB-231 and MCF-7 cells 129

Figure 3.30 siControl (non-targeting siRNA) and GPR30 siRNA did not 130 change VGSC131 mRNA levels in MDA-MB-231 cells

Figure 3.31 Empty-vector and GPR30 transfection did not affect VGSCI31 131 mRNA expression in MDA-MB-231 cells

Figure 3.32 Long-term treatment with PKA-inhibitor increased MDA-MB-231 132 cell adhesion and blocked short term effect of estrogen

14 Figure 3.33 EBNA-nNav1.5 cells expressed low levels of GPR30 protein. 136

Figure 3.34 A hypothetical model of non-genomic estrogen regulation of 140 VGSCs and adhesion in MDA-MB-231 cells via GPR30

Chapter 4 Long-term effects of 1713-estradiol on MDA-MB-231 cells: Voltage-gated sodium channel expression and adhesion

Figure 4.1 Conditioning in CS-FBS medium for 3 days did not affect 146 nNav1.5 mRNA expression in MDA-MB-231 cells

Figure 4.2 Long-term effect of DMSO treatment on nNav1.5 mRNA 148 expression in MDA-MB-231 cells was dose-dependent

Figure 4.3 Long-term effect of E2 treatment on nNav1.5 mRNA expression 149 in MDA-MB-231 cells was dose-dependent (bell-shaped)

Figure 4.4 Long-term effect of E2 treatment on nNav1.5 mRNA expresison 150 in MDA-MB-231 cells was time-dependent

Figure 4.5 Long-term E2 treatment did not affect nNav1.5 protein in MDA- 152 MB-231 cells

Figure 4.6 Long-term control treatments did not affect MDA-MB-231 cell 153 adhesion measured as detachement negative pressure (DNP)

Figure 4.7 Long-term treatment with E2 decreased MDA-MB-231 cell 154 adhesion measured as detachement negative pressure (DNP)

Figure 4.8 TTX treatment inhibited the long-term effect of E2 on MDA-MB- 156 231 cella dhesion measured as detachement negative pressure (DNP)

Figure 4.9 Long-term treatment with G1 did not affect nNav1.5 mRNA 157 expression in MDA-MB-231 cells

Figure 4.10 Long-term treatment with G1 did not affect MDA-MB-231 cell 158 adhesion measured as detachment negative pressure (DNP)

Figure 4.11 Control treatments with CS-FBS and DMSO did not affect 160 adhesion of empty-vector transfected MDA-MB-231 cells measured as detachment negative pressure (DNP)

Figure 4.12 Long-term treatment with E2 reduced but G1 did not affect 161 adhesion of empty-vector transfected MDA-MB-231 cells measured as detachment negative pressure (DNP)

15 Figure 4.13 Control treatments with CS-FBS and DMSO did not affect 162 adhesion of GPR30-14 cells measured as detachment negative pressure (DNP)

Figure 4.14 Long-term treatment with E2 and G1 decreased adhesion of 163 GPR30-14 cells measured as detachment negative pressure (DNP)

Figure 4.15 Control treatments with CS-FBS and DMSO did not affect 164 VGSC131 mRNA expression in MDA-MB-231 cells

Figure 4.16 Long-term treatment with E2 did not affect VGSCI31 mRNA 165 expression in MDA-MB-231 cells

Figure 4.17 Long-term treatment with G1 did not affect VGSCI31 mRNA 166 expression in MDA-MB-231 cells

Figure 4.18 A model of estrogen regulation of adhesion 175

Chapter 5 Long-term effects of 17p-estradiol on voltage-gated sodium channel expression and adhesion of ERa-expressing MDA- MB-231 cells

Figure 5.1 ERa transfection altered cell morphologies of MDA-10A cells 179

Figure 5.2 ERa mRNA was highly expressed in MDA-ERa, but not VC5 and 181 MDA-10A cells

Figure 5.3 GPR30 mRNA was expressed in all cell lines and ERa 182 transfection did not change its levels

Figure 5.4 nNavl.5 mRNA expression was reduced in MDA-ERa cells 183

Figure 5.5 ERa transfection reduced Nav1.7 mRNA levels and altered 185 relative VGSCa mRNA expression

Figure 5.6 nNav1.5 protein expression was reduced in MDA-ERa cells 186

Figure 5.7 Single-cell adhesion was not affected by ERa transfection 187

Figure 5.8 ERa transfection reduced MDA-MB-231 lateral cell motility 189

Figure 5.9 CS-FBS medium reduced pS2 mRNA expression in MDA-ERa 190 cells time-dependently

16 Figure 5.10 CS-FBS medium increased nNav1.5 mRNA time-dependently but 191 non-significantly in MDA-ERa cells

Figure 5.11 Adhesion of MDA-ERa cells did not change in CS-FBS medium 193

Figrue 5.12 Long-term E2 treatment decreased nNav1.5 mRNA in MDA-ERa 194 cells dose-dependently

Figure 5.13 Long-term effect of E2 on nNav1.5 mRNA expression was time- 195 dependent in MDA-ERa cells

Figure 5.14 Long-term E2 treatment decreased adhesion of MDA-ERa cells 197 VGSC-dependently

Figure 5.15 Long-term E2 treatment increased nNav1.5 mRNA expression in 198 VC5 cells dose-dependently

Figure 5.16 Long-term ICI on nNav1.5 mRNA expression was time and dose- 199 dependent in MDA-ERa cells

Figure 5.17 Long-term ICI treatment did not affect adhesion of MDA-ERa 201 cells

Figure 5.18 Long-term treatment with ICI-182,780 increased transverse 202 migration and lateral motility of MDA-ERa cells

Chapter 6 General Discussion

Figure 6.1 A hypothetical model of estrogen regulation of VGSCs and 222 adhesion in BCa cells

17 ABBREVIATIONS

(ca2+)i Intracellular Ca2+

Pg Microgram

Ill Microlitre

AM Micromolar

AM Micrometre

AC Adenylate cyclase

AF Activation function

AI Aromatase inhibitor

AKAP A kinase-anchoring protein

Apl Activating protein 1

APC Adenomatosis polyposis coli

AR Androgen receptor

AU Arbitrary unit

BCa Breast cancer

BF Bright field

BK channel Large-conductance Ca2+-activated K+ channel

BM Basement membrane

BRCA1 Breast cancer 1

BSA Bovine serum albumin

CAM Cell adhesion cAMP Cyclic adenosine monophosphate

Cav Voltage-gated Ca2+ channel isoform cDNA Copy deoxyribose nucleic acid

18 CHO Chinese hamster ovary

CNS Central nervous system

ConA Concanavalin A

CREB cAMP response element binding protein

CS-FBS Charcoal-stripped foetal bovine serum

Ct Threshold amplification cycle

C-terminal COOH-terminus

CXCR Chemokine receptor

D Voltage gated Na+ channel domain

DAG Diaglycerol

DBD DNA-binding domain

DMEM Dulbecco's modified Eagle's medium

DMSO Dimethyl sulfoxide

DNA Deoxyribose nucleic acid

DNP Detachment negative pressure

DRG Dorsal root ganglion

DTT Dithiothreitol

E2 1713-estradiol

E2-BSA Bovine serum albumin-conjugated 170-estradiol

EB Elution buffer

ECM Extracellular matrix

EDTA Ethylenediaminetetraacetic acid

EGF Epidermal growth factor

EGFR Epidermal growth factor receptor

EGTA Ethylene glycol-bis ((3-aminoethyl ether) tetraacetic acid

19 EMT Epithelial-to-mesenchymal transition

ENaC Epithelial Na+ channel

ER Estrogen receptor

ERE Estrogen response element

ERIC extracellular signal- regulated kinase

FAK Focal adhesion kinase

FBS Foetal bovine serum

FGF Fibroblast growth factor

FITC Fluorescein isothiocyanate

g Acceleration due to gravity

g Gram

GFR Growth factor receptor

GPCR G-protein coupled receptor

GPR30 G-protein coupled receptor — 30

GR Glucocorticoid receptor

h Hour

HDAC Histone deacetylase

HEK Human embryonic kidney

HER2 Human epidermal receptor factor 2

HGF Hepatocyte growth factor

HRP Horseradish peroxidase

HSP Heat-shock protein

Hz Hertz

20 ICAM Intracellular adhesion molecule

ICC Immunocytochemistry

ICI ICI-182,780

ID Interdomain region of VGSC

IFM Isoleucine-phenylalanine-methionine

Ig Immunoglobulin

IGF Insulin growth factor

IL-8 Interleukin-8

IM Intracellular membrane

INT Intracellular

TP3 Inositol 1,4,5-triphosphate

JNK c-Jun N-terminal kinase kDa Kilo Dalton

Kir Inwardly-rectifying K.+ channel kPa Kilo Pascal

L Litre

LB Luria broth

LBD Ligand-binding domain

LD Lab designed

LHRH Luteinizing hormone-releasing hormone

M Molar

MAPK Mitogen —activated protein kinase

MCB Metastatic cell behaviour

MEM Minimal essential medium miRNA Micro RNA

21 ml Millilitre mm Milli metre

MMP Matrix metalloproteinase

MoI Motility index

MPS Mammalian physiological saline

MR Mineralocorticoid receptor

MRI Magnetic resonance imaging mRNA Messenger ribose nucleic acid

MTT Thiazolyl blue tetrazolium bromide

MW Molecular weight

Nav Voltage-gated sodium channel isoform

NESO-pAb nNav1.5-specific polyclonal antibody

NFKB Nuclear factor-kappa B ng Nanogram

NGF Nerve growth factor

NLS Nuclear localization signals nM Nanomolar nm Nanometre nNav1.5 'Neonatal' Nav1.5 nt Nucleotides

NT-3 Neurotrophin-3

NTC No template control

N-terminus NH2-terminus

OD Optical density

22 P P-value

PBS Phosphate buffered saline

PC Personal computer

PC12 Pheochromocytoma cells

PCa Prostate cancer

PCR Polymerase chain reaction

PDGF Platelet derived growth factor

PDZ Post synaptic density disc-large zo-1

PET Positron emission tomography

PFA Paraformaldehyde

PI3K Phosphoinositide 3-kinase

PIP2 Phosphatidylinositol 4,5-biphosphate

PICA Cyclic AMP-dependent protein kinase A

PKC Protein kinase C

PLC Phospholipase C

PM Plasma membrane

pM Picomolar

PMSF Phenylmethylsulphonyl fluoride

PR Progesterone receptor

PSA Prostate specific antigen

PTEN Phosphatase and tensin homolog

Rb Retinoblastoma protein

REST RE1 binding silencer protein

RIPA buffer Radioimmunoprecipitation buffer RNA Ribose nucleic acid

23 RNAi RNA interference

rRNA Ribosomal RNA

RT-PCR Reverse-transcription polymerase chain reaction

S Voltage-gated transmembrane a-helical segment

SCAMA Single cell adhesion measuring apparatus

ScTx Scorpion toxin

SDS Sodium dodecyl sulphate

SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis

sdw Sterile distilled water

SEM Standard error of mean

SERM Selective estrogen receptor modulator

SH Steroid hormone

siRNA Small-interfering RNA

SK Small-conductance Ca2+-activated K+ channel

Spl Stimulating protein 1

STX Saxitoxin

TA Annealing temperature

TBE Tris-HCL-borate-EDTA

TEA Tetraethylammonium

TF

TGF-0 Transforming growth factor-0

TNF-a Tumour necrosis factor a

Tris Tris(hydroxymethyl)aminomethane

TTX Tetrodotoxin uPA urokinase plasminogen activator

24 USA The United States of America

UV Ultra-violet

V Volt v Volume

VC5 Empty-vector (pBK-CMV)-transfected MDA-MB-231-10A cell line

VCAM Vascular cell adhesion molecule

VEGF Vascular endothelial growth factor

VEGFR Vascular endothelial growth factor receptor

VGSC Voltage-gated Na+ channel

VGSCa Voltage-gated Na+ channel a-subunit

VGSCP Voltage-gated Na+ channel (3-subunit w Weight

Wo Initial wound width

WB

Wt Wound width at time t

a-SMA Smooth muscle a-actin

25 Chapter 1

GENERAL INTRODUCTION

26 This Chapter gives an overview of the current literature on (1) cancer and metastasis; (2) breast cancer (BCa), its diagnosis and treatment; (3) estrogen, its receptors and role in BCa development and progression; and (4) voltage-gated sodium channels (VGSCs), their regulation (especially by steroid hormones) and involvement in cancer (especially BCa) and metastatic cell behaviours. The Chapter is concluded with the aims and scope of the Thesis.

1.1 Cancer basics

Cancer is the second most common disease and cause of death after heart diseases in Western countries and 1,437,180 new cancer cases and 565,650 deaths from cancer were expected in the USA in 2008 (Jemal et al., 2008). Most cancers originate from epithelial cells and are known as "carcinomas". Cancer can form mainly because of genetic or epigenetic changes, which could be inherited or initiated by other factors such as aging, diet, alcohol and tobacco intake, and exposure to viruses (Dumitrescu and Cotarla, 2005; Go et al., 2004; Lin et al., 2008b). The two main groups of identified to be involved in cancer are (1) proto-oncogenes and (2) tumour suppressor genes (Hanahan and Weinberg, 2000). Proto-oncogenes (e.g. ras, myc, fos, src, bc12) are normal genes encoding for involved in cell proliferation and differentiation. Mutations leading to gain of function can turn these genes into oncogenes and cause uncontrolled cell division (Bocchetta and Carbone, 2004). Ras is the first human oncogene isolated from human bladder carcinoma (Feig, 1993). Uncontrolled growth and avoidance of differentiation are important properties that enable cancer cells to sustain proliferation and autonomy in the tissue/organ of origin. Tumour suppressor genes [e.g. p53, retinoblastoma (Rb), breast cancer 1 (BRCA1)] have a natural suppressive function signalling 'defective' cells to go into apoptosis (Bocchetta and Carbone, 2004). Thus, a recessive loss of function in the latter group of genes can disable programmed cell death (Hanahan and Weinberg, 2000). Epigenetic regulation, which involves reversible modifications in DNA methylation or chromatin structure without changing the actual gene sequence (e.g. causing tumour suppressor gene silencing), has been identified as an important risk factor in cancer (Feinberg and Tycko, 2004; Li et al., 2005). Hypermethylation,

27 hypomethylation and histone-acetylation modulate expression of many genes, including tumour-suppressors (Grote et al., 2005; Shutoh et al., 2005). These changes are mostly reversible suggesting that therapies targeting gene methylations could be successful.

1.1.1 MicroRNAs A new group of gene regulators called micro-RNAs (miRNAs) were suggested to be involved in cancer development and progression (Esquela-Kerscher and Slack, 2006; Zhang et al., 2007). Although it is estimated that there are about 1000 miRNAs in the , only 200-300 have so far been identified (Bentwich et al., 2005; Griffiths-Jones et al., 2006). miRNAs are non-protein coding small RNAs >50 % of which were reported to be located in cancer-associated genomic regions called "fragile sites" (CalM et al., 2002, 2004). This suggested a role of miRNAs in pathogenesis of cancer. Polymerase chain reaction (PCR) and microarray studies revealed several differentially expressed miRNAs in various cancers. For example, miR-15a and miR-16-1 were shown to be deleted or down-regulated in about 68 % of B-cell chronic lymphocyte leukaemia (Calin et al., 2002). Among the targets of miR-15a and miR-16-1 is BCL2 which is an anti-apoptotic gene that is overexpressed in many cancers including lymphomas and leukemias (Cimmino et al., 2005). Both miR-15a and miR-16-1 would downregulate BCL2 expression post-transcriptionally (Cimmino et al., 2005). Thus, a reduced expression of these miRNAs would increase BCL2 activity, and lead to increased growth of cancer cells. Another miRNA involved in cancer is let-7 which normally downregulates two key oncogenes, Ras and Myc, again by targeting their mRNAs for repression of translation (Akao et al., 2006; Johnson et al., 2005; Takamizawa et al., 2004). A reduced level of let-7 in cancer would lead to increased cell growth (Takamizawa et al., 2004). Upregulation of certain miRNAs has also been reported in cancer cells. For example, miR-17-92, which is predicted to target two tumour suppressor genes, phosphatase and tensin homolog (PTEN) and Rb2 (Lewis et al., 2003) was upregulated in lung cancer (Hayashita et al., 2005). Depending on their normal function, miRNAs could be tumour suppressors or oncogenes — "oncomirs" (Esquela-Kerscher and Slack, 2006; Zhang et al., 2007). Irregular miRNA expression has also been reported for colorectal cancer (Michael et al., 2003), brain cancer (glioblastoma multiforme; Ciafre et al., 2005), liver cancer

28 (Murakami et al., 2006), papillary thyroid cancer (He et al., 2005; Pallante et al., 2006), testicular germ cell cancer (Voorhoeve et al., 2006) and breast cancer (Iorio et al., 2005). Foekens et al. (2008) reported in vivo expression of four miRNAs (miR-7, miR-128a, miR-210, and miR-516-3p) in estrogen receptor (ER) -positive/lymph-node metastasized BCa and one miRNA (miR-210) in ER-negative/lymph-node metastasized BCa patients. A role in tamoxifen-resistance and ER-downregulation has also been reported for miRNA-221, miRNA-222 and miRNA-206 (Kondo et al., 2008; Miller et al., 2008; Zhao et al., 2008b). Further research is required to understand the mechanisms controlling expression of miRNAs, their involvement in cancer and therapeutic potential.

1.2 Metastasis

Metastasis - the spread of tumour cells from the primary neoplasm to distant organs - is the main cause of death from cancer (Fidler, 2003). This is a complex and systematic process in which tumour cells interact with each other as well as with surrounding host cells (stroma) via cytokines, chemokines and growth factors which collectively help with cancer cell invasion (Eccles, 2004; Eccles and Welch, 2007). Cancer cells can disseminate via three main routes: (1) lymphatics (via lymph vessels), (2) haematogenics (via blood vessels), and (3) transcoelomics (via coelomic cavities) (Bacac and Stamenkovic, 2008; Eccles and Welch, 2007). Metastasis consists of a series of steps (Figure 1.1): (1) Primary tumour cells proliferate and detach from the original site (Fidler, 2003; Schneider and Miller, 2005). (2) These cells locally invade through the surrounding stroma and (3) enter circulation — intravasate. (4) The cells that survive the circulation arrest in the vasculature. (5) Some cells stay dormant whilst others invade through the vessel wall (extravasate) into a secondary site. (6) Attached cells proliferate and form a microenvironment via angiogenesis (Bacac and Stamenkovic, 2008; Eccles and Welch, 2007; Pantel and Brakenhoff, 2004). Not all primary tumour cells are able to metastasize. At each step of the metastatic cascade, certain conditions need to be met before the cells can advance to the next stage. There are two theories of acquiring metastatic potential: (1) Tumour cells are pre- programmed to metastasize (Nguyen and Massague, 2007). Thus, only the cells containing certain genes/gene combinations or mutations can form secondary tumours. In

29 (a) Initial detachment, Invasive carcinoma proliferation and angiogenesis

In situ carcinoma

Norma! epith

(b) Epithelial-mesenchymal transition and basement membrane degradation

(c) Invasion and migration

(e)

(f) Extravasation Circulation (d) Intravasation into blood vessels or lymphatics

(9) Proliferation, angiogenesis and microenvironment activation

(h) Growing metastases

Figure 1.1: Stages of metastatic cascade. Normal epithelial cells are transformed into in situ carcinomas which evade apoptosis by uncontrolled proliferation (a). New blood vessels are formed (angiogenesis) to support the growing tumour mass with nutrients and extracellular signalling required for metastatic processes. Epithelial cells acquire mesenchymal properties where the adheren junctions are lost and basement membrane is degraded (b). In this way the cells evolve toward the invasive carcinoma stage with increased migration (c) and intravasate into blood (haematogenic route) or lymph nodes (lymphatic route) (d). Circulation kills some cells that can not withstand shear stress (e); the ones that survive could either be arrested on the vessel wall and stay dormant or extravasate to the surrounding organ (f) where they set up a microenvironment supported with new blood vessel formation and further proliferation (g and h). Possible metastases in lungs, bone and liver are shown here as examples. Modified from Bacac and Stamenkovic (2008).

30 this model, there is early emergence of metastatic markers. (2) Metastasis is a random process and tumour cells increasingly acquire mutations as they grow and progress, ultimately acquiring the potential to migrate to distant sites (Bacac and Stamenkovic, 2008). In this model, metastatic markers emerge late in the process (Bacac and Stamenkovic, 2008; Duffy et al., 2007, 2008). van Veer et al. (2002) and van de Vijver et al. (2002) reported a 70-gene signature that was shared between primary and metastatic human BCa samples. A later study revealed a 17-gene signature (Ramaswamy et al., 2003). These reports are suggestive of possible gene combinations in primary tumours that could predict the outcome of possible metastases. However, other studies have shown that primary and metastatic cancer cells can express different gene combinations (Suzuki and Tarin, 2007; Vecchi et al., 2008). Discrepancies in such studies can be due to impurities in the tissue samples used (i.e. mixture of surrounding tissue together with tumour cells could interfere with the gene signatures), or to differences in the sampling methods. For example, the primary and metastasis samples were matched in the study of Suzuki and Tarin (2007) but not matched in the study of Vecchi et al. (2008). The genetic variability between patients could also induce variability, further highlighting the need for careful experimental design (Suzuki and Tarin, 2007). It is possible that both mechanisms occur during metastasis i.e. the initial gene profile of the tumour cells helps them start the metastatic process but constant modification of is necessary to adjust to the environment and progress.

1.2.1 Epithelial-to-mesenchymal transition and invasion Epithelial cells normally are attached to each other via complex adhesion mechanisms, including tight and adheren junctions and desmosomes (Figure 1.2; Perez-Moreno et al., 2003). The normal simple epithelium is a sheet of epithelial cells with lateral connections and an 'apical-to-basal polarity' maintained by actin cytoskeleton on the apical side and basement membrane (BM) binding sites (e.g. focal contacts, 131-integrins) on the basal side (Bacac and Stamenkovic, 2008; De Wever et al., 2008). These connections are inhibited and eventually lost when the cells are transformed into a malignant state. Invasive potential is acquired as the cells replace their epithelial characteristics with mesenchymal properties. This involves changes to cellular morphology including

31

A. B.

Tight junction

Adheren junctions

Desmosome

Focal contacts

Figure 1.2: Adhesion mechanisms in epithelial cells. (A) The epithelial cell layer is attached to the basement membranes via focal contacts (orange squares) and to adjacent cells via adheren junctions (black rectangles) and desmosomes (pink ovals). The basal-to-apical polarity is maintained by tight junctions (blue circles). The epithelial cells divide parallel to the basement membrane (illustrated by brown mitotic spindles) to allow lateral expansion of the basal layer. (B) Illustrative diagram of the three major types of intercellular junctions in epithelial cells also shown in (A). Tight junctions are transmembrane proteins linked to the actin cytoskeleton forming a physical barrier between the apical and basolateral regions; adheren junctions are also linked to the actin cytoskeleton and are formed by homophilic interactions of transmembrane cadherins; and desmosomes are linked to intermediate filaments and are formed by interactions between desmosomal cadherins. Modified from Perez-Moreno et al. (2003).

32 acquisition of a more extended and elongated shape with loss of focal contacts, which imposes a 'front-to-back edge polarity' (De Wever et al., 2008). These changes in cell shape, cell-to-cell and cell-to-matrix adhesive properties are collectively called "epithelial-to-mesenchymal transition" (EMT) (De Wever et al., 2008). EMT is characterized by the loss of epithelial markers (e.g. E-cadherin, I3-catenin, laminin, occludin) and replacement of those with mesenchymal markers [e.g. N-cadherin, vimentin, matrix metalloproteinases (MMPs), smooth muscle a-actin (a-SMA)] (De Wever et al., 2008). These changes lead to BM degradation at the invasive front where the epithelial cells are freed from barriers like extracellular matrix (ECM) and cell junctions, and become invasive (De Wever et al., 2008; Sabbah et al., 2008). During EMT, there is an orchestrated cross-talk between oncogenic pathways (e.g. phosphoinositide-3 kinase (PI3K), mitogen-activated protein kinase (MAPK), Src, Myc, Ras) and consequent activation of EMT transcription factors (e.g. Twist, Slug, Snail) (De Wever et al., 2008; Sabbah et al., 2008). A wide range of extracellular stimuli are involved in EMT, including Wnt (Le Floch et al., 2005), transforming growth factor-13 (TGF-(3; Kim et al., 2008), epidermal growth factor (EGF; Lo et al., 2007), platelet- derived growth factor (PDGF; Ostman and Heldin, 2007), nonreceptor kinases (Src), ERa, G-protein coupled receptors (GPCRs), integrins (Burgermeister et al., 2008), vascular endothelial growth factor (VEGF; Yang et al., 2006), HGF (Grotegut et al., 2006), insulin-growth factor (IGF; Krueckl et al., 2004) and hypoxia (Higgins et al., 2007). Activation of the corresponding receptor systems can subsequently trigger downstream signalling pathways, including focal adhesion kinase (FAK; Bailey and Liu, 2008), PI3K (Wang et al., 2007a), Akt/nuclear factor-kappa B (NFKB) (Cheng et al., 2007; Chua et al., 2007), SMAD (Schmierer and Hill, 2007), MMPs (Thiery and Sleeman, 2006), and miRNAs (e.g. miR-10b, miR-200 and miR-205; Gregory et al., 2008; Ma et al., 2007). Such pathways eventually result in activation of EMT transcription factors, such as Zinc finger E-box Binding, Snail, Slug and Twist, which can lead to (1) transcriptional repression of E-cadherin and induction of N-cadherin (called `cadherin switch'; Cano et al., 2000; Vandewalle et al., 2005); (2) induction of Bcl-2 (inhibiting apoptosis; Wang et al., 2007a); (3) repression of hormone receptor (e.g. ERa) expression (Dhasarathy et al., 2007); (4) nuclear and cytoplasmic localisation of13-catenin as opposed to plasma membrane in normal cells (Stemmer et al., 2008); (5) increased expression of vimentin (Chen et al., 2008; Sarrio et al., 2008) and (6) a-SMA (Sarrio et

33 al., 2008); and (7) upregulation of MMPs such as MMP-1, -2, -3, -7, -9 and -14 (e.g. Nutt et al., 2003; Patel et al., 2007; Somiari et al., 2006). These processes help tumour cells acquire enhanced motility and resistance to apoptosis, which are essential to invasive behaviour and efficient metastasis. Circulating EMT markers have been detected in many cancer types including liver, kidney, lung, head and neck, pancreas, prostate and breast (De Wever et al., 2008). Such markers can form the bases of novel diagnostic techniques for early detection of cancer as well as treatment targeting any of the EMT signalling components.

1.2.2 Angiogenesis and tumour cell dissemination Dissemination of tumour cells to distant sites is initiated via intravasation of the cells into blood vessels and lymphatic circulation. For this, it is necessary to produce new vasculature in the surroundings through which cancer cells can access cytokines and proteinases (secreted by other cancer cells or immune cells) to help them grow and digest through the ECM and migrate towards circulation. The process of making new blood vessels is called "angiogenesis". The main angiogenic signalling mechanisms include growth factors like VEGF, fibroblast growth factor (FGF), TGF-13, HGF, tumour necrosis factor (TNFa), angiogenin, interleukin-8 (IL-8), angiopoietins, MMPs and urokinase plasminnogen (uPA) (Karamysheva, 2008; Rundhaug, 2005). VEGF is the most potent angiogenic factor studied so far (Duffy et al., 2008). It triggers a network of signalling pathways (e.g. FAK, PI3K, MAPK) to stimulate endothelial cell growth, migration and survival and allows vascular permeability for mobilization of endothelial precursor cells from bone marrow into peripheral circulation. The VEGF family consists of VEGF-A, -B, -C, —D, -E and placental growth factor (Duffy et al., 2008), VEGF-A being the major angiogenic mediator (Karamysheva, 2008; Kerbel, 2008). VEGF-A binds to VEGF receptor (VEGFR) -1 and -2, with about 10 times more affinity to the latter (Eccles, 2004; Kerbel, 2008). VEGF is often upregulated in cancer cells, mostly due to genetic and epigenetic modifications (Kerbel, 2008). VEGF secretion by macrophages or keratinocytes can be induced by hypoxia (via hypoxia-inducible factor-la), or decreased expression of tumour-suppressor genes (e.g. APC, PTEN, p53), EGF, IGF-1, PDGF, FGF, TGF-13 and TNFa (Rundhaug, 2005). Among downstream of VEGF signalling are MMPs and integrins (e.g. Bergers et al., 2000; Ferrara, 2005).

34 Integrins are indirectly involved in angiogenesis, mostly interacting with VEGFRs or MMPs to drive cellular migration (Rundhaug, 2005). VEGF stimulation induces integrins (a1131, a2f31, aV133) at the tips of sprouting endothelial cells and newly formed blood vessels (Li et al., 2003). Integrin aV133 also activates MMPs. Interestingly, activation of MAPK-ERK1/2 pathways by VEGF, and NFiB by TNFa was shown to be regulated by integrins (Moon et al., 2003; Senger et al., 2002). Both of these pathways are important for angiogenesis, as they induce uPA secretion and transcription of MMP-9 (Rundhaug, 2005). There is major interest in developing anti-angiogenic agents as cancer drugs. One such example is the monoclonal antibody directed against VEGF, called Bevacizumab (Shih and Lindley, 2006). Clinical trials have led to treatment of metastatic colon, lung cancers and breast cancer (Hayes et al., 2007). Synthetic MMP inhibitors (e.g. N- Biphenyl sulfonyl-phenylalanine hydroxiamic acid, batimastat, KB-R7785) and integrin inhibitors are also potential anti-angiogenesis agents and may control cancer cell invasion (Eccles, 2004; Rundhaug, 2005).

1.2.3 Adhesion and extravasation During their passage in circulation, tumour cells arrest near capillary beds of secondary organs. Whilst some cells stay dormant at these locations, others extravasate to the surrounding tissues. This process is maintained by (1) tumour cell adhesion to the endothelium, (2) migration across BM and endothelial lining, and (3) invasion of the surrounding tissue (Dittmar et al., 2008; Gumbiner, 1996). Thus, adhesion is dynamically regulated throughout the process of metastasis: At early stages, cells lose contact with each other and with ECM (cell-to-matrix interactions) for increased motility and angiogenesis; later, the cells need to interact with each other and ECM for attachment to vessel walls and migration to distant sites. Adhesion is coordinated by cell adhesion molecules (CAMs) such as cadherins, catenins, integrins, selectins and imrnunoglobulins (Mousa, 2008). Integrins are a family of transmembrane glycoproteins maintaining both cell-ECM and cell-cell interactions. They are composed of two subunits a and 13, and are expressed as heterodimers in many cell types (Mousa, 2008). Currently, there are 18 a and 8 13 subunits identified in mammals which combine to form more than 24 different integrin heteromers (Silva et al., 2008). These integrins can be grouped according to the ECM

35 protein(s) they recognize such as vitronectin, fibronectin, collagen and laminin receptors (Silva et al., 2008). Activation of these receptors via ligand binding leads to relocation of the receptors so as to form clusters called "focal adhesions" (Ivaska & Heino, 2000). In this way, integrins accumulate cytoskeletal proteins like tensin, a-actinin, talin, vinculin and FAK (Yamada and Miyamoto, 1995). Accumulation of FAK induces its autophosphorylation which activates Src kinase (Mitra and Schlaepfer, 2006), Ras, MAPK (e.g. ERK, JNK and p38) and other cytoskeletal proteins like F-actin and paxillin (Ivaska and Heino, 2000; Mitra and Schlaepfer, 2006). In this way, integrins mediate both cytoskeletal binding and regulate downstream signalling mechanisms involved in cell proliferation and motility. In addition to ECM proteins, integrins can interact with VEGF and TGF13 (Silva et al., 2008) as well as chemokine receptors like CXCR4 (Dittmar et al., 2008). Thus, all such integrin mechanisms can facilitate tumour cell-endothelium associations and extravasation. Immunoglobulins like intracellular adhesion molecule (ICAM) and vascular cell adhesion molecule (VCAM) are involved in leukocyte arrest which precedes extravasation (Bacac and Stamenkovic, 2008). There is a high-affinity interaction between ICAM/VCAM and integrins (Smith, 2008). This is mostly involved in attachment of leukocytes to blood vessel wall and migration through endothelium. At this stage, chemokine-receptors such as CXCR4 were shown to cooperate with integrins (mainly av(33) for efficient extravasation of leukocytes and cancer cells (Dittmar et al., 2008). Integrins are also a target in cancer therapeutics: Inhibitors such as endostatin and tumstatin and an antibody, Vitaxin, are in use experimentally against integrins (Eccles, 2004).

1.3 Breast cancer (BCa) Breast cancer (BCa) is the most commonly diagnosed cancer in women, especially in Western countries, and second lethal after lung cancer (Dumitrescu and Cotarla, 2005; Jemal et al., 2008). It affects about one in nine women during their lifetimes. Among the most important prognostic factors are lymph node status, tumour size, estrogen/progesterone receptor (ER/PR) status, HER2 status, histological grade, bone marrow micrometastases and expression of specific gene profiles (Ali and Coombes, 2000; Braun et al., 2005; Chang et al., 2005; Cianfrocca and Goldstein, 2004; Menard et

36 al., 2003; Sharma et al., 2005; van 't Veer et al., 2002; van de Vijver et al., 2002). Some genes whose expressions are altered in BCa include p53 (more than 80 % of BCa have a defect in this gene), PTEN, caveolin-1, BRCA-1 and BRCA-2 (which account for about 10 % of all BCa cases) (Fan et al., 2006; Ingvarsson, 2004). The most common detection technique used for BCa is X-ray mammography. In addition, ultrasonography, MRI and PET scans are also useful tools for early BCa detection (Veronesi et al., 2005). For detecting metastasis, such as lymph node metastases, sentinel lymph node biopsy, chest radiography, axillary and abdominal ultrasound and bone scintigraphy are supplemented to the other mentioned methods (Heusner et al., 2008; Yang et al., 2007). Depending on the pathological characteristics and menopausal state of women, there are several treatment methods for BCa: Surgical removal, radiation, hormone therapies and chemotherapies (Colozza et al., 2007; Duffy, 2005). The endocrine therapies for postmenopausal women include first-line treatments with selective estrogen receptor modulators (SERMs) such as tamoxifen (Ali and Coombes, 2002; Powles, 2008) and raloxifene for ER-positive BCa (Ali and Coombes, 2002; Powles, 2008; Vogel, 2008). Tamoxifen was shown to cause disease regression in about 30 % of BCa cases (Ali and Coombes, 2002). However, resistance to hormone therapy can develop and relapse can occur; and adjuvant therapies with more selective aromatase inhibitors (AIs) such as nonsteroidal/reversible anastrocole, letrozole and vorozole, and steroidal/irreversible exemestane can also be used (Buzdar et al., 1997, 1998; Colozza et al., 2007). In addition to SERMS, pure 'anti-estrogens', like Fulvestrant (ICI-182,780) can also be used (Robertson et al., 2003; Vergote et al., 2003). For pre-menopausal women, possible treatments include oophorectomy, ovarian irradiation, use of luteinizing hormone-releasing hormones (LHRH) analogs or tamoxifen (Colozza et al., 2007; Sharma et al., 2005). A combination treatment of LHRH with tamoxifen and/or AIs has also been suggested for patients with metastatic BCa (Cuzick, 2008; Sharma et al., 2008). In cases of ER-negative or estrogen insensitive BCa, expression of HER-2 may become important. In such cases, a monoclonal antibody against HER-2 (Herceptin) is being used alone or in combination with chemotherapy (Higgins and Wolff, 2008; Widakowich et al., 2008). Novel BCa treatments such as immunotherapies including

37 vaccines against predictive immunologic markers on tumour cells are also being tested (Emens, 2008).

1.4 Estrogen Estrogen is a member of the steroid hormone (SH) family which includes cholesterol- based molecules carried in blood bound to steroid-binding globulins. Estrogen, like all SHs, exerts its cellular effects classically by binding to its receptors in the nucleus and cytosol (Nadal et al., 2001). However, more recent evidence suggests a complexity of signalling pathways including a plasma membrane (PM) receptor and non-genomic mechanisms (e.g. Prossnitz et al., 2008a; Revankar et al., 2005). Thus, estrogen is associated with a wide variety of cellular functions through its many possible regulatory pathways. Such functions are important for development and differentiation of the main components of the female reproductive system (breast, ovary, and uterus) as well as bone, brain and liver, and some male reproductive organs such as testes and prostate gland (Pearce and Jordan, 2004). As estrogen is required for normal development of these organs, its abnormal functioning and/or abnormal expression of ERs may lead to cancer.

1.4.1 Genomic pathway The genomic role of estrogen is mainly through its nuclear receptors: ERa and ERI3. ERa was cloned originally from the non/weakly metastatic human BCa cell line, MCF-7 (Green et al., 1986); ERI3 was cloned a decade later from rat prostate (Kuiper et al., 1996). These ERs can be expressed separately or together in a wide variety of tissues (Figure 1.3A), such as breast, urogenital tract, heart, bone, central nervous system and prostate (Arts et al., 1997; Kuiper et al., 1997; Nilsson and Gustafsson, 2002; Pearce and Jordan, 2004). As with all SH receptors, both ERa and ERI3 share the six conserved regions (A-F) each of which constitutes a specific functional and structural domain (Figure 1.3B; Tsai and O'Malley, 1994): (1) The N-terminal "A/B domain" is composed of the transcription activation function 1 (AF-1) which regulates target genes via coactivators or transactivators. (2) The "C domain" is the DNA-binding domain (DBD), which allows DNA recognition and binding to specific DNA sequences called "estrogen response elements" (EREs) and dimerization of the ER protein on EREs. (3) The "D domain" is where the flexible 'hinge' region resides, allowing the protein to alter its

38

A. brain ERa, ERf3

Blood vessels ERp

cardiovascular system ERa, ERf3 breast ERa, ERf3 gastrointestinal tract liver I F.Rfl ERa urogenital tract ERa, ERI3 uterus: ERa dominant prostate: ERp dominant

bone ERa, ERp B. ',ANN-V.:VANN SSW ERa N ;;;;;;;A/13::::::: C E/F C 6q25-4

aa 1 180 263 302 595

Homology % 30% 96% 30% 53%

ERI3 N - C E/F C 14q22-24

aa 1 149 214 248 530

DNA binding

Ligand binding

Dimerization

HSP binding AF-2 Transactivation AF-1

Silencing

Nuclear localization

Figure 1.3: ERa and ERP tissue expression and functional domains. (A) ERa and ERf3 are coexpressed in the breast, brain, heart and bone; uterus and liver mostly express ERa; blood vessels and gastrointestinal tract express ERR. Modified from Pearce & Jordan (2004) and Fabian & Kimler (2005). (B) Both ERa and ERR, encoded by 6 and 14, respectively, share the six conserved domains (A-F) each having a specific function as shown. The (aa) homologies which define tissue and ligand specific activation of each receptor are given as percentages. Modified from Pearce & Jordan (2004), Platet et al. (2004), Tsai & O'Malley (1994) and Sommer & Fuqua (2001).

39 conformational state. This also contains the nuclear localization signals (NLSs) required for shuttling intracellular proteins to nuclear pores, where they bind to target genes and co-regulatory proteins. (4) The largest "E domain", includes regions for chaperone binding (e.g. heat-shock protein (HSP) 90 which keeps the receptor in an inactive form and ready for hormone binding), dimerization, NLSs, transactivation, intermolecular silencing, and most importantly, the ligand binding domain (LBD). (5) The C-terminal "F domain" contributes to the E domain ligand binding and contains the ligand-inducible transcription activation function 2 (AF-2) (Sommer and Fuqua, 2001; Tsai and O'Malley, 1994). ERa and ERI3 have distinct structures and functions being encoded by two separate genes on chromosomes 6 and 14, respectively, and differing by 65 amino acids (Pearce and Jordan, 2004). They also have different homologies in each of the six domains, suggesting differential coregulatory interactions and ligand activation characteristics (Figure 1.3B; Paech et al., 1997). Estrogenic changes in gene transcription could be initiated in two different ways: (1) The 'classical' pathway, which involves receptor dimerization upon binding to the ligand and association of coactivators (e.g. steroid receptor coactivator-1, receptor interacting 140 kDa protein and p160) or corepressors (e.g. nuclear receptor corepressor, silencing mediator for retinoid and thyroid horomone receptors and p53) which is followed by direct binding to EREs (Beato and Klug, 2000; Clarke et al., 2004; Dobrzycka et al., 2003; Olefsky, 2001; Rosenfeld and Glass, 2001). (2) The 'non- classical' pathway, where receptor-ligand complex binds to other transcription factors, mainly Ap 1, Sp 1 or NEKB which themselves are bound to the DNA sequences and regulate transcription (Beato and Klug, 2000; Biswas et al., 2005; Bjornstrom and Sjoberg, 2004; Clarke et al., 2004; Hall et al., 2001; Sommer and Fuqua, 2001). Some examples of genes whose transcription is regulated by estrogen are cyclin D1, Bc12, NFxB, IGFR (Arpino et al., 2008; Radisky and Bissell, 2007). In addition to the ligand-dependent activation of transcription by ERs via AF-2 region, there is also a ligand-independent mechanism which involves the AF-1 transactivation domain. This mostly involves cross-talk with growth factor receptor (GFR) mechanisms such as EGF, IGF and insulin, and HER-2 (Sommer and Fuqua, 2001). ER is usually activated by receptor phosphorylation, particularly at the serine residue 118 within the AM domain and coregulator recruitment. GFRs activate signalling

40 pathways such as MAPK-ERK1/2 and PI3K/AKT which were shown to phosphorylate ERa (Campbell et al., 2001; Faus and Haendler, 2006; Ikeda and Inoue, 2004; Kato et al., 1995). Such ligand-independent phosphorylation of ERa could enhance regulation of genes such as cyclin D1 in BCa (Balasenthil et al., 2004). Ligand-independent phosphorylation and activity of ERa via cross-talk with GFRs was shown to change its pharmacology which could result in resistance to antiestrogens like tamoxifen (Ali and Coombes, 2002; Arpino et al., 2008).

1.4.2 Non-genomic pathway The non-genomic action of estrogen produces rapid responses (seconds to minutes) which do not involve changes in gene transcription. This suggests involvement of secondary signalling mechanisms (e.g. cAMP, PI3K and MAPK) rather than nuclear signalling. Rapid action of estrogen could be mediated through two different receptor mechanisms: (1) classical ERs outside the nucleus, and/or (2) non-classical receptors in PM or cytoplasm.

1.4.2.1 Classical ERs ER expression outside the nucleus was discovered first in PM of endometrial cells (Pietras and Szego, 1977). Later studies showed ERa and ERI3 expression in PM (mER) after transfection of Chinese hamster ovary (CHO) cells, in mitochondria of human BCa cell line MCF-7, and in endoplasmic reticulum of rat pituitary cells (Chen et al., 2004; Gonzalez et al., 2008a; Govind and Thampan, 2003; Razandi et al., 1999). Immunocytochemistry revealed mERs in pituitary tumour cell line GH3/136/F10 and MCF-7 cells (Campbell et al., 2002; Watson et al., 2002). Use of fluorescent-tagged estradiol and membrane-impermeable bovine serum albumin (BSA) — conjugated estradiol (E2-BSA) proved beneficial in demonstrating effects of estrogen originating from mER (e.g. Berthois et al., 1986a; Yu et al., 2007a). Possible mechanisms controlling mER expression could involve post- transcriptional modifications of ERa by (1) myristoylation (linkage of the 14-carbon fatty acid myristate to the N-terminal glycine via an amide bond) or palmitoylation (post- translational linkage of the 16-carbon fatty acid palmitate to cysteine residues via a thioester bond) (Acconcia et al., 2005; Pedram et al., 2007; Rai et al., 2005); (2) interaction with caveolin-1 or striatin (Lu et al., 2004; Razandi et al., 2003); and (3)

41 association with adaptor molecules such as IGFR-1 and Shc (Song et al., 2004). Importantly, mER expression was shown also to be dynamically regulated by cell number, passage number and serum content, expecially estrogen (Campbell et al., 2002; Watson et al., 2002). Such experimental conditions could explain the differential reports on existence of mERs.

