Modulation of Glucocorticoid-Inducible Gene Expression: Effects of Inflammatory Stimuli and Long-Acting Β2-Adrenoceptor Agonists

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2014-09-15 Modulation of glucocorticoid-inducible gene expression: Effects of inflammatory stimuli and long-acting β2-adrenoceptor agonists

Rider, Christopher Francis

Rider, C. F. (2014). Modulation of glucocorticoid-inducible gene expression: Effects of inflammatory stimuli and long-acting β2-adrenoceptor agonists (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/26976 http://hdl.handle.net/11023/1764 doctoral thesis

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Modulation of glucocorticoid-inducible gene expression: Effects of inflammatory stimuli and

long-acting β2-adrenoceptor agonists

Christopher Francis Rider

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

GRADUATE PROGRAM IN CARDIOVASCULAR AND RESPIRATORY SCIENCES

CALGARY, ALBERTA

SEPTEMBER, 2014

Glucocorticoids, acting on the glucocorticoid receptor (GR; NR3C1), are the most effective medication for controlling inflammation in the majority of asthmatics. However, some asthmatics, particularly those with severe disease, have reduced responses to glucocorticoids, a condition known as glucocorticoid resistance. Likewise, glucocorticoids have reduced effectiveness in asthmatics who smoke and during exacerbations, which are frequently induced by human rhinovirus (HRV) infection. Glucocorticoids reduce inflammatory protein production by directly inhibiting inflammatory transcription factors, including nuclear factor-kappa B (NF-

κB) and by enhancing the expression of potentially anti-inflammatory genes (transactivation).

The importance of transactivation in glucocorticoid activity is increasingly apparent, but the impact of inflammatory mediators on anti-inflammatory gene expression is understudied. Human bronchial epithelial, BEAS-2B, cells stably transfected with a 2×glucocorticoid response element

(GRE) reporter system, which models glucocorticoid-inducible gene expression, demonstrate concentration-dependent activation by glucocorticoids. However, dexamethasone-induced

2×GRE activation was time-dependently reduced by pre-treatment with inflammatory mediators, including tumor necrosis factor (TNF), interleukin-1β (IL1B) and cigarette smoke extract (CSE).

Furthermore, TNF pre-treatment decreased dexamethasone-induced mRNA expression of genes with potentially anti-inflammatory activity, including cyclin dependent kinase inhibitor 1C

(CDKN1C) and TSC22 domain family protein 3 (TSC22D3/GILZ), in bronchial epithelial and airway smooth muscle cells. Likewise, pre-incubations with HRV or the synthetic double- stranded viral RNA mimetic polyinosinic:polycytidylic acid (poly(I:C)) reduced dexamethasone- induced 2×GRE activation. Poly(I:C) also reduced dexamethasone-induced CDKN1C

ii expression. Approaches to reverse TNF-induced glucocorticoid hyporesponsiveness were evaluated, including addition of long-acting β2-adrenoceptor agonists (LABAs), use of novel GR agonists and inflammatory signalling pathway inhibition. LABAs, such as formoterol, potentiated 2×GRE reporter activation and CDKN1C expression through a time- and PKA- dependent mechanism that did not enhance GR expression, agonist affinity or translocation, but instead allows for gene specific control. Therefore, LABA addition functionally reversed glucocorticoid hyporesponsiveness induced by TNF or poly(I:C). However, novel GR agonist- induced 2×GRE activation was repressed by TNF or poly(I:C) treatment, with the degree of repression correlating with agonist efficacy. Finally, inhibition of the NF-κB and c-Jun N- terminal kinase (JNK) mitogen activated protein kinase pathways partially reversed TNF- induced glucocorticoid hyporesponsiveness. These results may contribute to the development of improved treatments for combating glucocorticoid hyporesponsiveness during exacerbations and in severe asthma.

iii Preface

Genes and proteins in this thesis are referred to using their standardised names according to the HUGO Gene Nomenclature Committee (HGNC) as specified at http://genenames.org. Where possible, commonly used gene name acronyms are included in parentheses. One exception is the glucocorticoid receptor, which is referred to as GR, rather than NR3C1, throughout.

Some experiments in chapters 3, 5 and 6 were conducted by Neil S. Holden, Joanna E. Chivers, Suharsh Shah, David Gaunt, Dong Yan or Robert Newton. This is specifically noted in individual figure legends.