1.4.2.2 Non-classical ERs and other receptors There are contradictory reports about the structural nature of extranuclear ERs. Whilst mER expression was shown in CHO cells transfected with the cDNAs of ERa and ERI3 (Razandi et al., 1999), there are also reports of rapid actions of estrogen, which were not blocked by the anti-estrogen ICI-182,780 (Singh et al., 2000). For example, 17[3-estradiol (E2) could rapidly increase kainate-induced currents in hippocampal neurons from ERa knock-out mice and this was not inhibited by ICI-182,780 suggesting that the estrogen binding protein had a different structure than the classical ER (Gu et al., 1999). Additionally, postnatal neocortex and uterus from ERa knock-out mice were reported to express a different membrane-bound ER (ERX), which reacted to antibodies to ERa- LBD; however, ERX had a different molecular weight and ligand specificity than either ERa or ERI3 (Toran-Allerand et al., 2002). Furthermore, Nadal et al. (2000) studied mouse pancreatic p cells and found that xenoestrogens and E2 had common binding sites in PM which was unrelated to ERa and ERI3 since antibodies against ERa-LBD and N- or C-terminus of ERI3 did not stain the PM. These studies suggested existence of (1) non- classical ERs different from ERa and ERI3 (e.g. ERX), or (2) other receptor mechanisms. The latter category currently involves several possible candidates as described below: i) Estrogen may act through EGFR, suggested from the use of EGFR antibodies to inhibit estrogen-mediated proliferation in uterus (Nelson et al., 1991). Accordingly, in MCF-7 cells, ICI-182,780 treatment (for 24 h) blocked EGF-induced stimulation of cell proliferation and activation of Src/MAPK signalling pathway (Migliaccio et al., 2005). However, since MCF-7 cells also express classical ERa in PM and cytoplasm (Zivadinovic et al., 2005), these results could also indicate a possible ERa-EGFR cross- talk initiating rapid/non-genomic responses (Figure 1.4). ii) Estrogen responsive receptors in PM include G-protein coupled receptors (GPCRs). GPCRs are the largest class of signalling proteins which contain seven transmembrane segments. The main GPCR involved in estrogen signalling is GPR30,

42 HB-EGF n !VEGFR:11ER2 IGFR A lk E2 MMPs . r I c-Src z MAPK / AKT

Phosphorylatlon signals to the nucleus potentiate the activity of genomic ER and other TFs on gene regulation

N P P Transcription Transcription

Figure 1.4: ER, GPCR and EGFR cross-talk signalling mechanisms also showing possible integration of genomic and non-genomic pathways activated by estrogen. Estrogen (E2) can induce the genomic pathway via classical estrogen receptors (ERs) and recruitment of co-activators (CoA) in the nucleus (N) which could regulate gene transcription 'directly' by binding to DNA sequences or 'indirectly' by activating other transcription factors (TF). The non-genomic pathways involve activation of ERs that reside at the plasma membrane (M) usually bound to caveolin-1 (Cav) and/or cytoplasm; or GPCRs (e.g. GPR30). This in turn activates multiple interactions with signaling molecules such as phospholipase C (PLC), protein kinase A (PKA), Shc and Src. E2-ER interaction can activate growth factor (GF) tyrosine kinase receptors (TKR) such as EGFR/HER2 and IGFR. This turns on the downstream kinases like MAPK/AKT which can phosphorylate (P) nuclear ERs and its CoAs as well as other TFs; thus potentiating genomic ER activity. This provides that during excessive TKR signaling, such as in HER2-overexpressing tumors, the nongenomic pathway may become more prominent resulting in activation of downstream kinases. This can lead to endocrine resistance by modifying the activity of various TFs. Modified from Arpino et al. (2008).

43 first cloned by Carmeci et al. (1997) in MCF-7 cells. Many studies have demonstrated its expression patterns, ligand specifications and downstream signalling, particularly in BCa tissues and cell lines (e.g. Prossnitz et al., 2008b; Revankar et al., 2005; Thomas et al., 2005). GPR30 was reported also to be expressed in a wide variety of normal tissues including heart, lung, liver, intestine, ovary and brain, and malignant tissues from BCa and lymphomas (Prossnitz et al., 2008b). Development of antibodies against GPR30 helped further investigate its tissue distribution (Filardo et al., 2006; Revankar et al., 2005). One of the most important findings about GPR30 is its expression and function in cancer cell lines, such as breast (e.g. MCF-7 and SKBR3 cells), endometrial, ovarian and thyroid (Prossnitz et al., 2008b). Importantly, Filardo et al. (2006) have demonstrated in vivo expression of GPR30 in BCa samples: 62 % of invasive carcinoma expressed GPR30 of which 19 % were ERa—negative. GPR30 expression was also reported in SKBR3 BCa cells which do not express ERa or ERI3 (Thomas et al., 2005). High expression of GPR30 in MCF-7 cells (expressing both ERa and ERI3) would suggest that GPR30 can be expressed with or without classical ERs. Although GPCRs are generally known as PM-bound proteins, findings suggest that intracellular expression of GPCRs also occurs (Gobeil et al., 2006). In the case of GPR30, there is evidence for its location in both PM and cytosol (Funakoshi et al., 2006; Matsuda et al., 2008; Revankar et al., 2007; Thomas et al., 2005). GPR30 and ERa could have differential ligand specificities. Unlike ERa, GPR30 signalling can be activated by anti-estrogens like tamoxifen and ICI-182,780 (Thomas et al., 2005). In this regard, development of a GPR30-specific ligand, G1 compound, has been useful in studying GPR30-specific activation and signalling mechanisms (Bologa et al., 2006). For example, in ovarian cancer cells, G1 increased ERKI/2 phosphorylation (Albanito et al., 2007). Other signalling mechanisms activated by GPR30 involve EGFR, IGFR-1 which lead to PI3K, AKT and MAPK pathways, commonly associated with GPCRs (Filardo et al., 2002). Several signalling pathways can be associated with GPCR/GPR30 (Figure 1.4). One such pathway involves activation of PLC, which in turn catalyzes hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) to produce the second messengers, inositol 1,4,5-triphophate (IP3) and diacylglyceraol (DAG) (Rozengurt, 2007). IP3 binds to receptors on endoplasmic reticulum and releases

44 intracellular Ca2+ [(Ca2+)i] and DAG together with (Ca2)i activates PKC, which can phosphorylate and activate Raf-1, and induce ERK1/2 (Rozengurt, 2007). Another well known second messenger activated by GPCRs, including GPR30, is cAMP (Thomas et al., 2005). cAMP signalling leads to activation of PKA and lead to MEK-ERK1/2 signaling (Dumaz and Marais, 2005; Rozengurt, 2007; Figure 1.4). The above mentioned intracellular signalling mechanisms could well be shared with mER and GPR30 where expressed together. Importantly, some of the pathways such as PI3K, MAPK and ERK1/2 could also phosphorylate nuclear ERs (Manavathi and Kumar, 2006; Figure 1.4). Additionally, transcription factors like Elk-1, cAMP response element binding protein (CREB) and NFKB are all targets for phosphorylation by Akt or MAPK signalling (Cruzalegui et al., 1999; Romashkova and Makarov, 1999). Apl is also regulated by MAPK (Karin, 1996). Such effects could lead to 'indirect' genomic responses via mER or GPR30.

1.4.3 Role of estrogen in BCa Estrogen and its receptors are of significant importance to BCa because of their high expression levels in premalignant and malignant breast tissues. In normal breast, only 10- 15 % of the epithelial cells express ER whereas in BCa this rises to 50-80 % (Ali and Coombes, 2000; Dressman et al., 2001). The involvement of estrogen in human BCa has been known for over 100 years. For ER-positive BCa, therapeutic methods include ovarian ablation, use of LHRH agonists, aromatase inhibitors such as exemestane (which reduce level of estrogen synthesis and inhibits ligand-induced activation of ER) or use of steroidal anti-estrogens [e.g. fulvestrant (ICI-182,780)] to completely block ER functioning and/or to induce its degradation (Coombes et al., 2004; Hoffmann and Sommer, 2005; Osborne and Schiff, 2005). However, only about two-thirds of ER-positive BCa cases respond to anti-estrogen therapy and some ER-positive BCa lose ER expression during tumour progression (Giacinti et al., 2006). Tamoxifen, a partial ER antagonist, has been used widely against ER-positive tumours (Ali and Coombes, 2002; Fabian and Kimler, 2005). Nevertheless, resistance would build up after several years of endocrine therapy specifically due to (1) loss of expression or altered functioning (mutations) of ERa, (2) lack of PR, (3) increased ERP expression, (4) metabolism of hormonal agents, (5) altered expression of co-regulators,

45 (6) estrogen hypersensitivity, and (7) increased growth factor (e.g. EGF, IGF) signalling (Normanno et al., 2005). ERs expressed in PM were shown to bind growth factor signalling elements (e.g. PI3K, Src and Shc) or receptors (e.g. IGFR) to cross-activate AKT and MAPK pathways (Osborne and Schiff, 2005). ER cross-talk (e.g. with EGFR or HER-2) in BCa would enhance the non-genomic actions of ER through ERK 1/2, MAPK and PKA pathways. These effects could accelerate disease progression via activation of cell cycle proteins. In human BCa cells, estrogen treatment affected several mechanisms: (1) Estrogen-induced ERK activation via HER-2/EGFR/PKC/Ras pathway led to estrogen dependent growth (Keshamouni et al., 2002). (2) Estrogen decreased phosphorylation of FAKs modulating cell-ECM and cell-cell adhesion (Bartholomew et al., 1998). (3) Estrogen reduced expression of the cytoskeletal proteins vinculin and a-actinin (DePasquale et al., 1994) and the cell adhesion protein, E-cadherin (Oesterreich et al., 2003). (4) Estrogen stimulated MMP-2 activity, leading to increased cell invasiveness (Paquette et al., 2005). (5) Estrogen induced expression of biochemical markers involved in growth and invasion (e.g. MMP-9 and VEGF) (Seeger et al., 2006). Additionally, estrogen induced activation of second messenger systems (ERK1/2, c-Src, and FAK) and actin remodelling in endometrial cancer cells, leading to increased cytoskeletal arrangements and migration (Acconcia et al., 2006). Extensive gene expression profiling studies revealed a wide variety of cancer promoting genes induced by estrogen (Inoue et al., 2002). For example, expression of proliferation factors such as Ki67 and cell cycle activators such as c-myc and cyclin D1 were upregulated by E2 treatment of MCF-7 cells (Carroll et al., 2002; Dimitrakakis et al., 2002; Frasor et al., 2003). Consistently, treatment of MCF-7 cells with ICI-182,780 (100 nM) for 16 h increased p21Wafl gene expression, leading to cell cycle arrest (Varshochi et al., 2005). In another study, MCF-7 cells were treated with estrogen for different times up to 48 h and apoptosis genes (e.g. Bc12, Rb2, p130) and TGFI3 were repressed (Frasor et al., 2003). Importantly, there is also significant evidence suggesting a possible 'protective' role of estrogen in BCa (Platet et al., 2004; Yager and Davidson, 2006). For example, estrogen inhibited and anti-estrogens activated migration of human BCa cells (Mathew et al., 1997; Rochefort et al., 1998). A differential effect of E2 was shown in natively ERa- positive MCF-7 versus ERa-transfected MDA-MB-231 (MDA-ERa) BCa cells: E2

46 increased MCF-7 cell proliferation and in vivo tumour growth, and decreased invasion; in contrast, E2 treatment of MDA-ERa cells decreased in vitro proliferation, invasion and in vivo lung metastasis (Garcia et al., 1992; Mathew et al., 1997; Rochefort et al., 1998). The apparent discrepancies in the literature could stem from use of different cell lines with different ER status (natively expressing or transfected), different treatment doses and/or times (which will activate different receptors and signalling mechanisms). For these reasons, the choice of cell lines and treatment regime are very important in order to obtain consistent results and evaluate the precise involvement of estrogen in BCa.

1.5 Voltage-gated sodium channels (VGSCs)

Voltage-gated sodium channels (VGSCs) are glycosylated transmembrane proteins which are central for initiation and propagation of action potentials in excitable, and some non- excitable cells by permitting mainly rapid influx of Na+ in response to membrane depolarization (Diss et al., 2004; Yu and Catterall, 2003). The three main functional characteristics of VGSCs are voltage-dependent activation, rapid inactivation and selective Na permeation (Catterall, 2000). VGSCs are composed of a 'central' a-subunit (VGSCa) of —260 kDa and accessory 13-subunits (131-4) of 33-38 kDa (Cantrell and Catterall, 2001). VGSCa is the pore-forming component which is sufficient for functional VGSC expression. Its interaction with the auxiliary I3-subunits results in modulation of kinetics and voltage dependence of channel gating, as well as trafficking of VGSCa. The I3-subunits interact with cytoskeletal and ECM proteins maintaining the functional regulation of the channel (Vijayaragavan et al., 2004a; Yu et al., 2005). The VGSCs are usually formed as heteromers of one or more 13-subunits coupling with a-subunit (Figure 1.5). VGSCas are composed of four homologous domains, D 1 -D4, each of which is composed of six transmembrane alpha helical segments, S 1 -S6 with a 'pore-forming loop' between S5 and S6 (Figure 1.5). The S4 segment in each domain has positively charged amino acid residues and upon sensing the change in membrane voltage (depolarization) moves across the membrane thereby initiating channel activation (Catterall, 2001; Yang et al., 1996). A 'sliding helix' model has been proposed to describe channel gating, involving partial translocation of S4 of each domain and outward movement of the positively charged residues (Catterall, 2002). During sustained membrane depolarization, the intracellular loop between domains D3 and D4 'folds'

47

Domain Domain 2 Domain 3 Domain 4 +1-13N,

•ScIx

aui

In -02C CO2' pare 1 I lyaltago-S4 / I (S5-S8) lousing) 1 I voltage Fag.D3-4 inactivation sensing 0 I \

H3f4 Tht fa-terminus \ 1 li CO2 Modulation \. I Protein-inter i C-terminus actions \. Modulation 4Q) Protein-interactions 11D2-3 modulation Protein-interactions

Figure 1.5: Schematic diagram of the voltage-gated sodium channels. The channel is composed of a central a-subunit and associated (3-subunits (13-1 and (i-2 illustrated here). The numbers on the cylinders represent the six segments (S1-S6) in each of the four domains (D1-D4). The important regions to highlight are: voltage-sensing S4 with a positive charge, pore forming S5-S6 with the loop, the fast inactivation interdomain (1D3-4) loop between D3 and D4 and inactivation particle (h) and the VGSCa modulatory regions (1D2-3, N-terminus, C-terminus). The major modulatory mechanisms are at the glycosylation (y), phosphorylation (P in circles for protein kinase A (PKA) and P in diamonds for PKC) and G-protein (G-p) and PDZ protein binding sites. The toxin-binding sites are also shown for tetrodotoxin (TTX) (T in the diamond) and a- and (3-scorpion toxins (aSeTx and (3ScTx, respectively). Modified from Catterall et al. (2003), Diss et al. (2004) and Yu and Catterall (2003).

48 inwards thereby allowing fast inactivation of the channel by blocking the pore (Catterall et al., 2003). There are nine different VGSCa isoforms, Nav1.1-Nav1.9, variable in their amino acid sequences, thereby allowing some diversity in protein-protein interactions and electrophysiological properties (Diss et al., 2004; Goldin et al., 2000). Furthermore, alternative splicing of each isoform is possible where amino acid sequences are added, deleted or changed, thereby forming a wide variety of isoforms each with a specialised role (Diss et al., 2004). Despite the differences in the gene sequences, all isoforms have more than 50 % homology to each other: Nav1.1, Nav1.2, Nav1.3, Nav1.4, Nav1.6 and Nav1.7 are more than 90 % identical to each other, and are sensitive to tetrodotoxin (TTX) at nanomolar concentrations; Nav1.5, Nav1.8 and Nav1.9 have only 64 % homology to the other four isoforms, and are resistant to TTX (can be blocked by micromolar concentrations). Nav 1.1, Nav1.2, Nav1.3 and Nav1.6 are expressed in central nervous system (CNS); Nav1.4 and Nav1.5 are expressed in muscle (skeletal and cardiac, respectively); and Nav1.7, Nav1.8 and Nav1.9 are mainly expressed in peripheral neurons (Catterall et al., 2003; Yu and Catterall, 2003).

1.5.1 Regulation of VGSCs The functional diversity of the VGSCs is enhanced by highly dynamic regulation and plasticity of VGSC subunit expression and coupling. Several mechanisms are involved in VGSC regulation. These could be divided into three categories: (1) transcriptional, (2) post-transcriptional, and (3) post-translational.

1.5.1.1 Transcriptional regulation Transcriptional regulation of VGSCs is a developing area of research. Several factors such as transcription factors, growth factors and steroid hormones have been associated with VGSC gene expression (Borner et al., 2006; Brackenbury and Djamgoz, 2007; Chong et al., 1995; Ding et al., 2008; Diss et al., 2007). The most well known transcripton factor regulating VGSC expression is the repressor element 1-silencing transcription factor (REST) first studied for Nav1.2 (Chong et al., 1995). Although REST was proposed to act as a repressor via recruitment of histone deacetylases (HDACs), its repressing action on Nav1.2 was reported to be independent of any other co-factors (Belyaev et al., 2004). cAMP analogues were

49 reported to reverse the suppression of Nav1.2 by REST (Nadeau and Lester, 2002). Additonally, VGSC[33 subunit was transcriptionally regulated by REST in rat pheochromocytoma (PC12) cells (Pance et al., 2006). A potential REST binding site was reported near the Nav1.6 promoter suggesting that its transcription could also be altered by REST (Drews et al., 2005). Another transcription factor involved in VGSC regulation is NFiB. For example, angiotensin II treatment of rat embryonic cardiomyocyte cell line 1-19c2 activated NFKB pathway and suppressed VGSC (Nav1.5) mRNA expression (Shang et al., 2008). The same study also reported reduced VGSC (Nav1.5) mRNA expression by oxidative stress (induced by 11202) via PKC activation (Shang et al., 2008). NFiB was also reported to regulate Ca24-activated K+ channels in PC12 cells (Kye et al., 2007). In addition to transcription factors, trophic factors can also lead to genomic changes in VGSCs. For example, nerve growth factor (NGF) induced Nav1.7 mRNA expression in PC12 (Toledo-Aral et al., 1995) and prostate cancer (PCa) cells (Brackenbury and Djamgoz, 2007). Neurotrphin-3 (NT-3) decreased Nav1.8 and 1.9 mRNA expression in dorsal root ganglion (DRG) neurons (Wilson-Gerwing et al., 2008), and Brn-3 increased Nav1.7 mRNA expression in PCa cells (Diss et al., 2006). Details of VGSC regulation by steroid hormones are given in section 1.6.

1.5.1.2 Post-transcriptional regulation Post-transcriptional ion channel modifications include alternative splicing, miRNAs and RNA editing (which create variants of each ion channel subtype) (Altier et al., 2007; Heinzen et al., 2007; Jepson and Reenan, 2008). Several ion channel splice variants were reported in diseases. For example, a `neonatal' splice variant of Nav1.5 is highly expressed in human BCa (Brackenbury et al., 2007; Chioni et al., 2005; Diss et al., 2004; Fraser et al., 2005), and splice variants of AMPA glutamate receptors and Cl- channels were reported in diseases like myotonia, epilepsy and cancer (Heinzen et al., 2007; Lueck et al., 2007; Sprengel, 2006; Tate et al., 2005). Furthermore, in pain pathways, an alternative splice variant of N-type voltage- gated Ca2+ channel (Cav2.2) was found (Altier et al., 2007; Raingo et al., 2007). So far, five major alternative splice sites have been reported for VGSCs. These are: (1) D1 :S3 neonatal and adult isoforms; (2) D3:S3 isoforms; (3) D4:S3 isoforms; (4) interdomain (ID) 1-2 isoforms; and (5) ID 2-3 isoforms; these enable inclusion, exclusion

50 or substitution of amino acids in key modulatory regions (Diss et al., 2004). Splicing in Dl :S3 was reported for Nav1.2 and Nav1.3 (Gustafson et al., 1993; Sarao et al., 1991). ID 2-3 splicing was reported in Nav1.8 in DRG (Kerr et al., 2004). Additionally, splicing in D2/D3 intracellular linker of Nav1.5 has also been reported (Camacho et al., 2006). An important alternative splicing in D1 :S3, resulting in 'neonatal' and 'adult' splice variants, was reported for Nav1.5 (Chioni et al., 2005). This was shown to result in electrophysiological differences with the neonatal splice variant exhibiting slower channel kinetics and prolonged resultant current (Onkal et al., 2008). Importantly, this neonatal splice variant (nNav1.5) was shown earlier to be upregulated in metastatic BCa and also induce cellular invasion (Brackenbury et al., 2007). This suggested that investigations of cellular distributions of alternatively spliced VGSCs and other ion channels could provide important information about related diseases.

1.5.1.3 Post-translational regulation Ion channel proteins are under the control by several post-translational regulatory mechanisms. These include (1) phosphorylation (by PKA, PKC and MAPK), (2) glycosylation, (3) palmitylation and sulfation, (4) ubiquitination/degradation (by Nedd4- 2), (5) protein trafficking and (6) interactions with other proteins such as the (3-subunits, ankyrin and calmodulin (Brackenbury and Djamgoz, 2006; Cantrell et al., 1997; Cusdin et al., 2008; Herfst et al., 2004; Marban et al., 1998; Schmidt and Catterall, 1987; Vijayaragavan et al., 2004b; Wittmack et al., 2005; Zhou et al., 2007). Phosphorylation mechanisms of VGSCs include cAMP and PKA dependent pathways (Costa and Catterall, 1984; Few et al., 2007; Murphy et al., 1993; Vijayaragavan et al., 2004b). Phosphorylation by PKA can occur at five consensus sites of on the cytoplasmic linker between D1 and D2 of neuronal VGSCs (i.e. Nav1.1, 1.2, 1.3 and 1.7; Figure 1.5; Marban et al., 1998). In Navl.5, two distinct PKA phosphorylation sites were found in the D1 -D2 linker (Murphy et al., 1996). A phosphorylation site was found in D1 -D2 linker of Nav1.2 in hippocampal pyramidal cells where PKA binding occurred via A kinase-anchoring protein (AKAP15) and this reversed the inhibiting effect of dopamine on the peak Na current (Few et al., 2007). AKAP15 also regulated epithelial Na{ channel (ENaC) activity in Xenopus oocytes, via a PKA-independent and PKC- dependent mechanism (Bengrine et al., 2007).

51 Direct evidence for VGSC trafficking to plasma membrane by PKA modulation was provided by Hallaq et al. (2006). Nav1.5 expression in living cells was observed mostly in perinuclear areas before stimulation, and this pattern was replaced by increased PM staining after PKA activation (Hallaq et al., 2006). Similar trafficking via PKA activation was reported for Nav1.5 and Nav1.7 (Brackenbury and Djamgoz, 2006; Chioni, 2007; O'Connell et al., 2005; Zhou et al., 2002a). Phosphorylation of an inwardly rectifying K+ channels (Kir1.1) by PKA also regulated endoplasmic reticulum retention signals, leading to increased trafficking to PM (O'Connell et al., 2005). Interactive effects of PKA and PKC on VGSCs have been suggested (Chahine et al., 2005). A PKC-dependent mechanism increased Nav1.8 currents in rat nodose ganglion neurons (Matsumoto et al., 2007). Furthermore, PKC binding sites were found on D1 -D2 and D3-D4 linker of Nav1.2 (Cantrell et al., 2002). Unlike PKA, activation of PKC reduced PM expression of VGSCs via increased protein internalization (Kobayashi et al., 2002). Alternatively, PKC activation via (Ca2+)i increased VGSC degradation (Kobayashi et al., 2002). Unlike PKA, PKC increased internalization of Nav1.7 (Walla et al., 2004). Phosphorylation by PKA and PKC also enhanced slow inactivation of VGSCs which could suggest more frequent channel activation (Carr et al., 2003; Chen and Gumbiner, 2006; Chen et al., 2006). Such an effect was previously reported in periodic paralysis of skeletal muscle and cardiac arrhythmias (Ruff and Cannon, 2000; Wang et al., 2000a). VGSCs are also modulated by interactions with other proteins. Especially during trafficking from endoplasmic reticulum to PM, VGSCs can interact with modulatory proteins. For example, binding of annexin II light chain (pl 1) to Nav1.8 facilitated its export to PM, leading to reduced pain thresholds (Baker and Wood, 2001; Okuse et al., 2002; Poon et al., 2004). Contactin, a glycosyl-phosphatidylinositol-anchored CAM, is another protein involved in trafficking of VGSCs to PM. Contactin facilitated Nav1.3 and Nav1.9 expression in PM via binding to VGSCa and (31 subunits (Liu et al., 2001; Shah et al., 2004). Ankyrins (G and B), adapter proteins that link membrane proteins to cytoskeleton, were reported to bind to the D3-D4 loop of Nav1.2 and regulate channel inactivation (Abriel and Kass, 2005; Bouzidi et al., 2002). Ankyrin-G was involved in interaction between VGSCr31 and a variety of CAMs, including NrCAM and neurofascin (Malhotra et al., 2000; Zhang et al., 1998). Ankyrin-G binding was associated with

52 trafficking and PM anchorage of Nav1.2 and Nav1.5 (Garrido et al., 2003; Mohler et al., 2004).

1.6 Steroid hormone regulation of ion channels

There are multiple suggested pathways whereby steroid hormones including neurosteroids and estrogen can regulate ion channels (Chew and Gallo, 1998; Tasker, 2000). Steroid hormones can regulate ion channels by binding to the ion channel subtypes or via GPCRs or PICA-dependent pathways where acute effects can be seen (Lu et al., 1999; Valverde et al., 1999). Mammalian steroid hormones can be classified into five groups by their receptor types: mineralocorticoids, glucocorticoids, estrogens, progesterone and androgens (Joels, 1997). They were traditionally reported to be transcriptional regulators where they act on nuclear receptors: mineralocorticoid receptor (MR), glucocorticoid receptor (GR), ER, PRs and androgen receptor (AR) to exert their function on specific DNA sequences (Beato and Klug, 2000; Tsai and O'Malley, 1994). However, research on steroid hormones and their signalling mechanisms in the last two decades have revealed a new mode of action of steroid hormones where the response is too rapid to involve any transcriptional change (Revankar et al., 2005; Simoncini et al., 2000; Yager and Davidson, 2006; Zivadinovic et al., 2005). The first insight into the role of steroid hormones in regulation of ion channels came from the studies on cardiovascular and nervous system diseases (Stevenson, 1998; Wellman et al., 1996). Currently, steroid hormone regulation of ion channels via both genomic and non-genomic pathways could occur widely, as in brain, heart, skeletal muscle, kidney and cancer (Chen et al., 1999; Coiret et al., 2005; Nascimento et al., 2003; Ranki et al., 2002; Rich et al., 1999; Tsang et al., 2004a; Zakon, 1998).

1.6.1 Regulation of VGSCs A study on the Nav1.5 promoter sequence revealed three putative ER binding half-sites (ERE1/2) and a putative Spl binding site (Yang et al., 2004; Appendix I). This would indicate strongly that genomic regulation of Nav1.5 gene by estrogen could occur. Indeed, several VGSC subtypes were regulated by steroid hormones. For example, in MCF-7 BCa cells, VGSCI31 was found among ER up-regulated genes (Dressman et al., 2001; Lin et al., 2004). Interestingly, mRNA expression of a new Na

53 channel family member cloned from rat astroglia, the Na-G channel, was enhanced by dexamethasone treatment for over 6 h (Gautron et al., 2001). Further studies on dexamethasone also found that it inhibited Nav1.7 mRNA expression in human bronchial smooth muscle cells (Nakajima et al., 2008) and ENaC mRNA expression in alveolar epithelial cells (Dagenais et al., 2006). Additionally, genomic regulation of VGSCs could occur by androgen where it can modulate Nav1.7 and VGSCIS 1 mRNA expressions in PCa cells in a time- and dose-dependent manner (Diss et al., 2007). In addition to genomic steroid hormone effects on VGSCs, non-genomic modifications were also reported. For example, Boixel et al. (2006) found in mouse cardiomyocytes that aldosterone treatment even for over 24 h increased VGSC activity and lack of any change in mRNA and protein expression indicated a non-genomic mechanism. Earlier, Barann et al. (1999) showed rapid inhibition of VGSCs in mouse neuroblastoma cells by a wide range of steroid hormones including estrogen, progesterone and testosterone. The partial estrogen antagonist tamoxifen and dexamethasone were also found to rapidly inhibit VGSCs in rat glia, C1300 neuroblastoma cells and rat pituitary cells (Avila et al., 2003; Hardy et al., 1998; Smitherman and Sontheimer, 2001). Importantly, there is evidence for a G-protein coupled signalling involving PKA as a possible mechanism through which steroid hormones could regulate VGSCs (Lu et al., 1999).

1.7 Ion channels and disease

Ion channels are expressed in excitable cells and also in many non-excitable cells such as glia, lymphocytes, endothelial cells, osteoblasts, and fibroblasts (Bakhramov et al., 1995; Black and Waxman, 1996; Bordey and Sontheimer, 2000; Cahalan et al., 1987; Chiu,1984, 1987; Gordienko and Tsukahara, 1994). The roles of ion channels in these cells include regulation of cell volume, intracellular pH, Ca2+ and enzyme activity, proliferation, neurotransmitter and hormone secretion, and salt and water absorption (Hayashi et al., 2007; Jarvis and Zamponi, 2001; Lang et al., 2006; Okayama et al., 2006; Ouadid-Ahidouch and Ahidouch, 2008; Zhanping et al., 2007). Ion channel defects (genetic or epigenetic) can also cause disease. Such diseases referred to as channelopathies' include , cardiac arrhythmia, epilepsy, long QT syndrome, polycystic kidney disorder, myotonia, Alzheimer's disease and related degenerations, osteoporosis, migraine, diabetes mellitus, and cancer (Aizawa et al., 2007;

54 Auerbach and Liedtke, 2007; Brackenbury and Djamgoz, 2006; Cooper, 2007; Fraser et al., 2005; Heinzen et al., 2007; Kottgen, 2007; Ohmori et al., 2006; Weiergraber et al., 2005). Ion channels are also expressed in a variety of cancer cells from prostate, breast, lung, brain, mesothelioma, ovaries and cervix (Diaz et al., 2007; Fraser et al., 2005; Fulgenzi et al., 2006; Grimes et al., 1995; Onganer and Djamgoz, 2005; Zhanping et al., 2007).

1.7.1 Role of VGSCs in metastatic cell behaviours Involvement of VGSCs in metastatic disease can be summarized as follows: 1. Electrophysiological recordings showed that outward currents from human breast epithelial and BCa cells were increased as the cells became metastatic (Fraser et al., 2005; Figure 1.6). Furthermore, strongly metastatic MDA-MB-231 BCa cells express functional VGSCs, whereas non/weakly metastatic MCF-7 BCa cells only have intracellular non-functional VGSC protein (Fraser et al., 2005; Roger et al., 2003). 2. VGSC activity would potentiate a range of cellular behaviours integral to the metastatic cascade. These include invasion, motility, endocytic/secretory membrane activity, adhesion and gene expression (Fraser et al., 2003; Grimes et al., 1995; Krasowska et al., 2004; Laniado et al., 1997; Mycielska et al., 2003; Roger et al., 2003). Independently, Bennett et al. (2004) demonstrated that the invasiveness of human PCa cells could be increased significantly by VGSC over-expression and stated that VGSC expression "was necessary and sufficient" for the cellular invasiveness. 3. The dominant VGSC isoform in human BCa cell lines was found to be Nav1.5 in its newly defined 'neonatal' splice form (nNav1.5; Fraser et al., 2005). This was first identified by Diss (2001) through semi-quantitative RT-PCR and cDNA sequencing. The sequence of nNav1.5 has 7 amino acids different from the corresponding adult form which made it possible to raise a polyclonal antibody (NESOpAb) recognizing selectively nNav1.5 for further studies on its involvement in BCa (Brackenbury et al., 2007; Chioni et al., 2005). The expression level of this gene was about 1000 times higher in the strongly (MDA-MB-231) versus the non-metastatic (MCF-7) human BCa cells (Fraser et al., 2005). Use of NESOpAb or knock-down of nNav1.5 (with siRNA) in BCa cells revealed its role in cellular migration and invasion (Chioni, 2007; Brackenbury et al., 2007).

55

nA 2n4

50 ms 50 ms

C. D.

I nA 50 ms

Figure 1.6: Electrophysiological recordings showing voltage-gated membrane currents from human breast epithelial and human BCa cell lines. With increasing metastatic potential: (A) MCF-10A: Normal breast epithelial cells. (B) MCF-7: Non-metastatic BCa cells. (C) MDA-MB-468: Weakly-metastatic BCa cells. (D) MDA-MB-231 cells: Strongly-metastatic BCa cells. Modified from Fraser et al. (2005).

56 4. In vivo immunohistochemical and RT-PCR data showed that nNav1.5 and Nav1.7 expression correlated with lymph node metastasis in BCa and PCa, respectively (Diss et al., 2005; Fraser et al., 2005). Despite current knowledge about VGSC expression in cancer and its involvement in metastasis, the responsible mechanism(s) for its expression and function in cancer cells is not known. Several possible mechanisms could be involved in VGSC regulation. These include growth factors such as EGF, which was shown to increase VGSC current density in Mat-LyLu rat and PC-3M human PCa cells (Ding et al., 2008; Uysal-Onganer and Djamgoz, 2007). EGF treatment also induced PCa cell migration, endocytic membrane activity and invasion which were all inhibited by TTX treatment, suggesting VGSC involvement (Ding et al., 2008; Uysal-Onganer and Djamgoz, 2007). Recently, androgen treatment of LNCaP and PC-3 PCa cells also revealed Nav1.7 and VGSC[31 mRNA regulation (Diss et al., 2007).

1.8 Aims and scope of the Thesis

The overall aims of the, Thesis were (1) to evaluate the possible regulation of VGSC expression in human BCa cell lines via estrogen signalling, (2) to determine a possible non-genomic effect of estrogen; and (3) to investigate the possible outcomes on cellular adhesion. Specific pharmacological agents used to achieve these aims included 1713- estradiol (E2), BSA-conjugated-E2, G1-compound, ICI-182,780, and TTX. The main experimental techniques involved conventional and real-time PCR, Western blot, immunocytochemistry, confocal microscopy, and in vitro adhesion assays. The additional assays used for supplementary data in Chapter 5 were in vitro motility and migration. The specific aims were as follows: 1- To investigate non-genomic effects of E2 on nNav1.5 expression in MDA-MB- 231 cells and possible changes in cell adhesion. 2- To evaluate GPR30 as a candidate receptor for E2 action in MDA-MB-231 cells by using G1 compound treatments and GPR30 over expression and knock-out systems. 3- To determine possible genomic changes in nNav1.5 mRNA after E2 treatment of MDA-MB-231 cells; and the resultant effect on adhesion. 4- To examine genomic and behavioural changes in MDA-MB-231 cells expressing ERa and to determine genomic effects of E2 treatment on nNav1.5 mRNA and consequential effects on cell adhesion.

57 Chapter 2

MATERIALS AND METHODS

58 A multi-faceted approach involving a range of methodologies and materials were used in the present study, often in parallel. Essential details are described in this Chapter.

2.1 Cell culture

2.1.1 Cell lines The following cell lines were used in this project: • The strongly metastatic MDA-MB-231 BCa cells (Cailleau et al., 1978). • Weakly/non metastatic MCF-7 BCa cell line (Soule et al., 1973). • Human embryonic kidney cells (HEK-293; Graham et al., 1977). • HEK-derived EBNA cells stably transfected with 'neonatal' Nav1.5 (EBNA- nNav1.5; Chioni et al., 2005; Fraser et al., 2005). • MDA-ERa (MDA-MB-231 cells stably transfected with pCMV-ERa-neo; Jiang and Jordan, 1992). • VC5 (MDA-MB-231 cells stably transfected with empty pCMV-neo as control for MDA-ERa cells; Jiang and Jordan, 1992). • Parental MDA-MB-231 cells for pCMV-neo and pCMV-ERa-neo transfections (MDA-10A; (Jiang and Jordan, 1992).

2.1.2 Culture conditions All cell lines were grown in 100 mm Falcon tissue culture dishes (Beckton Dickinson Ltd., Plymouth, UK) and kept in 5 % CO2, 100 % humidified incubator (Heraeus) at 37 °C. Unless otherwise stated, all tissue culture reagents were purchased from Invitrogen (Paisley, Scotland). The human BCa and HEK-293 cells were maintained in Dulbecco's minimum essential medium (DMEM) (without phenol red) supplemented with 5 % foetal bovine serum (FBS) and 4 mM L-glutamine (Fraser et al., 2005; Palmer et al., 2008). The stably transfected MDA-ERa and VC5 cells were maintained in normal growth medium supplemented with 500 µg/ml of G418 (Sigma, Dorset, UK) to selectively grow the transfected cells (Levenson et al., 2003). The stably transfected EBNA-nNav1.5 cells were maintained in minimum essential medium (MEM; with Earles' salts and glutamine) supplemented with 10 % FBS, 1 % non-essential amino acids and 500 1.1,g/m1 Hygromycin B (Chioni et al., 2005).

59 The growth medium was refreshed every 2-3 days until cells reached —80 % confluence. For estrogen treatments (24 h or longer), after the cells were counted, plated in the experimental dishes/plates and stabilized for 24 h, the normal growth medium was replaced with DMEM supplemented with 5 % charcoal-stripped FBS (CS-FBS; Hyclone, Northumberland, UK) and 4 mM L-glutamine for 3 days prior to treatment to minimize the amount of steroid hormones present in the medium.

2.1.3 Passaging and trypsinizing the cells All cells except MCF-7 cells were removed from the dish by triturating when they were near-confluent and split into multiple dishes to be kept for future experiments. MCF-7 cells, being more adhesive than the other cell lines used, needed to be trypsinized before splitting. In this case, the medium was replaced with 2-3 ml of solution (x 1; Sigma) and incubated for 5 minutes or until the cells detached from the base of the dish. Then, the cells were removed from the dish by pipetting, placed into sterile tubes and 2 mis of fresh medium was added to replace/inactivate the trypsin. After centrifuging at 2000 g for 2 minutes, the supernatant containing the trypsin was removed and the cells were resuspended in fresh growth medium. The cells were mixed carefully by pipetting to obtain single cell suspension and seeded into new 100 mm dishes with 6 ml of medium to be incubated as before. During experimental set-ups, the cells were counted in a haemocytometer and the required number of cells was plated in the experimental dishes/plates with appropriate amount of normal growth medium and incubated overnight before any treatment to ensure stabilized conditions.

2.1.4 Freezing and thawing cells Frozen stocks were kept for all cell lines used. A near-confluent (— 80-90 %) dish of cells was taken at low passage number (< 10). After trypsinizing/triturating and centrifugation, cells were resuspended in freezing medium chilled at 4 °C; the latter composed of 70 % DMEM (without phenol red), 20 % FBS and 10 % sterile dimethyl sulfoxide (DMSO; Sigma). About 3 mls of medium was used for one confluent dish of cells and was then divided into 2-3 freezing vials. These were then placed in styrofoam boxes and frozen slowly at — 80 °C.

60 Whilst defrosting the frozen cells, the vials were placed at 37 °C humidified incubator quickly. The cells were then carefully pipetted into a 100 mm Falcon tissue culture dish with 6 ml of growth medium and placed back into the incubator. The medium was refreshed overnight to remove DMSO in the freezing medium. Cells were then cultured for 2 passages before being used for experiments.

2.2 Pharmacological agents and treatments

All pharmacological reagents used in this project were dissolved in the appropriate solvent and then diluted into cell culture medium (i.e. supplemented with FBS or CS- FBS). All stock solutions were sterile-filtered, aliquoted in small amounts (-50-100 Ill) and kept at -20 °C. Table 2.1 summarizes the pharmacological agents used, their solvents and stock and working concentrations.

2.2.1 17P-estradiol 1713-estradiol (E2) is the most potent form of estrogen involved in initiation and progression of BCa (e.g. Russo et al., 2006). It was reported to activate both estrogen receptors (ERa and ER13) and GPR30 in various cell types including cancer cells (Filardo et al., 2000; Haas et al., 2007). A stock concentration of 10 1.1.M E2 (Sigma, Dorset, UK) was prepared in DMSO (0.01 % v/v) and stored at — 20 °C. The working concentrations (0.1 - 100 nM) were prepared fresh daily for each by serially diluting the stock solution in fresh CS-FBS medium or mammalian physiological saline (MPS); for short-term single-cell adhesion measurements (Chapter 3). The DMSO solvent at working concentrations (e.g. 1 % for 1 nM E2) was also prepared for control experiments.

2.2.2 BSA-conjugated E2 There is evidence for both intracellular and plasma membrane (PM) expression of GPR30 (Filardo et al., 2007; Pedram et al., 2006; Revankar et al., 2005). E2 is membrane permeable whereas BSA-conjugated E2 (E2-BSA) is not because of BSA protein conjugation. E2-BSA has frequently been used to stimulate ERs (including GPR30), in PM of a large variety of cells including cancer cells (Prossnitz et al., 2008a; Revankar et al., 2005). In order to determine whether the short-term effect of E2 on MDA-MB-231 cell adhesion was via a cell-surface ER, E2-BSA was used at working concentrations of 1-100 nM. The stock of 10 µM solution was prepared in MPS and diluted again in MPS

61 Table 2.1 Pharmacological agents used in the experiments. Each of the following drugs used in this project was dissolved in the given solvent and stock solutions were kept in small aliquots at -20 °C. Working solutions were prepared fresh in the appropriate growth medium or MPS solution. DMSO control solutions were also prepared to test for any effect of the solvent. Final DMSO concentrations were 10-8 — 10-5 % v/v for E2 and GI (*); and 0.0002 - 0.002 % v/v for ICI (**). SC: Stock concentration, WC: Working concentration.

SOLVENT SUPPLIER

1711—estradiol 10 uM 0.1, 1, 10 and 100 nM DMSO* Sigma (E2)

BSA-conjugated 10µM 1, 10, and 100 nM MPS Sigma estradiol (E2-BSA)

G1 compound 10 uM 0.1, 1, 10 and 100 nM DMSO* Chemicon (G1)

ICI-182,780 50 i.tM 100 nM and 111M DMSO** Tocris (ICI)

Tetrodotoxin 3123 jaM 10 uM Water Tocris (TTX)

PICA inhibitor 1 mM 10 tiM MPS Tocris (PKI)

62 on the day of the experiments. Cells were treated with E2-BSA for 10-20 minutes and were only used for single-cell adhesion measurements.

2.2.3 G1 compound The compound G1 has been shown to be highly selective for GPR30 over other ERs in promoting estrogen activated signalling (Albanito et al., 2007). In the present study, G1 compound (Chemicon) was used to investigate whether specific activation of GPR30 would yield similar effects on MDA-MB-231 cells as E2. A 10 µM (0.01 % DMSO v/v) stock solution was prepared and the working concentrations were 0.1, 1, 10 and 100 nM in MPS for short-term treatments and in CS-FBS medium for long-term treatments.

2.2.4 ICI-182,780 ICI-182,780 is an estrogen antagonist which was reported to specifically bind to ERa and block its ligand-binding site and also increase its degradation (Robertson et al., 2003). ICI-182,780 was dissolved in DMSO (0.1 % v/v) to 50 1.1M stock concentration. It was used at working concentrations of 100 nM and 1 1AM in normal growth medium. The DMSO control solutions (0.0002 and 0.002 % v/v) in normal growth media were also prepared for control experiments.

2.2.5 Tetrodotoxin treatment Tetrodotoxin (TTX; Tocris) stock solution (3123 1.IM) was dissolved in sterile-distilled H2O (Sigma; Table 2.1). The working concentration (10 pM) was prepared in growth medium (either supplemented with FBS or CS-FBS depending on cell and treatment type). TTX treatments were initiated after the cells were settled 24 h after plating). In the case of co-treatments, TTX was prepared in the same solution as the other drug.

2.2.6 PKA inhibitor treatment In order to investigate possible involvement of PKA signalling, protein kinase A inhibitor fragment (6-22) amide (PM; Tocris Bioscience, Bristol, UK) was used in treatments. A 1 mM stock solution was prepared in MPS and the working concentration was 10 µM.

63 2.3 In vitro functional assays

2.3.1 Single-cell adhesion measurement apparatus (SCAMA) SCAMA was described previously by Palmer et al. (2008) and a schematic representation of the apparatus is shown in Figure 2.1. In summary, prior to the experiment, 2.5 x 104 cells were plated in 35 mm dishes in normal growth medium, so as to obtain single cells in culture. Long-term treatments started 24 h after plating and the media were refreshed every 24 h for the duration of experiment. Short-term treatments started 48 h after plating on the day of the measurements. Glass micropipettes (tip diameters, 15-20 um) were drawn on a pipette puller (Narishige pp-830). Individual cells were observed under a microscope at x 100 magnification and the tip of the pipette was positioned at the cell periphery using a micromanipulator. The adhesion of single cells was measured by using a vacuum pump connected to a manometer the output of which was displayed on a PC, via the program 'HandHeld'. Gradually closing the T-piece resulted in build-up of increasing negative pressure, recorded on the computer. The values of detachment negative pressure (DNP), measured in kilo Pascal (kPa) were then transferred into a Microsoft Excel file. About 80-100 cells were measured for 10 minutes in each dish; and one dish per treatment was used for each experimental set up.

2.3.2 Cell motility Cell motility was measured using a wound-healing ("scratch") assay (Fraser et al., 2003). Fifteen vertical and three horizontal lines were drawn on the bottom sides of each of 35 mm dishes giving rise to 45 points where horizontal and vertical lines joined for wound measurements. The cells were plated at a density of 5 x 105 cells in each of three dishes per experimental condition. 24 h after seeding three wounds were induced in each dish along each of the three horizontal lines with a sterile p200 pipette tip and the detached/floating cells were removed by washing 3-4 times with medium. After washes, 1 ml of the treatment or control medium was added and the individual wound widths were measured at each of the 45 points by using an eye-piece graticule on the microscope at a magnification of x 10. The dishes were incubated and the measurements were repeated after 24 h and 48 h, with medium refreshment every 24 h. For treatments longer than 48 h, the wounds were induced after pre-treatment.

64

Waste disposal Vacuum pump

Manometer

Computer connection

Micromanipulator

Cells in 35mm dish

T-piecem im

Figure 2.1: Schematic representation of the Single Cell Adhesion Measuring Apparatus (SCAMA) Using a micromanipulator, a glass micropipette was positioned at the periphery of a single cell from a 35 mm cell culture dish which was placed onto the moveable stage of an inverted microscope. The cells were observed with a x 100 objective. When the T- piece was blocked, negative pressure was generated by a vacuum pump connected to the micropipette via a reservoir. The pressure was measured using a digital manometer connected to a computer via a 82232 cable. When the cell was detached from the culture dish, the T-piece was unblocked and the pressure was released giving rise to a peak on the monitor.

65 The motility index (MoI) was calculated as follows: MoI = 1 — (Wt where Wt is the wound width at time of the test reading and Wo is the initial wound width. Thus, a MoI value of 1 would mean full closure, whilst a MoI value of 0 would indicate no cell movement.

2.3.3 Cell migration Cell migration through porous membrane was measured by using 12-well Transwell polycarbone membrane filters with 12 Lim pores (Corning Costar) as described previously (Fraser et al., 2005; Grimes et al., 1995). Briefly, cells were plated in 6-well falcon plates at a density of 5 x 105 cells in each well together with 1 ml of medium. After overnight incubation, cells were treated with either treatment reagent(s) or the control media; the solutions were refreshed every 24 h (for a total of 72h for ICI-182,780 treatment). A 12- well Transwell plate was prepared by hydrating the wells overnight with growth medium (two wells for each condition). On the day of the experiment, 2 x 105 cells were plated onto the membranes in each well. 1 FBS medium (500 [t1) was added to the inserts and 10 % FBS medium (1 ml) was added to the lower chambers to create a chemotactic gradient. The plate was incubated at 37 °C for 7 h. At the end of this time, the media were removed from both upper and lower compartments carefully without removing any cells. The cells in the upper chamber were then removed by swabbing. Cells in the lower chamber (migrated cells) were analyzed using 3-(4,5-Dimethy1-2-thiazoly1)-2,5-dipheny1- 2H-tetrazolium bromide (MTT) assay described in section 2.3.4. The number of migrated cells was calculated from the MTT standard curve (Figure 2.2).

2.3.4 MTT assay The MTT assay was performed as described previously (Chioni, 2007). All chemicals were from Sigma unless otherwise stated. Briefly, 0.25 ml MTT (5 mg/ml in growth medium) and 1 ml growth medium were added to each well and the plate was incubated for 3 h at 37 °C. The medium was then removed carefully and 1 ml DMSO and 125 ill glycine buffer (0.1 M glycine and 0.1 M NaCl; pH adjusted to 10.5) were added to each well. After 10 minutes, absorbance was measured at 570 nm and was converted to cell numbers by using the standard curve (Figure 2.2). The standard curve was repeated every

66 2.5

2.0

1.5

1.0

0.5

0.0 0 5 10 15 20 25 30 Cell number (x 104)

Figure 2.2: A typical standard curve for MDA-ERa cell number in relation to absorbance at 570 nm as determined by MTT assay. The standard curve was set up with different number of MDA-ERa cells upto 30 x 104 cells. Solid line is linear regression and the equation of the straight line is "y = 0.0614x + 0.0601" which was used to calculate cell numbers for migration assays. Data are presented as mean ± SEM (n=3).

67 time a new MTT solution was prepared.

2.3.5 Data analysis

Data from all in vitro functional assays were presented as means ± standard errors of mean (SEMs). The statistical significance was calculated by using Student's t-test or Mann-Whitney rank sum test where appropriate, by using SigmaStat 3.5 program (Systat software, Germany). The significance level was set at P < 0.05.

2.4 Molecular biology

2.4.1 Total RNA extraction and purification Total RNA was extracted from cell cultures by using two methods: (1) RNeasy mini kit (Qiagen) for Chapters 3 and 4; and (2) the TRIzol reagent (Invitrogen) for Chapter 5. In (1), performed according to the manufacturer's instructions, cells were washed with PBS and lysed with 1 ml of lysis buffer supplemented with 7 µ1 of 3-Mercaptoethanol. The viscous cell lysate was then collected into a sterile Eppendorf tube and homogenized by passing it through a 21 gauge syringe several times. Up to 0.7 ml of the homogenate was transferred to a pre-filter spin cap and centrifuged at 13791 g for 5 minutes. An equal volume of 70 % ethanol was added to the filtrate and the mixture was transferred to an RNA Binding Spin Cup and centrifuged as before. DNase treatment followed, where 50 µI DNase digestion buffer and 5 µ1 reconstituted RNase-free DNase I were added to each sample to remove any DNA contamination. The samples were then washed repeatedly with x 1 low salt wash bufferand x 1 high salt wash buffer. To elute RNA from the column, 20-30 Id elution buffer (EB) was added to each sample and centrifuged at 13791 g for 1 minute to collect purified RNA in a new sterile Eppendorf tube, and this step was repeated once. In (2) RNA extraction was performed according to TRIzol RNA extraction protocol provided by Whitehead Institute Center for Microarray Technology (WICMT, Cambridge, USA). Briefly, near-confluent (-80-90 %) cells were trypsinized and transferred into sterile Eppendorf tubes for centrifugation at 2000 g for 2 minutes. The cell pellet was washed with 1 ml PBS and centrifuged again. 1 ml TRIzol was added to each cell pellet and homogenized by passing through a 21 gauge syringe several times; and incubated at room temperature for 5 minutes. 0.4 ml of chloroform was then added and the tubes were vortexed until a milky solution formed. The mixture was then

68 centrifuged at 11312 g for 15 minutes at 4 °C. The clear supernatant solution was transferred to a new sterile Eppendorf tube and an equal volume of isopropanol was added to precipitate the RNA. Following 15-minute incubation at room temperature, the tube was centrifuged again as before. The supernatant was discarded and the pellet was washed in 70 % ethanol and centrifuged as before for the last time. The pellet was then air-dried and dissolved in RNase-free water and stored at -20 °C until needed.

2.4.2 Determination of RNA quality The quality of the extracted RNA was analyzed by gel electrophoresis. 1 agarose gel was prepared in x 1 TBE. To this, 3 µ1 of SYBR safe gel stain (Invitrogen) was added. 5 pg of each RNA sample was mixed with 1 µ1 loading buffer (Promega, Madison, USA) and loaded in a well. The gel was run at 70-90 V for about 1 h and was visualized under ultraviolet (UV) light. Figure 2.3 shows a typical example of an RNA gel where two bands corresponding to 28S and 18S rRNA can be seen. Good quality of RNA gave a higher intensity of 28S than 18S rRNA band.

2.4.3 Quantification of total RNA Spectrophotometer readings of RNA samples were taken at wavelengths of 260 nm and 280 nm, using Nanodrop (Thermo Scientific). RNA concentration was measured at 260 nm in ng/µ1 and a good quality RNA extraction gave a 260:280 ratio close to 2.0 (Sambrook et al., 1989)

2.4.4 Synthesis of single-stranded complementary DNA (cDNA) A total of 1 µg RNA per sample was used for single-stranded complementary DNA (cDNA) synthesis, using Superscript II reverse transcriptase kit (Invitrogen). Briefly, 2.5 R6/pd(N)6 (250 ng; Amersham) was added to 1 p,g RNA and then RNase/DNAse-free water (sdw) was added up to 11 µ1. This mix was placed at 70 °C for 10 minutes, briefly chilled on ice and span for 1 minute. To this, 8 µ1 of a reaction mix was added, which was composed of 2 IA DTT (0.1 M), 4 id Superscript II first strand buffer (x 5), 1µl dNTP mix (10 mM; GE Healthcare Life Sciences) and 1 µ.1 porcine RNA guard (24.5 u; GE Healthcare Life Sciences). After a quick vortex, the samples were incubated at room temperature for 2 minutes, after which 1 pl of Superscript II reverse transcriptase enzyme (or 1µl sdw for control samples) was added and incubated at room temperature for 10

69

A B

rRNA 28S

rRNA 18S

Figure 2.3: RNA quality determination by agarose gel electrophoresis. High quality RNA was determined by a greater intensity of the 28S rRNA band versus the 18S rRNA band when visualized under UV. 5 ug total RNA loaded from MDA-MB- 231 (A) and MCF-7 (B) cells.

70 minutes. The samples were then incubated at 42 °C for 1.5 h and the reaction was stopped by incubating at 70 °C for 15 minutes. Each cDNA synthesis was performed in a final volume of 20 iil and diluted to 100 µ1 with sdw prior to storage at -20 °C.

2.4.5 Polymerase chain reaction (PCR) Polymerase chain reactions (PCRs) were set up very carefully to avoid any contamination to reactions. For testing GPR30 and ERa mRNA expression, normal PCRs were performed using the MWG Biotech Primus PCR machine (MWG) and HotStar Taq Plus kit (Invitrogen, Paisley, UK) according to manufacturer's instructions with specific primer pairs (Table 2.2). For GPR30, the PCR steps included initial heat activation at 95 °C for 5 minutes followed by 35 cycles of 94 °C for 30 seconds, 59 °C for 30 seconds, and 72 °C for 2 minutes, and finally extension at 72 °C for 10 minutes (Thomas et al., 2005). For ERa, the PCR steps included initial 95 °C for 5 minutes followed by 35 cycles of 94 °C for 15 seconds, 58 °C for 15 seconds, and 72 °C for 30 seconds, and final extension at 72 °C for 3 minutes (O'Neill et al., 2004). The mRNA was visualized by running products on agarose gel electrophoresis. For quantitative measurements, real-time reverse-transcriptase (RT) PCRs were performed using the DNA Engine Opticon 2 system (MJ Research, Walthanm, MA, USA) as described previously (Brackenbury et al., 2006). Briefly, SYBR 1 Green technology was utilized to accurately determine target gene expression levels. Each PCR reaction was performed in 20 µI final volume containing 5 µI cDNA (from section 2.4.5), 0.5 µM each of sense and antisense primers and 1 x QuantiTect SYBR Green PCR mix (Qiagen). Amplification was performed via an initial denaturation at 95 °C for 15 minutes to activate the HotStar Taq, with subsequent three-step cycling of 95 °C for 30 seconds, annealing temperature depending on the primers used for 30 seconds (Table 2.2) and 72 °C for 30 seconds. Fluorescence intensity from SYBR green incorporated to double- stranded DNA was measured after each cycle (Figure 2.4A). A final melt curve was also carried out from 65 °C to 95 °C with 0.3 °C steps in order to verify product composition. A pure PCR product was characterised by one sharp drop in fluorescence over a small temperature range (Figure 2.4B). Each reaction was performed as a duplicate simultaneously for each sample cDNA and amplification of 0-actin was measured in each sample as the normalizing/house-keeping gene. A standard calibration curve for each

71 Table 2.2: PCR primer sequences and related details. The forward and reverse primer sequences are given. These are used in both normal and real-time PCR. Primers with different annealing temperatures were run separately. TA: annealing temperature; LD: Lab designed.

TARGET SEQUENCE TA °C REFERENCES GE NE,

ft-actin 5'-ATGGATGATGATATCGCCGC-3' 58 Onkal et al. 5'-ATCTTCTCGCGGTTGGCCTT-3' (2008)

ERa 5'-AGACATGAGAGCTGCCAACC-3' 58 O'Neill et al. 5'-GCCAGGCACATTCTAGAAGG-3' (2004)

GPR30 5'-GCAGCGICTTCTTCCTCACC-3' 59 Thomas et al. 5'-ACAGCCTGAGCTTGTCCCTG-3' (2005)

Nav1.7 5'-TATGACCATGAATAACCCGC-3' 59 Diss et al. 5'-TCAGGT'TTCCCATGAACAGC-3' (2007)

nNav1.5 5'—CATCCTCACCAACTGCGTGT-3' 58 LD 5'-CCTAGTTTTATATTTTCTGATACA-3'

pS2 5'-TTCTATCCTAATACCATCGAC-3' 58 LD 5'-TGAGTAGTCAAAGTCAGAGC-3'

VGSCfI1 5'- AGAAGGGCACTGAGGAGTTT-3' 60 Diss et al. 5'- GCAGCGATCTTCTTGTAGCA-3' (2007)

VGSCI32 5'-GAGATGTTCCTCCAGTTCCG-3' 62 Onkal et al. 5'-TGACCACCATCAGCACCAAG-3' (2008)

VGSCI33 5'-CTGGCTTCTCTCGTGCTTAT-3' 60 Onkal et al. 5'-TCAAACTCCCGGGACACATT-3' (2008)

VGSCf4 5'-TAACCCTGTCGCTGGAGGTG-3' 64 Onkal et al. 5'-TGAGGATGAGGAGCCCGATG-3' (2008)

72 A.

. 4 4- MDA-MB-231

4- MCF-7 0.2

.

Cycle.

MDA-MB-231

MCF-7 Fluoiescence

65 70 7s ,S 0 85 90 T. rl up el .itIfl

Figure 2.4: Typical real-time PCR amplification and melting curves. (A) Amplification curves for nNav1.5. Fluorescence intensity from SYBR green incorporation to double stranded DNA measured after each PCR cycle using DNA Engine Opticon 2 System (MJ Research). Dashed line illustrates the threshold determined by Opticon Monitor 2 Software. (B) The product verified by the sharp drop in the final melt curve generated by heating from 65 °C to 95 °C in 0.3 °C steps. Red line: sample from MDA-MB-231 cells; and green line: sample from MCF-7 cells.

73 14

12- 0 10- 0 9 8-

6 - co 4- C) 4 2-

0 0.001 0.01 0.1 1

cDNA dilutions

Figure 2.5: An example of gene calibration curve for real-time PCR. cDNA synthesized from 1 p.g of RNA extracted from MDA-MB-231 cells was serially diluted into five concentrations (1, 0.25, 0.0625, 0.015, 0.004). Real-time PCR was performed with specific primers for nNav1.5. ACT was calculated for each cDNA dilution: CT (nNav1.5) — CT ((3-actin). Data are presented as mean ± SEM and were fit using semi-logarithmic regression (n=3).

74 target gene using five serial dilutions of a cDNA template was also performed (Figure 2.5). No template controls (NTC), with 5 µI sdw instead of cDNA, were performed as a cross-contamination control.

2.4.5.1 Analyzing the quality of PCR products In addition to the melt curves, the qualities and sizes of PCR products were analyzed with 1 agarose gel electrophoresis where 5 ill of each product mixed with 1 id of loading dye (Promega, Madison, USA) was loaded in a lane. The gel was prepared and run as before (section 2.4.2), with a DNA molecular weight marker (Fermentas) loaded next to the samples to confirm the product sizes.

2.4.5.2 Data analysis The threshold amplification cycle (Ct) for each reaction was determined using the Opticon software (2.02). The 2-AACT method (Livak and Schmittgen, 2001) was used to analyse the relative gene expression of each sample by using the following equation:

Y = 2 —[mean ACt (test) — mean ACt (control)] where ACt is the difference in the Ct values for target gene and sample-matched control gene (13-actin). The values of Y (relative expression levels of target gene) were presented as mean folds ± SEMs. Differences in expression between different samples (n > 3 for all experiments) were analysed statistically with Student's t-test using SigmaStat software (version 3.5).

2.5. Protein-level studies

2.5.1 Whole-cell protein extraction Total protein was extracted from the cell lines according to manufacturer's guidelines (Upstate Biotechnology) and as previously described (Brackenbury et al., 2007). All chemicals were from Sigma-Aldrich (Dorset, UK) unless otherwise stated. Briefly, 80 % confluent cells were washed twice with cold PBS, without calcium and magnesium (Invitrogen). Cold RIPA lysis buffer (x 1; Upstate) supplemented with phosphatase and protease inhibitors (200 mM Phenol-methyl-sulfonyl-fluoride (PMSF), , 1µg/m1 Leupeptin, 1 M NaF, 1µ1/m1 Pepstatin) was added onto the dishes. The cells were removed from the plates with rubber scrapers and transferred into sterile Eppendorf tubes.

75 Following homogenization with a 26 gauge syringe several times, the tubes were left on a rocker in an ice bucket for about 15 minutes. Then, the cell lysates were centrifuged at 13791 g at 4 °C for 15 minutes. The supernatant, containing the total protein extract, was transferred into a new Eppendorf tube and kept on ice. Immediately, the protein concentration was determined as described in section 2.5.2. Following protein concentration determination, the samples were mixed with an equal amount of Laemmli sample buffer and boiled at 95 °C for 5 minutes before temporary storage at -20 °C.

2.5.2 Protein concentration determination Total protein extract from the cells were quantified by using the Bio-Rad Protein Assay (Bio-Rad). Diluted protein extracts (x 10 in sdw) were mixed with 5 ml diluted reagent (1 ml concentrated reagent + 4 ml sdw) and absorbances were measured on a spectrophotometer (CECIL, CE 1020) at 595 nm. The blank consisted of 10 µl lysis buffer in 90 µI sdw added to the dye. The absorbance readings were then used to calculate the protein concentration from the standard curve. The standard curve was generated by using known concentrations of Bovine serum albumin (BSA; 20-136 µg/m1) diluted in sdw and measured as above (Figure 2.6). A new standard curve was done every time the reagent was renewed.

2.5.3 Western blotting SDS-PAGE (polyacrylamide gel electrophoresis) was performed as described previously (Brackenbury et al., 2007; Chioni et al., 2005). All chemicals were from Sigma unless otherwise stated. Briefly, protein extracts were separated by 6 or 10 % SDS-PAGE gel, for nNavl.5 and GPR30, respectively. A protein molecular weight marker (Fermentas) was run simultaneously with the samples to confirm band size. The gels were run at 110- 160 V for 2-3 h in a running buffer (1 1 (x 10): 144 g glycine, 30 g Tris, 20 g SDS) and electroblotted onto nitrocellulose membrane (Protran BA83 Cellulose nitrate, Schleicher and Schuell) at 21 V for 18-20 h in a transfer buffer (1 1(x 10): 144 g glycine, 30 g Tris). After transfer, membranes were blocked at room temperature for 1 h in 5 % (w/v) non-fat dried milk powder in PBS and for 30 minutes in 2 % (w/v) BSA in PBS. Blots were then probed with the appropriate primary antibody (Table 2.3): anti-GPR30 (Santa Cruz Biotechnology), NESOpAb (Chioni et al., 2005) or anti-a-actinin (Sigma) as an internal loading control, at working concentrations of 1:1000, 4 µg/m1 and 1:2000, respectively

76

1.2 -

1-

E 0.8 - Ol 0.6 -

0 0.4 -

0.2 -

0 • 0 10 20 30 40 50 60 70 80 90 100 110

BSA [pg]

Figure 2.6: Typical BSA standard curve for Bio-Rad protein assay. Several concentrations of BSA between 20 and 136 pg/m1 were prepared to generate a standard curve. Water (sdw) was used as the blank. The standard curve was used to calculate the concentration of the protein extracts and the protein concentrations were selected from the linear part of the graph.

77 Table 2.3: Primary antibodies. SC: Stock concentration; WB: Western blot; ICC: Immunocytochemistry; MW: Molecular weight; kDa: kilo Daltons; EP: Eric Prossnitz antibody, MG: Manufacturer's guidelines, HM: Home-made.

:REFERENCES .

Anti-GPR30 Santa Cruz Goat 200 1:1000 40 MG pg/ml kDa

Anti-GPR30 Prof. E. Rabbit 1:1750 40 Revankar et al. (EP) Prossnitz kDa (2005)

Anti-nNav1.5 HM Rabbit 0.7 4 220 Chioni et al. (NESOpAb) mg/ml pg/m1 kDa (2005)

Anti-a-actinin Sigma Mouse 1:2000 100 MG kDa

Table 2.4: Secondary antibodies. SC: Stock concentration; WB: Western blot; ICC: Immunocytochemistry; HRP: Horseradish Peroxidase; FITC: Fluorescein isothiocyanate.

SPECIES

Anti-goat HRP DAKO Mouse 0.5 g/L 1:2000

Anti-mouse HRP DAKO Goat 1 g/L, 1:2000

Anti-rabbit HRP DAKO Pig 0.24 g/L 1:3000

Anti-rabbit FITC DAKO Pig 0.8 g/L 1:50

Anti-rabbit Invitrogen Goat 2 mg/ml 1:100 Alexafluor568 (Molecular probes)

78 (Table 2.3). These antibodies were prepared in 2 % BSA/PBS (w/v) and incubated at 4 °C overnight on a rocking platform. At the end of the incubations, the membranes were washed 3-4 times with PBS containing 0.2 % tween-20, and then incubated for 1 h at room temperature with the appropriate HRP-conjugated secondary antibody (anti-goat, anti-rabbit and anti-mouse (all from DAKO) for anti-GPR30, NESOpAb and anti-a- actinin, respectively; Table 2.4). After 3-4 times of washes with PBS containing 0.2 % tween-20 and a short wash in PBS, the membranes were developed by ECL chemiluminescence (Amersham, Little Chalfont, Buckinghamshire, UK). The protein bands were visualised by exposure to Super RX100NF film (Fujifilm, London, UK). Densitometric analysis was performed using the Image) software (1.39 U, National Institute of Health, USA). Signal density was normalised to anti-a-actinin antibody as a loading control, for at least three separate experiments. All antibodies used in this study were tested for linearity of their response to changing protein concentrations loaded to the gel. A range of protein concentrations (10- 120 lig) were selected depending on the antibody and densitometry analyses were performed where the band intensities were measured in arbitrary units (AU; Figure 2.7). The protein concentrations loaded to the gels for each antibody were chosen from the linear part of the standard curve (i.e. 30 1.ig for GPR30 and 60-80 1.1g for NESOpAb).

2.5.4 Immunocytochemistry and digital imaging Immunocytochemistry was performed as described previously (Brackenbury et al., 2007; Chioni et al., 2005). Briefly, 5 x 104 cells were plated on poly-L-lysine coated 13 mm sterile coverslips (BDH, Poole, England) in a 24-well plate and incubated overnight. Medium was then removed and cells were washed once with cold PBS. Fixation was performed in 4 % paraformaldehyde (Sigma) in PBS (PFA/PBS, pH 7.4) for 5 minutes. After 4 x 5-minutes washes in cold PBS, the cells were permeablized in 0.1 % Saponin (Sigma) diluted in PBS at room temperature for 4 minutes. Following 4 x 5-minute washes in cold PBS, the cells were incubated in 5 % BSA/PBS (w/v) for 1 h at room temperature to block non-specific binding sites. The primary antibody, anti-GPR30 (kindly provided by Prof. E. Prossnitz, Department of Cell Biology and Physiology, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA; Revankar et al., 2005; Table 2.3) was diluted in 5 % BSA/PBS and applied onto the cells in an incubation chamber with 100 % humidity for 1 h, on a rocking platform. 5 %

79 A. 10 30 50 70 N pg

Anti-GPR30 4- 40 kDa

30 50 70 80 100 120 pg 4- 220 kDa NESO-pAb

10 20 30 40 50 60 70 80 pg

allogo Anti-a-actinin egad 100 kDa

B. C. 35 18

4 15 28 , C 12 21 S 9 co CO O03 14 C O. 7 3 C C 0 0 10 20 30 40 50 60 70 80 0 15 30 45 60 75 90 Protein (ug) Protein (pg) D.

35 — AU) (

ity 28 - ns te 21 - d in

14 - Ab Ban

7 - SO p E N 0 0 30 60 90 120

Protein (pg)

Figure 2.7: Antibody standard curves used for densitometry analyses. Antibodies used for Western blotting were optimised for densitometry analysis. A range of protein concentrations (10-120 lig) were loaded to the SDS-PAGE gel and immunolabeled with the appropriate antibody. (A) An example of Western blot images for anti-GPR30 with protein from MCF-7 cells, and NESO-pAb and acti-a-actinin with protein from MDA-MB-231 cells. (B-D) Examples of standard curves from densitometry analyses of different amount of protein in relation to band intensity from each antibody. Data are presented as means ± SEMs (n=3) and were fit with linear regression.

80 BSA/PBS without the primary antibody was used as a negative control. The cells were washed 4 x 5 minutes with cold PBS and incubated with the appropriate secondary antibody (Table 2.4), i.e. FITC-conjugated anti-rabbit, diluted in 5 % BSA/PBS in an incubator chamber with 100 % humidity for 1 h, on a rocking platform. The cells were washed again 4 x 5 minutes with cold PBS and then washed once in distilled water before mounting onto glass microscope slides with frosted ends (VWR) in Fluorescence mounting medium (Dako). The slides were kept at 4 °C overnight before being imaged with a Zeiss fluorescence microscope under oil immersion (x 100). The staining pattern was documented by direct image-capture using a digital camera (AxioCam; 14 bits per colour channel, resolution up to 3900 x 3090 pixels; Zeiss). The immunoreactivity was documented using Axio Vision 3.0 software (Zeiss).

2.5.4.1 Confocal microscopy For a more detailed image analysis, confocal microscopy was used. For this, cells were double-stained with the plasma membrane (PM) marker concanavalin A (ConA) and anti- GPR30 (EP; Table 2.3). In this case, the cells were incubated with FITC-labeled ConA (20 µg/ 100 pl; Sigma) for 45 minutes at room temperature before the permeabilization step. They were washed 4 x 5 minutes in cold PBS and quickly fixed in 4 % PFA/PBS for 2 minutes. The rest of the procedure was performed as described in section 2.5.4 except that Alexa568-labelled anti-rabbit secondary antibody (Table 2.4) was used as the secondary antibody for anti-GPR30 (EP). Samples were imaged using Leica upright TCS SP2 confocal microscope (Leica Microsystems) under x 100 objective with a confocal laser scanner (Leica TCS-SP2 with Ar/Kr laser). FITC was excited at 488 nm and Alexa568 was excited at 561 nm. The images (512 x 512 pixels) were obtained simultaneously from two channels using a confocal pinhole of 183.91 ptm (Airy 1). The electronic zoom was factor of 1; the scan mode was XYZ and the scanning speed was 400 Hz. For further adjustments 'continuous' scan was started. After checking for possible bleed through between channels, the UV beams were set at 5 and 16 % for FITC and Alexa568, respectively. 'Gain' and 'offset' were optimized by using the quick look-up tables (Q-LUT) on the image window to adjust saturation of pixels for each fluorophore. The 'smart gain' was increased until just a few blue dots appeared (649.8 V for FITC and 745.6 V for Alexa568) and the 'smart offset' was reduced until just a few green dots appeared (0.0 % for FITC and 0.4 % for

81 Alexa568). The settings were saved and used for each experiment. The images were captured by arranging the Z-position in the centre of the cells and an average of 6 single scans were taken. Densitometric quantification of GPR30 protein expression in over-expressing and knocked-down cells was performed with the Leica confocal software LCS Lite (version 2.61). Two different digital analyses were performed: (i) "freeform line profile" and (ii) "cross-section line profile" (Brackenbury et al., 2007). The "histogram profile" function was used for (i) to obtain measurements from the whole cell where a line was drawn around the cells over the ConA staining and total plasma membrane intensity for GPR30 was calculated. About 30-60 randomly chosen cells were used from three independent experiments. The "straight-line profile" function was used for (ii) where a straight line was drawn across the cytoplasm avoiding the nucleus as described previously (Brackenbury and Djamgoz, 2006; Okuse et al., 2002). Signal intensity in plasma membrane region, set to cover 1.5 pm inward from the edge of ConA staining, was compared with cytoplasmic signal intensity within the central 30 % of the line profile. About 30-80 randomly chosen cells were analysed from three independent experiments. Data were analysed on SigmaStat software (version 3.5) by using Student's t-test and significance was set at P < 0.05.

2.6 Plasmid transfection of GPR30 into MDA-MB-231 cells

Over-expression studies were performed by using pBK-CMV phagemid vector (4.5 kb; Stratagene, Appendix II) with GPR30 (-2.65 kb) already inserted (pGPCR-BR; Carmeci et al., 1997) provided by Prof. Ronald J. Weigel (Department of Surgery, University of Iowa, Iowa City, IA, USA; Carmeci et al., 1997) and Prof. Eric J. Filardo (Tumour Cell Biology and Experimental Therapeutics Group, Department of Medicine, Division of Hematology & Oncology, Brown University, USA). Empty pBK-CMV was provided by Prof. Martin Allday (Department of Virology, Imperial College Faculty of Medicine, UK; Radkov et al., 1997). Both plasmids were received on Whatman 3 mm paper (Clifton, NJ) and were recovered by adding 25-30 pl of TE (10 mM Tris — 1 mM EDTA, pH 8) and rehydrated at room temperature for about 5 minutes. The plasmid stocks were stored at - 20 °C.

82 Top10 F' competent cells (Invitrogen) were transformed by adding 1-2 µI of pGPCR-Br to 50 pl of competent cells and incubating at 4 °C for 30 minutes and at 42 °C for 30 seconds after which 250 pi of SOC medium (Invitrogen) was added and the mixture was incubated at 37 °C for 1 h on a shaking platform. This mixture (100 pl) was then spread on a kanamycin (30 ng/ml)-supplemented Luria broth (LB) agar (1 1: 950 ml H2O, 10 g tryptone, 50 g yeast extract, 10 g NaC1, pH 7 with 1 M NaOH) plate and incubated at 37 °C overnight. The following day, a colony was picked from the plate and transferred into 200 ml of LB medium, supplemented with kanamycin, in a conical flask, and incubated overnight at 37 °C on a shaking platform. Plasmid extraction from bacteria was performed according to manufacturer's instructions (Qiagen). Briefly, the 200 ml LB medium was centrifuged at 3300 g for 10 minutes at 22 °C. The pellet was resuspended with 4 ml buffer P1 and 4 ml buffer P2 was added, mixed gently until the colour turned blue (indicating efficient cell lysis). After 5 minute incubation, 4 ml chilled buffer P3 was added and mixed by inverting the tube until a milky solution formed. The lysate was poured into a QlAfilter cartridge with the cap on and incubated at room temperature for —10 minutes until a precipitate formed on top. In the mean time, a plastic Hi-speed midi column was equilibrated with 4 ml of buffer QBT. After incubation, the lysate was filtered by inserting a syringe barrel into the cartridge, then was loaded onto the midi-column and let to flow through. The column was then washed with 20 ml buffer QC and plasmid DNA was eluted into a new 50 ml tube with 5 ml buffer QF. To this, 3.5 ml isopropanol was added. After centrifugation at 13791 g for 30 minutes at 4 °C, the supernatant was removed and the pelleted was resuspended with 2 ml of 70 % ethanol and centrifuged again as before for 5 minutes. The ethanol was removed and the pellet was air dried. The plasmid was then dissolved in 200 p.1 of EB (5 mM Tris, pH 8.5). The plasmid concentration was measured on Nanodrop with EB as blank. The inserted GPCR-Br was confirmed by gel electrophoresis (Figure 2.8) and sequencing (MWG) with T3 and T7 primers (Appendix III). MDA-MB-231 cell transfections were performed using Lipofectamine 2000 reagent (Invitrogen) according to manufacturer's instructions. Briefly, 2.5 x 105 cells were plated in 35 mm dishes and incubated overnight. Two sterile Eppendorf tubes were prepared. In tube one, 2 µg pGPCR-Br was mixed with 100 µ1 Opti-MEM transfection medium (Invitrogen) and in tube two 6 1.11 of Lipofectamine 2000 reagent was mixed with 100 µ1 Opti-MEM. After incubating at room temperature for 5 minutes, the contents of

83 -7 kb

4.5 kb

Figure 2.8: Agarose gel electrophoresis picture of the two plasmids. Size of pGPCR-Br (-7 kb) and pBK-CMV (4.5 kb) were confirmed on gel electrophoresis.

84 two tubes were mixed and incubated at room temperature for 20 minutes. The cells were washed twice with 1 ml Opti-MEM, and 200 µ1 of the mixture was added to the cells with 800 µI Opti-MEM. After incubation at 37 °C for 5 h, the solution was changed to normal growth medium (DMEM/5 % FBS) and incubated at 37 °C overnight. The next day, cells were transferred into 100 mm dishes and the selection was started using medium containing 1 mg/ml neomycin (G418 solution, Sigma). After 2-3 weeks, 24 individual colonies (GPR30-1-GPR30-24) were picked from multiple plates and re-plated into a 24- well dish. The media were replaced every other day and the colonies were continuously selected. Colonies grew into confluent cultures and were individually triturated into new 35 mm dishes. Cells were later transferred into 100 mm dishes when they were 80 % confluent. The G418 concentration was reduced to 0.5 mg/ml after the final transfer and G418-supplemented media were refreshed every 3-4 days for 1-2 weeks before experiments. GPR30 over-expression was checked and confirmed by real-time RT-PCR and Western blotting. The empty-vector control transfections were performed as above. Two colonies were selected after transfections and only one of these were used in experiments as a control for GPR30 over-expressing cells.

2.7 RNA interference

RNA interference was performed as described previously (Brackenbury et al., 2006). MDA-MB-231 cells were plated at a density of 2.5 x 105 cells in 35 mm dishes. After incubation at 37 °C for 24 h, cells were transfected with 40 nM siRNA using Oligofectamine reagent (20 µM; Invitrogen). Initially, four different siRNA sequences (FlexiTube siRNA, Qiagen) were used in transfections:

(1) siRNA-1 target sequence: 5'-CGGCCACGUCAUGUCUCUAAA-3' (2) siRNA-2 target sequence: 5'-CUGGAUGAGCUUCGACCGCUA-3' (3) siRNA-3 target sequence: 5'-ACGAAUUUGUUUCUACAGAAA-3' (4) siRNA-4 target sequence: 5'-AAAGAUGGAUUCACCAUUUAA-3'

Briefly, 4 µ1 siRNA (5 µM) and 2.5 µ1 Oligofectamine were mixed with 50 µ1 Opti-MEM in two separate tubes. These were incubated at room temperature for 5 minutes and then mixed together. After incubation for 20 minutes, the cells were washed

85 twice with 1 ml Opti-MEM, and then 100111 siRNA-Oligofectamine mix was added to the cells with 400 µ1 Opti-MEM. After incubation at 37 °C for 5 h, the medium was changed to normal growth medium and the cells were incubated at 37 °C overnight. Mock (no siRNA) and control siRNA (siControl/non-targeting siRNA pool; D-001206-13-05; Dharmacon) transfections were performed simultaneously. 72 h post-transfection, mRNA and protein were extracted to analyse GPR30 knock-down (n = 1 for siRNA-1, -2 and -3, and n = 3 for siRNA-4). siRNA-4 knocked down GPR30 mRNA expression more than the other siRNA used; thus siRNA-4 was used in further experiments. Transfection efficiency was independently assessed by using Alexa488-labelled negative control siRNA kindly provided by Dr. Dongmin Shao (Imperial College London, UK). The transfections were carried out as described above. Images of the cells were taken 24 h post-transfection using inverted Zeiss fluorescence microscope. About 20 cells out of 29 showed green fluorescence (Figure 2.9); corresponding to a transfection efficiency of —70 % (n = 1).

86 A. B.

Figure 2.9: siRNA transfection efficiency in MDA-MB-231. Image of MDA-MB-231 cells 24 h post-transfection with 40 nM A11exa488-labelled negative control siRNA taken on inverted Zeiss fluorescence microscope. (A) Phase- contrast image. (B) The green fluorescence in the transfected cells. (C) Overlay of (A) and (B). Transfection efficiency was about 70 % (-20 cells out of 29). The scale bar denotes 10 i.tm and is applicable to all panels.

87 Chapter 3 SHORT-TERM EFFECTS OF 1713-ESTRADIOL ON MDA-MB-231 CELL ADHESION: EVALUATING THE ROLE OF GPR30

88 3.1 Introduction Involvement of estrogen in breast cancer (BCa) development and progression is well known. However, complications exist in hormone-based therapies and there are conflicting reports on the modes of action of estrogen (Ali and Coombes, 2002; Thompson et al., 2008). Recently, evidence has suggested non-genomic (`cell surface') actions of estrogen, as well as, the classic transcriptional regulation by nuclear estrogen receptors (ERs) (Razandi et al., 1999, 2000a; Revankar et al., 2005; Thomas et al., 2005) There are a number of suggestions for the receptors involved in the non-genomic effects of estrogen. These include 'classical' ERs (ERa and/or ERf3; Razandi et al., 1999), non-classical ERs (e.g. ERx; Toran-Allerand et al., 2002) and orphan G-protein coupled receptor, GPR30 (Revankar et al., 2005). The associated intracellular signaling mechanisms include cAMP, PKA, PKC, PI3K, MAPK, ERK1/2, nitric oxide synthase, and tyrosine kinase receptors (e.g. EGFR, IGFR) (Filardo et al., 2008; Hewitt et al., 2005; Prossnitz et al., 2008a; Razandi et al., 1999; Razandi et al., 2000a; Revankar et al., 2005; Simoncini et al., 2000; Thomas et al., 2005; Zivadinovic and Watson, 2005). Several types of metastatic cell behaviours (MCBs) have been shown to be regulated by estrogen. These include cell-matrix and cell-cell adhesion, migration and invasion where focal adhesion kinase (FAK), E-cadherin, cytoskeletal proteins (e.g. vinculin, a-actinin) and matrix-metalloproteinases (e.g. MMP-2 and MMP-9) were affected (Bartholomew et al., 1998; DePasquale et al., 1994; Oesterreich et al., 2003; Paquette et al., 2005; Seeger et al., 2006). Research on ion channels, especially voltage-gated sodium channels (VGSCs) in cancer cells revealed their role in disease development and progression, and regulation of MCBs, including invasiveness, motility, endocytic/secretory membrane activity, adhesion and gene expression (Bennett et al., 2004; Brackenbury and Djamgoz, 2007; Brackenbury et al., 2007; Fraser et al., 2003, 2005; Grimes et al., 1995; Krasowska et al., 2004; Laniado et al., 1997; Mycielska et al., 2003, 2005, 2006; Palmer et al., 2008; Roger et al., 2003; Smith et al., 1998). However, the mechanism(s) controlling ion channel expression in cancer cells and the downstream signaling pathways are currently not well known. Interestingly, several reports have shown both genomic and non-genomic regulation of a wide variety of ion channels in different cell types, including cancer cells, by steroid hormones including estrogen, aldosterone, neurosteroids and androgen (Avila et al., 2003;

89 Barann et al., 1999; Borg et al., 2002; Diss et al., 2007; Elfverson et al., 2008; McEneaney et al., 2008; Shimoni et al., 2008; Wang et al., 2008a). A few examples include the following: (1) Long-term (3 days) treatment with estrogen (300 pM) increased mRNA expression of Ca2+ and voltage-activated K+ channel a and 134 subunit in mouse hypothalamic cell line GT1-7 (Nishimura et al., 2008). (2) Acute (-2 minutes) treatment with estrogen (50 1.1.M) inhibited L-type Ca2+ channel activity in mouse cardiomyocytes (Ullrich et al., 2008). (3) Long-term (2 days) treatment with androgen (100 nM) increased mRNA expression of Nav1.7 and VGSCf31 in metastatic prostate cancer (PCa) cell line PC-3 (Diss et al., 2007). The present study tested whether estrogen could regulate non-genomically the MCBs in MDA-MB-231 cells via VGSC activity.

3.2 Aims and scope

The overall aim of the present study was to investigate non-genomic/short-term effects of estrogen on MDA-MB-231 cells with an emphasis on adhesion as a key MCB and to elucidate the receptor responsible for this effect. The specific aims were as follows: 1. To investigate effects of short-term estrogen application on adhesion of MDA- MB-231 cells; 2. To test involvement of VGSC activity in estrogen response; 3. To determine expression of GPR30 in MDA-MB-231 cells by PCR, western blotting and immunocytochemisty; 4. To confirm GPR30 functioning by use of receptor-specific ligands; 5. To over-express GPR30 and test its effects on estrogen-induced change in adhesion; 6. To silence GPR30 with siRNA and test its effects on estrogen-induced change in adhesion; 7. To determine the subcellular distribution of GPR30 after over-expression and siRNA treatment; and 8. To evaluate PKA as a possible signalling intermediary in the effect of estrogen on MDA-MB-231 cells. A part of this study is included in a manuscript to be submitted for publication (Fraser et al., 2008).

90 3.3 Results

3.3.1 Adhesion Adhesion was used as a key component of the metastatic cascade. MDA-MB-231 cell adhesion was quantified using the "single-cell adhesion measuring apparatus" (SCAMA) (Palmer et al., 2008). The duration of the measurements was kept to 10 minutes to maintain consistency among experiments, avoiding any genomic effect. MDA-MB-231 cells were conditioned in mammalian physiological saline (MPS; NaC1 5 mM, CsC1 145 mM, MgC12 2 mM, CaC12 1 mM, HEPES 10 mM and EGTA 11 mM, adjusted to pH 7.4 with 1 M CsOH) for 10 minutes prior to treatments with 170-estradiol (E2). Two different E2 treatments were performed: (1) Acute treatments where MPS solution was replaced with E2 and SCAMA measurements were taken immediately (i.e. treatment time was 0- 10 minutes); and (2) Short-term treatments where MPS solution was replaced with E2 and cells were incubated for 10 minutes prior to SCAMA measurements (i.e. treatment time was 10-20 minutes).