Many of the figures presented in this thesis have been published in the following manuscripts: Rider, C.F., King, E.M., Holden, N.S., Giembycz, M.A., and Newton, R. (2011). Inflammatory stimuli inhibit glucocorticoid-dependent transactivation in human pulmonary epithelial cells: rescue by long-acting beta2-adrenoceptor agonists. J. Pharmacol. Exp. Ther. 338, 860–869. Copyright © 2011 by The American Society for Pharmacology and Experimental Therapeutics. Reprinted with permission of the American Society for Pharmacology and Experimental Therapeutics. All rights reserved.

Rider, C.F., Shah, S., Miller-Larsson, A., Giembycz, M.A., and Newton, R. (2013). Modulation of transcriptional responses by poly(I:C) and human rhinovirus: Effect of long-acting β2- adrenoceptor agonists. European Journal of Pharmacology 708, 60–67. Copyright © Elsevier B.V. Reprinted with permission from Elsevier. All rights reserved.

Rider, C.F., Miller-Larsson, A., Proud, D., Giembycz, M.A., and Newton, R. (Submitted).

Cytokine-induced loss of glucocorticoid function: Effect of kinase inhibitors, long-acting β2- adrenoceptor agonists and glucocorticoid receptor ligands. PloS ONE.

Potential conflicts of interest: During my undergraduate degree I was an employee of AstraZeneca for one year. My initial PhD studentship was funded by a grant to RN from GlaxoSmithKline. Work on these projects and in the laboratories of Dr. Robert Newton and Dr. Mark Giembycz was funded by AstraZeneca, Gilead Sciences and GlaxoSmithKline.

iv Acknowledgements I would like to thank my supervisor Rob Newton for his advice, guidance, skiing trips and stimulating conversation throughout my time as a student (both at Warwick and Calgary). I am yet to meet a supervisor with more energy, passion and enthusiasm for his work and there is no way I will ever be able to repay him for all the help he has given me. My co-supervisor Mark Giembycz has always been a calm and wise source of advice and I cannot thank him enough for his guidance throughout my studies in Calgary. Likewise, I am incredibly lucky that Quentin Pittman and Richard Leigh agreed to be my committee members; both have provided exceptional guidance, constructive feedback and have always gone the extra mile to support me throughout these studies (including retrieving tissue samples from my lungs for a microarray study). Thank you to all members of the Newton and Giembycz labs, past and present for all your help, advice and for making the lab a generally fun place to be. Thank you also to everyone in the Amrein, Kelly, Leigh, Proud and Slater labs. I would particularly like to acknowledge Wei Gong, Neil Holden, Manny Kaur and Sylvia Hills for everything they taught me, Suharsh Shah, David Gaunt and Dong Yan for data and Liz King (and Peter) for all of the above, plus help, consolation and guidance throughout my time in Calgary. I would like to thank the organisations that provided funding for my research: Alberta Innovates-Health Solutions (AI-HS), AstraZeneca, Canadian Institutes of Health Research (CIHR), GlaxoSmithKline (GSK), The Lung Association (Alberta & NWT) and the University of Calgary. For help and advice with experiments I would like to thank Magda Hudy, Claire Tacon, Suzanne Traves, Raza Zaheer, Pina Colarusso, Tehmeena Malik and Xiuling Wang. Thank you also to all the people who ensure you can get things done at the University, but are too rarely acknowledged, including the admin staff, cleaners, distribution services, waste disposal and maintenance. I would also like to thank all my teachers who encouraged me to study science, I could never have tackled a PhD without the base of knowledge you provided. A variety of people provided help and friendship throughout my other major endeavours, in the GSA, CRSA and CFD. Special thanks to Stefan, Lindsay, Melanie, Dave, Chris, Paul, Andrea, Jason, Brooke, Anna, Leslie, Keir, Lauren, Donald and Frans - you are all awesome! Last, but definitely not least, I would like to thank my friends and family in England (and elsewhere)! I appreciate you not disowning me (despite threats to the contrary) for deciding to pack up and move ~6940 km away and for all your support and visits from across 'the pond'.

v Table of Contents Abstract ...... ii Acknowledgements ...... v List of Tables ...... x List of Figures and Illustrations ...... xi List of Symbols, Abbreviations and Nomenclature ...... xiv Epigraph ...... xviii