3.3.1.1 Control experiments The effect of incubating in MPS for up-to 90 minutes on adhesion was investigated. Only in the 50-60 and 80-90-minute time bins MPS increased adhesion significantly by 34 ± 14 % and 25 ± 5 %, respectively (P < 0.05; n = 6-11; Figure 3.1). Incubation in MPS for less than 40 minutes did not affect adhesion (P > 0.05; n = 4-8; Figure 3.1). Thus, for both acute and short-term E2 treatments any change seen would be solely due to E2 and not MPS. Since E2 was dissolved in DMSO, a concentration-dependent control analysis also was performed to investigate any possible effect of DMSO on adhesion (Figure 3.2). While concentrations lower than 104 % DMSO (v/v in MPS) had no effect (p > 0.05; n = 3-5; Figure 3.2), adhesion was highly variable in MDA-MB-231 cells treated with 104 % and higher concentrations of DMSO; and appeared significantly reduced in 10-2 % DMSO by 16 ± 7 % (p < 0.05; n = 4; Figure 3.2). The highest concentration of DMSO used in E2 treatments was 10-5 % (corresponding to 100 nM E2). It was concluded that any effect of 100 nM or less E2 would be solely due to E2 and not to DMSO.

91 50 -

** 30 -

20 -

-10 -

-20 - 10-20 20-30 30-40 50-60 80-90

Time (min)

Figure 3.1: Incubation in MPS increased MDA-MB-231 cell adhesion time- dependently. MDA-MB-231 cell adhesion was measured for time-dependent effect of incubation in MPS. Cells were cultured in normal growth medium for 48 h before the experiment. Adhesion at each time bin was measured in separate dishes for 10 minutes. Cells were incubated in MPS for 10, 20, 30, 50 and 80 minutes. Incubation for more than 50 minutes increased DNP values significantly. Data are presented as mean ± SEM (n = 6-11). DNP values were normalized to control (normal growth medium = 100 %) and analysed by Mann-Whitney rank sum test. Significance: (*) P < 0.05, (**) P < 0.01.

92 DMSO [vA/ % in MPS]

Figure 3.2: Incubation in DMSO decreased MDA-MB-231 cell adhesion dose- dependently. MDA-MB-231 cell adhesion was measured for dose-dependent effect of incubation in DMSO. Adhesion at each dose was measured in separate dishes for 10 minutes each. Cells were treated with DMSO for 10 minutes after a 10 minute pre-incubation in MPS. Only 10-2 % DMSO (v/v in MPS) decreased adhesion significantly (n = 4; P < 0.05). Data are presented as mean ± SEM (n = 3-6). DNP values were normalized to control (MPS = 100 %) and analysed by Mann-Whitney rank sum test. Significance: (*) P < 0.05.

93 3.3.1.2 Acute treatments with estrogen For acute treatments, MDA-MB-231 cells were incubated in MPS for 10 minutes and treated with E2 (1, 10 and 100 nM E2) only during the 10-minute SCAMA measurements. Adhesion decreased with E2 in a dose-dependent manner. When compared to MPS control (DNP = 7.1 ± 0.4 kPa), adhesion stayed the same with 1 nM E2 (DNP = 7.1 ± 0.7 kPa; P > 0.05; n = 6; Figure 3.3A); but significantly decreased with 10 and 100 nM E2 (DNP = 5.7 ± 0.2 kPa and 6.6 ± 0.5 kPa, respectively; P < 0.001 and P < 0.05, respectively; n = 16 and n = 9, respectively; Figure 3.3A). When the DNP values were normalized to the control (MPS) values, the change in DNP (ADNP, %) was 17 ± 3 % and 22 ± 3 % with 10 and 100 nM E2, respectively (P < 0.001 and P < 0.05, respectively; n = 16 and n = 9, respectively; Figure 3.3B). There was no difference in the values of ADNP for 10 and 100 nM E2 (P > 0.05; Figure 3.3B). Thus, 10 nM was selected as the working concentration. The reversibility of the acute effect of 10 nM E2 on adhesion was tested with a `wash' step where the cells were incubated in MPS for an additional 10 minutes after treatment. The 'wash' alone controls did not affect adhesion. The reduction in adhesion with E2 was reversed with the wash step. The values of ADNP following the wash was 6 ± 4 % and was significantly different from acute E2 treatment (P < 0.001; n = 12; Figure 3.3C). Importantly, ADNP in wash was not significantly different from control values in MPS (P > 0.05; n = 12; Figure 3.3C). This demonstrated that the effect of acute E2 treatment was completely reversible after a 10-minute wash.

3.3.1.3 Short-term treatments with estrogen Short-term treatments were performed where the cells were incubated with E2 for 10 minutes before SCAMA measurements; thus increasing the total time of treatment to 20 minutes. Adhesion of MDA-MB-231 cells was again significantly reduced from 8.9 ± 0.5 to 6.3 ± 0.4 kPa (P < 0.01; n = 7; Figure 3.4A) by 27 ± 7 % (P < 0.01; n = 7; Figure 3.4B) after short-term E2 (10 nM) treatments. Similar to acute treatments, the effect of short-term treatment with 10 nM E2 was completely reversible after a 10-minute wash in MPS (P < 0.01; n = 7; Figure 3.4B). Interestingly, adhesion in wash was significantly increased by 25 ± 9 % (P < 0.05; n = 7; Figure 3.4B) when compared to control (MPS). The treatment time at the end of

94 A. 8 - - —I----- 6 - 73 0 ..1e 4 - a. z 0 2

0 MPS 1 nM E2 10 nM E2 100 nM E2

Treatments

B. C. *** r 10 x 10 - ....p...... 5 e ..-..... 0 o. a_ z z -5 o -10 *** * im <1 4 -10 - -15 . -20 * -20 1 10 100 -25 - 10 nM E2 Wash Estradiol [nM] Treatments

Figure 3.3: Acute effects of estrogen on MDA-MB-231 cell adhesion were dose- dependent and reversible.

Adhesion of MDA-MB-231 cells during acute treatments with E2 at 1, 10 and 100 nM was measured in separate dishes. Compared to control (MPS), the DNP was reduced significantly by both 10 and 100 nM E2 (A). The change in DNP (ADNP, %), when normalized to control (MPS =- 100 %) was significant with both 10 and 100 nM E2 (B). The effect on adhesion with 10 nM E2 treatment was completely reversible (C). Data are presented as mean ± SEM (n = 6-16) and was analyzed by Mann-Whitney rank sum test (A) and unpaired t-test (B & C). Significance: (*) P < 0.05, (***) P < 0.001., (X) P > 0.05.

95

A. 12 - I 9 -

0 MPS E2 Wash

Treatments

B. ** 35 * 25 - I •:*. 15 - a. 5 - z _5 • 01 -15 - -25 - -35 - 10 nM E2 Wash Treatment

Figure 3.4: Short-term effects of estrogen on MDA-MB-231 cell adhesion were reversible.

Adhesion of MDA-MB-231 cells after short-term treatment with E2 at 10 nM was measured in separate dishes. (A) Compared to control (MPS), the DNP was reduced significantly and this was significantly reversed by 10-minute wash in MPS. (B) The change in DNP (ADNP, %) when normalized to MPS (100 %) was significantly reduced after short-term E2. The 10-minute 'wash' step in MPS increased adhesion significantly when compared to control (MPS; A & B). Data are presented as mean ± SEM (n = 7) and was analyzed by Mann-Whitney rank sum test (A) and unpaired t-test (B). Significance: (*) P < 0.05, (**) P < 0.01., (X) P > 0.05.

96 the wash after short-term treatments was 40 minutes, thus the increase in adhesion after wash is consistent with the time-dependent effect of MPS (Figure 3.1). For consistency in the future experiments of this chapter, the selected treatment regime was short-term treatment with 10 nM E2.

3.3.2 Tests of VGSC involvement in the effect of estrogen on MDA-MB-231 cell adhesion.

3.3.2.1 Effect of blocking VGSC activity with tetrodotoxin Blocking VGSC activity with tetrodotoxin (TTX, 10 iuM) for 10 minutes before and 10 minutes during the experiment increased adhesion of MDA-MB-231 cells significantly from 7.2 ± 0.4 kPa to 9 ± 0.6 kPa; i.e. by 25 % (P < 0.05; n = 14; Figure 3.5). This effect was completely reversed after a 10-minute wash in MPS (n = 4; Figure 3.5).

3.3.2.2 Short-term effects of estrogen and TTX co-treatments In order to investigate whether VGSC activity was involved in the short-term effects of E2 on MDA-MB-231 cell adhesion, co-treatments with E2 (10 nM) and TTX (10 uM) were performed. As before (Figure 3.5), 10-minute TTX treatment increased adhesion from 7.9 ± 0.2 kPa in control/MPS to 9.2 ± 0.6 kPa (P < 0.05; n = 10; Figure 3.6A). Treatment with E2 in the presence of TTX (E2+TTX) for 10 minutes did not change adhesion when compared to TTX alone: DNP = 9.5 ± 0.5 kPa (P > 0.05; n = 8; Figure 3.6A). However, this was significantly higher than the value in MPS (P < 0.01; n = 8; Figure 3.6A). As before (Figure 3.4), short-term E2 (10 nM) treatment significantly reduced adhesion from 7.9 ± 0.2 kPa in MPS to 5.9 ± 0.2 kPa (P < 0.001; n = 8; Figure 3.6B). Interestingly, E2+TTX treatment for 10 minutes increased adhesion significantly to 9.4 ± 0.4 kPa (P < 0.001; n = 8; Figure 3.6B). When DNP values were normalized to MPS (100 %), the overall effects were 16 ± 7 % increase with TTX alone (P < 0.05; n = 10; Figure 3.6C); 25 ± 3 % decrease with E2 alone (P < 0.001; n = 8; Figure 3.6C); and 21 ± 3 % increase with E2+TTX (P < 0.001; n = 8; Figure 3.6C). Thus, short-term effect of E2 on adhesion was completely reversed by addition of TTX. These data suggested a role of VGSC activity in the effects of estrogen on MDA-MB-231 cell adhesion.

97 10- *

i MPS TTX Wash

Figure 3.5: Short-term tetrodotoxin treatment increased MDA-MB-231 cell adhesion and the effect was reversible.

DNP values were significantly higher after 10-minute pre-treatment of MDA-MB-231 cells with tetrodotoxin (TTX; 10 µM). This effect was completely reversible after 10- minute wash in MPS (n = 4-14; P < 0.05). Data are presented as mean ± SEM and was analyzed by Mann-Whitney rank sum test. Significance: (*) P < 0.05.

98 10 -

8 - -

2-

1 0 E2 + TTX MPS TTX MPS E2 E2 + TTX

C. 30

20 - • 10 - 0. z o 0 • -10

-20

-30

TTX E2 E2 + TTX

Figure 3.6: Short-term TTX treatment blocked the effect of E2 on MDA-M13-231 cell adhesion.

(A) Increased adhesion after short-term TTX (10 ilM) and E2 (10 nM) + TTX treatments when compared to control (MPS) (P < 0.05 and P < 0.01, respectively). (B) Reduced adhesion with short-term E2 (P < 0.001) followed by increased adhesion with short-term E2 + TTX treatment (P < 0.001). (C) Compiled data from (A) and (B) normalized to control (MPS =- 100 %). Change in DNP (ADNP, %) was in opposite directions for TTX and E2 (P < 0.001); and for E2 + TTX it was not different from TTX values (P > 0.05). Data are presented as mean ± SEM (n = 8-10) and was analyzed by Mann-Whitney rank sum test (A & B) and un-paired t-test (C). Significance: (*) P < 0.05, (**) P < 0.01, (***) P < 0.001, (X) P > 0.05.

99 3.3.3 Studies on the estrogen receptor expressed in MDA-MB-231 cells: Evaluation of GPR30 as a candidate mechanism Studies at mRNA and protein levels were performed to investigate GPR30 as a candidate receptor responsible for the effects of short-term E2 treatments on MDA-MB-231 cell adhesion.

3.3.3.1 Expression of GPR30 and absence of ERa mRNA in MDA-MB-231 cells MDA-MB-231 cells are known as "ERa-negative" BCa cells (Rochefort et al., 2003). Absence of classical ERa receptor mRNA in MDA-MB-231 cells was confirmed by reverse-transcriptase PCR (RT-PCR) experiment where MCF-7 cells were used as positive control (Figure 3.7A). GPR30 mRNA expression was tested in MDA-MB-231 cells after 35 cycles of RT-PCR. By using MCF-7 cells as positive and HEK-293 cells as negative controls, mRNA expression of GPR30 was confirmed by gel electrophoresis which revealed that MDA-MB-231 cells expressed GPR30 mRNA at a lower level than MCF-7 cells and that HEK-293 cells did not express it at all (Figure 3.7B). A no template control (NTC) where no cDNA was added was also included in the experiment and absence of a band confirmed that there was no contamination.

3.3.3.2 Expression of GPR30 protein in MDA-MB-231 cells Western blot with a goat-anti-GPR30 antibody (Santa Cruz) on 30 i.tg of total protein revealed that GPR30 protein was present in MDA-MB-231 cells, where total protein from MCF-7 cells was used as a positive control (Figure 3.8). A monoclonal anti-a-actinin antibody (Sigma) was used on the same western blot to confirm equal loading of protein among samples (Figure 3.8). Immunocytochemistry by conventional fluorescence microscopy supported the Western blot data showing that GPR30 protein was present in both MCF-7 and MDA- MB-231 cells (Figure 3.9A). A polyclonal rabbit-anti-GPR30 antibody (provided by Prof. Prossnitz) was applied onto MCF-7 and MDA-MB-231 cells and green fluorescence was visualized by use of a secondary antibody conjugated with FITC (Figure 3.9A). MCF-7 cells were used again as positive controls and a higher fluorescence than MDA-MB-23 I cells was observed (Figure 3.9A) supporting a higher protein expression also found in Western blot (Figure 3.8). Control immunocytochemisty experiments where primary

100 A. 1 23 MB- LII'

0 DA-

2 M ERa =IL - 299 kb

B. r ke ar 231 m MB- ht ig DA- We M

GPR30 4— - 585 kb

1 2 3 4 5 6

Figure 3.7: ERa mRNA was absent; GPR30 mRNA was present at low levels in MDA-MB-231 cells.

Gel pictures of ERa (A) and GPR30 (B) mRNA expression. (A) Absence of ERa mRNA in MDA-MB-231 cells and its expression MCF-7 cells (positive control). (B) GPR30 mRNA expression after 35 cycles of PCR with specific primers. Bands at correct positions confirmed its expression in MCF-7 cells (positive control; lanes 2 & 3) and its absence in HEK-293 cells (negative control; lane 5). MDA-MB-231 cells (lane 4) expressed GPR30 mRNA at lower levels than MCF-7 cells. NTC: No template control (lane 6).

101 Figure 3.8:WesternblottingshowedGPR30proteinexpressioninMDA-MB-231 and a-actininantibody(loadingcontrol). stably transfectedwithnNav1.5,andMCF-7cells (positivecontrol),usinganti-GPR30 cells. Western blotof30pgtotalproteinperlane fromMDA-MB-231cells,EBNAcells a-actinin GPR30

MDA-MB-231 U- E 0 I 1- A- 100kDa 40 kDa 102 A. Anti-GPR30

MCF-7

MDA-MB-231

B. BF Swine anti-rabbit-FITC only b

MCF-7

;'K

MDA-MB-231

Figure 3.9: Immunocytochemistry confirmed GPR30 protein expression in MDA- MB-231 cells.

(A) of MCF-7 (a-d) and MDA-MB-231 (e-h) cells with anti-GPR30 antibody. Fluorescence was visualised by fluorescence microscopy using secondary antibody conjugated with FITC. (B) Control experiments where only FITC-conjugated secondary antibody was applied did not show any fluorescence in either MCF-7 (a & b) or MDA-MB-231 (c & d) cells. BF: Bright field images. Scale bars denote 10 pm in both (A) and (B) and applicable to all panels.

103 antibody was omitted and only FITC-labeled secondary antibody was applied were also performed on both MCF-7 cells (Figure 3.9B, a & b) and MDA-MB-231 cells (Figure 3.9B, c & d). Absence of fluorescence confirmed that the secondary antibody was specific and did not cross react with an unknown antigen (Figure 3.9B). Confocal microscopy following immunocytochemistry was used for subcellular localization of GPR30 protein in MDA-MB-231 and MCF-7 cells (Figure 3.10). Cells were co-stained with concanavalin A (ConA) as a plasma membrane (PM) marker (green; Figure 3.10A, a, d, g & j) and anti-GPR30 antibody which was visualized by using Alexafluor568-labeled secondary antibody (red; Figure 3.10A, b, e, h & k). Merged images revealed that GPR30 was co-localized with ConA as well as occurring in intracellularly in both MDA-MB-231 cells (Figure 3.10A, c & 1) and MCF-7 cells (Figure 3.10A, i & 1). In general, the staining was stronger in MCF-7 cells (Figure 3.10A, panels h & k). Control experiments were also performed where both cell lines were stained with ConA and the secondary antibody only — MDA-MB-231 cells and MCF-7 cells (Figure 3.10B, a-c % d-f, respectively). No red fluorescence was observed in both MDA-MB-231 cells and MCF-7 cells confirming that the secondary antibody was specific and did not cross-react with any unknown antigens (Figure 3.10B, b & e, respectively).

3.3.3.3 Effect of BSA-conjugated E2 on MDA-MB-231 cell adhesion The role of a possible plasma membrane estrogen receptor on adhesion was investigated by using membrane impermeable E2 conjugated to BSA (E2-BSA). When normalized to control (MPS .== 100 %), short-term treatment with E2-BSA (1 nM) decreased MDA-MB- 231 cell adhesion significantly by 11 ± 4 % (from 8.9 ± 0.7 kPa to 7.9 ± 0.7 kPa; P < 0.05; n = 8-12; Figure 3.11A). Higher concentrations of E2-BSA (10 and 100 nM) produced smaller effects (Figure 3.11A). These data indicated that a plasma membrane estrogen receptor could be involved in controlling MDA-MB-231 cells adhesion, consistent with the non-genomic effect of E2.

3.3.3.4 Effect of GPR30-specific ligand, G1 compound, on MDA-MB-231 cell adhesion In order to investigate whether E2 could be acting through GPR30 to affect adhesion, MDA-MB-231 cells were treated with G1 compound (0.1, 1, 10 and 100 nM) for 10 minutes and their adhesion was measured. There was a dose-dependent effect and 1 nM

104 (A) ConfocalimagesobtainedwithXYZscans of MDA-MB-231cells(a-f)andMCF-7 antibody (red).Mergedimages(c,f,i&1)arealso shown.(B)Controlexperimentswhere cells (g-1),co-stainedwithconcanavalinA(ConA) PMmarker(green)andanti-GPR30 Figure 3.10:GPR30proteinlocalizationinMDA-MB-231 andMCF-7cells. MDA-MB-231 cells(a-c)andMCF-7(d-f) wereco-stainedwithConA(a&d, A. respectively) andAlexafluor568-labeled secondaryantibodyonly(b& e,respectively). BF: Brightfieldimages (c &f).Scalebarsdenote30umforallpanels. B.

U- 0 MDA- MB- 2 231 MDA-MB-231 ConA Anti-GPR30 Merged 105

A.

1 10 100

E2-BSA [nM] B.

0.1 1 10 100

G1 [nM]

Figure 3.11: Short-term effect of E2-BSA treatment on MDA-MB-231 cell adhesion was dose-dependent.

Dose dependent reduction in MDA-MB-231 cell adhesion with short-term treatments of BSA-conjugated estradiol (E2-BSA; A) and GPR30-specific ligand, G1 compound (B). Change in DNP values (ADNP) normalized to control (MPS ==-- 100 %) showing that only 1 nM E2-BSA (A) and 1 nM G1 (B) reduced adhesion significantly. Data are presented as mean ± SEM (n = 8-12) and was analyzed by un-paired t-test. Significance: (*) P < 0.05.

106 G1 significantly reduced DNP values 12 ± 6 % (from 9.8 ± 0.3 kPa in MPS to 8.7 ± 0.4 kPa; P < 0.05; n = 8; Figure 3.11B). These data suggested that GPR30 was involved in regulating MDA-MB-231 cell adhesion.

3.3.3.5 Over-expression of GPR30 in MDA-MB-231 cells Plasmid transfection with pBK-CMV-GPR-Br was performed to over-express GPR30 in MDA-MB-231 cells. Real-time PCR with specific primers for GPR30 mRNA was used to check for over-expression. Eight GPR30-transfected colonies were selected (GPR30-2, GPR30-3, GPR30-11, GPR30-14, GPR30-15, GPR30-16, and GPR30-17 and GPR30- 24). A control experiment where MDA-MB-231 cells were transfected with an empty plasmid (pBK-CMV) was also done and one colony was selected which is referred to as "empty-vector" control. 0-actin was used as the housekeeping/normalizing gene. Quantification using the 2-A6ct method revealed that empty-vector transfection did not change GPR30 mRNA levels in MDA-MB-231 cells (P > 0.05; n = 3; Figure 3.12B). Six out of eight colonies selected (GPR30-3, GPR30-11, GPR30-14, GPR30-15, GPR30-16, GPR30-17) expressed GPR30 mRNA at significantly higher levels than the empty-vector controls (P < 0.01 for GPR30-14 and P < 0.05 for the others; n = 3; Figure 3.13C). GPR30-14 expressed the highest level of GPR30 mRNA by around 200-fold increase relative to the empty-vector control (Figure 3.12C). Gel electrophoresis confirmed high- quality of PCR products with the bands at the expected sizes (Figure 3.12A); there was no amplification with the NTC (Figure 3.12A). Western blot with an anti-GPR30 antibody on 30 µg of total protein confirmed over-expression of GPR30 protein in the GPR30-transfected colonies; again GPR30-14 cells expressed the highest level of protein (Figure 3.13). GPR30-14 was selected as the colony to be used in subsequent experiments.

3.3.3.5.1 Basal adhesion of GPR30-14 cells Adhesion of GPR30-14 cells was measured under normal culturing conditions. When compared to non-transfected and empty-vector transfected MDA-MB-231 cells over- expression of GPR30 in GPR30-14 cells did not affect the DNP values (Figure 3.14).

3.3.3.5.2 Effect of short-term estrogen treatment on GPR30-14 cells GPR30-14 cells were treated short-term with E2 (10 nM). When compared to control/MPS, short-term E2 (10 nM) reduced the DNP values significantly from 9.9 ± 0.9

107

Figure 3.12:Real-timePCRconfirmedover-expressionofGPR30mRNAin control (non-transfectedMDA-MB-231cells;lane 1),empty-vector(lane2)andGPR30- transfected colonies(lanes3-10).NTC:notemplate control(lane11).(B)GPR30mRNA (A) TypicalgelelectrophoresisimagesofPCR productsforGPR30and13-actinfrom transfected colonies. expression inempty-vectortransfectedcellsrelative tocontrolMDA-MB-231cells(n= 3). (C)GPR30mRNAexpressioninGPR30-transfected coloniesrelativetoempty- analyzed byunpairedt-test. Significance:(*)P<0.05,(**)0.01. vector. GPR30-14hadthehighestmRNAlevel amongallcolonies.mRNAlevelswere normalized to13-actinby T C. A. B. GPR30 p.„ ) GPR30 mRNA expression (relative tin

1 234567891011 72 ... o o c

irs itIt vector Em ptyGPR30- Ill 0 f:. 64:$ E a.I-

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method.Dataarepresented asmean±SEM(n=3)and GPR30 mRNA expression (relative rl C3 0 CZ CCCLX T 3

r) ,-, , t. Control

11

el %- Nr

14 Em ptyvector

el '0

15 .- r) 6 to

rt re r-. 6 0 Z eq ,-. 16

—1111114— NI. r) eq 17

0 24 -585 nt -359 nt 108

tor c ti

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ty cd, 4.1

p re a. a_

Em 0 0

GPR30 1— 40 kDa

a-actinin -me 4.0 vtio. 4. 100 kDa

1 2 3 4 5 6

Figure 3.13: Over-expression of GPR30 protein in transfected colonies.

Western blot of 30 pg total protein from empty-vector (lane 1) and GPR30-transfected MDA-MB-231 colonies (lanes 2-6). The blot was immunostained with anti-GPR30 antibody and anti-a-actinin antibody for loading control. GPR30-14 had the highest intensity band among the transfected cell lines.

109 14-- 12 - 10 - I o. 8- o. 6- Z p 4 - 2 -

0 I I I Control Empty-vector GPR30-14

Figure 3.14: GPR30 over-expression did not affect basal adhesion.

GPR30-14 cells had the same adhesion (DNP) as the control (non-transfected; MDA normal) and empty-vector transfected MDA-MB-231 cells (P > 0.05). Data are presented as mean 1 SEM and were analyzed by Mann-Whitney rank sum test (n = 3).

110 kPa to 8.3 ± 0.9 kPa. This effect was completely reversible (P < 0.05; n = 4; Figure 3.15A). When normalized to MPS (100 %), the reduction was by 16 ± 4 % (P < 0.05; n = 4; Figure 3.15B). Thus, GPR30 over-expression did not change the basic effect of short- term E2 (10 nM) treatment on adhesion of MDA-MB-231 cells.

3.33.5.3 Subcellular distribution of GPR30 protein in GPR30-14 cells. Immunocytochemistry followed by confocal microscopy imaging was used to determine subcellular distribution of GPR30 protein in GPR30-14 cells. Confocal images from XYZ scans qualitatively revealed that GPR30 protein intensity was higher rather than in PM, defined by ConA staining, in GPR30-14 cells (Figure 3.16, m-x) when compared to empty-vector controls (Figure 3.16, a-1). Further quantification of relative PM and intracellular (INT) immunoreactivity was performed by `cross-sectional' analysis where lines were drawn across the cells (red lines in 'Merged' images, Figure 3.16, g & s), through the PM, avoiding the nucleus, as described previously (Brackenbury and Djamgoz, 2006). Staining with ConA as a PM marker was used as a tool for determining the cell periphery in cross-sections. In GPR30-14 cells, this analysis showed that INT GPR30 protein expression was higher than GPR30 protein expression in PM fraction, when compared with empty-vector controls (Figure 3.17A and B, for empty-vector and GPR30-14 cells, respectively). Importantly, GPR30 over- expression increased fractional INT immunoreactivity significantly from 27 ± 1 % in empty-vector cells to 31 ± 1 % in GPR30-14 cells (P < 0.05; n > 100 cells/3 experiments; Figure 3.18A, left-hand bars). In contrast, fractional expression in PM decreased from 12 ± 1 % to 10 ± 0.4 % (P < 0.05; n > 100 cells/3 experiments; Figure 3.18A, right-hand bars). A second quantification by 'freeform line' profile drawn around the edges of the cells using ConA as a PM marker revealed that GPR30 over-expression did not change GPR30 immunoreactivity in PM of GPR30-14 cells when compared to empty-vector cells (P > 0.05; n > 100 cells/3 experiments; Figure 3.18B).

33.3.6 Effect of GPR30 siRNA on MDA-MB-231 cells

3.3.3.6.1 mRNA studies MDA-MB-231 cells were transfected with GPR30 targeting siRNA to knock-down GPR30 expression. Control experiments were the following: (1) "mock" transfection

111

A. 12 -

10-

4 -

2 •

0

M PS E2 Was h

Treatments

B. 10- 5 0 a. 0 z C3 -5 -

-10 - I -15 - -20 -

E2 Wash Treatments

Figure 3.15: Short-term effect of estrogen treatment on GPR30-14 cell adhesion was reversible.

(A) DNP values compared with MPS. GPR30-14 cell adhesion decreased significantly with short-term E2 (10 nM) treatment (n = 4) and this effect was reversible after 10- minute wash with MPS. (B) Change in DNP (ADNP) normalized to control (MPS; n = 4). Data are presented as mean ± SEM and was analyzed by Mann-Whitney rank sum test. Significance: (*) P < 0.05.

112 Empty-vector

ConA GPR30 Merged BF

b

GPR30-14

ConA GPR30 Merged BF

Figure 3.16: Over-expression increased intracellular immunoreactivity of GPR30 protein.

Confocal images of empty-vector (a-1) and GPR30-14 cells (m-x) showing ConA in green (a, e, i, m, q, u) and GPR30 in red (b, f, j, n, r, v). Merged images are shown for empty- vector (c, g, k) and GPR30-14 cells (o, s, w). Bright field (BF) images are shown (d, h, 1, p, t, x). Red lines in merged images show typical lines across the cells for 'cross- sectional' analysis. White arrows indicate the increased intracellular staining in GPR30- 14 cells. Scale bars denote 30 pm for all panels.

113 cells havehigherlevelsof intracellularGPR30intensitycomparedtoempty-vector cells. Typical graphsfrom'cross-sectional'analysisshowing signalintensityofConA(green) intracellular GPR30intensity.Thearrowsindicate thePMGPR30intensity.GPR30-14 Figure 3.17:Over-expressionincreasedintracellular GPR30protein. PM markerandGPR30(red)alongthecross-section fromanempty-vector(A)and GPR30-14 (B)cells.Thehorizontaldashed linesindicateapproximatelevelof B. A. Fluorescence (AU) Fluorescence (AU) 120 150 180 120 - 150 - 180 - 90 - 60 - 30 60 30 90 0 0

0 0

2 2

4 4

Cross section(pm) Cross section(pm) 6 6 I

8 8 I

10 10

12 12 •

14 14

ConA GPM ConA GPR30 114

A. 35 - *** — 14 %) %) ( 30 - — 12

NT I PM ( I

-

25 - — 10 - ity ity iv

20 - 8 iv t t c c 15 - —6 rea rea no 10 - —4 no

5 - —2 mu 0 - 0 im Empty- I GPR30-14 Em pty- GPR30-14 vector vector GPR30 immu GPR30 Internal Plasma membrane

x B. 120 -

80 -

• Empty-vector GPR30-14

Figure 3.18: Over-expression increased relative proportion of intracellular GPR30 protein without changing plasma membrane expression.

(A) GPR30 immunoreactivity in the PM and cytosol shown here as a percentage of total intensity (%). Left-hand bars demonstrate intensity (%) of middle 30 % cross-section defined as intracellular (INT). Right-hand bars demonstrate intensity along the straight- line sections measured 1.5 gm inward from the edge of ConA staining defined as PM. (B) Freeform line analysis for PM intensity from measurements around cell periphery by using ConA as PM marker. Data were obtained from XYZ confocal images from both empty-vector and GPR30-14 cells. Data are presented as means ± SEMs (n=3, 30-80 cells per experiment in A; 30-60 cells for each experiment in B) and were analysed by unpaired t-test. Significance: (***) P < 0.001, (X) P > 0.05.

115 where no siRNA was used but the cells were treated with transfecting medium (Opti- MEM) containing oligofectamine reagent; and (2) "siControl" where cells were transfected with a non-targeting siRNA. Real-time PCR experiments using 13-actin as the normalizing gene revealed that neither mock nor siControl cells altered GPR30 mRNA levels when compared with non- transfected (control) cells (P > 0.05; n = 5; Figure 3.19). Gel images showed that the PCR products were of high quality and at the expected size; no template control (NTC) did not give any product (Figure 3.19). Transfection with targeting siRNA for 3 days decreased GPR30 mRNA expression significantly from siControl levels by about 50 (P < 0.05; n = 3; Figure 3.20). Gel electrophoresis confirmed high product quality and the right size of bands where no amplification was seen with NTC (Figure 3.20).

3.3.3.6.2 Protein studies Western blot with an anti-GPR30 antibody on 30 lig total protein revealed that siRNA transfected MDA-MB-231 cells expressed significantly lower GPR30 protein when compared to siControl cells by about 70 ± 14 % (P < 0.05; n = 3; Figure 3.21). siControl transfection did not affect GPR30 protein levels when compared to mock-transfected cells (Figure 3.21). For further analysis, confocal microscopy following immunocytochemistry was used, where possible changes in subcellular distribution of GPR30 were analysed. ConA was used again as a PM marker (green), and GPR30 was visualized again by using an Alexafluor568-conjugated secondary antibody (red). XYZ scans from siControl and siRNA treated cells revealed that knock-down of GPR30 protein occurred mostly INT rather than in PM (Figure 3.22, a-1 and m-x, for siControl and siRNA, respectively). Quantification of images was done as described before (section 3.3.3.5.3). From `cross-sectional' analysis (red lines in 'Merged' images, Figure 3.22, c and o) siRNA cells showed lower intensity peaks internally when compared to siControl cells (Figure 3.23A & B, for siControl and siRNA, respectively). GPR30 siRNA knocked-down NT GPR30 immunoreactivity significantly from 28 ± 1 % to 25 ± 1 % (P < 0.05; n > 100 cells/3 experiments; Figure 3.24A, left-hand bars). This was accompanied by increased PM intensity from 11 ± 0.4 % to 13 ± 1 % (P < 0.05; n > 100 cells/3 experiments; Figure 3.24A, right-hand bars).

116 A. 7(2 72 .1.. 4.4 _c E 0 U 0 o P 0 I- o Cl) 2 z

GPR30 -585 nt P-actin 1=1== -359 nt 1 2 3 4

B. 2.4 -

MM. • 2.0

.0y 1.6 -

N 1.2 - x

Z 0.8 - MEM E o 0.4 M O_ 0.0 Control siControl Mock

Figure 3.19: siControl (non-targeting siRNA) and mock (no siRNA) did not affect GPR30 mRNA levels in MDA-MB-231 cells.

(A) Typical gel electrophoresis images of PCR products for GPR30 and 0-actin from control (non-transfected MDA-MB-231 cells; lane 1), siControl (non-targeting siRNA; lane 2) and mock (no siRNA; lane 3) transfected MDA-MB-231 cells. NTC: no template control (lane 4). (B) GPR30 mRNA expression in siControl and mock-transfected cells relative to control (non-transfected) MDA-MB-231 cells. GPR30 mRNA level was normalized to 13-actin by the 2-Aectmethod. Data are presented as means ± SEMs propagated through the 2-°Act analysis (n = 5).

117

A. 79. .... a co Z 0 p Fe 1- ii 7) z GPR30 -585 nt

13-actin IZIMIII4- -359 nt 1 2 3

B. c; 1.0 - co ...... e 0.8 - a •-0 * Cl' Cl) 0.6 - L.a) a x a) 0.4 - Z CZ 0.2 - o (#) ce 0.0 • • a_ C..7 siControl siRNA

Figure 3.20: GPR30 siRNA reduced GPR30 mRNA levels significantly in MDA-MB- 231 cells.

(A) Typical gel electrophoresis images of PCR products for GPR30 and 13-actin from siControl (non-targeting siRNA; lane 1) and siRNA (lane 2) transfected MDA-MB-231 cells. NTC: no template control (lane 3). (B) GPR30 mRNA expression in siRNA- transfected cells relative to siControl cells. GPR30 mRNA level was normalized to 13- actin by the 2-°Act method. Data are presented as means ± SEMs propagated through the "-AACt Z analysis (n = 3). Data were analyzed by unpaired t-test. Significance: (*) P < 0.05.

118 A. 0 O C O z 0 Fe (7) — 40 kDa GPR30

a-actinin — 100 kDa

1 2 3

B. 1.0 — >

ED 0.8 -

O co 0.6 -

X ** a) • 0.4 - 2 • 0.2 - O

0 0.0 Control siControl siRNA

Figure 3.21: GPR30 siRNA reduced GPR30 protein levels significantly in MDA-MB- 231 cells.

(A) A typical western blot with anti-GPR30 and a-actinin antibody on 30 pg of total protein from control (non-transfected; lane 1), siControl (non-targeting siRNA; lane 2) and siRNA transfected cells (lane 3). (B) Band intensities from blots like (A) were quantified (n = 3). The band intensities in siRNA cells were significantly less than siControl cells. Data are presented as mean ± SEM and analysed by unpaired t-test. Significance: (**) P < 0.01.

119 siControl

ConA GPR30 Merged BF

siRNA

ConA GPR30 Merged BF

Figure 3.22: siRNA decreased intracellular immunoreactivity of GPR30 protein.

Confocal images of siControl (a-1) and siRNA cells (m-x) showing ConA in green (a, e, m, q, u) and GPR30 in red (b, f, j, n, r, v). Merged images are shown for siControl (c, g, k) and siRNA cells (o, s, w). Bright field (BF) images are shown (d, h, 1, p, t, x). Red lines in merged images show typical lines across the cells for 'straight-line' analysis. Scale bars denote 30 tm for all panels.

120 A. 180 - ConA GPR30

150 -

AU) 120 - (

nce 90 -

esce 60 - or 30 - Flu

0 0 2 4 6 8 10 12 14 Cross section (pm)

B. 180 - ConA -GPR30 150 - U) A

( 120 -

nce 90 -

60 - resce o 30 - Flu

0 • 0 2 4 6 8 10 12 14 Cross section (pm)

Figure 3.23: siRNA decreased intracellular GPR30 protein expression.

(A) & (B) Typical graphs from 'cross-sectional' analysis showing signal intensities of ConA (green) PM marker and GPR30 (red) along the cross-section from an siControl (A) and siRNA (B) transfected MDA-MB-231 cell. The horizontal dashed lines indicate approximate levels of intracellular GPR30 intensity. The black arrows indicate the PM GPR30 intensity. siRNA cells have reduced intracellular intensity for GPR30 when compared to siControl cells.

121 without changingplasmamembraneexpression. Figure 3.24:siRNAdecreasedrelativeproportionofintracellularGPR30protein (A) Intracellular(INT)andplasmamembrane(PM)GPR30immunoreactivitywas a percentageoftotalintensity(%).Left-handbarsshow(%)middle30% cross-section definedasINT.Right-handbarsshow intensity(%)alongthestraight-line quantified bystraight-lineprofileanalysisusingConAasthePMmarkerandshown sections measured1.5[tininwardfromtheedge ofConAstainingdefinedasPM.Empty for eachexperimentin B) andwereanalysedbyunpairedt-test.Significance: (*)P< from measurementsaroundcellperipheryby usingConAasPMmarker.Datawere Data arepresentedasmeans±SEMs(n=3,30-80 cellsperexperimentinA;30-60 0.05, **P<0.01,(X) > 0.05. obtained fromXYZconfocalimagesboth siControlandsiRNAtransfectedcells. bars, siControlcells;greysiRNAcells.(B) FreeformlineanalysisforPMintensity A. B.

GPR30 immunoreactivity - INT (%) 30 - 10 15 - 20 - 25 - - siControl IsiRNA (-) t.7 40 a. a 0 • E a. Internal 120 140 100 80 60 20 ** siControl siControl IsiRNA Plasma membrane siRNA

—2 —4 —6 —8 — 10 —12 — 14 0

GPR30im munoreactivity - PM ( A) 122 Freeform line profile analysis performed as described before (section 3.3.3.5.3) revealed that GPR30 intensity in PM did not change significantly between siControl and siRNA cells (n = 3, 30-60 cells per experiment; P > 0.05; Figure 3.24B).

3.3.3.6.3 Single-cell adhesion studies MDA-MB-231 cell adhesion was measured 3-day post-transfection with siControl (non- tatgering siRNA) and targeting siRNA. Basal adhesion was not different in siControl and siRNA cells compared to control cells (P > 0.05; n = 3; Figure 3.25).

(i) Block of estrogen's effect on adhesion A potential change in the effect of estrogen on adhesion was investigated in siRNA- treated cells. First, mock, siControl and siRNA transfected MDA-MB-231 cells were treated short-term with E2 (10 M) and their adhesion was measured by SCAMA. When normalized to control (MPS = 100 %), E2 significantly reduced adhesion in mock and siControl cells by 15 ± 4 % and 19 ± 4 %, respectively (P < 0. 05; n = 4; Figure 3.26). In contrast, in siRNA cells, short-term E2 did not affect adhesion (P > 0.05; n = 6; Figure 3.26). Thus, knock-down of GPR30 (mainly internal) protein inhibited the effect of short- term E2 on adhesion of MDA-MB-231 cells.

(ii) Block of G1 compound's effect on adhesion Adhesion of both siControl and siRNA-treated cells was measured after short-term treatment with G1 compound (1 nM). In siControl cells ADNP (normalized to control/MPS = 100 %) was significantly different with G1 (1 nM) with 13 ± 3 % reduction whereas in siRNA cells ADNP was not different with 01 (P < 0.05 and P > 0.05, respectively; n = 4 and n = 8, respectively; Figure 3.27).

3.3.3.7 Effect of GPR30 siRNA and overexpression on VGSC mRNA expression in MDA-MB-231 cells

3.3.3.7.1 nNav1.5 Possible changes in nNav1.5 mRNA levels in MDA-MB-231 cells after GPR30 siRNA transfection were investigated by real-time PCR experiment. As before, 13-actin was used as the normalizing gene and the data were analysed by using the 2-6'Act method. There was

123 12 - r 10 -

Control siControl siRNA

Figure 3.25: siControl (non-targeting siRNA) and GPR30 siRNA did not affect MDA-MB-231 cell adhesion.

Basal adhesion of MDA-MB-231 cells measured 3-day post-transfection with siControl or siRNA. Data are presented as mean ± SEMs (n = 3) and analysed by Mann-Whitney rank sum test. (X) P > 0.05.

124 X CI MPS E2 120 - • 100 - 1=M111•1•IMI,

80 -

Z 60 - C:1 40 -

20 -

0

Mock siControl siRNA

Figure 3.26: GPR30 siRNA inhibited the short-term effect of E2 treatment on MDA- MB-231 cell adhesion.

Change in DNP (A DNP, %) normalized to MPS (100 %) by short-term E2 (10 nM) in mock, siControl and siRNA cells. Data are presented as mean ± SEM (n = 4-6) and analysed by unpaired t-test. Significance: (*) P < 0.05, (X) P > 0.05.

125

120 - * x 0 MPS 0 G1 100 -

80 -

60 -

40 -

20 -

0

siControl siRNA

Figure 3.27: GPR30 siRNA inhibited the effect of G1 compound on MDA-MB-231 cell adhesion.

Change in DNP (A DNP, %) normalized to MPS (100 %) by short-term G1 (1 nM) in siControl and siRNA cells. Data are presented as mean ± SEM (n = 4-8) and analysed by unpaired t-test. Significance: (*) P < 0.05, (X) P > 0.05.

126 considerable variability in the results but, overall, neither siControl nor GPR30 siRNA treatment changed nNav1.5 mRNA levels in MDA-MB-231 cells significantly (P > 0.05; n = 3; Figure 3.28).

3.3.3.7.2 VGSC13 subunits VGSC13 subunits were previously reported to have a role in cell adhesion (Isom, 2002). The mRNA expression levels of the known four VGSC0 subunits ((1-4) were investigated. In both normal MDA-MB-231 and MCF-7 cells 03 mRNA was not expressed (n = 3; Figure 3.29A & B). MDA-MB-231 cells expressed 01, 02 and 134 mRNA; 01 and 134 occurred at significantly lower levels than in MCF-7 cells (P < 0.01; n = 3; Figure 3.29A & B) and 02 at slightly higher levels than MCF-7 cells (P > 0.05; n = 3; Figure 3.29A & B). Each cell line was then re-analyzed for relative expression of 132 and 04 mRNA expression normalized to 131 levels. In both MDA-MB-231 cells and MCF-7 cells, 02 and 04 mRNAs were expressed at significantly lower levels than 01 (P < 0.001; n = 3; Figure 3.29C & D, respectively). Thus, 01 mRNA was expressed at the highest levels compared to other 0 subunits in both cell lines, as found by Chioni (2007). VGSC131 subunit mRNA expression was analysed in GPR30 siRNA and over- expressing GPR30-14 cells. It was found that neither GPR30 siRNA nor GPR30 over- expression affected VGSC131 subunit mRNA levels in MDA-MB-231 cells (P > 0.05; n = 3; Figure 3.30 and Figure 3.31, respectively).

3.3.4 Possible role of PICA in short-term effect of estrogen on MDA-MB-231 cell adhesion Previously, GPR30 was reported to activate signaling pathways involving cAMP, ERK1/2 and PKA (Hsieh et al., 2007; Pedram et al., 2006). Here, possible involvement of PKA in the short-term estrogen effects on adhesion was investigated by a using PKA inhibitor (PKI). Cells were first pre-treated with PM (10 ptM) for 24 h and their adhesion was measured. When compared to control (normal growth medium), PKI treatment increased MDA-MB-231 cells adhesion significantly from 8.2 ± 0.3 kPa to 9.7 ± 0.7 kPa by 18 ± 8 % (P < 0.05; n = 6-8; Figure 3.32A & B).

127 A. 0

o Z c.) Fe PFa (7) Z

nNav1.5 4— 219 nt

I-actin =4— 359 nt 1 2 3

B. X X

47. P2 0

U) 0. 0)

ZN E LP.

co

Control siControl siControl siRNA

Figure 3.28: siControl (non-targeting siRNA) and GPR30 siRNA did not change nNav1.5 mRNA levels in MDA-MB-231 cells.

(A) Typical gel image of PCR products of nNav1.5 and 13-actin in siControl (lane 1), siRNA (lane 2) and no template control (NTC; lane 3). (B) Relative nNav1.5 mRNA levels in siControl (normalized to non-transfected control) and siRNA (normalized to siControl) cells. Data are presented as mean ± SEM and analysed by unpaired t-test after quantification by 2-AACt method where nNav1.5 mRNA was normalized to I3-actin (n = 3). (X) P > 0.05.

128 A. B. 231 MB-

A- u. O 1— e) iv MD

• z t la re

voscrsi .4— 379 nt ( n io

VGSC132 • • 410 nt ress

VGSC133 (363 nt)

OM. RNA exp

4... 459 nt VGSCP4 -4— 310 nt 3 m

13-actin • 359 nt VGSCI 132 2 3 131 133 134

D. 100

0

a it**

E a)

ea CC

111 p2 P3 P1 P3

Figure 3.29: VGSC1 subunit expression in MDA-MB-231 and MCF-7 cells.

(A) Typical gel electrophoresis images of PCR products for VGSCf31-4 and (3-actin (normalizing gene) from MDA-MB-231 (lane 1) and MCF-7 (positive control; lane 2) cells show bands at expected sizes. NTC: no template control (lane 3). (B) Comparative levels of VGSC(31-4 subunits in MDA-MB-231 and MCF-7 cells. VGSCI3 subunit mRNA levels were normalized to 13-actin levels and are presented relative to levels in MCF-7 cells (100 %). (C) VGSC(32-4 subunit mRNA levels in MDA-MB-231 cells relative to VGSCI31 subunit (100 %). (D) VGSC(32-4 subunit mRNA levels in MCF-7 cells relative to VGSCP1 subunit (100 %). Data are presented as mean ± SEM and analysed by 2-AAct method (n = 3). Significance: (**) P < 0.01, (***) P < 0.001.

129

A. IT! a 0 z c) 2 x 1— 7) 'F) Z

VGSCf31 :11:314— 379 nt

JI-actin 359 nt

1 2 3

B. 2.5 - w X X > r r Ts' e C .O 7w€ ) 1.5 e Q. x 0 a zre E a 0.5 - C) ca CO > Control siControl siControl siRNA

Figure 3.30: siControl (non-targeting siRNA) and GPR30 siRNA did not change VGSCD1 mRNA levels in MDA-MB-231 cells.

(A) Typical gel image of PCR products for VGSCI31 and [3-actin in siControl (lane 1) and siRNA (lane 2) cells. NTC: no template control (lane 3). (B) Relative VGSC131 subunit mRNA expression in siControl (relative to non-transfected control) and siRNA (relative to siControl). Data are presented as mean ± SEM and analysed by unpaired t-test. Data was quantified by using 2- AAct method and 0-actin was the normalizing gene (n = 3). (X) P > 0.05.

130

A.

a) .zr

4-. M o_ IY 0 E 0. (.9 Z

VGSCril =II-- 379 nt

13-actin =MI— 359 nt 1 2 3 B. ic 6 - X X

co • 11/ 6

.2 4 - (0

O.▪ 3 - X

2 - cc E • 1 - (..) o Fl Control Empty-vector Empty-vector GPR30-14

Figure 3.31: Empty-vector and GPR30 transfection did not affect VGSCI1 mRNA expression in MDA-MB-231 cells.

(A) Typical gel images of PCR products for VGSC131 and 13-actin in empty-vector (lane 1) and GPR30-14 (lane 2) cells. NTC: no template control (lane 3). (B) Relative VGSCf31 subunit mRNA expression in empty-vector cells (relative to non-transfected control) and GPR30-14 (relative to empty-vector) cells. Data are presented as mean ± SEM and analysed by unpaired t-test. Data was quantified by using 2-6'Act method and 13-actin was the normalizing gene (n = 3). (X) P > 0.05.

131

A. B.

1 2 -

2 -

0

Control PKI Control PKI

C. 12 - X X

10 -

713 8 - a

O. 6 - Z 0 4 -

2 -

0 I PKI MPS E2

24h 10-m in

Figure 3.32: Long-term treatment with PKA-inhibitor increased MDA-MB-231 cell adhesion and blocked short-term effect of estrogen.

(A) Adhesion in control (normal growth medium) and 24 h PKA inhibitor (PM) treatment. (B) Change in DNP (ADNP, %) after 24 h PKI treatment normalized to control. (C) DNP values in MPS and short-term E2 (10 nM) after 24 h pre-treatment with PKI (white bar). Data are presented as mean ± SEM and analysed with Mann-Whitney rank sum test (A & C) and un-paired t-test (B) (n = 6-8). Significance: (*) P < 0.05, (X) P > 0.05.

132 PKI pre-treated cells were used in short-term E2 (10 nM) treatments as before (i.e. 10 minutes in MPS and 10 minutes in E2). The PKI pre-treatment blocked the effect of E2 on adhesion: DNP = 9 ± 1.4 kPa in MPS and 8 ± 0.9 kPa in PKI+E2 (P > 0.05; n = 6; Figure 3.32C). These data indicated that PKA was involved in E2 signaling through GPR30 in MDA-MB-231 cells, in controlling adhesion.

3.4 Discussion

The main findings of this chapter were as follows: (1) Strongly metastatic human MDA-MB-231 BCa cells expressed GPR30 mRNA and protein; the latter was localised in both PM and cytosol. (2) Acute and short-term E2 treatment decreased adhesion of MDA-MB-23 I cells; this effect was dose dependent (1-100 nM) and fully reversible. (3) Co-treatment with TTX inhibited the effect of E2 on adhesion suggesting involvement of VGSC (nNav1.5) activity. (4) Use of membrane-impermeable E2 (E2-BSA) significantly decreased adhesion of MDA-MB-231 cells dose dependently (1-100 nM), indicating possible involvement of a receptor in PM. (5) GPR30-specific 01 compound significantly decreased adhesion of MDA-MB- 231 cells dose dependently (0.1-100 nM), suggesting GPR30 as the receptor. (7) Over-expression of GPR30 mRNA and protein in MDA-MB-231 cells led to protein upregulation only internally, and did not change the short-term effect of E2 on adhesion. (8) siRNA knocked down both GPR30 mRNA and protein by 50 and 70 %, respectively; this inhibited the effect of both E2 and 01 on adhesion, confirming GPR30 as the receptor activated by E2 in MDA-MB-231 cells. (9) Knock-down of GPR30 did not change mRNA levels of nNav1.5 and VGSC 31 subunit, predominant isoforms in MDA-MB-231 cells. (10) Pre-treatment with a PKA inhibitor (PKI) suppressed the short-term effect of E2 on adhesion, suggesting that PKA could be an intermediary in the non-genomic effects of E2 on MDA-MB-231 cell adhesion.

133 3.4.1 Short-term effect of estrogen on MDA-MB-231 cell adhesion: Involvement of VGSCs Steroid hormones were previously reported to regulate adhesion molecules. For example, estrogen and tamoxifen (partial estrogen antagonist) were found to reduce surface expression of integrins in human squamous carcinoma cells (Nelson et al., 2008). Progesterone increased phosphorylation of FAK and focal adhesion proteins paxillin and talin in human BCa cells (Lin et al., 2000). In these studies, a wide range of concentrations were from as low as 1 nM (Lin et al., 2000) to 1-5 iuM (Nelson et al., 2008); also, treatment times could last more than 20 h. In the present study, E2 (10 nM) decreased MDA-MB-231 cell adhesion after both acute (0-10 minutes) and short-term (10-20 mintues) treatments. Previous studies of short-term functional effects of estrogen in cancer cells mostly involved measurements of intracellular Ca2+, nitric oxide and cAMP production (Stefano et al., 2000; Zivadinovic et al., 2005). The present study is the first report of a functional non-genomic effect of estrogen on cancer cell behaviour. An interesting finding in the present study is the involvement of VGSCs in the short-term effect of estrogen on BCa cell adhesion. VGSCs were previously reported to potentiate cancer cell behaviour including motility, migration and invasion (Brackenbury et al., 2007; Brackenbury and Djamgoz, 2007; Fraser et al., 2003, 2005). Increased adhesion by TTX (10 µM) treatment found in the present study (Figure 3.5), confirmed previous reports that VGSCs could have a role in cancer cell adhesion (Chioni, 2007; Palmer et al., 2008). Importantly, patch clamp recordings revealed an increased VGSC activity in MDA-MB-231 cells after acute E2 treatment (Fraser et al., 2008). This suggested a possible involvement of VGSCs in short-term effects of E2 on adhesion. Indeed, co-application of E2 with TTX to TTX pre-treated cells failed to produce an effect on adhesion (Figure 3.6). This strongly indicated VGSC-dependence of the short- term E2 response in MDA-MB-231 cells. How VGSCs could alter adhesion is not currently known. However there are some possible mechanisms to be proposed which involve association with cell adhesion molecules (CAMs) such as integrins, neurofascin and Nr-CAM, and cytoskeletal proteins such as ankyrin-G (Hedstrom et al., 2007; Isom, 2002; Jenkins and Bennett, 2001). Interestingly, recent works stated that VGSCO subunits could behave like CAMs (Isom, 2002). In line with this, knock down of VGSCI31 by siRNA decreased cell adhesion in weakly/non-metastatic MCF-7 cells making them behave more like the metastatic BCa

134 cell line MDA-MB-231 (Chioni, 2007). Importantly, autoregulation mechanism(s) of VGSCs also were reported where VGSCa activity in cancer cells was up-regulated in a positive-feedback mechanism (Brackenbury and Djamgoz, 2006). From this, it can be suggested that VGSC13 subunits may also be modulated by VGSCa, which could provide one way VGSCs regulate cell adhesion. Further work is required to evaluate this possibility.

3.4.2 Identity of the receptor responsible for the non-genomic estrogen regulation in MDA-MB-231 cells: Pharmacological evidence The effects of E2 on VGSC activity and adhesion in MDA-MB-231 cells were generated within a few minutes. This suggested a fast, non-genomic modulation by E2. Previously, regulation of ion channels by E2 was reported (e.g. Korovkina et al., 2004). Possibility of direct binding of E2 to nNav1.5 (dominant VGSC subtype in MDA-MB-231 cells) was tested by patch clamp recordings in EBNA-nNav1.5 cells. These cells express a great amount functional nNav1.5 protein (Fraser et al., 2005; Onkal et al., 2008) and very low levels of GPR30 protein compared to MDA-MB-231 cells (Figure 3.33). No change in VGSC activity was observed after E2 treatment, indicating that E2 did not induce VGSC activity by direct binding to the channel (Fraser et al., 2008). Three different receptor possibilities have been suggested for the non-genomic E2 signaling: (1) Classical estrogen receptors expressed intracellularly or in PM (e.g. mER, Razandi et al., 1999); (2) new estrogen receptors in PM (e.g. ERX; Toran-Allerand et al., 2002); (3) other proteins including G-protein-coupled receptors (GPCRs; especially GPR30), ion channels and growth factor receptors (epidermal growth factor (EGF), insulin growth factor; Normanno et al., 2005; Revankar et al., 2005). MDA-MB-231 cells are known to be ERa-negative and absence of its mRNA was also confirmed here (Figure 3.6). There is increasing number of studies showing GPR30 expression in BCa tissues and cells, including MDA- MB-231 cells (Ahola et al., 2002; Carmeci et al., 1997; Otto et al., 2008; Smith et al., 2007; Thomas et al., 2005). By using specific and previously published primers (Thomas et al., 2005), GPR30 mRNA expression in MDA-MB-231 cells was confirmed (Figure 3.7). Using specific antibodies against GPR30 its protein expression was shown at a lower level than MCF-7 cells as reported previously (Filardo et al., 2002; Revankar et al., 2005). In the present study, the data from Western blots and immunocytochemistry were consistent (Figures 3.8 and 3.9). Confocal microscopy following immunocytochemistry

135 stably transfectedwithnNav1.5(EBNA-nNav1.5), usinganti-GPR30anda-actinin antibody (loadingcontrol). Figure 3.33:EBNA-nNav1.5cellsexpressedlowlevelsofGPR30protein. Western blotof30ligtotalproteinperlanefrom MDA-MB-231cellsandEBNA a-actinin GPR30

MDA-MB-231

EBNA-nNav1.5 1— 4 — 40kDa 100 kDa 136 revealed expression of GPR30 protein in both PM and cytoplasm (Figure 3.10). Membrane-impermeable, BSA-conjugated E2 (E2-BSA) was previously used to identify a plasma membrane generated response (Filardo et al., 2007; Hsieh et al., 2007). Use of E2-BSA in this study showed significant reduction in adhesion only at low concentrations (1 nM; Figure 3.11A). Interestingly, this effect was not as big as the effect seen with E2 alone (Figure 3.4). This could be due to two main reasons: (1) E2 activated GPR30 both in PM and cytoplasm whereas E2-BSA was selective for GPR30 in PM, and (2) the large BSA protein conjugated to E2 in E2-BSA suppresses its binding affinity to GPR30. Conversely, patch clamp recordings revealed that application of E2-BSA (10 nM) was enough to increase VGSC activity as much as E2 would do (Fraser et al., 2008). This suggested that activation of GPR30 only in PM was sufficient to regulate VGSC activity. Further experiments are needed to evaluate the relative roles of GPR30 in PM and cytosol in controlling adhesion. Although the results with E2-BSA would support GPR30 as the estrogen receptor in PM of MDA-MB-231 cells, it did not answer the question: 'Is it GPR30 specifically that E2 and E2-BSA acts on to regulate adhesion in these cells?' In this regard, a specific agonist for GPR30, called the G1 compound, was reported (Bologa et al., 2006). In the present study, short-term treatment with G1 compound (1 nM) of MDA-MB-231 cells significantly reduced adhesion in the same way as E2 (Figure 3.11B). Patch clamp recordings also showed increased VGSC activity with G1 (Fraser et al., 2008). This indicated that GPR30 is the estrogen receptor in MDA-MB-231 cells and its short-term activation regulates cell adhesion via VGSC.

3.4.3 Effects of GPR30 over-expression on MDA-MB-231 cells Plasmid transfection led to over-expression of GPR30 mRNA and protein in MDA-MB- 231 cells (Figures 3.12 and 3.13) without altering basal adhesion (Figure 3.14). Since endogenous GPR30 levels in MDA-MB-231 cells were low compared to MCF-7 cells, effect of E2 on adhesion was initially expected to be increased in GPR30-14 cells. Surprisingly, E2 reduced adhesion in GPR30-14 cells (Figure 3.15) to the same extend as in MDA-MB-231 cells (Figure 3.3). Importantly, confocal microscopy and digital image analyses revealed that the over-expressed protein in GPR30-14 cells was mainly intracellular rather than in PM (Figures 3.16-3.18).

137 GPR30 expression in endoplasmic reticulum was previously reported in transfection studies (Revankar et al., 2005). Cellular localization is important for the activity of G-proteins and the secondary messenger (e.g. cAMP) signaling (Cooper and Crossthwaite, 2006; Ostrom et al., 2002). Although higher intracellular GPR30 protein was achieved by over-expression, no further increase in effect of E2 on adhesion or VGSC activity was observed (Fraser et al., 2008). This was unexpected since increased intracellular GPR30 was previously shown to increase signaling pathways (e.g. ERK1/2; Filardo et al., 2000) which could lead to cellular activities and ion channel regulation (Raz et al., 2008). A plausible explanation for the lack of an increase in the effect seen in the present study could reside in activation of signaling molecules, such as adenylate cyclase (AC) in a compartmentalized manner. For example, detergent-free membrane fractionation revealed that AC is expressed in both caveolin-rich and non-caveolin domains of PM (Ostrom et al., 2002). Expression of different isoforms of AC (AC3, AC5 and AC6) was shown to regulate its localization and cAMP production in response to GPCR activation (e.g. P-adrenergic receptors; Ostrom et al., 2002). Stimulation of GPR30 and downstream of cAMP pathway would lead to activation of PKA and its different regulatory and catalytic subunits, of which may be activated differentially by various components of G-proteins (Ghil et al., 2006). It would follow that G-protein signaling itself (i.e. GPR30 in the present study) could be compartmentalized. Thus, activation of GPR30 in PM may lead to a specific downstream signaling that is not shared by internalised GPR30 protein. This would explain E2 regulating adhesion and VGSC activity at the same level in both MDA-MB-231 and GPR30-14 cells where the only difference is the higher expression of intracellular GPR30 protein in the latter.

3.4.4 Silencing GPR30 in MDA-MB-231 cells In order to further investigate GPR30 as the candidate estrogen receptor in MDA-MB-231 cells, specific siRNA sequences were used where both mRNA and protein expression were knocked-down by 50 and 70 %, respectively (Figures 3.20 and 3.21, respectively). This resulted in inhibition of the effect seen with both E2 and G1 on adhesion (Figure 3.26 and 3.27, respectively). These results further suggested that GPR30 was the likely receptor mediating the short-term effect of E2 on adhesion of MDA-MB-231 cells. Unlike the effects on adhesion, however, patch clamp recordings did not show any change in VGSC activity after GPR30 siRNA (Fraser et al., 2008). One explanation of

138 this could be the changes in subcellular distribution of GPR30 protein after siRNA transfections, as in the case with over-expression (Figures 3.22-3.24). This was analyzed by immunocytochemistry followed by confocal microscopy and digital image analyses. Indeed, as predicted, the relative internal GPR30 immunoreactivity was decreased whilst total protein levels in PM remained the same. A reason for this could be possible changes in protein localization signals (Hawkins et al., 2003; Kanno and Fukuda, 2008; Wagstaff and Jans, 2006) or lipid modifications (e.g. palmitoylation; Escriba et al., 2007). As hypothesized for GPR30-14 cells, the lack of an effect with siRNA on effect of E2 on adhesion and VGSC activity could be due to differential signaling messengers activated via PM and intracellular GPR30 protein. The phenomenon of possible compartmentalization of GPR30 signaling should be further evaluated.

3.4.5 A model for GPR30 involvement in non-genomic estradiol signaling and metastatic cell behaviour From the data collected in the present study, together with previous evidence, a model can be proposed (Figure 3.34). As presented here, and reported previously, GPR30 is expressed both in PM and internally in MDA-MB-231 cells (Matsuda et al., 2008; Otto et al., 2008; Thomas et al., 2005). Upon activation by E2 (or G1), GPR30 associates with G-protein subunits a and 137 complex (Luttrell, 2003; Prossnitz et al., 2008b). Activation of either or both of these subunits initiates the downstream signalling pathways such as AC leading to accumulation of cAMP and activation of PKA (Hsieh et al., 2007; Thomas et al., 2005; Figure 3.34). PKA was shown to affect VGSCs in a complex way where channel properties were regulated in electrophysiological recordings (Baba et al., 2004; Hallaq et al., 2006; Zhou et al., 2002a). For example, Nav1.5 was found to have phosphorylation sites for PKA (Murphy et al., 1996), and tyrosine phosphorylation of Nav1.5 was reported to cause a depolarizing shift in steady-state inactivation of the channel (Ahern et al., 2005). VGSCs could also undergo autoregulation by positive feedback mechanism following post-transcriptional and translational regulations such as phosphorylation (Brackenbury and Djamgoz, 2006). Direct phosphorylation of VGSCs (e.g. Nav1.5 and Nav1.7) by PKA could increase the channel expression in PM of BCa and PCa cells (Chioni, 2007; Brackenbury and Djamgoz, 2006). Interestingly, Na+ influx via VGSCs

139 VGSC

GPR30 VGSCa PKA, p _ Adhesion (nNav1.5) _ - ► (DNP)

Integrins

Figure 3.34: A hypothetical model of non-genomic estrogen regulation of VGSCs and adhesion in MDA-MB-231 cells via GPR30.

Estrogen (E2) signalling through GPR30 in plasma membrane (PM) and cytosol is presented. Downstream signalling involves PKA which can increase VGSC activity (nNa1.5 in MDA-MB-231 cells) and trafficking to PM. VGSCs could change adhesion via different mechanisms involving interactions with cell adhesion molecules. Here VGSC-induced PKA activity and further modulation of adhesion molecules (X) such as VGSC13 and integrins are illustrated for MDA-MB-231 cells. Adhesion is measured as detachment negative pressure (DNP) by single-cell measuring apparatus. PKA1 and PKA2 could consist of different or the same PKA subunits.

140 was also shown to directly promote cAMP production and increase PKA activity (Cooper et al., 1998; Murakami et al., 1998). Thus, a mutual regulatory interaction between VGSCs and PKA is present. This would indicate that PKA activation by GPR30 could regulate VGSCs; and increased VGSC activity could further increase the PKA activity (Figure 3.34). PKA have different regulatory subunits and these could be differentially activated (Taylor et al., 2005) Whether PKA activated by GPR30 (Figure 3.34, PKA1) and/or VGSCs (Figure 3.34, PKA2) is the same subunit/group of PKA is not known. Accordingly, activation of different subgroups of PKA (i.e. PKAI and/or PKA2) could lead to different downstream signaling. The fmdings from the present study are consistent with involvement of PKA in GPR30-induced VGSC activity and reduced adhesion (i.e. DNP values; Figure 3.34). This could involve many signalling mechanisms (X, Figure 3.34) including modulation of adhesion molecules, VGSCI3 and integrins being the two important ones expressed in MDA-MB-231 cells (Mitsushima et al., 2006; Patterson et al., 2000; Spurzem et al., 2002). Increased PKA activity following GPR30 and/or VGSC activation could modulate these molecules and reduce adhesion (Figure 3.34). Importantly, VGSCa and [3 subunits could regulate each other's activity and expression (Chioni, 2007; Pertin et al., 2005). Since VGSCI3 subunits could behave like adhesion molecules (CAMs; Isom, 2002; Malhotra et al., 2000), their regulation by VGSCa could also change adhesive properties. Consistent with this, knock down of VGSCO1 increased Nav1.5 expression in PM and decreased adhesion in MCF-7 cells (Chioni, 2007). Signalling via GPR30 has also been reported to cross-talk with growth factor receptors such as EGF receptor (EGFR) (Dorsam and Gutkind, 2007; Filardo et al., 2000; Prossnitz et al., 2008a). VGSCs could be regulated by EGF (Ding et al., 2008; Liu et al., 2007; Uysal-Onganer and Djamgoz, 2007); thus, GPR30-EGFR cross-talk could be another mechanism whereby VGSCs are regulated by E2 in MDA-MB-231 cells. The possibility of this mechanism should be investigated by using EGFR blockers (e.g. AG1478) or activators (e.g. EGF) together with E2 to evaluate possible changes in VGSC activity and MCBs (e.g. adhesion). An interesting finding in the present study was that both over-expression and silencing of GPR30 affected only the internal but not PM GPR30. G-proteins were previously reported to shuttle between PM and internal compartments (Chisari et al.,

141 2007; Marrari et al., 2007). Although reports exist where GPR30 overexpression in different cell types could localize in both PM and cytosol (Revankar et al., 2005; Thomas et al., 2005), the exact reason and mechanism for this type of a differential expression is unknown. However, changes in membrane lipid structures are among proposed mechanisms for GPCR trafficking (Escriba et al., 2007). Different AC isoforms (nine membrane-associated and one soluble) are known to exist (Sunahara and Taussig, 2002) and activation of one versus another could produce differential effects (Cooper and Crossthwaite, 2006; Ostrom et al., 2002). Compartmentalized signalling was also reported for PKA, ERK, Ras and MAPK (Mor and Philips, 2006).

3.4.6 Concluding remarks The present study provided new information regarding differential role of GPR30 in PM and cytosol on VGSC activity and adhesion: the former being regulated by PM GPR30 and the latter being regulated by internal GPR30, and the downstream signalling involving PKA. Further studies are required to clarify the following: (1) Possible expression of different AC/cAMP/PKA subtypes in MDA-MB-231 cells. (2) Effects of different AC/cAMP/PKA subtypes on VGSC activity and adhesion and (3) Alternative signalling pathways (e.g. EGFR) associated with E2 signalling in BCa, in relation to VGSCs and adhesion.

142 Chapter 4

LONG-TERM EFFECTS OF 1713-ESTRADIOL ON

MDA-MB-231 CELLS: VOLTAGE-GATED SODIUM

CHANNEL EXPRESSION AND ADHESION

143 4.1 Introduction

Voltage-gated sodium channels (VGSCs) have been shown to have potential significance to metastatic disease. VGSC up-regulation was correlated with metastatic cell behaviours (MCBs) in vitro and lymph node metastasis in vivo (Fraser et al., 2005; Laniado et al., 1997). VGSC isoforms Nav1.7 and Nav1.5 were reported to promote invasion of prostate cancer (PCa) and breast cancer (BCa) cells, respectively (Brackenbury et al., 2007; Diss et al., 2005). Nav1.5 in its 'neonatal' splice form, nNav1.5, was reported to be highly expressed in strongly metastatic MDA-MB-231 BCa cells (Fraser et al., 2005). Interestingly, this channel was not functional in weakly/non-metastatic MCF-7 cells, although internalised VGSC protein was present (Fraser et al., 2005). The fact that MDA- MB-231 cells are ERa-negative and MCF-7 cells are ERa-positive would suggest a possible relationship between estrogen and VGSC expression. Importantly, bioinformatics confirmed putative estrogen response element (ERE) half-sites (ERE1/2) and Spl binding site in Nav1.5 promoter (J.K.J Diss, unpublished data; Appendix I). Regulation of ion channel expression by steroid hormones has been studied but there is limited information on the underlying mechanisms (Borg et al., 2002; Nakajima et al., 2008; Tsang et al., 2004a; Zakon, 1998). As shown in Chapter 3, MDA-MB-231 cells express the novel estrogen receptor GPR30 both intracellularly and in plasma membrane (PM; Prossnitz et al., 2008a; Revankar et al., 2005). Activation of this receptor was shown to lead to downstream signaling involving cAMP, PKA, MAPK and ERK1/2 (Hsieh et al., 2007; Pedram et al., 2006; Prossnitz et al., 2008b; Razandi et al., 2000a). These signaling mechanisms could activate transcription factors, such as CREB and NFiB (Carlstrom et al., 2001; Hirano et al., 2007; Szego et al., 2006) which could lead to genomic modulation of ion channel expression (Kye et al., 2007; Shang et al., 2008). In the previous study (Chapter 3), MDA-MB-231 cells were shown to give a fast/non-genomic response to estrogen, i.e. 1713-estradiol (E2). The present study was designed to investigate whether E2 would have any long-term/genomic effect on nNav1.5 in MDA-MB-231 cells, again, with an emphasis upon their adhesiveness.

144 4.2 Aims and scope

The general aim of this study was to investigate possible long-term/genomic effects of estrogen on nNav1.5 expression and cellular adhesion, using again the MDA-MB-231 cell line model. The specific aims were as follows: (1) To investigate changes in nNav1.5 expression (mRNA and protein) after long- term (24 h) treatment with different doses of E2 (1 - 100 nM); (2) To study possible time-dependence (2 - 24 h) of the effect of E2 on nNav1.5 mRNA expression; (3) To study possible effects of long-term E2 treatment on cellular adhesion; and (4) To investigate possible involvement of GPR30 signaling in any long-term effect, using G1 compound and GPR30 over-expressing MDA-MB-231 cells.

4.3 Results

Effects of long-term E2 treatment on VGSC expression in MDA-MB-231 cells were investigated by measuring mRNA and protein levels. Possible functional consequences were studied by measuring cell adhesion as a key metastatic cell behaviour. mRNA levels were measured by real-time RT-PCR, protein levels were measured by Western blotting and adhesion was measured by SCAMA, as described in Chapter 2.

4.3.1 Long-term effects of estrogen on nNav1.5 mRNA expression in MDA-MB-231 cells

4.3.1.1 Control experiments In order to minimize the amount of E2 in growth medium, MDA-MB-231 cells were conditioned in 5 % charcoal-stripped serum (CS-FBS) supplemented medium for 3 days prior to long-term treatments. Possible effects of CS-FBS on nNav1.5 mRNA expression were investigated. It was found that 3-day culture in CS-FBS medium did not affect nNav1.5 mRNA expression in MDA-MB-231 cells when compared to normal growth medium supplemented with 5 % FBS (P > 0.05; n = 7-10; Figure 4.1). Since DMSO was the solvent for E2, its effect on nNav1.5 mRNA expression in MDA-MB-231 cells was also investigated. The concentration of DMSO used in these experiments was between 10-8 and 10-5 % (v/v in CS-FBS medium). When compared to the control levels in CS-FBS medium (100 %), 10-8 and 10-6 % DMSO decreased nNav1.5

145

A.

u) m La_

nNav1.5 4— 219 nt

f3-actin 4- 359 nt 1 2 3

B.

>1 1.5 - X "4= r" co ..., C) ...... L a •o._ 1.0 - N co 22 Q. x cu < 0.5 - Z Et E it? 3 as 0.0 I I z a FBS CS

Figure 4.1: Conditioning in CS-FBS medium for 3 days did not affect nNav1.5 mRNA expression in MDA-MB-231 cells.

(A) Typical gel electrophoresis of PCR products for nNav1.5 and 13—actin in MDA-MB- 231 cells cultured in normal (FBS) medium (lane 1) and CS-FBS medium for 3 days (lane 2). NTC: no template control (lane 3). (B) nNav1.5 mRNA expression in MDA-MB-231 cells in CS-FBS medium (CS) relative to FBS medium. Data are presented as mean ± SEM (n = 7-10) and analyzed by unpaired t-test. (X) P > 0.05.

146 mRNA levels significantly to 26 ± 9 and 45 ± 10 %, respectively (P < 0.01; n = 3-10; Figure 4.2). 10-7 % and 10-5 % DMSO did not affect nNav1.5 mRNA expression (P > 0.05; n = 7; Figure 4.2). This suggested that nNav1.5 mRNA regulation in MDA-MB-231 cells was partially sensitive to DMSO concentration, and this should be taken into account when analyzing any effect of E2.

4.3.1.2 Dose dependence Possible dose-dependence of 24 h treatment with E2 (0.1, 1, 10 and 100 nM) on nNav1.5 mRNA expression in MDA-MB-231 cells was investigated after 3-day growth in CS-FBS medium. The data were compared to levels in corresponding DMSO controls (i.e. 10-8, 106, % DMSO, respectively for each E2 concentration). There was some variability in the effects but dose-response relationship was clearly bell-shaped, the effect of E2 initially increasing with concentration, then decreasing, typical of steroid hormones (e.g. Diss et al., 2007; Lavigne et al., 2008; Tsai et al., 2001). Thus, 0.1, 1 and 10 nM E2 increased nNav1.5 mRNA by 7 ± 4 (P > 0.05), 13 ± 2 (P < 0.001) and 8 ± 4 folds (P > 0.05), respectively; whereas 100 nM E2 did not have any effect (P > 0.05; n = 3-9; Figure 4.3). Importantly, at 1 nM E2 (the only dose having a significant effect) the corresponding DMSO concentration (i.e. le % v/v) did not have any effect on nNav1.5 mRNA (Figure 4.2). Thus, 1 nM E2 was selected as working concentration in this chapter.

4.3.1.3 Time dependence The effect of E2 (1 nM) on nNav1.5 mRNA expression in MDA-MB-231 cells was analyzed at different time points: 2, 12 and 24 h, after 3 days conditioning in CS-FBS medium, as before. Possible effects of DMSO control were also investigated simultaneously. When compared to control (CS-FBS), the nNav1.5 mRNA expression in DMSO controls were 1 ± 1, 2 ± 0.4 and 1 ± 0.3 folds higher after 2, 12 and 24 h treatments, respectively (n = 3-9; Figure 4.4A). None of these changes was significant (P > 0.05) due to high variability of data, especially after 2 h (Figure 4.4A). Treatments with E2 for 2 and 12 h did not affect nNav1.5 mRNA expression; when compared to DMSO controls (P > 0.05; n = 3-9; Figure 4.4B). However, after 24 h, E2 increased nNav1.5 mRNA expression significantly by 13 ± 2 folds (P < 0.001; n = 9;

147 o 0 0 0 A. u) U) U) cn 2 2 2 2 cn C) CI Cl CI CO e. Ne. •-i..) -4..' ur 0 0 0 C.) U)0 ,-a 0, o, ,o z1- nNav1.5 219 nt

13-actin C3=11Q=M4-- 359 nt 1 2 3 4 5 6

B. 3.0 -

ive) t 2.5 - la re ( 2.0 - ion

ress 1.5 -

NA exp 1.0 - R *** m

5 ** 1. 0.5 - Nav n

0.0 1 1 1 I 1111 I 1 1111111 1 1 1 1 1 111 1 1 1 1 1 111 10-8 10-6 10-5

DMSO rio

Figure 4.2: Long-term effect of DMSO treatment on nNav1.5 mRNA expression in MDA-MB-231 cells was dose dependent.

(A) Gel electrophoresis of PCR products form nNav1.5 and 3-actin in MDA-MB-231 cells cultured in CS-FBS medium for 3 days (lane 1) and after 24 h treatment with increasing DMSO concentrations (10-8, 10-7, 10-6, and 10-5 %; lanes 2-5, respectively). NTC: no template control (lane 6). (B) nNav1.5 mRNA levels in DMSO treatments relative to CS-FBS (horizontal dashed line). Data are presented as mean ± SEM (n = 3- 10) and analyzed by unpaired t-test. Significance: (**) P < 0.01, (***) P < 0.001.

148

A. CI CI Cl Cl N N ILI N LLI e eeN LLI e r so c; o - c) 0 0 t- .t- ▪ •t- • •a- n-0 li

nNav1.5 1:361iiiia.4114ZEZI11- 219 nt 3-actin cl:ILIZaL;1;;E:1:3==4— 359 nt 1 2 3 4 5 6 7 8 9

B. *** 15 - ive) t la

re 12 - ( ion

ss 9 - re xp

6 - NA e R

5 m 3 - 1. Nav

n 0 • • • •••••2 • • • • • • • • • • • • UV§ • • • • • • •• 0.1 1 10 100 E2 [nM]

Figure 4.3: Long-term effect of E2 treatment on nNav1.5 mRNA expression in MDA-MB-231 cells was dose dependent (bell-shaped).

(A) Typical gel electrophoresis of PCR products for nNav1.5 and I3-actin in DMSO (B) controls (10-8, 10-7, 10-6 and 10-5 %; lanes 1, 3, 5 and 7, respectively) and after 24 h E2 treatments (0.1, 1, 10 and 100 nM; lanes 2, 4, 6 and 8, respectively). NTC: no template control (lane 9). (B) nNav1.5 mRNA expression after 24 h E2 treatments relative to DMSO controls (horizontal dashed line) 13—actin was the normalizing gene. Data are presented as mean ± SEM (n = 3-9) and were analyzed by unpaired t-test. Significance: (***) P < 0.001.

149

2.0

A. e) iv t la 0

(re 1.5 - n io

MEM ress 1.0 - xp 0 NA e R 0.5 - 5 m 1. Nav

n 0.0

2 12 24

Treatment time (h)

15 - ***

B. e) iv t 0 la 12 - (re n io 9 - ress

6 - RNA exp m 5 3 - 1. Nav n 0

2 12 24 Treatment time (h)

Figure 4.4: Long-term effect of E2 treatment on nNav1.5 mRNA expression in MDA-MB-231 cells was time dependent. (A) nNav1.5 mRNA expression after 2, 12, and 24 h DMSO (10-7 %) treatments relative to CS-FBS control (dotted line). (B) nNav1.5 mRNA expression after 2, 12 and 24 h E2 (1 nM) treatments relative to DMSO controls (horizontal dashed line). 0-actin was the normalizing gene. Data are presented as mean ± SEM and were analyzed by unpaired t- test (n = 3-9). Significance: (***) P < 0.001.

150 Figure 4.4B). Accordingly, 24 h treatments were used for the subsequent experiments described in this Chapter.

4.3.2 Long-term effects of estrogen on nNav1.5 protein expression in MDA-MB-231 cells Whole-cell protein extracts from MDA-MB-231 cells were obtained after 24 h treatments with E2 (1 nM). Western blotting on 80 ag protein by using the nNav1.5 specific antibody, NESOpAb (Chioni et al., 2005), revealed that there was no effect on total protein expression, when normalized to a-actinin expression (P > 0.05; n = 3; Figure 4.5).

4.3.3 Long-term effects of estrogen on MDA-MB-231 cell adhesion

4.3.3.1 Control experiments MDA-MB-231 cells were conditioned in CS-FBS medium for 3 days as before. Single- cell adhesion was measured as detachment negative pressure (DNP) in kPa as described in Chapter 2 (section 2.3.1). Possible effect of conditioning in CS-FBS medium on adhesion was measured and no effect was detected; DNP values were 9.9 ± 0.6 kPa in control (FBS) and 10.3 ± 0.6 kPa in CS-FBS (P > 0.05; n = 11; Figure 4.6A). A second control experiment was carried out in which the cells were treated with DMSO (1e %) for 24 h after 3 days growth in CS-FBS medium. The DNP was 10.3 ± 0.4 kPa in DMSO (n = 11; Figure 4.6B), which was not different from the value in CS- FBS (P > 0.05).

4.3.3.2 E2 treatment The adhesion of MDA-MB-231 cells was reduced significantly after 24 h E2 (1 nM) treatment, falling from 10.3 ± 0.4 to 8.8 ± 0.3 kPa (P = 0.01; n = 8-11; Figure 4.7A). When normalized to respective control (DMSO) medium, the reduction was 15 ± 3 % (P < 0.01; n = 8-11; Figure 4.7B).

4.3.4 Possible involvement of VGSC activity in the long-term effect of E2 on adhesion In order to investigate a possible role of VGSC expression/activity in the effect of E2 on adhesion, the effect of co-treatments with E2 (1 nM) + TTX (10 aM) were tested simultaneously with the E2 treatment (section 4.3.3.2). This co-treatment increased

151

A. 0

Ej 0 0

nNav1.5 — 220 kDa

a-actinin — 100 kDa

1 2

B. >cl) 2 •0 — ca a) L_ c 1.5 - .NO a) Lx1.0 -

715 2 0.5 - o. i0

co 0.0 z DMSO E2

Figure 4.5: Long-term E2 treatment did not affect nNav1.5 protein expression in MDA-MB-231 cells.

(A) Typical Western blots with 80 lig of total protein per lane extracted after 24 h treatment with DMSO %; lane 1) and E2 (1 nM; lane 2). NESO-pAb and anti-a- actinin antibodies were used. (B) Relative nNav1.5 protein expressions (normalised to a- actinin) post-treatment. Data are presented as mean ± SEMs (n = 3). Data were analysed by unpaired t-test.

152

A. 12 10 - I 8 -

6 -

4 -

2 -

0 I I FBS CS-FBS B.

12 -

10 -

8 -

6 -

4 -

2 -

0 I I CS-FBS DMSO

Figure 4.6: Long-term control treatments did not affect MDA-MB-231 cell adhesion measured as detachment negative pressure (DNP).

(A) Adhesion of MDA-MB-231 cells after 3 days growth in CS-FBS medium compared to FBS medium (control). (B) Adhesion after 24 h treatment with DMSO (10 "7 % v/v) compared to CS-FBS medium. Data are presented as mean ± SEMs and were analyzed by Mann-Whitney rank sum test (n = 11).

153 A. 12 -

10 - I **

8 -

a 6 - z 4 -

2 -

0 DMSO E2 B. 100 - ***

80 -

60 -

20 -

0 DMSO E2

Figure 4.7: Long-term treatment with E2 decreased MDA-MB-231 cell adhesion measured as detachment negative pressure (DNP).

(A) Adhesion after E2 (1 nM) treatment compared to DMSO control (10 -7 % WV). (B) Change in DNP values (ADNP; %) after E2 treatment when normalized to DMSO control. Data are presented as mean ± SEMs (n = 8-11), and were analyzed by Mann- Whitney rank sum test (A) and unpaired t-test (B). Significance: (**) P < 0.01, (***) P < 0.001.

154 adhesion to 10.5 ± 1.7 kPa, i.e. by 19 ± 2 % when compared to E2 treatment (8.8 ± 0.3 kPa); however, this effect was not significant (P > 0.05; n = 3-8; Figure 4.8). This was probably due to the increased variability of DNP values by the E2 + TTX co-treatment after 24 h; standard error of mean (SEM) increased from 0.3 in E2 to 1.7 in E2 + TTX (Figure 4.8). Nevertheless, adhesion after 24 h E2 + TTX treatment (DNP = 10.5 ± 1.7 kPa) was not different from the DMSO (10-7 %) control (DNP = 10.3 ± 0.4 kPa; P > 0.05; n = 3-8; Figure 4.8). This indicated that VGSC activity was involved in the long-term effect of E2 on MDA-MB-231 cell adhesion.

4.3.5 Possible involvement of GPR30 in the long-term effects of estrogen on MDA- MB-231 cells The possible involvement of a GPR30 driven mechanism in the long-term effects of E2 was studied in two ways: (1) using the GPR30-specific ligand Gl, and (2) using the GPR30-overexpressing MDA-MB-231 cells, GPR30-14 cells, from Chapter 3.

4.3.5.1 Long-term effects of G1 treatment on nNav1.5 mRNA expression in MDA- MB-231 cells The cells were treated with DMSO control (10-7 %, v/v in CS-FBS) as before. nNav1.5 mRNA expression did not change after 24 h treatment with 1 nM G1 (P > 0.05; n = 3; Figure 4.9).

4.3.5.2 Long-term effects of G1 treatment on cell adhesion

(i) MDA-MB-231 cells MDA-MB-231 cell adhesion was also measured after 24 h treatment with G1 (1 nM). When compared to the control (DMSO) value (9.1 ± 0.6 kPa), there was no effect on adhesion with G1 (DNP = 8.6 ± 1.1 kPa; ADNP = 6 ± 12 %; P > 0.05; n = 4-5; Figure 4.10A).

(ii) GPR30-14 cells MDA-MB-231 cells express low levels of GPR30 (sections 3.3.3.1 and 3.3.3.2). GPR30- 14 cells were developed to express GPR30 at around 200-fold higher levels than normal and empty-vector transfected MDA-MB-231 cells (section 3.3.3.5). Long-term (24 h) treatments with E2 and G1 (both at 1 nM) were repeated on these cells in order to test the possible role of GPR30 in long-term effects of E2.

155 A. X 14 ** X 12 -

OMVIA, 1 0 - ca 8 z o 6 -

4 -

2 -

0 DMSO E2 E2 + TTX

C. X *** X 120 —

100 - .1 1•11•11r

80 - CLz CI 60- a 40 -

20 -

0 DMSO E2 E2 + TTX

Figure 4.8: TTX treatment inhibited the long-term effect of E2 on MDA-MS-231 cell adhesion measured as detachment negative pressure (DNP).

(A) Adhesion of MDA-MB-231 cells after 24 h treatment with DMSO control (10 -7 % v/v), E2 (1 nM) and E2 + TTX (10 gM). (B) Change in DNP values (ADNP; %) after E2 and E2 + TTX treatments when normalized to DMSO control. Data are presented as mean SEMs (n = 3-8), and were analyzed by Mann-Whitney rank sum test (A) and unpaired t-test (B). Significance: (***) P < 0.001. (X) P > 0.05.

156 A. 0 co C) 2 z

nNav1.5 4- 219 nt

13-actin 4- 359 nt 1 2 3

B. &) 2.0

c 1.5 - .0 cn a) x 1.0 -

MN=

0.5 - M)

Z 0.0 I DMSO G1

Figure 4.9: Long-term treatment with G1 did not affect nNav1.5 mRNA expression in MDA-MB-231 cells.