CHAPTER ONE: INTRODUCTION ...... 1 1.1 Asthma ...... 2 1.1.1 Asthma Diagnosis ...... 3 1.1.2 Burden of Asthma ...... 4 1.2 Chronic Obstructive Pulmonary Disease ...... 5 1.3 Asthma-COPD Overlap Syndrome ...... 6 1.4 Inflammation in Asthma and COPD ...... 7 1.4.1.1 Epithelial Cells and the Development of Allergy in Asthma ...... 9 1.5 Inflammatory Signalling in Asthma ...... 11 1.5.1 Gq-Linked G Protein-Coupled Receptor Signalling ...... 11 1.5.2 Mitogen-Activated Protein Kinases ...... 12 1.5.3 Nuclear Factor-kappa B ...... 14 1.5.4 Activator Protein-1 ...... 15 1.6 Therapies for Asthma and COPD ...... 16 1.6.1 Asthma Severity and Control ...... 17 1.6.2 COPD Pharmacotherapy ...... 19 1.6.3 β2-Adrenoceptor Agonists ...... 20 1.6.4 Glucocorticoids ...... 22 1.6.4.1 Side Effects of Glucocorticoids ...... 23 1.6.4.2 The Glucocorticoid Receptor ...... 25 1.6.4.3 The Glucocorticoid Receptor Gene ...... 26 1.6.4.4 Glucocorticoid Receptor Translocation ...... 27 1.6.5 Transrepression and Transactivation ...... 28 1.6.5.1 Glucocorticoid-Inducible Genes ...... 30 1.6.5.2 Selective Glucocorticoid Receptor Agonists ...... 32 1.7 Combination Therapy with Glucocorticoids and LABAs ...... 33 1.7.1 Effects of Glucocorticoids on LABA-Dependent Responses ...... 34 1.7.2 Effects of LABAs on Glucocorticoid-Dependent Responses ...... 36 1.8 Glucocorticoid Resistance ...... 38 1.8.1 Severe Asthma ...... 40 1.8.2 Asthma Exacerbations ...... 41 1.8.2.1 Upper Respiratory Tract Infections and Human Rhinovirus ...... 42 1.8.3 Smoking ...... 43 1.8.4 Mechanisms of Glucocorticoid Resistance ...... 44 1.8.4.1 Genetics of Glucocorticoid Resistance ...... 45 1.8.4.2 Tumor Necrosis Factor Alpha as a Mediator of Glucocorticoid Resistance ...... 46 1.9 Overall Hypothesis and Specific Aims ...... 49

vi CHAPTER TWO: MATERIALS AND METHODS ...... 52 2.1 Materials and Suppliers ...... 52 2.2 Reagents and Cell Lines ...... 55 2.2.1 Dilution of Drugs and Cytokines ...... 55 2.2.2 Preparation of Cigarette Smoke Extract ...... 55 2.2.3 Human Rhinovirus (HRV) Serotype 16 Preparation ...... 56 2.2.4 Cell Culture Methods ...... 56 2.2.4.1 A549 Cell Culture ...... 56 2.2.4.2 BEAS-2B Cell Culture ...... 56 2.2.4.3 Primary Cell Culture ...... 57 2.2.4.4 HRV-16 Infection of BEAS-2B Cells ...... 57 2.2.4.5 Reporter Cell Lines ...... 57 2.3 Assays ...... 59 2.3.1 Calcium Assay ...... 59 2.3.2 Immunofluorescence Staining and Confocal Microscopy ...... 59 2.3.3 Cytoplasmic and Nuclear Extract Preparation ...... 60 2.3.3.1 Preparation of Cytoplasmic Extracts ...... 60 2.3.3.2 Preparation of Nuclear Extracts for Western Blotting ...... 60 2.3.4 Enzyme-Linked Immunosorbent Assay ...... 60 2.3.5 Luciferase Assay ...... 61 2.3.6 Microarray Sample Preparation and Scanning ...... 61 2.3.7 MTT Cell Viability Assay ...... 62 2.3.8 RNA Isolation, cDNA Generation and Real Time PCR ...... 62 2.3.9 Western Blotting ...... 63 2.4 Data Analysis and Statistics ...... 63 2.4.1 Densitometry of Western Blots ...... 63 2.4.2 Analysis of RT-PCR Data ...... 64 2.4.3 Microarray Analysis ...... 64 2.4.4 Confocal Microscopy Image Analysis ...... 64 2.4.5 Statistics ...... 65