(A) Typical gel electrophoresis of PCR products for nNav1.5 and [3-actin in MDA-MB- 231 cells treated with DMSO control (10 -7 %; lane 1) and G1 (1 nM; lane 2) for 24 h. NTC: no template control (lane 3). (B) nNav1.5 mRNA expression after 24 h treatment with G1 (1 nM) relative to DMSO control. Data are presented as mean f SEMs and were analyzed by unpaired t-test (n = 3).

157

A. 10-

8

0. 6 -

0 Z 4 - C3

2

0 DMSO G1

B. 120 -

100 -

80 -

60 -

40 -

20 -

0 I DMSO G1

Figure 4.10: Long-term treatment with G1 did not affect MDA-MB-231 cell adhesion measured as detachment negative pressure (DNP).

(A) Adhesion of MDA-MB-231 cells after 24 h treatment with G1 (1 nM) and DMSO control. (B) Change in DNP (ADNP; %) when normalized to DMSO control (100 %). Data are presented as mean ± SEMs (n = 4-5) and were analyzed by Mann-Whitney rank sum test (A) and unpaired t-test (B).

158 Control experiments involved empty-vector transfected MDA-MB-231 cells. Incubating these cells (1) for 3 days in CS-FBS medium or (2) for 24 h in DMSO (10 -7 %) did not change their adhesion (Figure 4.11A & B). In (1) the value of DNP in CS-FBS was 8.9 ± 1.3 kPa (n = 4) compared to 10.1 ± 0.5 kPa in control (FBS; n=3); and in (2) the value of DNP after 24 h treatment with DMSO (10 -7 %) was 9.8 0.3 kPa (n = 4) compared to 8.9 ± 1.3 kPa (n = 4) in CS-FBS (P > 0.05 for (1) and (2); Figure 4.11). Consistent with the data from MDA-MB-231 cells, adhesion of empty-vector transfected control cells was significantly reduced by 1 nM E2 after 24 h, DNP values falling from 9.8 ± 0.3kPa (DMSO) to 6.6 ± 1.2 kPa (P < 0.05; n = 3; Figure 4.12A), i.e. by 33 ± 13 % (Figure 4.12B). Also, as before, adhesion was not affected by 1 nM G1 after 24 h (DNP = 10.3 ± 0.3 kPa; P > 0.05; n = 3; Figure 4.12). As regards GPR30-14 cells, again, culture in CS-FBS medium for 3 days and 24 h treatment with DMSO had no effect on adhesion (DNP = 11.9 ± 0.9, 11.6 ± 0.5 and 12.7 ± 0.3 kPa in FBS, CS-FBS and DMSO, respectively; P > 0.05; n = 3-5; Figure 4.13). However, adhesion was significantly reduced with 24 h treatment with both (i) 1 nM E2 (DNP values falling from 12.7 ± 0.3 kPa in DMSO to 8.7 ± 0.3 kPa) by 31 ± 2 % and (ii) 1 nM G1 (DNP values falling from 12.7 ± 0.3 kPa in DMSO to 9.6 ± 0.4 kPa) by 24 ± 3 % (P < 0.01 and P < 0.001 in (i) and (ii), respectively; n = 3; Figure 4.14). The effect of 24 h treatment with E2 was twice as big in GPR30-14 cells as in MDA-MB-231 cells (Figure 4.7).

4.3.6 Long-term effects of estrogen on VGSCIEll mRNA expression in MDA-MB-231 cells VGSCP subunits were previously reported to have a role in cell adhesion (Isom, 2002). VGSC131 is the dominant VGSCO subunit expressed in MDA-MB-231 cells as previously shown (Chapter 3). Control experiments revealed no effect of either 3-days growth in CS- FBS medium or 24 h treatment with DMSO (10 -7 %) on VGSC131 mRNA expression in MDA-MB-231 cells (P > 0.05; n = 4; Figure 4.15). Also, there was no effect of 24 h treatment with 1 nM E2 (P > 0.05; n = 4; Figure 4.16). This and the absence of an effect by 24 h treatment with 1 nM G1 (P > 0.05; n = 3; Figure 4.17), suggested that GPR30 was not involved in the regulation of VGSCf31 mRNA expression in MDA-MB-231 cells.

159

A. 12 -

10 - I

8 -

2 -

0 FBS CS-FBS

B. 12

10-

8 I

2

0 CS-FBS DMSO

Figure 4.11: Control treatments with CS-FBS and DMSO did not affect adhesion of empty-vector transfected MDA-MB-231 cells measured as detachment negative pressure (DNP).

(A) Adhesion of empty-vector control cells after 3-day growth in CS-FBS medium compared to FBS medium (control). (B) Adhesion after 24 h treatment with DMSO (10 -7 %) compared to CS-FBS medium (control). Data are presented as mean ± SEMs and were analyzed by Mann-Whitney rank sum test (n = 3-4).

160

A. x 12 ,- * r -% 10 -

8 -

2 -

0 • DM SO E2 G1

x 120 — r-- * B. 100 - r -N -.b. 80 - a. z 60- 0

20 -

0

DMSO E2 G1

Figure 4.12: Long-term treatment with E2 reduced, but G1 did not affect, adhesion of empty-vector transfected MDA-MB-231 cells measured as detachment negative pressure (DNP).

(A) Adhesion of empty-vector control cells after 24 h treatment with E2 (1 nM) and G1 (1 nM) when compared to DMSO control (10 -7 %). (B) Change in DNP (ADNP; %) with 24 h treatments with E2 and G1 when normalized to DMSO control (100 %). Data are presented as mean ± SEMs (n = 3) and were analyzed by Mann-Whitney rank sum test (A) and unpaired t-test (B). Significance: (*) P < 0.05, (X) P > 0.05.

161 A. 14 -

12 - I 10 -

8 - 0- Z 6- C1 4 -

2 -

0 o II B. FBS CS -FBS

14 —

12 -

I 1 0 -

4 -

2 -

0 CS-FBS DMSO

Figure 4.13: Control treatments with CS-FBS and DMSO did not affect adhesion of GPR30-14 cells measured as detachment negative pressure (DNP).

(A) Adhesion after 3-day growth in CS-FBS medium compared to FBS control. (B) Adhesion after 24 h treatment with DMSO (10 -7 %) compared to CS-FBS control. Data are presented as mean ± SEMs (n = 3-5) and were analyzed by Mann-Whitney rank sum test.

162 A. ** 14 - *** 12 - 10 - CI13 /4 a 8 - 11. Z 6 - 4 - 2 - 0

DMSO E2 G1

B. ** *** 1 100

80 - (:) a 60 - z

20 -

0

DMSO E2 G1

Figure 4.14: Long-term treatment with E2 and G1 decreased adhesion of GPR30-14 cells measured as detachment negative pressure (DNP).

(A) Adhesion after 24 h treatments with E2 (1 nM) and G1 (1 nM) compared to DMSO control (10 -7 %). (B) Change in DNP (ADNP; %) in E2 and Gl, relative to DMSO control (100 %). Data are presented as mean ± SEMs (n = 3) and were analyzed by Mann- Whitney rank sum test (A) and unpaired t-test (B). Significance: (**) P < 0.01, (***) P < 0.001.

163 A. m 0 u_r m 2 IL C.) Z

VGSCI31 Mal 4- 379 nt

4-- 359 nt 13-actin 1 2 3 4

B. C.

1.0 -

ive) 2.5 - t ive) t la la

(re 2.0 - (re n 0.8 - io ion 1.5 - ress ress 0.5 - exp 1.0 - RNA RNA exp 0.3 -

1 m 0.5 - 3 31 m SC1 0.0 0.0 GSC( VG FBS CS V CS DMSO

Figure 4.15: Control treatments with CS-FBS and DMSO did not affect VGSCD1 mRNA expression in MDA-MB-231 cells.

(A) Typical gel electrophoresis of PCR products for VGSC(31 subunit and 13—actin in cells cultured in FBS medium (lane 1), in CS-FBS medium for 3 days (lane 2) and treated with DMSO (10 -7 %) for 24 h (lane 3). NTC: no template control (lane 4). Real-time PCR analysis of VGSCI31 mRNA expression in (B) CS-FBS (CS) medium relative to FBS medium and (C) in DMSO relative to CS-FBS (CS) medium. Data are presented as mean SEMs (n = 4) and were analyzed by unpaired t-test.

164 A.

2 tNI

VGSCI31 379 nt

(3-actin MO OP 1— 359 nt

1 2 3

B. 2.0 —

ca °_) 1.5 - 0 2! to - a)

4:t

E 0.5 -

CD 0.0 DMSO E2

Figure 4.16: Long-term treatment with E2 did not affect VGSCI31 mRNA expression in MDA-MB-231 cells.

(A) Typical gel electrophoresis of PCR products for VGSC131 subunit and (actin in cells treated with control/DMSO (10 -7 %; lane 1) and E2 (1 nM; lane 2) for 24 h. NTC: no template control (lane 3). (B) Real-time PCR analysis of VGSCP1 mRNA expression after E2 treatment relative to DMSO control. Data are presented as mean ± SEMs (n = 4) and were analyzed by unpaired t-test.

165

A. z VGSCI31 1— 379 nt

13-actin -amor 411160 1— 359 nt

1 2 3 B.

2.0 - Ca

a 1.5 - •o_ U)

1.0 - a)

E 0.5-

co > 0.0 DMSO G1

Figure 4.17: Long-term treatment with G1 did not affect VGSCP1 mRNA expression in MDA-MB-231 cells.

(A) Typical gel electrophoresis of PCR products for VGSC[31 subunit and 13—actin in cells treated with control/DMSO (10 -7 %, lane 1) and G1 (1 nM; lane 2) for 24 h. NTC: no template control (lane 3). (B) Real-time PCR analysis of VGSC131 mRNA expression in GI treatment relative to DMSO control. Data are presented as mean ± SEMs (n = 3) and were analyzed by unpaired t-test.

166 4.4 Discussion

The main findings of the studies described in this chapter are as follows: (1) Long-term (24 h) treatment of MDA-MB-231 cells with E2 increased nNav1.5 mRNA expression time- and dose-dependently; total nNav1.5 protein expression was not affected. (2) Long-term (24 h) E2 treatment decreased MDA-MB-231 cell adhesion and this was dependent on VGSC activity. (3) Long-term (24 h) G1 treatment did not affect nNav1.5 mRNA expression or adhesion of MDA-MB-231 cells; however, it reduced adhesion of GPR30-14 cells. (4) Long-term (24 h) E2 and G1 treatments did not affect VGSC[31 subunit mRNA expression in MDA-MB-231 cells.

4.4.1 Effects of long-term estrogen treatment on VGSC expression in MDA-MB-231 cells

4.4.1.1 mRNA studies The present study provided the first evidence of estrogen regulation of VGSC (nNav1.5) gene expression in BCa cells. Previously, androgen treatment increased VGSC (Nav1.7 and VGSC(31) mRNA expression in PCa cells (Diss et al., 2007). Accordingly, increased VGSC expression could accelerate progression of metastatic disease, as reported before (Brackenbury et al., 2007). Estrogen could regulate gene expression by either a direct and/or an indirect mechanism: (i) Direct: This would involve binding of the estrogen receptor (ER) on estrogen response elements (ERE) on gene sequences. Response elements for androgens (ARE) and glucocorticoids (GRE) were shown to be upstream to the promoter regions of epithelial Na channel a subunit (aENaC) and small conductance Ca2+-activated K+ channel (SK2), both of which were transcriptionally up-regulated by steroid binding (Kye et al., 2007; Quinider et al., 2005; Sayegh et al., 1999). Importantly, a bioinformatics study performed by Dr. Diss revealed three putative ERE half-sites (ERE1/2) (unpublished data; Appendix I) on the Nav1.5 promoter sequence (Yang et al., 2004).

167 This served as a strong indication for a potential genomic regulation of Nav1.5 by estrogen. (ii) Indirect: This would involve activation of other transcription factors (e.g. Apl and Spl) by ERs which then could activate gene transcription (Cherlet and Murphy, 2007; Marino et al., 2006; Saville et al., 2000; Wittliff et al., 2008). A putative Spl binding site was identified on the Nav1.5 promoter sequence (Dr. Diss, unpublished data; Appendix I). Promoter regions of other ion channels also contain Sp binding sites, e.g. SK3 (Kundu et al., 2007) and voltage-and Ca2+-activated K+ (BK) channel (Jacobson et al., 2003). Importantly, estrogen induced transcription of mouse BK and rat SK3 channels via association between ERa and Sp binding sites (Jacobson et al., 2003; Kundu et al., 2007). This would indicate a possible similar activation of Nav1.5 transcription by estrogen via Spl binding sites. Genomic regulation of ion channels by steroid hormones is not a new notion; both up- and down-regulation of ion channels were reported depending on the treatment and cell type. In support of the present study, estrogen previously induced transcription of the following: (i) Voltage gated K+ channels (VGPCs) in HeLa, COST cells, guinea pig aorta and brain, rat embryonic heart, rat aortic smooth muscle cells and mouse uterine cells (Bosch et al., 2002; Holdiman et al., 2002; Jacobson et al., 2003; Kundu et al., 2007; Ranki et al., 2002; Tsang et al., 2004a). (ii) Voltage-gated Ca2+ channels (VGCCs) in guinea pig hypothalamus and pituitary cells and rat aortic rings (Qiu et al., 2006; Tsang et al., 2004b). (iii) Voltage-gated Cl' channels (VGC1Cs) in rat kidney cells (Nascimento et al., 2003). Interestingly, aENaC was reported among estrogen-receptor (ER) up-regulated genes in non/weakly metastatic BCa cell line MCF-7 (Dressman et al., 2001). In addition to estrogen, testosterone, aldosterone and dexamethasone were also found to increase VGCC, VGC1C and aENaC transcription in male Yucatan swine coronary artery, human kidney and lung epithelial cells, respectively (Bowles et al., 2004; Gautron et al., 2001; Ornellas et al., 2002; Quinkler et al., 2005; Sayegh et al., 1999). There is also evidence for down-regulation of ion channel genes by steroid hormones. For example, Song et al. (2001) demonstrated reduction in VGPC mRNA and protein levels by E2 treatment in rat myometrial smooth muscle cells. Also, an extensive microarray study showed that a VGPC subtype (KCNG1) was among the ER-down- regulated genes in MCF-7 and ZR-75-1 BCa cells (Lin et al., 2004). Other reports showed no effect of steroid hormones on ion channel regulation (Boixel et al., 2006; Patterson et

168 al., 1998; Tsang et al., 2004a). The apparent discrepancies among studies could result from different doses of hormones and cell types used. For example, Nakajima et al. (2008) demonstrated in human smooth muscle cells that long-term (24 h) treatment with 1 nM dexamethasone reduced mRNA expression of the dominant VGSC isoform Nav1.7, whereas Kye et al. (2007) showed in rat pheochromocytoma (PC12) cells that higher concentrations of dexamethasone (25 — 750 nM) increased transcription of SK2 after 3 h. The present study (Chapter 3) and previous work showed expression of a G- protein coupled receptor (GPCR) subtype 30 (GPR30) in MDA-MB-231 cells (Prossnitz et al., 2008a; Revankar et al., 2005). The absence of a classical ERa in MDA-MB-231 cells could suggest GPR30 as a candidate receptor for the long-term effects of E2 on nNav1.5 mRNA expression. Involvement of GPR30 in VGSC modulation in MDA-MB- 231 cells by short-term E2 treatment was shown in Chapter 3. To assess the possibility of a GPR30-driven long-term, genomic effect, the cells were treated with GPR30 specific ligand G1 compound (Albanito et al., 2007; Bologa et al., 2006). The specificity of G1 was demonstrated by its higher affinity to bind to GPR30 rather than ERa and ER13 (Albanito et al., 2007; Albanito et al., 2008; Bologa et al., 2006). However, whether it can activate other receptor mechanisms such as other ER variants or cross-react with growth factor receptors (e.g. EGFR) is not known. In the present study, no change in nNav1.5 mRNA expression was detected after G1 treatment. With the assumption that G1 only activates GPR30, this would suggest that GPR30 signaling alone was not sufficient to provoke a genomic effect in MDA-MB-231 cells. One possibility could be E2 activation of ER13 receptors which were previously shown to be expressed in MDA-MB-231 cells (Mak et al., 2006). An ERf3-specific ligand (2,3-bis(4-hydroxyphenyl)-propionitrile) exists which could be used to further validate this possibility (Morissette et al., 2008). There is increasing evidence for many (up-to twenty) other ERa and ERf3 variants expressed in BCa and PCa cells (Poola et al., 2000; Poola and Speirs, 2001; Wang et al., 1999; Ye et al., 2000). Poola et al. (2000) even showed expression of some of these ERa variants in classical ERa — negative MDA-MB-435 BCa cells. Possible endogenous expressions of such ER variants and their possible functional consequences have not been investigated in MDA-MB-231 cells. However, transfection with one of the ERa variants (exon 3 deleted; ERA3) was reported to respond to long-term (24 h) treatment with 10 nM E2 more strongly than wild type ERa, by activating vascular endothelial growth factor (VEGF) promoter through interaction with Spl (Koduri et al., 2006). The evidence for

169 multiple ER variants would also raise the possibility of multiple GPCR variants being expressed in BCa cells. In fact, CXCR4 (a chemokine receptor family) which is a type of GPCR, has been shown to be involved in cancer metastasis and was correlated with lymph node metastasis in ERa — negative BCa cases (Kang et al., 2005; Woo et al., 2008; Zlotnik, 2008). For these reasons, further studies involving specific primers and antibodies for different/additional ER/GPCR variants should be carried out to specifically identify the receptor mechanism(s) responsible for promoting genomic effects in MDA- MB-231 cells. On the other hand, the dominant VGSC I3 subunit, 131, mRNA expression in MDA- MB-231 cells was not affected by E2, even though VGSC131 was previously reported to be among ER up-regulated genes in MCF-7 cells (Lin et al., 2004). This suggested that steroid hormone regulation of ion channels could be subtype/subunit-specific. Accordingly, King et al. (2006) demonstrated in HEK-293 cells transfected with human BK channel that expression of f32 and f34 subunits caused increased activity by steroid hormones such as corticosterone and dehydroepiandrosterone.

4.4.1.2 Protein-level studies The increased nNav1.5 mRNA expression after E2 treatment for 24 h was not reflected on protein levels (Figure 4.5). This could be due to mRNA and protein expressions being regulated independently and possible mRNA (Chang and Ramos, 2005; Orphanides and Reinberg, 2002; Wang et al., 2007b). Discrepancies between mRNA and protein expressions were also studied in several diseases such as rheumatoid arthritis and PCa (Brackenbury and Djamgoz, 2006; Schedel et al., 2004). VGSCs were previously shown to change their locations between PM and intracellular compartments without affecting total protein levels (Brackenbury and Djamgoz, 2006). Thus, long-term effect of E2 on VGSC protein expression in MDA-MB-231 cells could involve trafficking. This would need to be validated further via protein fractionation or confocal microscopy studies.

4.4.1.3 Functional aspects: Adhesion VGSCs are highly expressed in metastatic tumours and regulate cellular behaviours such as motility, migration, invasion and endocytic membrane activity in BCa and PCa cells (Diss et al., 2005; Fraser et al., 2005; Le Guennec et al., 2007). Adhesion is one of the

170 main components of metastasis and is a dynamic process. During early metastasis, when cancer cells detach from their surroundings and invade through the vascular endothelium to enter circulation, reduced adhesion is important to allow them spread more easily. However, in late metastasis, cancer cells need to be adherent again so to lodge into distant sites and re-proliferate. Thus, reduced adhesion could be important for the early stages of metastasis. Long-term E2 treatment reduced adhesion of MDA-MB-231 cells significantly and co-application of TTX inhibited this effect. This is consistent with increased nNav1.5 mRNA expression by E2. One possibility of VGSCs' involvement in adhesion is via VGSCI3 subunits (Isom, 2002). These are members of the immunoglobulin superfamily cell adhesion molecules (Isom and Catterall, 1996; Isom et al., 1992) and can interact with other adhesion molecules such as N-cadherin, contactin, NrCam or ankyrin (Kazarinova-Noyes et al., 2001; Malhotra et al., 2004; McEwen and Isom, 2004; Brackenbury et al., 2008). Additionally, VGSCP subunits are known to have cleavage sites for enzymes like y-secretase, 0-site amyloid precursor protein-cleaving enzyme 1 (BACE1) and a-secretase enzyme (ADAM10) (Kim et al., 2005; Wong et al., 2005). Cleavage of f3 subunits by these enzymes yields membrane bound "C-terminal fragments" and "small intracellular domains" which could interact with adhesion molecules such as E-cadherin and ankyrin (Kim et al., 2005; Malhotra et al., 2000). Interestingly, both y- and a-secretases were reported to be involved in ER signaling (Rizzo et al., 2008). Furthermore, ERa can regulate signaling of BACE1 (Bao et al., 2007) which contains ERE, GRE and multiple binding sites for transcription factors such as CREB, NKicB, and Sp 1 , all directly regulated by estrogen (Sambamurti et al., 2004). This evidence provided a strong basis for possible E2 regulation of VGSCf3 subunits. However, the present study demonstrated that VGSCI31 mRNA expression in MDA-MB-231 cells did not change by long-term (24 h) treatment with E2. Although, no genomic effect was detected, changes in VGSCI31 protein expression by E2 are possible. Additionally, other proteins, such as integrins, could also be modulated by E2 (Lin et al., 2006; Nebe et al., 2006; Nelson et al., 2008), leading to regulation of cell adhesion. Further studies on protein expressions of VGSCr31 and integrins are required in order to rule out a functional role of these molecules in the long-term effect of E2 on adhesion.

171 4.4.1.3.1 Why does the short-term effect of G1 compound disappear in long-term treatment? Data from Chapter 3 revealed significant reduction of MDA-MB-231 cell adhesion after short-term (10-20 minutes) treatment with GPR30-specific G1 compound. However, in the present study, long-term (24 h) treatments with G1 compound did not affect adhesion of MDA-MB-231 cells (Figure 4.10). This was somewhat surprising as activation of GPR30 for as short as 10 minutes was enough to decrease adhesion in the same cells (Chapter 3). A possible explanation of this discrepancy between the effects of short- and long-term G1 treatments on adhesion could be changes in GPR30 protein activity and downstream signaling after ligand binging. Previously, Sun et al. (2007) demonstrated that GPCRs can change their signaling in a dose-dependent manner. This may indicate that GPCR activity also changes by time. Interestingly, Filardo et al. (2007) demonstrated internalization of PM GPR30 after E2 stimulation for as short as 15 minutes. As was discussed in section 3.4.3, G-proteins and downstream signaling mechanisms (e.g. AC, cAMP, PKA) work in a compartmentalized manner where their PM and subcellular localizations are important for proper functioning. The reduction in adhesion by G1 treatment for up to 20 minutes (Chapter 3) could indicate activation of a signaling mechanism which suppressed long-term (24 h) effect of G1 on adhesion. Various signaling mechanisms were reported downstream to change in adhesion: Fibronectin- and poly-L-lysine-induced adhesion reduced MAPK phosphorylation in rat osteablasts (Krause et al., 2000), integrin-mediated adhesion induced c-fos and Apt transactivation in rat osteblasts (Cowles et al., 2000) and integrins activated PKA in human bone marrow endothelial cells (Gonzalez et al., 2008b). These data and the present findings could indicate that short-term activation of GPR30 by G1 resulted in receptor internalization, which activated signaling mechanisms reducing adhesion; this eventually modified intracellular signaling pathways and possibly led to genomic modifications in long-term, which resulted in suppression (`turn off) of the short-term effect. Further investigations of long-term effects of G1 involved GPR30-14 cells, over- expressing internal GPR30 (Chapter 3). Short-term treatment of these cells with E2 reduced adhesion significantly (Chapter 3). Consistent with this, long-term treatment with E2 also reduced adhesion of GPR30-14 cells significantly (Figure 4.14). Importantly, long-term treatment with G1 also reduced GPR30-14 cell adhesion significantly (Figure

172 4.14). This was intriguing since long-term G1 treatment failed to affect adhesion of MDA-MB-231 cells. This difference could be an effect of the increased intracellular GPR30 in GPR30-14 cells, i.e. the possible G1-induced internalization of GPR30 can be affected by the amount of already internalized protein. Thus, the signaling pathways modulated by G1 in MDA-MB-231 cells may not be affected in GPR30-14 cells. Alternatively, over-expression of GPR30 could have changed the intracellular balance in the cells which may have modulated expressions of other signaling molecules. The shortcoming of the present study is the lack of investigation for cellular localization of GPR30 after long-term G1-stimulation. This would help identify the mechanism(s) involved in the time-dependent effect of G1 on adhesion. The fact that long-term treatment with E2 in MDA-MB-231 cells reduced adhesion suggested an alternative mechanism where E2 could by-pass the GPR30 to affect adhesion in long-term. This could include other ER or GPCR variants or unknown estrogen-sensitive receptors (Rx). Such a 'receptor-switch' is common in BCa, e.g. amplified expression of HER2 receptor in ER-negative BCa cases (Marchio et al., 2008; Milanezi et al., 2008). However, whether Rx is already expressed or its expression is induced by GPR30 signaling, is not known. Since G1 is selective for GPR30, a possible switch to another estrogen-sensitive receptor would not change the long-term effects of G1 in MDA-MB-231 cells.

4.4.2 A model for long-term effects of estrogen in MDA-MB-231 cells From the data obtained in the present study and previous published evidence, taken together, a hypothetical model is proposed for the long-term effects of estrogen in MDA- MB-231 cells (Figure 4.18). This model proposes that the two receptors — GPR30 and Rx — interact in response to estrogen to regulate VGSC expression and, in turn, adhesion. There are two ways in which the receptors could be interacting: 1) Serial (Figure 4.18A): Estrogen (E2) binds and activates GPR30, and downstream signaling which involves cAMP and PKA. Importantly, activated GPR30 induces expression of a variety of genes (Albanito et al., 2007) one of which could be an alternative receptor (Rx). During long-term stimulation with E2, GPR30 is internalized and whereupon E2 starts directly stimulating Rx. In long-term, the GPR30-dependent route could 'switch-off', which would disable activity of Gl. 2) Parallel (Figure 4.18B): GPR30 and Rx co-exist in cells simultaneously and E2

173 binds and activates both concurrently. In both cases, activation of either or both of these receptors will promote downstream signaling - X (Figure 4.18C). This could involve many mechanisms such as secondary messenger activation (e.g. PKA, MAPK, ERK1/2), even further gene transcription (e.g. Apl , NFiB), which could induce genomic effects on VGSCa (nNav1.5) mRNA and increase its trafficking to PM. Adhesion of MDA-MB-231 cells can be regulated via (i) a VGSC-dependent pathway where increased nNav1.5 expression/activity could induce further molecular mechanisms (Y), including regulation of multiple adhesion molecules such as integrins and VGSCr3s and (ii) a VGSC- independent pathway in which adhesion molecules are regulated by another mechanism (Figure 4.18C). In order to understand which of the two models is nearer to the truth, investigating whether knocking-down GPR30 from MDA-MB-231 cells will suppress the long-term effect of E2 will help understand whether Rx is downstream to GPR30. Absence of an effect would indicate that the two receptors co-exist, supporting the second, parallel, model. Further investigation of the two models presented here will provide important information for therapeutic approaches to BCa. Data exist where ER-positive cells switched to ER-negative status and EGFR/HER2 became over-expressed in vivo during/following tamoxifen therapy (Massarweh et al., 2008). Additionally, GPR30 was shown to be activated with tamoxifen, which could suggest GPR30 being involved in tamoxifen resistance (Thomas et al., 2005; Vivacqua et al., 2006). Thus, similar to the first, serial, model presented here (Figure 4.18A), activation of GPR30 by tamoxifen in BCa cells could lead to activation of another receptor sensitive to tamoxifen. Importantly, there is now evidence for "triple-negative" BCa cases where neither ER/PR nor HER2 exists (Cleator et al., 2007). Thus, evaluation of a possible receptor-switch downstream of GPR30, or co-existence of another receptor (as in the second, parallel, model; Figure 4.18B) would shed light for novel receptors and further clarify the role of GPR30 in BCa development and progression.

174

A. Serial interaction

E2 CGPR30.) — X

B. Parallel interaction

CGPR30' • 00 A E2 /".

C. Downstream signaling

(VGSC-independent) r

(from A/B) — — Adhesion VGSC mRNA t L — < • 4 VGSC trafficking

(VGSC-dependent)

Figure 4.18: A model of estrogen regulation of adhesion.

(A) GPR30 and Rx could be serially associated where GPR30 signaling after estrogen (E2) stimulation activates Rx expression. In long-term, where GPR30 signaling 'switches off, E2 can work via Rx to induce downstream signaling (X). (B) GPR30 and Rx could be two different routes that E2 can act on. In long-term when GPR30-depdenent route `switches off, Rx-dependent route is activated, leading to downstream signaling (X). (C) The secondary messengers (X) activated by E2 via GPR30 and/or R, could induce VGSC (nNav1.5) mRNA expression and membrane trafficking. Further downstream signaling (Y) could modulate adhesion molecules and reduce adhesion. Signaling from GPR30 and Rx could also reduce adhesion via a VGSC-independent route.

175 Chapter 5

LONG-TERM EFFECTS OF 1713-ESTRADIOL

ON VOLTAGE-GATED SODIUM CHANNEL

EXPRESSION AND ADHESION OF

ERa-EXPRESSING MDA-MB-231 CELLS

176 5.1 Introduction Ion channels can be regulated via transcriptional and/or post-transcriptional mechanisms (Diss et al., 2004; Schulz et al., 2008). Transcriptional regulation was shown to be initiated by various growth factors such as nerve growth factor (NGF), epidermal growth factor (EGF), fibroblast growth factors (FGF) and hormones such as dexamethasone, androgen, aldosterone, testosterone and estrogen (Brackenbury and Djamgoz, 2007; Ding et al., 2008; Holdiman et al., 2002; Nascimento et al., 2003; Uysal-Onganer and Djamgoz, 2007). Ion channels were also shown to be differentially regulated in disease states such as epilepsy (Gastaldi et al., 1997), neuropathic pain (Dib-Hajj et al., 1999; Kim et al., 2001), and more recently various cancers such as cervical (Diaz et al., 2007), small-cell lung (Diss et al., 2005; Roger et al., 2007), prostate (Diss et al., 2005), and breast cancer (BCa; Fraser et al., 2005). Voltage-gated sodium channel (VGSC) subtype Nav1.5, was reported to be involved in progression of metastasis in BCa (Brackenbury et al., 2007; Fraser et al., 2005). Blocking this channel with TTX, a specific antibody or siRNA inhibited migration and invasion, and increased adhesion of metastatic MDA-MB-231 BCa cells (Chioni et al., 2005; Palmer et al., 2008). Whilst involvement of estrogen in human BCa is well documented, there are significant inconsistencies in its reported roles. The classic role of estrogen as a cancer- promoting factor is being challenged by studies reporting decreased metastatic behaviours via estrogen signaling (Barron-Gonzalez and Castro Romero, 2004; Garcia et al., 1992; Lundholt et al., 2001; Ohlsson et al., 2001). Importantly, estrogen receptor (ER) a- positive BCa cells such as MCF-7 are less invasive/metastatic compared to ERa-negative BCa cells such as MDA-MB-231 (Rochefort et al., 2003). Additionally, the newly defined 'neonatal' splice variant of Nav1.5, (nNav1.5) is the predominant VGSC isoform highly expressed in MDA-MB-231 cells (Fraser et al., 2005). Furthermore, putative ER binding sites were found in Nav1.5 promoter (Appendix I), and 1713-estradiol (E2) was shown to regulate genomic expression of nNav1.5 in MDA-MB-231 cells (Chapter 4). The present study was designed to investigate whether E2 would have any long- term/genomic effect on nNav1.5 expression in MDA-MB-231 cells transfected stably with ERa (MDA- ERa). Possible effects on cellular adhesion were also investigated.

177 5.2 Aims and scope The overall aim of this study was to investigate possible long-term effects of estrogen on nNav1.5 expression and cellular adhesion in MDA-ERa cells. The specific aims were as follows: (1) To investigate possible effects of ERa transfection on basal GPR30 and nNav1.5 mRNA and protein expressions; and adhesion in MDA-MB-231 cells. (2) To determine the effects of charcoal-stripped (CS-FBS) medium on nNav1.5 expression and adhesion of MDA-ERa cells. (3) To analyze any time and dose-dependent effects of E2 on nNav1.5 mRNA expression and adhesion of MDA-ERa and empty-vector transfected control (VC5) cells. (5) To test effects of the ERa blocker, ICI-182,780 on nNav1.5 mRNA expression adhesion of MDA-ERa cells. (6) To evaluate VGSC's involvement in effect of E2 on adhesion.

The following three new human BCa cell lines (kindly provided by Prof. V.C. Jordan, Department of Molecular Pharmacoogy and Biological Chemistry, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA) were used: (1) MDA-ERa: MDA-MB-231 cells stably transfected with ERa (Jiang and Jordan, 1992). (2) VC5: Empty-vector (pCMV-neo) control for MDA-ERa cells. (3) MDA-10A: Parental MDA-MB-231 cells used for empty-vector and ERa transfections (Jiang and Jordan, 1992).

5.3 Results

5.3.1 Initial investigations

5.3.1.1 Morphological observations Light microscopic observation of cell morphologies revealed that BCa cells with different ERa status had variable morphological changes in normal culture conditions (Figure 5.1). MDA-10A and VC5 cells (Figure 5.1A & B) had similar morphologies exhibiting elongated processes. Also, MDA-ERa (Figure 5.1C) cells appeared more heterogeneous in their morphology compared to MDA-10A and VC5 cells. On the whole, MDA-ERa

178 Figure 5.1: ERa transfection altered cell morphologies of MDA-10A cells.

MDA-10A (A), VC5 (B) and MDA-ElZu (C) cells photographed in normal culture conditions. Scale bar denotes 10 rim, applicable to all panels.

179 cells were rounder, relatively shorter and appeared more 'scattered' around the dish. They had more cellular processes with which they seemed to attach to neighboring cells. Possible effects of ERa expression on adhesion was investigated in section 5.3.1.3 and further discussed in section 5.4.2.

5.3.1.2 Studies of basal mRNA expression

(i) ERa The development of the MDA-ERa cells was previously described (Jiang and Jordan, 1992). The expression of ERa mRNA in MDA-ERa cells was confirmed here by using specific primers (details given in Chapter 2). Real-time RT-PCR revealed that MDA-ERa cells expressed ERa mRNA at a significantly higher level than VC5 cells, by around 20,000 ± 7,000 folds (P < 0.001; n = 3; Figure 5.2B). There was no ERa mRNA in MDA- 10A and VC5 cells when compared to MCF-7 cells which were used as a positive control (P < 0.001; n = 3; Figure 5.2C).

(ii) GPR30 MDA-MB-231 cells express the novel estrogen receptor GPR30 (Chapter 3; Revankar et al., 2005). Expression of GPR30 in MDA-10A and the transfected cell lines was confirmed here at mRNA level. Real-time RT-PCR revealed that MDA-10A cells expressed GPR30 mRNA at about 97 ± 0.1 % lower levels than MCF-7 cells (P < 0.001; n = 3; Figure 5.3B). ERa transfection into MDA-10A cells did not affect GPR30 mRNA expression when compared to VC5 control cells (P > 0.05; n = 3; Figure 5.3C).

(iii) nNav1.5 MDA-MB-231 cells were previously shown to express nNav1.5 (Brackenbury et al., 2007; Fraser et al., 2005). The expression of nNav1.5 mRNA in MDA-10A cells was confirmed here. Real-time PCR revealed that VC5 cells also expressed nNav1.5 mRNA; although the latter was around 27 ± 17 folds higher than MDA-10A cells, this difference was not significant (P > 0.05; n = 3; Figure 5.4B). Interestingly, MDA-ERa cells exhibited significantly reduced levels of nNav1.5 mRNA when compared to VC5 by around 96 ± 2 % (P < 0.05; n = 3; Figure 5.4C). This suggested that ERa expression significantly reduced basal nNav1.5 mRNA levels in MDA-10A cells (similar to MCF-7).

180 A. II" 0 LLo 2 I—Z

ERa IEIME4-299 nt

13-actin 11=1114-359 nt 1 2 3 4 5

H. C. 70- 3000 — *** *** x > r, , \ > 1 413 z5 - 2 2500 — R .....i2 E 0.8 c C 2000 'al .•0— 0.6- g 1500 — g 0. 0. X x a) a)

Figure 5.2: ERa mRNA was highly expressed in MDA-ERa, but not VC5 and MDA- 10A cells.

(A) Typical gel electrophoresis picture of PCR products for ERa and 13-actin in MDA- 10A (lane 2), VC5 (lane 3) and MDA-ERa (lane 4) cells; MCF-7 cells were used as positive control (lane 1). NTC: no template control (lane 5). (B) Relative ERa mRNA expression levels relative to controls (white bars): MCF-7 cells for MDA-10A and VC5 cells and VC5 cells for MDA-ERa (ERa) cells. Data are presented as mean ± SEM (n = 3) and analyzed by unpaired t-test. Significance: (***) P < 0.001, (x) P > 0.05.

181 B. A. not changeitslevels. Figure 5.3:GPR30mRNAwasexpressedinallcelllinesandERatransfectiondid (A) Typicalgelelectrophoresispictureofreal-time PCRproductsforGPR30and analyzed byunpairedt-test.Significance:(***)P <0.001,(x)P>0.05. control (lane in MDA-10A(lane1),VC52)andMDA-ERa (lane3)cells.NTC:notemplate bars; MCF-7VC5cells,respectively).Dataare presentedasmean±SEM(n=3)and GPR30 m RNA expression (relative) 1.0 0.6 0.8 0.2 0.4 0.0 MCF-7 4).

(B) RelativeGPR30mRNAexpressioncompared tocontrols(white 13-actin GPR30 *** MDA10A

O 1 VC5 41111111111111 2

C. 0 re 3

GPR30 mRNA expression (relative) 1.4 - 1.2 - 1.0 - 0.0 0.2 - 0.4 - 0.6 - 0.8 - 4 0 4- ♦ -585 nt 359 nt VC5

ERa [3-actin 182 A. B. (A) TypicalgelpicturesofPCRproductsfornNav1.5 and13-actininMDA-10A(lane1), VC5 (lane SEM (n=3)andanalyzedbyunpairedt-test.Significance: (***)P<0.001,(x)>0.05. Figure 5.4:nNav1.5mRNAexpressionwasreduced inMDA-ERacells. Relative nNav1.5mRNAexpressionscompared to controls.Dataarepresentedasmean±

nNav1.5 mRNA expression (relative) 40 - 45 - 10- 15- 30 - 35 - 20 - 25 - 5- 0 2) MDA10A and MDA-ERa(lane3)cells.NTC:notemplate control(lane4).(B) I3-actin nNav1.5 x GNI Eli VC5 0 1 234

OS 0 >

C. 4111111 04. < 0 2 z nNav1.5 mRNA expression (relative) 1.0 0.0 0.2 0.4 0.6 0.8 i— 4- 4-219 nt 359 nt VC5 ERa 183

(iv) Nav1.7 MDA-MB-231 cells were previously reported to express Nav1.7 mRNA at about 75 % lower levels than than nNav1.5 (Fraser et al., 2005). Real-time PCR revealed that Nav1.7 mRNA expression was also significantly reduced in MDA-ERa cells, by 74 ± 16 % when compared to VC5 cells (P < 0.01; n = 3; Figure 5.5B). When normalized to the housekeeping gene I3-actin, in control (i.e. VC5) cells, Nav1.7 mRNA expression was significantly lower than nNav1.5 by 65 ± 8 % (P < 0.05; n = 3; Figure 5.5C, left-hand bars). Interestingly, this difference between the mRNA expressions of the two VGSCa subtypes disappeared in MDA-ERa cells (Figure 5.5C, right-hand bars).

5.3.1.3 Basal nNav1.5 protein expression Similar levels of nNav1.5 protein were found in MDA-10A and VC5 cells (Figure 5.6A & B). In contrast, Western blots revealed that the nNav1.5 protein level was significantly reduced in MDA-ERa cell, by 15 ± 2 % compared to VC5 cells (P < 0.05; n = 3; Figure 5.6A & C).

5.3.1.4 Basal adhesion studies MDA-MB-231 cells were previously shown to be much less adhesive than the less/weakly metastatic cell line MCF-7 (Palmer et al., 2008). This was confirmed here (Figure 5.7). Also, SCAMA measurements revealed that all three cell lines used were much less adhesive than the MCF-7 cells: MDA-10A, VC5 and MDA-ERa cells had average DNPs of 6.7 ± 0.6, 7.6 ± 1.3, and 6.4 ± 0.4 kPa, respectively whereas MCF-7 cells had an average DNP of 11 ± 0.6 kPa (P < 0.01, 0.05 and 0.001 for MDA-10A, VC5 and MDA-ERa cells, respectively; n = 3-4; Figure 5.7). Importantly, the empty-vector transfection or ERa expression in MDA-10A cells did not change their basal adhesion (DNP; 7.6 ± 1.3, and 6.4 ± 0.4 kPa, respectively; P > 0.05; n = 3-4; Figure 5.7).

5.3.1.5 Basal cell motility studies MDA-ERa cells were compared to MDA-MB-231 and MCF-7 cells for their motilities. Wound-healing assays revealed that MDA-ERa cells were significantly less motile than MDA-MB-231 cells: (1) The motility index (MoI) calculated after 24 h was 0.5 for MDA-MB-231 cells, and 0.1 for both MDA-ERa and MCF-7 cells; and (2) MoI after 48 h was 0.8 for MDA-MB-231 cells, and 0.3 for both MDA-ERa and MCF-7 cells (P <

184

**

e) 2.5 - e)

iv x t A. iv 1.0 - t la la e

2.0 - re (r

n ( 0.8 - n io io s 1.5 - res

ess 0.6 - r xp xp

1.0 - e

A e 0.4 - NA RN 0.5 - R 0.2 - 7 m 7 m 1. 1. 0.0 Nav 0.0 MDA10A VC5 Nav VC5 ERa

C.

* X

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—3 e) -.0--) 1- El nNav1.5

> iv t ONav1.7 as la a) — 2.5 re

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0 0.5 - — 1.5 re a a) — 1 exp a) e 0.25 - ▪a. tiv

76 — 0.5 la 2 t$ re 0 co C.9 VC5 ERa

> VGSCa Cell type

Figure 5.5: ERa transfection reduced Nav1.7 mRNA levels and altered relative VGSCa mRNA expression.

(A) Relative Nav1.7 mRNA expression levels (normalized to (3-actin) in MDA-10A, VC5 and MDA-ERa (ERa) cells compared to respective controls (MDA-10A for VC5 and VC5 for ERa cells). (B) Relative Nav1.7 mRNA expression levels (normalized to (3-actin) compared to nNav1.5 levels in ERa cells. Data are presented as mean ± SEM (n = 3) and analyzed by unpaired t-test. Significance: (*) P < 0.05, (**) P < 0.01, (x) P > 0.05.

185

A. O

U) C) 2 2

nNav1.5 4— 220 kDa

a-actinin 4— 100 kDa

1 2 3

B. C. x 1.0 - Tr) 1.0

I 0. c- — 0.8 - c 0 0 H 2.) Kx 0.5 - x 0.5 - a) a)

2 O • o . 0.3- 'AI

as as

0.0 • 0.0

MDA-10A VC5 VC5 ERa

Figure 5.6: nNav1.5 protein expression was reduced in MDA-ERa cells.

(A) Western blot with 60 lig total protein per lane, using NESO pAB again nNav1.5. a- actinin antibody was used as a loading control. Lane 1: MDA-ERa; Lane 2: VC5 and Lane 3: MDA-10A cells. (B) Relative nNav1.5 protein levels (normalized to a-actinin) in MDA-10, VC5 and MDA-ERa (ERa) cells, relative to controls (MDA-10A for VC5, and VC5 for ERa cells). Data are presented as mean ± SEM (n = 3) and analyzed by unpaired t-test. Significance: (*) P < 0.05, (x) P > 0.05.

186

*** * 12 — -I- 9 - co O. .. 6 O. Z 0 3

o I MCF-7 MDA10A VC5 ERa

Figure 5.7: Single-cell adhesion was not affected by ERa transfection.

Detachment negative pressure (DNP) measurements from SCAMA experiments showing adhesion of MDA-10A, VC5 and ERa cells. MCF-7 cells were used as a control. Data are presented as mean ± SEM and analyzed by Mann-Whitney rank sum test (n = 3-4). Significance: (*) P < 0.05, (**) P < 0.01, (***) P < 0.001, (X) P > 0.05.

187 0.01; n = 4; Figure 5.8). These data indicated a similarity of MDA-ERa cells to MCF-7 cells in their movements.

5.3.2 Effect of CS-FBS medium in MDA-ERa cells The effects of growing MDA-ERa cells in E2-deprived medium were investigated. Preliminary observations, suggested that cell morphologies were not affected. Additional tests involved mRNA and adhesion studies as follows.

5.3.2.1 pS2 mRNA expression Culturing in CS-FBS medium is a standard method to deprive cells of steroid hormones endogenous to serum before treatments. Cells are usually kept in CS-FBS medium for at least 1-3 days before applying estrogen. Here, the time needed to keep MDA-ERa cells in CS-FBS medium was tested by measuring the mRNA levels of a classic estrogen responding gene, pS2 (Scott et al., 2007). Real-time PCR revealed that when compared to normal growth (FBS) medium pS2 mRNA expression was reduced significantly in CS- FBS medium by 51 ± 1 , 69 ± 2, 85 ± 7 and 62 ± 15 % after 1, 2, 3 and 5 days, respectively (P < 0.05 for 1 and 5 days and P < 0.001 for 2 and 3 days; n = 3; Figure 5.9). Interestingly, 4-days' growth in CS-FBS medium caused huge variability in pS2 mRNA levels and the effect was not significant (P > 0.05; n = 3; Figure 5.9). Thus, a period of 3 days (when the pS2 mRNA levels were reduced the most, i.e. the cells were deprived of most of the endogenous estrogen in the medium) was adopted for 'pre-conditioning'.

5.3.2.2 nNavl.5 mRNA expression A possible effect of culturing in CS-FBS medium on nNav1.5 mRNA expression was tested. Real-time PCR revealed that 3-5 days growth increased nNav1.5 mRNA expression in MDA-ERa cells (Figure 5.10). There was a large variability in the mRNA levels especially after 3-5 days, and the changes seen were not significant (P >0.05; n = 3; Figure 5.10). It was observed that the increasing trend 'plateaued' after 3 days (Figure 5.10). As a result of this, and the pS2 mRNA expression in CS-FBS, the MDA-ERa cells were cultured in CS-FBS medium for 3 days prior to long-term E2 treatments.

5.3.2.3 Adhesion studies A time-course study revealed that CS-FBS medium did not affect adhesion for up-to 3

188 ** 1 - O MDA 0 MDA-ERa l) ■ MCF7 0.8 - Mo ** (

x ** 0.6 - de

in 0.4 - ility

t 0.2 - Mo 0 I 24 48 Time (h)

Figure 5.8: ERa transfection reduced MDA-MB-231 lateral cell motility.

Motility index (MoI) of MDA-MB-231 (MDA), ERa-transfected MDA-MB-231 (MDA- ERa) and MCF-7 cells after 24 and 48 h. Data are presented as mean ± SEMs (n = 4) and analyzed by unpaired t-test. Significance: (**) P < 0.01.

189 A.

FBS 1d 2d 3d 4d 5d NTC

pS2 1111111111P /Mb ONO 4— 218 nt

13-actin 1==21111 4— 359 nt 1 2 3 4 5 6 7

B. 3.0 -

e) 2.5 - tiv la re

( 2.0 - ion 1.5 - ress xp 1.0 * RNA e 0.5 S2 m p 0.0 0 1 2 3 4 5 Time in CS-FBS (days)

Figure 5.9: CS-FBS medium reduced pS2 mRNA expression in MDA-ERa cells time-dependently.

(A) Gel electrophoresis picture of PCR products for pS2 and 3-actin in MDA-ERa cells after 1-5 day culture in CS-FBS. Lane 1: FBS control and Lanes 2-6: 1-5 days in CS-FBS. NTC: no template control (lane 7). (B) Relative pS2 mRNA expression (normalised to 13- actin) in each sample, relative to control (FBS; dotted line). Data are presented as mean ± SEM and analyzed by unpaired t-test (n = 3). Significance: (*) P < 0.05, (***) P < 0.001.

190

A. FBS 1d 2d 3d 4d 5d NTC

nNav1.5 "1"0 111111i mup 411111b 219 nt

(3-actin IND 411111110 1- 359 nt 1 2 3 4 5 6 7

B.

14 -

12 L_co 10- 0 -cn 8- rt. a) 6 -

CL 4 - E . 14 2 co c 0

0 1 2 3 4 Time in CS-FBS (days)

Figure 5.10: CS-FBS medium increased nNav1.5 mRNA time-dependently but non- significantly in MDA-ERa cells.

(A) Gel electrophoresis picture of PCR products for nNav1.5 and 13-actin in MDA-ERa cells after 1-5 day culture in CS-FBS. Lane 1: FBS control and Lanes 2-6: 1-5 days in CS-FBS. NTC: no template control (lane 7). (B) Relative nNav1.5 mRNA expression (normalised to (3-actin) in each sample, relative to control (FBS medium, white diamond). Data are presented as mean ± SEM and analyzed by unpaired t-test (n = 3).

191 days, the DNP values being 6.2 ± 0.3 lcPa, 6 ± 0.2 kPa, 5.4 ± 0.2 kPa, and 5.7 ± 0.4 kPa on days 0, 1, 2 and 3, respectively (P > 0.05 for each; n = 3; Figure 5.11).

5.3.3 Long-term effect of E2 on nNav1.5 mRNA expression in MDA-ERa cells

5.3.3.1 Dose-dependence The MDA-ERa cells were treated with 1 - 100 nM E2 for 24 h and nNav1.5 mRNA expression levels were investigated by real-time PCR. The corresponding DMSO controls (10-v - le %) did not affect nNav1.5 mRNA expression (P > 0.05; n = 3; Figure 5.12A). Only 1 nM E2 reduced nNav1.5 mRNA expression significantly, by 76 ± 12 % (P < 0.001; n = 4; Figure 5.12B). There was a large variability with 10 and 100 nM E2, and these had no effect on nNav1.5 mRNA expression although there was an increasing trend (50 ± 58 and 16 ± 88 % increase with 10 and 100 nM E2, respectively; P > 0.05; n = 5; Figure 5.12C). Thus, the effect of E2 on nNav1.5 mRNA expression was biphasic with a reduction at 1 nM and 10-100 nM having no effect.

5.3.3.2 Time-dependence Since 1 nM E2 had the biggest and 10 nM E2 the second biggest effect on nNav1.5 mRNA levels after 24 h, they were used in time-dependence studies (Figure 5.13). Real- time PCR revealed that the corresponding DMSO controls (le -10-6%) did not change nNav1.5 mRNA expression after 24, 48 and 72 h (P > 0.05; n = 3; Figure 5.13C for 10-7 % DMSO and Figure 5.13E for 10-6 % DMSO). Importantly, change in nNav1.5 mRNA expression with 1 nM E2 was not time-dependent in MDA-ERa cells, the level decreasing significantly by 76 ± 12, 70 ± 13 and 80 ± 9 % after 24, 48 and 72 h, respectively (P < 0.01 after 48 h and P < 0.001 after 24 and 72 h; n = 3-4; Figure 5.13D). Interestingly, 10 nM E2 changed nNav1.5 mRNA expression in the opposite direction, the level increasing significantly by 2.6 ± 0.4 -folds after 72h (P < 0.01; n = 3-5; Figure 5.13F).

5.3.4 Long-term effect of E2 on MDA-ERa cell adhesion Single-cell adhesion was measured as a key component of metastatic cascade. 1 and 10 nM E2 was applied to MDA-ERa cells for 24 h and their adhesion was measured by SCAMA. It was found that adhesion was significantly reduced by 12 ± 7 % (DNP falling from 7.7 ± 0.5 kPa to 6.7 ± 0.2 kPa) and 21 ± 1 % (DNP falling from 7.6 ± 0.4 kPa

192 Time in CS-FBS (days)

Figure 5.11: Adhesion of MDA-ERa cells did not change in CS-FBS medium.

DNP values from SCAMA measurements of MDA-ERa cells in CS-FBS medium compared to control (FBS; white symbol at t = 0). Data are presented as mean ± SEM (n = 3).

193

A.

CS-FBS D1 D2 D2 E1 E2 E3 NTC

nNav1.5 -4— 219 nt

(3-actin 4111111. VINO 1111111111 111111110 MOW mow 1- 359 nt 1 2 3 4 5 6 7 8

B. C.

X e)

e) 2.5 - iv t iv t la la re re

( 2.0 - ( n io ion 1.5 - ress ess r irk* xp 1.0 A e RNA exp RN

m 0.5 - 5 m 5 1. 1. v

Nav 0.0 Na n n DMSO E1 E2 E3

Figure 5.12: Long-term E2 treatment decreased nNav1.5 mRNA in MDA-ERa cells dose-dependently.

(A) Typical gel electrophoresis picture of PCR products for nNav1.5 and I3-actin in MDA-ERa cells after 24 h treatments with 1, 10 and 100 nM E2 (E1, E2, and E3, respectively; lanes 5-7) and 10-7, 10-6, and 10-5 % DMSO (D1, D2, and D3, respectively; lanes 2-4). Lane 1: CS-FBS control and NTC: no template control (lane 8). (B) Relative nNav1.5 mRNA expression levels in D1, D2, and D3 (grey bars; normalised to (3-actin), compared to control (CS-FBS medium, white bar). (C) Relative nNav1.5 mRNA expression E1, E2, and E3 (grey bars; normalized to 13-actin), relative to respective controls (D1, D2, and D3, respectively; represented with the white bar). Data are presented as mean ± SEM and analyzed by unpaired t-test (n = 3-5). Significance: (***) P < 0.001 and (x) P > 0.05.

194 A. B. 24h 48h 72h 24h 48h 72h

CS-FeS CS-Fes NTC nNav1.5 4- 219 nt nNav1.5 4- 219 nt

(3-actin 108 ats 01 fa MOW 4— 359 nt 11-actin 41111 4.410 MP 4F- 359 nt 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 C. D.

E2 (1 nM) -"f 10 DMSO (10-7 %) ive)

t 1.0 -

ii la 8-

(re 0.8

6 ion 6- 0.6 ** ress *** 4- 0.4 Z 2 - RNA exp 0.2 5 m 1. 0 0.0 24 48 72 24 48 72 Nav Time (hours) n lime (hours)

F.

) DMSO (10-6 %) 3.0 - E2 (10 nM) ive t 47 4 - la > 2.5 - t- * (re

ion 2.0 - c 3- 0 ress 1.5 - i g. 2- 1.0 - rt

RNA exp a 0.5 - g 1 5 m E 1. u, 0.0 t, 0 Nav 24 48 72 n to 24 48 72 Time (hours) c Time (hours)

Figure 5.13: Long-term effect of E2 on nNav1.5 mRNA expression was time- dependent in MDA-ERa cells.

(A & B) Typical gel electrophoresis picture of PCR products for nNav1.5 and 13-actin in MDA-ERa cells after 24, 48 and 72 h treatments (lanes 2-7, A and B). Lanes 3, 5 & 7: 1 nM E2 (E1) in A; and 10 nM E2 (E2) in B. Lanes 2, 4 & 6: 10-7 % DMSO (Di) in A; and 10-6 % DMSO (D2) in B. Lane 1 (A & B): CS-FBS. NTC: no template control (lane 8, A & B). (C & D) Relative nNav1.5 mRNA expression (normalised to (3-actin) in le % DMSO and 1 nM E2, respectively. (E & F) Relative nNav1.5 mRNA expression (normalised to [3-actin) in 10-6 % DMSO and 10 nM E2, respectively. Data are presented as mean ± SEM and analyzed by unpaired t-test (n = 3-5). Significance: (*) P < 0.05, (***) P < 0.001 and (x) P > 0.05.

195 to 6 ± 0.4 kPa) with 1 and 10 nM E2, respectively, when compared to DMSO controls (P = 0.05 and P < 0.01 for 1 and 10 nM E2, respectively; n = 3; Figure 5.14A). Tetrodotoxin (TTX; 10 AM) treatment was performed and adhesion was increased significantly from 7.6 ± 0.4 kPa to 8.4 ± 0.3 kPa (P < 0.01; n = 4; Figure 5.14B), by 11 ± 4 % (Figure 5.14C). In order to assess the involvement of VGSCs in the long-term E2 effect on MDA- ERa cell adhesion, co-treatment with TTX was performed. E2 (10 nM) and TTX (10 µM) co-application did not affect adhesion of cells when compared to DMSO control (DNP being 7.6 ± 0.4 kPa in DMSO and 8.5 ± 0.1 kPa in E2+TTX; P > 0.05; n = 3; Figure 5.14B). E2+TTX treatment increased adhesion significantly, by 12 ± 7 %, which was significantly higher than the effect of E2 (21 ± 1 % decrease; P < 0.01; n = 3-4; Figure 5.14C). This indicated that VGSCs are downstream to ERa signaling in MDA-ERa cells.

5.3.5 Long-term effect of E2 on nNav1.5 mRNA expression in VC5 cells VC5 cells were treated with 1 and 10 nM E2 for 24 h and total RNA was extracted. Real- time PCR revealed that the respective DMSO controls (le % and 10-6 %, respectively) induced a significant decrease in nNav1.5 mRNA expression, by 74 ± 20 and 63 ± 18 %, respectively (P < 0.01 and P < 0.05 for 104 and 10-6 % DMSO, respectively;; n = 3-6; Figure 5.15B). E2 affected nNav1.5 mRNA expression dose-dependently: 1 nM E2 increasing by 3 ± 0.5 folds, and 10 nM E2 not having any effect (P < 0.01 and P > 0.05 for 1 and 10 nM E2, respectively; n = 3-6; Figure 5.15C).

5.3.6 Long-term effects of anti-estrogen, ICI-182,780 on MDA-ERa cells

5.3.6.1 nNav1.5 mRNA expression ICI-182,780 (ICI) was applied to MDA-ERa cells at different doses: 100 nM and 1 µM, and times (24, 48 and 72 h). As regards the respective DMSO controls: 0.0002 % DMSO (control for 100 nM ICI) did not have any significant effect at either time point (P > 0.05; n = 3; Figure 5.16C) and 0.002 % DMSO (control for 1 µM ICI) increased nNav1.5 mRNA expression significantly by 4 ± 1 folds only after 72 h (P < 0.05; n = 3; Figure 5.16E). At both doses of ICI, the effect on nNav1.5 mRNA expression was bell-shaped, i.e. time-dependent: nNav1.5 mRNA expression was increased significantly with 100 nM ICI by 9.6 ± 2 folds after 48 h (P < 0.05; n = 3; Figure 5.16D) whereas 1 µM ICI decreased it significantly by 73 ± 7 % after 72 h (P < 0.001; n = 3; Figure 5.16F).

196 A. ** DDMSO r----) o E2

1 10

B. x ** r 20 10 * e" ** x --. 15 .—.. 10 8 - ...... O 5 0. 0 •Z -5 <1 -10 -15 2 - -20 o . I -25 DMSO E2 TTX E2+TTX E2 TTX E2+TTX

Figure 5.14: Long-term E2 treatment decreased adhesion of MDA-ERa cells VGSC- dependently.

(A) DNP values of MDA-ERa cells after 24 h treatment with E2 (grey bars) and respective DMSO controls (white bars). (B) DNP values following 24 h after E2 (10 nM), E2 + TTX and TTX (10 LIM) treatments (grey bars); and DMSO control (white bar). (C) Change in DNP (ADNP, %, normalized to DMSO control) in E2 (white bar) and E2 + TTX (grey bar) treatment. Data are presented as mean ± SEM and analyzed by Mann- Whitney rank sum test (n = 3-4). Significance: (*) P < 0.05, (**) P < 0.01, (X) P > 0.05.

197 A. CS Di E1 02 E2 NTC nNav1.5 219 nt

6-actin MOP 1111111 1111111 IMP 411- 359 nt

1 2 3 4 5 6

B. C.

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re R 1.0 - E ▪ 0.2 m 5 0.5 - 3 1. 0.0 0.0 Nav CS-FBS Dl 02 n DMSO E1 E2

Figure 5.15: Long-term E2 treatment increased nNav1.5 mRNA expression in VC5 cells dose-dependently.

(A) Typical gel electrophoresis picture of PCR products for nNav1.5 and 13-actin in VC5 cells after 24 h treatments with 1 and 10 nM E2 (E1 and E2, lanes 3 & 5, respectively) and

10-7 and 10-6 % DMSO (Di and D2, lanes 2 & 4, respectively). Lane 1: CS-FBS (CS) control. NTC: no template control (lane 6). (B) Relative nNav1.5 mRNA expression levels in D1 and D2 (grey bars; normalised to (3-actin), compared to control (CS-FBS, white bar). (C) Relative nNav1.5 mRNA expression in E1 and E2, (grey bars; normalized to (3-actin), compared to respective DMSO controls (white bar). Data are presented as mean ± SEM and analyzed by Mann-Whitney rank sum test (n = 3-6). Significance: (*) P < 0.05, (**) P < 0.01.

198 A. 24h 48h 72h B. 24h 48h 72h FBS ID1 11 I Di 11 I D. II INTO nNav1.5 nNav1.5 R1112=1111W 219 r"

ri-actin .011. 4NN• IMO .0.1. MD am I— 359 nt I3-actin 359 nt 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8

C. D.

) ICI (100 nM) DMSO (0.0002 %)

ive 8

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n Time (hours) Time (hours) E. F.

DMSO (0.002 %) ICI (1 pM) 15 ive)

t 4 - la

re 12 T12 ( n io gS 3- 9 S ress 0. 2 - 6 0x z. RNA exp 3 re E

5 m U) 1. 0 0 24 48 72 0 24 48 72 Nav

n Time (hours) Time (hours)

Figure 5.16: Long-term ICI on nNav1.5 mRNA expression was time and dose- dependent in MDA-ERot cells.

(A & B) Typical gel electrophoresis picture of PCR products for nNav1.5 and 13-actin in MDA-ERa cells after 24, 48 and 72 h treatments (lanes 2 - 7, in A and B) with 100 nM ICI (I)) in A and 1 p.M ICI (I2) in B. Lanes 2, 4 & 6: 0.0002 % DMSO (D)) in A; and 0.002 % DMSO (D2) in B. Lane 1 (A & B): FBS. NTC: no template control (lane 8, A & B). (C & D) Relative nNav1.5 rnRNA expression (normalised to (3-actin) in 0.0002 % DMSO and 100 nM ICI, respectively. (E & F) Relative nNav1.5 mRNA expression (normalised to (3-actin) in 0.002 % DMSO and 1 µM ICI, respectively. Data are presented as mean ± SEM and analyzed by unpaired t-test (n = 3). Significance: (*) P < 0.05, (***) P< 0.001.

199 5.3.6.2 Adhesion Studies on adhesion showed no effect on MDA-ERa cell adhesion by long-term (24 h) treatment with ICI (1 µM); DNP was 6.2 ± 0.4 kPa in FBS medium, 6.6 ± 0.1 kPa in DMSO control and 6.8 f 0.2 kPa in ICI (P > 0.05; n = 3; Figure 5.17).

5.3.6.3 Cell motility and migration Preliminary experiments to further investigate possible effects of long-term (> 24 h) treatments with ICI revealed increased MCBs such as transverse migration and lateral motility of MDA-ERa cells (Figure 5.18). When compared to DMSO control (which itself did not affect migration; Figure 5.18A), treatment with ICI for > 72 h induced transverse migration via porous membranes by 32 ± 13 % (P < 0.05; n = 8; Figure 5.18B). Regarding lateral motility, ICI significantly increased motility after > 96 h treatment (by 22 ± 6 % and 22 ± 5 % after 96 and 120 h, respectively; P < 0.01; n = 5-6; Figure 5.18C). These data are indicative of increased metastatic potential following ICI treatment.

5.4 Discussion

The main findings of this chapter were as follows: (1) Transfecting MDA-MB-231 cells with ERa (giving MDA-ERa cells) did not affect GPR30 mRNA expression. (2) nNav1.5 mRNA expression was reduced significantly in MDA-ERa cells, compared with empty-vector transfected MDA-MB-231 (VC5) cells. (3) MDA-ERa cells had similar adhesiveness to VC5 and MDA-10A cells. (4) CS-FBS medium did not affect nNav1.5 mRNA expression or adhesion in MDA-ERa cells. (5) Effects of long-term (24 — 72 h) E2 and ICI treatments on nNav1.5 mRNA expression in MDA-ERa cells were biphasic and dependent on time and dose. (6) Long-term (24 h) E2 treatment increased nNav1.5 mRNA expression significantly in VC5 cells, with no effect on cellular adhesion. (7) Long-term (24 h) E2 (but not ICI) treatment reduced MDA-ERa cell adhesion significantly; the effect was VGSC dependent.

200

7 X I 6

5

4

3

2

1

0

FBS DMSO ICI

Figure 5.17: Long-term ICI treatment did not affect adhesion of MDA-ERa cells.

DNP values of MDA-ERa cells after 24 h treatment with 1 uM ICI, DMSO control (grey bars) and FBS. Data are presented as mean ± SEM and analyzed by Mann-Whitney rank sum test (n = 3).

201

A. B. X 120 ti 160 — 100 - 80 - Oc 60

40 40 - 20

0

FBS DMSO DMSO ICI

C.

60 O DMSO 50 -0- ICI 40 ** Zi 30 ** 747, 20 2 10

Time (h)

Figure 5.18: Long-term treatment with ICI-182,780 increased transverse migration and lateral motility of MDA-Ella cells.

(A) Lack of effect of > 72 h treatment with DMSO on transverse migration. (B) Treatment with ICI-182,780 (ICI) for > 72 h induced transverse migration of MDA-ERa cells through porous membranes. (C) ICI treatment increased lateral motility in a time- dependent manner where change in motility (Amotility, %) was significant after 96 h treatment. Data are presented as mean ± SEMs (n = 8 for A & B; n = 5-6 for C) and analyzed by unpaired t-test. Significance: (*) P < 0.05, (**) P < 0.01, (X) P > 0.05.

202 5.4.1 Lack of effects of ERa transfection on GPR30 mRNA expression A possible association between GPR30 and ERa expression was suggested by in vivo studies where almost half of invasive breast tumours studied co-expressed GPR30 and ERa (Filardo et al., 2006; Kuo et al., 2007). Interestingly, half of ERa-negative tumours also expressed GPR30 (Filardo et al., 2006; Filardo et al., 2008). Although they may not be 'interdependent', expression of both receptors could be connected (Filardo et al., 2008). GPR30 expression was also reported in ERa-positive and negative BCa cell lines: MCF-7 and SKBR-3 cells, respectively (Thomas et al., 2005). However, there are contradictory reports on GPR30 expression in ERa-negative MDA-MB-231 cells. Some report MDA-MB-231 cells as being GPR30-negative and use them in transfection studies (Carmeci et al., 1997; Filardo et al., 2000; Liu et al., 2008; Maggiolini et al., 2004), whereas others have shown cytoplasmic expression of GPR30 in MDA-MB-231 cells (Filardo et al., 2002; Revankar et al., 2005). It was suggested that GPR30 expression in ER-negative cells could be a mechanism for maintaining estrogen sensitivity and give rise to non-genomic effects (Prossnitz et al., 2008c). In Chapter 3, GPR30 mRNA and protein expression in MDA-MB-231 cells was demonstrated. Several possible explanations for the discrepancies between various groups are as follows: (i) use of different cell stocks/populations and/or culture conditions; (ii) use of different antibodies for GPR30; and (iii) use of different detection techniques, e.g. Western blots versus immunocytochemistry. Regulation of hormone receptor (e.g., ER, PR) expression by the estrogen content of culture media was previously reported (Kakugawa et al., 2007). Thus, it is also possible for GPR30 expression to be affected by the contents of the medium (Leblanc et al., 2007). The importance of medium in determining cancer cell characteristics has indeed frequently been emphasized (Pan and Djamgoz, 2008). In the present study, the three cell lines, MDA-10A, VC5 and MDA-ERa (all obtained from the Jordan group) expressed GPR30 mRNA at similar levels (Figure 5.3). It was concluded that under the culture conditions used here, ERa expression in MDA- MB-231 cells did not affect GPR30 mRNA expression. This does not rule out possible changes in GPR30 protein expression and its cellular localization. ERs were previously shown to interact with G-proteins (Simoncini et al., 2006; Su et al., 2002) and activated G-proteins are usually internalized (Filardo et al., 2007). This suggests that a possible interaction between ERa and GPR30 in these cells may increase internalization of

203 GPR30. It would be interesting to investigate this possibility in MDA-ERa cells as well as other cells with ERa-transfected or knocked out (e.g. SKBR-3 and MCF-7 cells, respectively).

5.4.2 Effects of ERa transfection on nNav1.5 mRNA and protein expression Elevated levels of voltage-gated sodium channel (VGSC) subtype 'neonatal' Nav1.5 (nNav1.5) mRNA and protein expression were previously reported in BCa cells (Brackenbury et al., 2007; Fraser et al., 2005). Electrophysiological studies showed that the size of outward current was correlated negatively with increasing metastatic potential (Fraser et al., 2005). Interestingly, the nNav1.5 protein was functionally expressed on the plasma membrane in highly metastatic and ERa-negative MDA-MB-231 cells whereas only internal protein was detected in the low/non-metastatic ERa-positive MCF-7 cells (Fraser et al., 2005). These findings point strongly to a possible relationship between ERa and functional nNav1.5 expression in BCa cells. Real-time PCR revealed that MDA-ERa cells had significantly reduced nNav1.5 mRNA expression, by 96 % (Figure 5.4). nNav1.5 protein expression was also reduced significantly in these cells by 15 % (Figure 5.6). This reduction in protein levels was also reflected in the electrophysiological recordings (Appendix IV). The VGSC (i.e. nNav1.5) current densities were comparable between VC5 and MDA-ERa cells (Appendix NB); however only 43 % of the latter cells expressed functional VGSCs compared to 71 % in the former (Appendix IVC). This suggested inhibition of functional VGCS expression by ERa in BCa cells. Other studies also support the view of a correlation between ER and voltage-gated ion channel (VGIC) expression. For example, Brevet et al. (2008) demonstrated in human BCa and normal breast tissues that Ca2+-activated K+ channel and voltage-gated K+ channel (VGPC) protein expressions were repressed by increased ERa expression in carcinoma samples. Conversely, G-protein inwardly rectifying K+ channel 1 expression was directly correlated with ERa expression in the same study (Brevet et al., 2008). Consistent with the latter, Abdul et al. (2003) reported in human BCa samples that VGPC protein was highly expressed compared to normal breast samples. These studies and the present study clearly stated a regulatory mechanism between ERa and VGIC expression in BCa. ERa is known 'classically' as an estrogen receptor in the cytoplasm or nucleus. Its main mode of action is via gene regulation where it binds to estrogen response elements (ERE) on the gene sequence or activates other transcription factors (e.g. Apl, Spl, NFkB)

204 (Hirano et al., 2007; Marino et al., 2006). At least three putative ERE half sites and a putative Sp 1 binding site were found in the promoter region of Navl.5 gene (J.K.J Diss, unpublished data; Appendix I). Direct binding of ERa to EREs on Navl.5 promoter may explain the long-term effects of estrogen on mRNA and protein levels. Gene profile studies revealed that most of the genes regulated by ERa expression in BCa cells/tissues have a role in transduction of mitogenic signal (such as c-myc, c-jun), cellular adhesion and motility (such as integrins), transcription factors (such as Apl, Spl and TGFa and (l) and apoptotic factors (such as Bc12 and p21) (Carroll et al., 2002; Frasor et al., 2003; Nagai et al., 2004). The present study is the first report illustrating regulation of expression and function of a VGSC by ERa status in BCa cells. The findings of the present study are in line with previous work showing low levels of Nav1.5 expression and function in ERa-positive BCa (MCF-7) cells compared to ERa-negative (MDA-MB-231) cells (Fraser et al., 2005). This is important for understanding the role of ERa in BCa metastasis. It is known that ERa-positive tumours are generally less aggressive than ERa-negative tumours (Ali and Coombes, 2000) and one explanation was the loss of controlled gene expression in the latter case (Levenson and Jordan, 1994). For example, estrogen was shown to limit cell growth via inhibition of growth regulatory genes (Nagai et al., 2004). Role of VGSC expression in progression of metastasis is reported in various cancer types, e.g. prostate, breast, small-cell lung cancer and cervical cancer (Diaz et al., 2007; Diss et al., 2005; Fraser et al., 2005; Roger et al., 2007). Thus, a reduction in nNav1.5 expression by ERa transfection could be one way estrogen may protect against metastasis. Investigating the mechanism of estrogen regulation of nNav1.5 and other VGSC subtypes could help the understanding of the role of ERa in cancer development. Interestingly, preliminary work on another minor VGSCa subtype expressed in MDA- MB-231 cells, Nav1.7, revealed that its mRNA expression was also significantly reduced in MDA-ERa cells when compared to VC5 cells (Figure 5.5). This result is consistent with a previous report in ERa-negative MDA-MB-231 cells where Nav1.7 mRNA levels were about 75 % lower than nNav1.5 (Fraser et al., 2005). Intriguingly, the difference between the mRNA expressions of the two VGSCa subtypes (i.e. nNav1.5 and Nav1.7) disappeared in MDA-ERa cells (Figure 5.5). It would be interesting to study whether such changes in the relative mRNA expressions of different VGSCa subtypes are reflected at protein level and could affect cells' metastatic behaviour. Importantly, Nav1.7

205 expression was correlated with metastasis in human PCa, and its expression was elevated in androgen receptor (AR)-negative cell lines PC-3 compared to AR-positive LNCaP cells (Diss et al., 2001). This is consistent with the present findings that ERa transfection reduced nNav1.5 mRNA and protein expression in BCa. In addition to VGSCa subtypes, VGSC subunits have been shown to be differentially expressed in PCa cells depending on the AR expression status (Diss et al., 2007). Specifically VGSCI31 subunit mRNA was found to be repressed in AR-positive PCa cells (Diss et al., 2007). This further supports a reverse correlation between VGSC and hormone receptor expressions.

5.4.3 Effects of ERa transfection on cellular behaviours MDA-ERa cells had similar adhesiveness with MDA-10A and VC5 cells (Figure 5.7). Cell adhesion is one of the main processes involved in metastatic cascade (Bacac and Stamenkovic, 2008; Sahai, 2007). Adhesive behaviour of cancer cells are dynamically regulated since earlier detachment from primary location and later attachment to a secondary site is important for metastasis (Bacac and Stamenkovic, 2008). Although about 60 % of breast tumours express ERa during diagnosis, more than a third of these cells later become ERa-negative and gain resistance to estrogen-related therapies (Ali and Coombes, 2000). In vivo studies revealed ERa-positive BCa cells to be less aggressive than the ERa-negative cells because of increased activation of alternative signaling (e.g. EGFR) and resistance to endocrine therapies in the latter (Massarweh et al., 2008). In vitro studies are consistent with this whereby decreased metastatic potential (i.e. invasiveness) was detected in ERa-transfected BCa cells (such as MDA-MB-231; Garcia et al., 1992; Levenson and Jordan, 1994; Long and Rose, 1996). In support of this, in the present study, preliminary data were obtained showing MDA-ERa cells having significantly reduced lateral motilities when compared to MDA-MB-231 cells (Figure 5.8). Thus, MDA-ERa cells exhibited similar motilities to non-metastatic MCF-7 cells, again suggesting ERa transfection having a protective role for metastatic potential in BCa. Further studies exist where transfection of ERa cDNA into ERa-negative mammalian cell lines mostly had growth inhibitory effects in various cell lines such as MDA-MB-231 (Barron-Gonzalez and Castro Romero, 2004; Garcia et al., 1992; Lazennec and Katzenellenbogen, 1999; Levenson and Jordan, 1994), 21T (Zajchowski et al., 1993), MDA-MB-468 (Wang et al., 1997), chemically immortalized non-tumorigenic

206 epithelial human mammary cell lines (Zajchowski and Sager, 1991; Zajchowski et al., 1993) and a spontaneously immortalized non-tumorigenic human breast epithelial cell line HMT-3522 (Lundholt et al., 1996). Such contradictory effects of estrogen could be due to the following: (1) Expression of genes encoding growth inhibitory/cytotoxic proteins in the presence of E2 due to genetic rearrangements consequent to transfection (Gaben and Mester, 1991). (2) Regulation of genes which are not normally E2-responsive by overexpression of ER (Kushner et al., 1990). (3) Cross-coupling mechanism that could occur with other transcription factors as was shown for ER interaction with Apt (Feng et al., 2001; Kushner et al., 2000).

5.4.4 Effects of CS-FBS medium Earlier studies reported that culture medium supplemented with FBS contains sufficient steroid hormones and growth factors to support growth of BCa cells (Butler et al., 1981). Especially phenol red containing medium was shown to contain enough estrogen for growth of ERa-positive MCF-7 cells (Berthois et al., 1986b; Fan et al., 2007). In the present study, the medium used was without phenol red thus reducing the amount of estrogen. The parental MDA-10A cells and MDA-ERa cells were normally cultured in medium supplemented with 5 % FBS. On the other hand, VC5 cells were continuously cultured in charcoal-stripped serum (CS-FBS) supplemented medium (Dr. Catherine Sharma/ Prof. Jordan, personal communication). For long-term estrogen studies, the cells were cultured in CS-FBS medium to minimize the amount of endogenous estrogen. Charcoal stripping is a technique used to remove endogenous hormones, growth factors and cytokines in the serum so to allow accurate investigations of exogenous treatments. Dang and Lowik (2005) reported that CS-FBS-supplemented medium could itself have effects on cell signaling systems. Importantly, for ERa-transfected cells the amount of estrogen in the medium could indeed have an effect. For example, ERa expression itself was previously shown to be regulated by estrogen (Haas et al., 2007; Sowers et al., 2006). Thus, it is possible for CS-FBS medium to affect gene expression and functioning in BCa cells. pS2 gene is one of the classical ER regulated genes used as a control for ER activity (Scott et al., 2007). In the present study, pS2 mRNA expression was investigated as a measure of ERa activity in CS-FBS medium. It was found that 1-5-day culture in CS-

207 FBS medium reduced the pS2 mRNA expression time-dependently in MDA-ERa cells when compared to FBS medium (Figure 5.9). Especially after 3 days, pS2 mRNA expression was at a minimum level. This suggested that the estrogen content of FBS was sufficient to activate ERa, and at least 3-day culture in estrogen-deprived medium was needed to reduce endogenous estrogen activity. As discussed in section 5.4.1, ERa expression inhibited nNav1.5 mRNA expression (Figure 5.4). This could be due to activation of ERa by endogenous estrogen and removal of estrogen from media could accordingly affect nNav1.5 mRNA expression in MDA-ERa cells. nNav1.5 mRNA expression was indeed altered in CS-FBS medium. Thus, there was a time-dependent increase in nNav1.5 mRNA expression in MDA-ERa cells cultured in CS-FBS medium (Figure 5.10). However, the data were highly variable and not significant; nevertheless, there was a strong tendency for increased expression especially after 3 days. This is consistent with the reduction seen after ERa expression. As was illustrated with the pS2 levels, after 3-day CS-FBS treatment, the ERa activity (measured by pS2 mRNA expression) was at its minimum and following this, nNav1.5 mRNA levels started to increase again. VGSC expression is a dynamic process regulated by multiple mechanisms such as growth factors, cytokines and hormones (Brackenbury and Djamgoz, 2007; Diss et al., 2004). It is known that serum concentrations can affect characteristics of VGSCs in rat PCa cells (Ding et al., 2008) and biochemical constitution of serum could modulate VGSC expression and metastatic behaviours, including adhesion (Pan and Djamgoz, 2008). In the present study, MDA- ERa cell adhesion was not affected by CS-FBS medium (Figure 5. 11). One possibility is that normal serum contains factors that would stimulate or inhibit adhesion, so that charcoal-stripping produces no net effect.

5.4.5 Effects of DMSO The present study revealed considerable variability in nNav1.5 mRNA expression after long-term treatment with DMSO, although the concentrations used were much lower than the ones generally used in literature: In the present study, 0.002 % and 10-5 % were the highest DMSO concentrations used in ICI and E2 experiments, respectively, whereas in the literature DMSO concentrations usually range between 0.01-0.1 % (Charles et al., 2000; Lewandowski et al., 2005). However, most previous studies presented their data on estrogen/anti-estrogen effects by only comparing the treatments to the respective vehicle

208 used, i.e. without showing the effect(s) of solvent (Filardo et al., 2007). Thus, no comparison of the solvent to the normal growth conditions exists. The findings in the present study that DMSO could in fact alter gene expression (i.e. nNav1.5 mRNA expression in BCa cells) suggested the importance of experiments where the vehicle is also tested. There are, in fact, reports on DMSO affecting gene and protein expressions. For example, Camici et al. (2006) showed in human endothelial and vascular smooth muscle cells that 0.1 % DMSO inhibited a coagulation protein and mRNA expression after as low as 2 h treatment. The present study showed time- and dose-dependent effects of DMSO on mRNA expression where 10-7 and 10-6 % % DMSO treatment for 24 — 72 h resulted in considerable variability and 0.002 % DMSO treatment for 72 h caused a significant increase in nNav1.5 mRNA expression in MDA-ERa cells. A cell-specific effect was also observed where both 10-7 and 10.6 % DMSO treatments for 24 h significantly decreased nNav1.5 mRNA expression in VC5 cells. Such a time-dependent effect of DMSO was previously observed by Mortensen and Arukwe (2006) where treatment of salmon hepatocytes with 0.1 % DMSO increased ERa mRNA expression after 12-72 h whilst increasing ERP mRNA expression after 12-48 h and decreasing it after 72 h. In view of these studies and the present studies, it is clear that DMSO could affect gene expression even at low concentrations. Thus, in experiments where it is used as a solvent, a separate control should be included where DMSO is compared to normal growth conditions.

5.4.6 Effects of long-term E2 and ICI treatments

5.4.6.1 nNav1.5 mRNA expression Hormonal effects on ion channel expression are source of increasing interest. Investigations of ion channel promoter regions have revealed the following: (1) Putative hormone receptor (HR) binding sites, e.g. glucocorticoid and androgen (Diss et al., 2007; Kye et al., 2007; Quinkler et al., 2005; Sayegh et al., 1999) which suggest possible direct regulation with HR binding. (2) Putative transcription factor (TF) binding sites, e.g. Apl, Spl, NFiB (Cherlet and Murphy, 2007; Marino et al., 2006; Saville et al., 2000; Wittliff et al., 2008) which suggest possible indirect regulation via HR binding to TFs. A recent study specifically looked at regulation of VGSC13 subunit expressions in human PCa cells in relation to androgen sensitivity (Diss et al., 2007). Interestingly, cell type specific and time and dose-dependent effects were seen. VGSCI31 subunit mRNA

209 expression was lower in androgen receptor (AR)-positive LNCaP cells than AR-negative PC-3 cells (Diss et al., 2007). Treatment with 10 nM dehydrotestosterone (DHT) decreased VGSCril subunit mRNA expression in both LNCaP and PC-3 cells after 24 h and in only LNCaP cells after 48 h. Interestingly, 48 h treatment with 100 nM DHT decreased VGSCI31 subunit mRNA expression in LNCaP cells, but increased it in PC-3 cells (Diss et al., 2007). Both doses of DHT did not have any effect after 72 h. These data suggested androgen regulated expression of VGSC[31 subunit in PCa cells. These results complement the present study showing regulation of a VGSCa subunit (i.e. nNav1.5) mRNA expression by long-term treatment with E2 in BCa cells. In the present study, E2 was shown to have time- and dose-dependent effects on nNav1.5 mRNA expression in MDA-ERa cells. After 24 h treatments, 1 nM E2 significantly decreased nNav1.5 mRNA whilst 10 and 100 nM E2 had no effect (Figure 5.12). The effect of E2 was also time-dependent and 10 nM E2 significantly induced nNav1.5 mRNA expression only after 72 h (Figure 5.13). E2 was previously reported to have similar time- and dose-dependent effects in different cancer cells. For example, Caiaz7a et al. (2007) reported a biphasic change in ERr3 mRNA expression in human colon cancer cells where 10 nM E2 caused a reduction after 4 h and an increase after 24 h. Another study found a gradual increase in Akt activation in ERa-negative MDA-MB- 435 BCa cells after 5-10 minute treatment with 1µM E2 which was reversed after 30-100 minutes (Tsai et al., 2001). The same group also showed that a lower dose of E2 (100 nM) decreased Akt activation. Zhao et al. (2004) reported time-dependent effect of E2 on ERa over-expressing MCF-7 cells where levels of cell cycle proteins such as c-Myc, Cyclin D1 and p21 increased after 8 h and decreased after 24 h. Sengupta et al. (2004) reported differential effect of E2 on VEGF-A expression in SKBR-3 cells. Thus, 10 nM E2 increased VEGF-A mRNA expression after 2 h, did not change after 4 - 6 h, and increased it again after 24 h (Sengupta et al., 2004). Phytoestrogens were also found to have dose- and time-dependent effects. For example, genistein, an isoflavonoid found in soy and soy products (Allred et al., 2005), was shown to have estrogenic effects in BCa cells (Seo et al., 2006). A recent study reported differential expressions of several genes with low (1-5 uM) and high (25 04) doses of genistein in MCF-7 and LNCaP cells (Lavigne et al., 2008). Resveratrol, found in the skin of red grapes (Athar et al., 2007; Burns et al., 2002), has been widely studied in BCa cell lines. At concentrations of 5-20 uM, it was shown to

210 increase proliferation of MCF-7 and T47D cells (Gehm et al., 2004; Lu and Serrero, 1999) whereas at higher concentrations (25-180 µM) it inhibited proliferation of both MCF-7 and MDA-MB-231 cells (Basly et al., 2000; Mgbonyebi et al., 1998). Such variable effects of E2, phytoestrogens and estrogen-like subtances on gene expression and proliferation could be due to expression of ERa variants and/or other ERs in ERa-positive or ERa-transfected cell lines. Furthermore, Gehm et al. (2004) reported different types of mutations in ERa constructs and discussed that these mutations could cause complex effects in a ligand and target gene dependent manner. Supporting this view, an ERa variant was revealed in western blots and assays in ERa and ERI3-negative SKBR-3 cells (Sengupta et al., 2004). Use of ICI in the present study also exhibited time- and dose-dependent effects on nNav1.5 mRNA expression in MDA-ERa cells: After 48 h, 100 nM ICI significantly increased whereas 1 µM ICI did not affect nNav1.5 mRNA expression (Figure 5.16), and after 72 h, 1 µM ICI significantly decreased whereas 100 nM ICI did not affect nNav1.5 mRNA expression (Figure 5.16). These data suggests that ERa-dependent gene regulation is complex and accordingly nNav1.5 mRNA expression could be induced and/or reduced with ERa activity in a time- and dose-dependent manner. This complex behaviour of ERa may also be due to the regulation of the receptor expression upon ligand binding, e.g. E2 was found to decrease ERa expression in BCa cells (Nonclercq et al., 2004) and ICI was found to increase its degradation (Peekhaus et al., 2004). Thus, any possible change in ERa expression/activity via ligand binding could accordingly result in a time-dependent effect on gene regulation. On the other hand, the notion of ICI being a pure 'anti-estrogen' has been challenged; it has been found to activate the novel estrogen receptor, GPR30 (Filardo et al., 2002) and enhance signaling via transcription factors (Jakacka et al., 2001). In the previous study (Chapter 4), E2 was shown to increase nNav1.5 mRNA in ERa-negative MDA-MB-231 cells. This effect was again time- and dose-dependent: 1 nM E2 caused a significant increase by — 12-folds after 24 h and no effect was seen after 2 - 12 h; and 0.1, 10 nM and 100 nM E2 showed no effect (Figures 4.3 and 4.4). This suggested an ERa-independent increase in nNav1.5 mRNA expression in these cells and GPR30 was suggested to play a role. In the current study, MDA-ERa cells express both ERa and GPR30; thus E2 regulation of Nav1.5 could be via either receptor. In order to specify, VC5 cells (ERa-negative and GPR30-positive) were also treated with E2.

211 Consistent with the previous study (Chapter 4), 24 h treatment with 1 nM E2 increased nNav1.5 mRNA significantly by — 3-folds (Figure 5.15). The difference in the size of the effects could be due to the different culture conditions or possible effect of vector- transfection into VC5 cells. Nevertheless, the overall effects were in the same direction. Thus, it was concluded that nNav1.5 mRNA expression in BCa cells is reduced by E2 via an ERa-dependent pathway. The possibility still exists that there is an ERa-independent pathway increasing nNav1.5 mRNA expression at higher dose of E2 in MDA-ERa cells. A possible mechanism involved could be cross-talk with growth factor receptors (Azios and Dharmawardhane, 2005; Fan et al., 2007). Importantly, EGF was shown to regulate VGSC expression and activity in both BCa and PCa cells (Uysal-Onganer and Djamgoz, 2007; Pan, 2006). Thus, further investigation of the comparative/interactive role of EGFR and ER(s) in nNav1.5 expression would be worthwhile.

5.4.6.2 Cellular behaviours Estrogen involvement in adhesion was previously reported by gene expression and functional studies. Cell adhesion molecules such as integrin a3f31 (Licznar et al., 2003), E-cadherin (Oesterreich et al., 2003), focal adhesion kinase (FAK; (Bartholomew et al., 1998), and CD36 (Uray et al., 2004) were down-regulated by E2 treatment in BCa cells. Interestingly, an interaction was also reported between integrin 01 and FAK phosphorylation (Lin et al., 2000): Use of an antibody against integrin 131 inhibited FAK phosphorylation and reduced focal adhesions. Another hormone, progesterone, increased focal adhesions and this effect was also inhibited by use of integrin 01 antibody (Lin et al., 2000). Resveratrol decreased FAK activity in ERa-negative MDA-MB-231 cells and directly regulated integrin 133 in MCF-7 and MDA-MB-231 cells (Lin et al., 2006). Additionally, ICI was also reported to decrease cell-cell adhesion of MCF-7 cells (Paredes et al., 2004). Change in adhesion could modulate other metastatic cell behaviours (MCBs) such as motility, migration and invasion (Acconcia et al., 2006; Azios and Dharmawardhane, 2005; Paredes et al., 200). Importantly, integrin expression is associated with histologic grade of breast tumours (Zutter et al., 1990): It exhibits decreased expression in poorly- differentiated breast carcinoma tissues and higher in normal and well-differentiated tissues (Zutter et al., 1990). Thus, there is a complex and coordinated regulation of

212 adhesive properties during metastasis, and E2 regulation of integrin presents example of estrogen involvement in cancer cell adhesion/MCB. In the present study, adhesion of MDA-ERa cells decreased following 24 h treatments with 1 and 10 nM E2 (Figure 5.14). Co-treatments with TTX revealed that this effect was VGSC-dependent. VGSCs were previously shown to increase MCBs such as invasion and migration (Fraser et al., 2005). Furthermore, blocking VGSC activity with TTX increased adhesiveness of cancer cells (Palmer et al., 2008). Here, adhesion of MDA-ERa cells was also increased with TTX treatment, and E2 application in the presence of TTX failed to reduce adhesion. This could suggest increased VGSC activity after E2 treatment, which would contradict the decrease in nNav1.5 mRNA expression after 1 nM E2 treatment in these cells (discussed in section 5.4.6.1). Accordingly, long- term E2 treatment of MDA-ERa cells could have increased nNav1.5 protein expression and/or activity which would have resulted in reduced adhesion. Nevertheless, consistency exists between this and previous study (Chapter 4) in which long-term E2 also decreased adhesion of MDA-MB-231 cells VGSC-dependently. In an attempt to identify involvement of ERa in adhesion of MDA-ERa cells, long-term (24 h) ICI treatment was performed. Surprisingly, no effect was detected (Figure 5.17). As discussed in section 5.4.6.1, this does not provide a definitive answer, as ICI could itself provoke signaling via GPR30 (Filardo et al., 2002) or non-classical pathways (involving transcription factors such as Ap 1 ; Jakacka et al., 2001). Preliminary experiments to further investigate possible effects of long-term (> 24 h) treatments with ICI revealed increased MCBs such as migration and motility of MDA-ERa cells (Figure 5.18). These data are indicative of increased metastatic potential following ICI treatment. Thus, it may follow from the present study on adhesion that ICI actually blocked ERa- dependent pathway; however, since the basal ERa activity was insufficient to change adhesion, blocking ERa had no detectable effect. On the other hand, the data on migration and motility (Figure 5.18) with ICI could also indicate an ERa-independent effect, as discussed before. Additionally, a sufficient level of functional VGSC expression (which is relatively low in MDA-ERa cells) may be needed to evoke a change in adhesion. Further investigation of MCBs (e.g. adhesion, migration and motility) would be necessary for understanding the role of ICI and/or ERa, whereby (1) ICI is applied after E2 treatments (where ERa is activated), or (2) ICI treatments follow VGSC activation.

213 Chapter 6

GENERAL DISCUSSION

214 Despite recent developments in research on breast cancer (BCa), there is an urgent need for better diagnostic/prognostic and therapeutic tools for its clinical management. The present study aimed to evaluate the potential role of neonatal Nav1.5 (nNav1.5) in metastatic disease. The main results are as follows: 1. ERa-negative MDA-MB-231 cells expressed a novel estrogen receptor, GPR30 (mRNA and protein) at levels that were considerably lower than in the MCF-7 cells. 2. Short-term treatment of MDA-MB-231 cells with 1713-estradiol (E2) reduced their adhesiveness via a GPR30-dependent pathway since (i) a GPR30-specific ligand (G1) mimicked the effect of E2; and (ii) knock-down of intracellular GPR30 protein (by siRNA) inhibited both E2- and G1 -induced reduction in adhesion. Importantly, (i) blockage of VGSCs by tetrodotoxin (TTX) and (ii) a PKA- inhibitor (PKI) suppressed the effect of E2 on adhesion. 3. Long-term treatment with E2 (but not Gl) significantly increased nNav1.5 mRNA expression in MDA-MB-231 cells and reduced their adhesiveness. This effect was also inhibited by co-treatment with TTX. 4. Over-expression of internal GPR30 protein in MDA-MB-231 cells (giving GPR30-14 cells) enhanced long-term reduction of adhesion by E2. Long-term treatment with G1 also reduced adhesion in GPR30-14 cells. 5. nNav1.5 mRNA and protein expression were reduced significantly after stable transfections of MDA-MB-231 cells with ERa (giving MDA-ERa cells). However, GPR30 mRNA expression was not affected by the ERa transfection. 6. Long-term treatments of MDA-ERa cells with E2 significantly reduced nNav1.5 mRNA expression time- and dose-dependently. Long-term treatment of ERa- negative/empty-vector transfected VC5 cells with E2 significantly increased nNav1.5 mRNA, similar to MDA-MB-231 cells. 7. Long-term treatment of MDA-ERa cells with E2 reduced their adhesion VGSC- dependently. 8. Long-term treatment of MDA-ERa cells with anti-estrogen ICI-182,780 (ICI) did not affect their adhesiveness.

215 6.1 Problems in the therapy of breast cancer

BCa therapies involve chemotherapy, radiotherapy, surgery and immunotherapies (e.g. Bentzen et al., 2008; EBCTCG, 2005). Although survival of BCa patients has increased over the last decade because of improved screening methods and systemic therapies (hormone therapy and chemotherapy), many patients still die from metastatic relapse (Bertucci et al., 2006). Like many cancers, metastatic BCa is a complex disease which involves multiple molecular alterations which could potentially cause increased invasiveness and treatment-resistant phenotypes. The traditional diagnostic/prognostic factors for BCa include tumour size, nodal status, histologic subtype and hormone and growth factor receptor status (Ali and Coombes, 2002; Andreopoulou and Hortobagyi, 2008). Accordingly, BCa can be classified into three main groups depending on the potential benefit from endocrine- related therapies: (1) hormone-receptor positive, for which anti-estrogens (e.g. tamoxifen) can be used. (2) HER-2 positive, for which antibody-based therapy (i.e. trastuzumab) can be used; and (3) hormone- (estrogen and progesterone) receptor- and HER-2-negative, "triple-negative", which consists 15 % of all BCa patients (Cleator et al., 2007) for which chemotherapy is the only available therapy (Reis-Filho and Tutt, 2008). However, one in three women with BCa is premenaopausal (Kurebayashi, 2008) which limits the efficiency of the tamoxifen treatment and poses a high risk of local and systemic relapse (Cleator et al., 2007). The response to systemic treatment and disease-free interval are patient specific, reflecting the complexity of individual tumour behaviour (Mansour and Schwarz, 2008). For identification and efficient treatment of BCa, especially the "triple-negative" group, specific molecular markers are needed. Thus, research is required to identify and validate new BCa markers and novel molecular therapies. In this regard, studies have concentrated on use of cancer stem cells, proteomics, miRNAs and circulating tumour cells (Dawood et al., 2008; Fraser et al., 2005; Slade and Coombes, 2007; Zhu et al., 2008). Patient relapse within 5 years of tamoxifen treatment could be due to cancer cell dissemination (micrometastases) in bone marrow or peripheral blood at an early stage (Andreopoulou and Hortobagyi, 2008; Slade and Coombes, 2007). A challenge, therefore, is to detect micrometastases at an early stage. The presently-used techniques are immunocytochemistry and reverse-transcriptase PCR, latter being more specific. There are several markers (e.g. cytokeratins) used to detect circulating tumour cells but these are

216 not strictly BCa specific (Slade and Coombes, 2007). It is vital to identify BCa specific markers that can easily be detected not only in bone marrow but also in peripheral blood. Neonatal Nav1.5 mRNA/protein could be one such marker.

6.2 Role of estrogen and its multiple receptors in BCa

Estrogen is an important hormone molecule that regulates a range of cellular signaling pathways involved in cell proliferation, differentiation and homeostasis of mammary gland development and bone density. The involvement of estrogen and its receptors in BCa development and progression is well established (Ali and Coombes, 2002). Indeed, the standard and most successful systemic BCa therapy for estrogen receptor (ER) positive BCa patients is endocrine therapy involving blockage of ER activity. Tamoxifen, a selective estrogen receptor modulator (SERM), is the first-line therapy for ER-positive patients. A main advantage of tamoxifen was it being a 'partial' antagonist where it can be anti-estrogenic in some cells and estrogenic in others where estrogen is still required for normal functioning (e.g. bone). However, endocrine therapy has limitations and side effects. Although early clinical trials with tamoxifen proved it successful with significant disease-free survival rates during 5-year follow-up, over the subsequent years it became apparent that — 25 % of patients ceased to respond and — 30 % of patients became `resistant' to tamoxifen (EBCTCG, 2005). Several reasons have been suggested for the failure of long-term tamoxifen therapy. Among these are intratumoral heterogeneity in ER expression, expression of ER variants or mutants with differential affinities to ligands (e.g. ERI3), partial agonistic activity of tamoxifen, and activation of alternative signaling mechanisms (e.g. EGF) (EBCTCG, 2005; Filardo et al., 2006; Normanno et al., 2005). The side effects of tamoxifen treatment include endometrial cancer and thromboembolism (EBCTCG, 2005). A possible reason for tamoxifen toxicity in BCa patients is activation of receptor mechanisms other than ER; this could also explain the low efficacy of tamoxifen treatment in ER-negative patients. One potential receptor that is activated by tamoxifen is GPR30 (Maggiolini et al., 2004; Thomas et al., 2005). GPR30 is expressed in both ER-positive and negative BCa cells (Filardo et al., 2008). Consequently, newer treatments are required with reduced toxicity to ensure prolonged high quality of life during/after treatment. Reverse-transcriptase PCR showed that ERa-negative BCa cell line MDA-MB-

217 231 expressed GPR30 mRNA at lower levels than the ERa-positive MCF-7 cells (Chapter 3). Western blot and immunocytochemistry supported the PCR data by showing GPR30 protein expression in MDA-MB-231 cells, again at lower levels than MCF-7 cells (Chapter 3). Confocal imaging following immunocytochemistry revealed GPR30 staining in both plasma membrane (PM) and intracellular membranes (IMs; Chapter 3). Quantification studies further demonstrated that GPR30 protein expression in IMs was higher than in PM by — 15 % (Chapter 3). Previous work was inconsistent regarding GPR30 expression in MDA-MB-231 cells. Reports exist where MDA-MB-231 cells (1) were found GPR30-negative (Thomas et al., 2005), (2) expressed GPR30 in PM (Filardo et al., 2002) and (3) expressed GPR30 in IMs (e.g. endoplasmic reticulum) (Matsuda et al., 2008; Prossnitz et al., 2008b). The discrepancies among such studies could be due to different detection methods (i.e. immunocytochemistry vs Western blot) or use of different antibodies with most groups producing their own antibodies (e.g. Revankar et al., 2005; Thomas et al., 2005), as well as different batches of cells and/or culture conditions. The different studies were consistent, however, in showing rapid activation of GPR30 with estrogen and involvement of downstream signaling pathways, such as cAMP, ERKI/2, and c-fos (Filardo et al., 2000; Liu et al., 2008; Maggiolini et al., 2004; Vivacqua et al., 2006). The present study showed both fast/non-genomic and long-term/genomic effects of E2 in MDA-MB-231 cells: (1) E2 reduced adhesion after short-term (10 minutes) and long-term (24 h) treatments (Chapters 3 & 4) and (2) E2 increased gene expression (nNav1.5) after long-term (24 h) treatment (Chapter 4). Both (1) and (2) occurred via GPR30 and could involve PKA activity. Adhesion is one of the important stages of metastasis and cancer cells with low cell-to-substrate (or-cell-cell) adhesion are more likely to invade through extracellular matrix and migrate into circulation. Accordingly, reduced adhesion of BCa cells after GPR30 activation, possibly via VGSC activity, is a novel mechanism whereby cells could gain resistance to partial-agonistic tamoxifen therapy, leading to disease recurrence (Bacac and Stamenkovic, 2008; Dittmar et al., 2008; Gumbiner, 1996). Activation of GPR30 with E2 and tamoxifen induced c-fos induction and proliferation of endometrial cancer cell line HEC1A, and knock-down of GPR30 by antisense oligonucleotides inhibited this effect (Vivacqua et al., 2006). Intriguingly, in human saphenous veins, which express GPR30, E2 caused increased vasoconstriction

218 which was suggested to be via ERK1/2 phosphorylation (Haas et al., 2007). This could be a mechanism whereby tamoxifen treatment can cause venous complications in BCa patients. These data could also explain the possible side effects of tamoxifen where ER- independent, and possibly GPR30-dependent, pathways are involved. Therapies to block or inhibit GPR30 pathway, for example by using RNAi technology, GPR30-antagonists (development of G1 analogues), could have potential therapeutic importance. RNAi- based drugs are found successful in clinical trials of various diseases such as muscular degeneration, hepatitis C, asthma and viral infections (Putral et al., 2006). There are pre- clinical in vivo studies supporting RNAi use in novel cancer therapeutics: (1) to block VEGF in human colorectal caner cells (Lv et al., 2007), (2) to inhibit human papilloma virus oncogenes in human cervical cancer cells (Gu et al., 2008) and (3) against human prostate specific membrane antigen in human prostate cancer cells (Zhao et al., 2008a). The present study also utilized RNAi technology in vitro, which efficiently knocked- down both GPR30 mRNA and protein by 50-70 % (Chapter 3). This was enough to inhibit the effect of E2 treatment on cell adhesion (Chapter 3) which would support the potential benefit of an RNAi approach to novel cancer therapy.

6.3 Role of VGSCs in cancer

Studies showing ion channel involvement in cancer progression and metastasis are increasing in number. Expression of many voltage gated ion channels have been reported in different cancer cell types (Fiske et al., 2006): Prostate, lung, glioma colon, neuroblastoma, melanoma, cervix, lymphoma and breast (Allen et al., 1997; Bennett et al., 2004; Diaz et al., 2007; Diss et al., 2001, 2005; Farias et al., 2004; Fraser et al., 2004, 2005; John et al., 2004; Onganer and Djamgoz, 2005; Preussat et al., 2003; Roger et al., 2003, 2007). There is also increasing evidence for association of VGSC activity with metastatic cell behaviours (MCBs). Blocking the VGSCs expressed in metastatic BCa cell line MDA-MB-231 (i.e. nNav1.5) with tetrodotoxin (TTX), RNAi or a specific polyclonal antibody (NESOpAb) reduced in vitro migration and invasion (Brackenbury et al., 2007; Chioni et al., 2005; Fraser et al., 2005). Additionally TTX increased in vitro cancer cell adhesion, which could involve VGSC subunits (Palmer et al., 2008). The present study also demonstrated regulation of MCBs in BCa cells (i.e. MDA- MB-231) by VGSC (i.e. nNav1.5), where both short and long-term TTX treatments

219 increased adhesion (Chapters 3 & 4). Interestingly, increased gene expression of nNav1.5 after E2 treatment of MDA-MB-231 cells resulted in a significant reduction in cell adhesion (Chapter 4). Although the exact mechanism(s) of how VGSCs could regulate MCBs is not currently known, there are several possibilities, including association with other proteins such as cytoskeletal, intracellular signaling (e.g. PKA, cAMP) and adhesion molecules (e.g. NrCAM and VGSC(I) (Hedstrom et al., 2007).

6.4 Estrogen regulation of VGSCs and its role in BCa

Ion channel regulation occurs at transcriptional, post-transcriptional and post-translational levels where different regulatory molecules are involved such as growth factors, transcription factors, steroid hormones and other modulatory proteins, e.g. PKA, PKC, VGSCI3 (Diss et al., 2004; Schulz et al., 2008). VGSCs are transcriptionally regulated by repressor element 1-silencing transcription factor (REST) (Chong et al., 1995), NFKB, nerve growth factor (NGF), epidermal growth factor (EGF) (Ding et al., 2008; Onganer and Djamgoz, 2005), neurotrphin-3 and Brn-3 (Brackenbury and Djamgoz, 2007; Chong et al., 1995; Ding et al., 2008; Diss et al., 2006; Onganer and Djamgoz, 2005; Wilson-Gerwing et al., 2008). Hormonal regulation of VGSCs and many other ion channel genes are also increasingly being reported (e.g. Chew and Gallo, 1998; Furukawa and Kurokawa, 2007; Herve, 2002; Tasker, 2000). For example, androgen was shown to regulate Navl.7 and VGSC131 gene expression in PCa cells and aldosterone was reported to regulate VGSCs in mouse cardiomyocytes (Boixel et al., 2006). Long-term estrogen treatment of ERa-negative MDA-MB-231 cells increased nNav1.5 mRNA levels (Chapter 4) whereas ERa expression in these cells (MDA-ERa cells) inhibited nNav1.5 mRNA and protein expression significantly (Chapter 5). This was further supported by a decrease in nNav1.5 mRNA after long-term E2 treatment of MDA-ERa cells (Chapter 5). This was intriguing because whereas E2 activation of only GPR30 increased nNav1.5 mRNA expression (Chapter 4), a combined activation of ERa and GPR30 reduced nNav1.5 mRNA and protein expression (Chapter 5). This supports the differential signaling mechanisms activated by ERa and GPR30 (Madak-Erdogan et al., 2008). Importantly, data from previous reports suggested reduced metastatic potential with decreased nNav1.5 expression (e.g. Brackenbury et al., 2007; Fraser et al., 2005). This would suggest that E2 treatment of MDA-ERa cells should inhibit MCBs, i.e.

220 increase cell adhesion, via reduced nNav1.5 expression. Conversely, treatment of MDA- ERa cells with E2 for 24 h showed significant reduction in adhesion and this was VGSC- dependent (Chapter 5). Importantly, treatment of ERa-negative/empty-vector transfected control cells (i.e. VC5 cells) with E2 for 24 h showed increased nNav1.5 mRNA expression (Chapter 4). These data further suggested (1) that GPR30 is involved in E2- induced VGSC activity and reduced adhesion in these cells, and (2) that expression of ERa in normally non-expressing cells (i.e. in MDA-ERa cells) represses VGSC mRNA and protein expression. Regarding (1), the findings from Chapter 3 provided information about the signaling mechanisms downstream of GPR30. Pre-treatment of MDA-MB-231 cells with PKA inhibitor PKI inhibited the E2-induced reduction in cell adhesion (Chapter 3). This indicated a model for regulation of adhesion by estrogen via GPR30 which involves PKA as the downstream signaling molecule (Figure 6.1). According to this model, E2 could activate GPR30 both in PM and cytosol (Chapter 3). This would activate adenylate cyclase (AC) isoforms in PM and cytosol, respectively (Cooper and Crossthwaite, 2006; Sunahara and Taussig, 2002). Increased cAMP activity via either or both AC isoforms (Figure 6.1, 2a & 2b) would increase activity of different PKA regulatory subunits (Ghil et al., 2006). The activation of PKA could then induce VGSCa expression in PM and activity (Brackenbury and Djamgoz, 2006; Chioni, 2007). Alternatively, association of GPR30 with EGFR (Figure 6.1, 5; Filardo et al., 2008) could also result in increased VGSCa expression and activity (Figure 6.1, 6; Ding et al., 2008; Uysal-Onganer and Djamgoz, 2007) which would in turn increase PKA activity (Figure 6.1, 4; Brackenbury and Djamgoz, 2006). VGSC-induced PKA activity can regulate adhesion molecules such as integrins (Chilcoat et al., 2008; El Zein et al., 2008; Gonzalez et al., 2008b) and VGSCI3 subunits which can interact with cytoskeletal proteins (e.g. ankyrins) and alter adhesion (Malhotra et al., 2004; McEwen and Isom, 2004). VGSCI3 subunits can also modulate VGSCa interaction with cytoskeletal molecules (e.g. ankyrins), leading to changes in adhesion (Figure 6.1, 9; Chioni, 2007). Regarding (2), the findings from Chapter 5 suggested that transfection of ERa into natively ERa-negative cells could make them less metastatic as previously reported (e.g. Garcia et al., 1992; Levenson and Jordan, 1994; Rochefort et al., 1998). In the present study, E2 treatment (for 24 h) reduced nNav1.5 mRNA and protein expression in MDA- ERa cells. Surprisingly, adhesion was still reduced (Chapter 5), which was not consistent

221 EGFR GPR30 VGSCa

1 Na* GPR30

cAMP

PKA

MCB (adhesion)

Figure 6.1: A hypothetical model of estrogen regulation of VGSCs and adhesion in BCa cells.

Estrogen signalling through GPR30 in both plasma membrane (PM) and cytosol is presented. Active GPR30 initiates downstream signalling where adenylate cyclase (AC) isoforms are activated by G-proteins in PM (la) or cytosol (lb). Differential activation of cAMP is possible via different AC isoforms (2a & b). Different PKA regulatory subunits are activated (3). PKA can regulate VGSCa (4), and VGSCa activity can in turn induce PKA (4, double sided arrow). GPR30-EGFR cross-talk (5) is possible which can regulate VGSCas (6). MCBs (i.e. adhesion in the present study) can be regulated via PKA through integrins (7) and VGSC13 (8).VGSC(3 subunits can also interact with VGSCa (9) to modulate their interaction with cytoskeletal proteins and change adhesion.

222 with decreased metastatic potential. Further investigation of additional MCBs is needed to provide further information regarding the protective role of ERa transfection in BCa cells and its potential use in novel therapeutic applications.

6.5 Clinical implications The role of estrogen in BCa progression and development has been well studied (Ali and Coombes, 2002; Urruticoechea, 2007). ER status of patients is among important prognostic factors which also predict the benefit from endocrine therapies (EBCTCG, 2005). Standard tamoxifen treatment for ERa-positive BCa was shown to be highly successful in 5-year follow up studies (EBCTCG, 2005). However, patients still develop resistance and BCa recurrence follows (EBCTCG, 2005; Jemal et al., 2008). Possible mechanisms for resistance include loss of ERa expression, increased estrogen sensitivity and signaling via other receptor mechanisms (e.g. ERR, HER2, GPR30) (Normanno et al., 2005). For ERa-negative BCa, current treatments are limited to aromatase inhibitors and HER2 inhibitors which have limitations since ER/HER2-independent signaling exists (Buzdar et al., 2008; Cleator et al., 2007; Reis-Filho and Tutt, 2008). Importantly, recent advancements in identification methods for novel receptor systems (e.g. GPR30) and gene signatures (e.g. MMPs) have provided important information on possible ways to target resistance and disease recurrence. Clinical trials currently involve inhibitors against signaling mechanisms (e.g. VEGF and PI3K inhibitors) which have produced promising results (Garcia-Echeverria and Sellers, 2008; Lv et al., 2007). There are protein-kinase inhibitors under development for use in BCa, e.g. Src inhibitors and drugs working on HSP90 pathways are currently being tried in clinical studies (Cleator et al., 2007). One important receptor mechanism increasingly shown to be involved in estrogen signaling is GPR30, which is involved in several cross-talk mechanisms including growth factors (Filardo et al., 2008). Unlike ERa, GPR30 could also be activated by tamoxifen (Thomas et al., 2005). Additionally, GPR30 expression in endometrial cells and mammary veins support a possible role for GPR30 in endometrial cancer and venous problems resulting from tamoxifen treatment (Haas et al., 2007; Vivacqua et al., 2006). Reduced treatment efficacy in ER-negative BCa patients could also be a result of GPR30 activity. The present study demonstrated functional expression of GPR30 in ERa- negative BCa cells (Revankar et al., 2005). Activation of GPR30 with estrogen reduced adhesion of BCa cells, which could lead to increased cell migration and invasion.

223 Importantly, the effect on adhesion was blocked by GPR30-RNAi treatment. Further evidence also show association of GPR30 with in vivo BCa metastasis and activation of various signaling mechanisms (e.g. cAMP, ERK1/2) could indicate that GPR30 is a potential `oncogenic' marker in BCa (Filardo et al., 2000). A novel role-player in cancer metastasis is VGSC. It has been shown to increase metastatic potential of BCa, PCa and lung cancer cells (Diss et al., 2005; Fraser et al., 2005; Onganer and Djamgoz, 2005). Additionally, neonatal Nav1.5 expression was highly correlated with in vivo lymph node BCa metastasis (Fraser et al., 2005). Intriguingly, the present study demonstrated activation of nNav1.5 rnRNA expression and activity by estrogen. Indeed, possible increased metastatic potential of BCa cells (i.e. reduced adhesion) was inhibited by VGSC blocker TTX, which was previously shown to inhibit other MCBs such as migration and invasion (Fraser et al., 2005). Significantly, blocking nNav1.5 with a specific antibody (NESOpAb) or RNAi also inhibited cellular invasiveness of BCa (Brackenbury et al., 2007). The finding in the present study that estrogen increases nNav1.5 expression and activity provides a novel mechanism where estrogen could promote cancer metastasis in ERa-negative BCa patients. Furthermore, increased expression and activity of nNav1.5 via GPR30 activation demonstrates a possible mechanism where GPR30 could increase metastasis, resistance to therapy and disease recurrence via tamoxifen treatment. Importantly, the 'neonatal' nature of VGSC expressed in BCa cells provides a good therapeutic potential where specific blockers can be used which will not have cardiovascular side effects. Further investigation of involved signaling mechanism connecting GPR30, VGSC and adhesion revealed a role of PKA which was previously reported to regulate VGSCs (Brackenbury and Djamgoz, 2006; Chioni, 2007). In addition to this, available data on GPR30-EGFR cross-talk (Filardo et al., 2008) and EGF regulation of VGSC (Ding et al., 2008; Onganer and Djamgoz, 2005) provide alternative ways in which GPR30 could activate VGSC and change adhesion. One of the most striking fmdings in the present study was estrogen down- regulation of VGSC expression in ERa-transfected BCa cells. Following the previous findings of estrogen-induced VGSC expression and activity in ERa-negative/GPR30- positive BCa cells, this finding suggests a potential protective role of ERa expression in normally non-expressing cells. Early work by several groups demonstrated similar results where ERa transfection decreased cellular invasiveness and metastatic potential (Garcia

224 et al., 1992; Levenson and Jordan, 1994; Rochefort et al., 1998). The present study provides important information about possible role of VGSCs in the protective role of ERa, which could suggest ERa transfection as a therapeutic method to target ERa- negative BCa. Surprisingly, investigation of functional outcome of ERa-induced VGSC inhibition did not provide sufficient information regarding its effects on MCBs. BCa cell adhesion was reduced after estrogen treatment via a VGSC-dependent pathway. This could suggest (1) that ERa acts on at least two different mechanisms to regulate gene/protein expression and adhesion; and (2) that ERa-transfection affects gene expression whereas pre-existing GPR30 regulates adhesion in BCa cells. Both of these predictions serve as potential mechanisms to be further investigated and could provide novel therapeutic advantages.

6.6 Future perspectives

Despite decades of research, BCa maintains its nature as a complex disease for which a definite cure still awaits. The present work raises possibilities for novel therapeutic approaches involving new estrogen receptors (e.g. GPR30), signaling mechanisms (e.g. PKA) and novel role players (e.g. VGSC). First of all, the exact mechanism of how VGSCs affect MCBs should be elucidated in order to specifically understand how estrogen activation of VGSCs via GPR30 could affect cancer progression. Interactions with cytoskeletal proteins and signaling complexes provide a good start point to further study. Consequently, how GPR30 regulates VGSC expression and activity is also important to clarify. Use of selective inhibitors of signaling molecules (e.g. cAMP, PKC, PI3K, VGSC(3) and possible growth factor mechanisms (e.g. EGFR, IGFR) will not only provide information of possible pathways involved in VGSC regulation by estrogen, but will also suggest new molecular targets for blocking cancer progression. Further characterization of VGSCs' involvement in estrogen-induced metastasis would also be important. Possible effects of knocking down nNav1.5 with RNAi could be used instead of TTX treatment to investigate effect on adhesion. An intriguing experiment would involve use of MCF-7 cells (ERa and GPR30-positive) in which nNav1.5 is only expressed internally. Treating these cells with estrogen and analyzing effects on VGSC expression and activity will provide insight about VGSC regulation in these cells.

225 The fording that estrogen reduced VGSC expression in ERa-transfected MDA- MB-231 cells suggested a mechanism where ERa could inhibit metastasis. Further investigation of this could be achieved as follows: (1) Use of MCF-7 cells which natively express ERa and GPR30 to study VGSC expression and activity after estrogen treatment will shed light into differences of estrogen-regulation between ERa- negative and ERa- positive BCa. (2) Knocking down ERa from transfected cell lines and then treating them with estrogen to test whether (i) VGSC expression would be reduced and (ii) estrogen would still have an effect. Conversely, the proposed role of GPR30 in reducing adhesion in ERa transfected cell lines could also be tested by knocking down GPR30 from these cells and then investigating possible outcome on estrogen's effect on adhesion. Another intriguing experiment would involve use of tamoxifen to test possible activation of GPR30 in BCa cells and its potential effects on VGSC expression/activity and MCBs. This will help further understand the mechanisms involved in resistance and disease recurrence during/after tamoxifen treatments. Finally, the studies presented in this Thesis and the additional suggested experiments should be performed in in vivo BCa models in order to complement the in vitro work and prepare the ground for possible future clinical applications.

226

APPENDIX I (A) Nav1.5 promoter region (Genbank Accession No: AY313163). Sequences corresponding to two of the three putative ERE half-sites and one Spl binding site are underlined and labeled. (B) Schematic view of human Nav1.5 proximal promoter (Yang et al., 2004). Three putative estrogen receptor half-sites (ERE1/2) (diagonal hatching) are evident upstream of the transcription initiation site (TIS), one of which is in close proximity to a putative Spl site that may potentiate estrogen receptor binding to the promoter (Porter et al., 1997). Data provided by Dr. J.K.J. Diss.

ERE A. -1027 CCIGTGACCATGTCTCIGAGTGAGAAACAGIGGGTGTGTAAGTATGMACTCC

AGGCrICTGCATGTGICAAGGTGAAGGTTGTATGIGGC1CAAGAGGGTGGAAGTA

TATATATAAAGAGGTATATACATG TATATATKIGTATUTGMTUIGTGTGTIT

GCGCGCGCGCGTGTGIUGGIGTC'ICTGTGTIGGTIGCCTGCTTGCTIrTGGGT

-814 CTGGVIGTOTGTVIGGIMUIGTCAGCATGIGCGIVCGTVIGTICAGGTAGATG

IGTACCATTGTGCAGATITCIVIGGCATCACTAAGTGTGMTCCAGGAAAGTGT

GGTrCGAGIGAGMTGTGTGTCTCTUTGIrAGTGTGTCAGTGGAIUTGTGTCT

AAGIUAIGIUGGTGICTAAGTITGTCAGAGIVICTTCCTCAGTGWAGTG'IGT

-601 GIVAATUATGTGTCTGTCIGTGTC'IMGIUGGIUTGTGGGGGTGTGTATCTGM

MAGGGIGCATGIGIU'IGICTGTGTCAGTGCAGGTATGCCTATGGCAGCGTUT

GTCTGTCTCGGCATGAGTGIrAGTGTATGCCCGTGTCCACGTGGGMGGTGGGT

GTCTGGTAGCCITCCCAAGTCAOCAAGGIWCGTGTGTGTGTGTUTATACTCTG

-386 GCGGGTGCMGTGIGTATGCCAG'IG 1"1"1L., TTAATG TGAGCC'IGTCCGCGTCCG

CGTGGGIGGCCATCTGTGGTGAAGCGTCGCCGGGTCGCCUIGIUTGTACCCC

CGCCTATU 11.71isTCTUICCGCGGCCGCGTGIGCGGCTGTCTGTGGCTMGAGC ERE Sp 1 -22 8 CCCCGGGTCAGTGTGGGAGTGTGCGCCCCGGCGGGCGCTVG'TGTGTCCCCC

CTCCGAGCGGGCGGAGCACCACGTGCGGAGCCCIGGGCGCGTUGCTCTGGGG

CGGAGCCAGCCCGGGGCCCCAAGCCCCAGGCCGAACCCAGGCGGGGCCCGC

CCCGACCCCGCCCCCGACCCCGCCCCCAGCCCGAGCCCGCGCCGCCTGCCC a b -22 GCCCGGGAGCCCGAACAGAGCCbCGGAGCCGAGACG

a = Minor transcript start site

b=Mai Of transcri pit start sit e

B. -1870 -1450 -1000 -200 -150 I I TIS P*41 fflA I

-2109 +140

227

APPENDIX II pBK-CMV phagemid vector (Stratagene): (A) The vector map. (B) The expression cassette. (C) Primer sequences for T3 and T7 used in sequencing.

A. .01

4411PINSVO p,.

^eolkor Izc -Kpn MCS. pB K-CMV -Sac 4.5 kb lac ---Nhe

7K c F DAV 4111111.101. puc or,

pl3K-CMV Multiple Cloning Site Region (sequence shown 952-1196}

T7Pmmatar 1114.1Zirm i I GTAAAAC3AOGGCCAGTGAATTGTAA.TACGACTCAL— A..A.GGGCGAATTWATACAC7TACCTIIG7A000CACCCGSGTSGAAA. M13.40 prim, 3.in&ng xis TY chi

Apa N at I Ma I S ac fccR 1,za L'f.,a1Ti1 ' Pit I ...ATCLATUGGCCUACGGCCGUCTAGAAGTACTC—CGAGAAGCTITTTGAA7TCTTIGGATZICAGTG7CC'.7.—GCAG..

Eazi a Sac P-amid., a-Fraqtrwro

__GCGCGOGAGCTCCAGOT--TG—TCC:::TTTALTGAGG0.7--AA—T—CGAGOTTGGOTTAATCAAGG7CATAGCTGTT—=7,— TS crmar a IA -? BK ra,•aria rimer

B. irocrl +.P; in$ert DNA. $V40 3 Rplico 5i10 Jazz .N.T§ sac% r iv, lin nil eu ka ryo tic prom o ier 1 LIT promote cZ MC5 T .6{011961iAIS 5 Sri kr •i14. ijaiart a S.: ,7a.tic:.lp z.t.1 7717027,Alit.wmil

C. PRIMER SEQUENCE T3 5' AATTAACCCTCACTAAAGGG 3' T7 5' GTAATACGACTCACTATAGGGC 3'

228

APPENDIX III GPCR-Br mRNA complete coding sequence (GenBank accession no: HSU63917). Location of nucleotides from sequencing with T3 and T7 primers is shown in 'pink' and `blue', respectively. Location of forward and reverse primers (Table 2.2) used in PCR experiments are labeled and shown shaded in grey. The sequence alignment was performed on ClustlW2 program (European Bioinformatics Institute).

1 uagccagccg ggaaccttcc ctcgcgggct cccagggcgg gtctcttcct ctctct 6cqgcagg tccagcagg,j Lgcagegggt tccg,gca 121 cetccagect gatmcctg accaaggagg ettccaggag cacagaaggq gctqcaacce 161 aggtacccag agagtgagca gctccacgcg ggactgtgca eggtggccga cacccgcagg 241 gacgcccgcc ggacgagcac geggagggcc ctcgcctcca eggatgcacc atgccggtgt 301 gaggagcatc tgttettecc actctctgca gttaacaagc ccaacccaaa ccaccacagg 361 tgctcctcct ggggagtttc ctitctgaca aatgccaggc tcacttcaag gagaatcacg T3 421 cttetttcta aagatggatt caccatttaa aacagagctc tgggagectt tcggcaaatc 481 ttgaaagctg cacggtgcag agacatggat gtgacttccc aagcCc9999 c9tgggcctg 541 gagatgtacc caggcaccqc gcagectgcg gcccccaaca ccacctccce cgagctcaac 601 ctgteccacc cgctcctgqg caccgccctg gccaatggga caggtgagct cteggageac 661 cagcagtacq tgatcggect gttectctcg tgectetaca ccatettect ettecccatc 721 ggctttgtgg gcaacatect gatectggtg gtgaacatca gettccgcga gaagatgacc 781 atccccgacc tqtacttcat caacctqgcq gtqqcqqacc tcatectgqt ggccgactec 841 ctcattgagg tgttcaacct gracgagegq qtgcacctt ,

901 atutcgctut tcctqcaggt caacatgtac agcagcgtct tuttectcac ctggatgagc Forward 961 ttcgaccgct acatcgccct ggccagggcc atgcgctgca gcctgttccg caccaagcac 1021 cacgcccggc tgagctgtgg cctcatctgg atggcatccg tgtcagccac gctggtgccc 1081 ttcaccgccg tgcacctgca gcacaccgac gaggcctgct tctgtttcgc ggatgtecgg 1141 gaggtgcagt ggctcgaggt cacgctgggc ttcatcgtgc ccttcgccat catcggcctg 1201 tgctactccc tcattgtccg ggtgctggtc agggcgcacc ggcaccgtgg gctgcggcce 1261 cggcggcaga aggcgctccg catgatcctc gcggtggtgc tggtcttctt cgtctgctgg 1321 ctgccggaga acgtottcat cagcgtgcac ctcctgcagc ggacgcagcc tggggccgct 1381 ccctgcaagc agtctttccg ccatgcccac ccectcacgg gccacattgt caacctcgcc 1441 gccttctcca acagctgcct aaacccectc atctacagct tectcgggga gacctt, 1501 aoaagot (1110- acat tgagcagaaa acaaatttc(2cggccctgaa cccicttcegt Reverse 1561 cacgctgccc tgaaggccgt cattccagac agcaccgagc agtcggatgt gaggettagc 1621 agtgccgtgt agacagcctt ggccgcatag gcccagccag ggtgtgactc gggagctgca 1681 cacacctggg tggacacaag gcacggccac gtcatgtctc taaattgcgg tcagatgtgg 1741 cttctggctc ctcggggcct cgcgagggtc acgcttgcct ggtcaccctg gggctgctta

1801 ggaaacctca cgactggtca ccttgcactc ctcacacaga attgetacaa tcccaaagcg 1861 ctcgccccgc agggtccaaa ggccagcggt gaccagectg tcacccaget cctecccgcc 1921 aaccetgect gccgctgcac ctgcctgccg ctgcaggaaa catttctgac accgtcgacc 1981 aggaaagcca cacggagagg ccactgtggg tgaagcgcct cagttacaca ggaaccctaa 2041 agcaaatctg ccaccgtggg ggaactgacg ctggagatgc aaggtgctgg tgggtoctgag 2101 ctggacgtcg eggtgtgtec totgtgccca eggtutgage tagetagegc accgccgagt 2161 taaagaggag aaggaaaaca tgetgctetg gtgcacgcct gagegtecte catettocag T7 2221 gatggcagca atggcgctgt gcgcctcacc aggcccacga ggagcagcag cgctmnecc 2281 ggagcagcag gaaggcccct ctgtggagcg cccgccgtct gctccggggt ggttcagtca

2341 ctgettgttg acatcaacat ggcaattgca ctcatgtgga ctgggaccgt gcgagctgcc 2401 gtgtgggtta gtcgggtgcc aggacaatga aatactccag cacctgtggc tgaegaattt 2461 gtttctacag aaataacagc tggggacaac tgcggtgatg atgtaaaaac cttcccataa 2521 aatgtaagaa aagctgatga ggctggtgac gttcagcctt tgtcaataaa cctgtcatgt 2501 gcggaaaaaa aaaaaaaaaa aaaa

229

APPENDIX IV (A) Typical whole-cell patch clamp recordings from MDA-MB-231 cells. Data provided by Dr. Scott P. Fraser. (B) and (C) Preliminary data on VGSC (nNav1.5) current densities and percentage of functional VGSC-expressing VC5 and MDA-ERa (ERa) cells. * indicates the difference (n = 10-15 cells). Data provided by Rustem Onkal.

A.

B. > E 7

• 6

C. 6 Q.

Z' 3 (7) a)O 2

• 0

VC5 ERa

C. %) 80 VGSC ( 60 ing (43%) ress 40 exp lls 20 f ce o ber

m 0

Nu VC5 ERa

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266 MANUSCRIPT PREPARATIONS

Fraser, S.P., Ozerlat, I., Onkal, R., Diss, J.K.J. and Djamgoz, M.B.A. Non-genomic regulation of voltage-gated Na+ channel activity by estrogen in MDA-MB-231 human breast cancer cells. 2008. (Manuscript is close to submission).

Ozerlat, I. and Djamgoz, M.B.A. Regulation of ion channels by steroid hormones: Genomic and non-genomic effects. 2008. (Review in preparation).

PRESENATIONS AND ABSTRACTS Fraser, S.P., Ozerlat, I., Onkal, R., Diss, J.K.J. and Djamgoz, M.B.A. Electrophysiological effects of estrogen on voltage-gated Na+ channels in human breast cancer cells. (2007) The 6th European Biophysics Conference (EBC), Imperial College London, London, UK (Oral presentation by Dr. Fraser).

Ozerlat, I., Fraser, S.P., Diss, J.K.J., Ushkaryov, Y.A., Latchman, D.S. and Djamgoz, M.B.A. Estrogen regulation of voltage-gated Na channel expression and activity in the MDA-MB-231 human breast cancer cell line transfected with alpha-oestrogen receptor. (2006) The Physiological Society Main Meeting. University College London, London, UK. (Poster communication).

Ozerlat, I., Fraser, S.P., Diss, J.K.J., Ushkaryov, Y.A. and Djamgoz, M.B.A. Estrogen signalling and human breast cancer: Potential role of voltage-gated sodium channels. (2006) The 31St Federation of European Biochemical Societies (FEBS) Congress, Istanbul, Turkey. (Poster communication and abstract).

Ozerlat, I. and Djamgoz, M.B.A. A novel mode of action of estrogen in breast cancer: Potentiating role of voltage-gated sodium channels. (2005) The 7th European Molecular Biology Laboratories (EMBL) International PhD Symposium, Heidelberg, Germany. (Poster communication and abstract).

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