CHAPTER THREE: PRO-INFLAMMATORY STIMULI REDUCE GLUCOCORTICOID- INDUCED 2×GRE REPORTER ACTIVATION AND GENE EXPRESSION ...... 66 3.1 Rationale ...... 66 3.2 Hypothesis ...... 67 3.3 Results ...... 67 3.3.1 Effects of the Pro-Inflammatory Cytokines TNF and IL1B on Dexamethasone- Induced 2×GRE Reporter Activation...... 67 3.3.2 Effects of Fetal Calf Serum on Dexamethasone-Induced 2×GRE Reporter Activation ...... 70 3.3.3 Effect of Glucocorticoid Concentration on the Repression of 2×GRE-Reporter Activation by TNF, IL1B or FCS ...... 71 3.3.4 Effects of Epidermal Growth Factor on 2×GRE Reporter Activation ...... 74 3.3.5 Effects of Agonists of Gq-Linked G Protein-Coupled Receptors and Activation of Protein Kinase C on Dexamethasone-Induced 2×GRE Reporter Activation ..75 3.3.6 Effects of Cigarette Smoke Extract and Hydrogen Peroxide on 2×GRE Reporter Activation ...... 77 vii 3.3.7 Effect of TNF and FCS on 2×GRE Reporter Activation Induced by the Glucocorticoids Dexamethasone, Fluticasone Propionate and Budesonide ....79 3.3.8 Effects of Pro-Inflammatory Stimuli on Dexamethasone-Induced Gene Expression ...... 80 3.4 Discussion ...... 84

CHAPTER FOUR: RHINOVIRUS AND POLY(I:C) MODULATE GLUCOCORTICOID- DEPENDENT AND OTHER TRANSCRIPTIONAL RESPONSES ...... 88 4.1 Rationale ...... 88 4.2 Hypothesis ...... 90 4.3 Results ...... 90 4.3.1 Effects of Rhinovirus on 2×GRE Reporter Activation in BEAS-2B Cells .....90 4.3.2 Effects of Poly(I:C) on Dexamethasone-Induced 2×GRE Reporter Activation in BEAS-2B and A549 Cells ...... 92 4.3.3 Effects of Poly(I:C) on cAMP-Induced and Constitutive Reporter Systems ..97 4.3.4 Effects of Poly(I:C) on NF-κB Activated Reporter Systems in BEAS-2B and A549 Cells ...... 98 4.3.5 Effect of Poly(I:C), Dexamethasone and Formoterol on Inflammatory Cytokine Expression ...... 100 4.4 Discussion ...... 101

CHAPTER FIVE: APPROACHES TO OVERCOMING INDUCED GLUCOCORTICOID HYPORESPONSIVENESS ...... 106 5.1 Rationale ...... 106 5.2 Hypothesis ...... 108 5.3 Results ...... 108 5.3.1 Effects of Long-Acting β2-Adrenoceptor Agonists on Glucocorticoid Hyporesponsiveness Induced by TNF or Poly(I:C) ...... 108 5.3.2 Effects of Different Glucocorticoid Receptor Agonists on Cytokine-Induced Glucocorticoid Hyporesponsiveness ...... 112 5.3.3 Effects of TNF and Formoterol on GR Agonist-Induced Gene Expression .117 5.3.4 Effects of Full and Partial Glucocorticoids on NF-κB Reporter Activation and CXCL8 Production ...... 119 5.3.5 Effects of Inhibition of NF-κB and MAPK Signalling Pathways on TNF or Poly(I:C) Mediated Repression of Dexamethasone-Induced 2×GRE Reporter Activation ...... 120 5.3.6 Effect of Phosphatidylinositol 3-Kinase and Protein Kinase C Inhibitors on TNF- Induced Glucocorticoid Hyporesponsiveness ...... 124 5.3.7 Effects of NF-κB and JNK Pathway Inhibitors on the Repression of Glucocorticoid-Inducible Gene Expression by TNF ...... 126 5.4 Discussion ...... 128

CHAPTER SIX: ENHANCEMENT OF GLUCOCORTICOID-INDUCIBLE GENE EXPRESSION BY LONG-ACTING Β2-ADRENOCEPTOR AGONISTS ...... 133 6.1 Rationale ...... 133 6.2 Hypothesis ...... 134 6.3 Results ...... 134

viii 6.3.1 Enhancement of Glucocorticoid Activity by Formoterol is Time-Dependent and Occurs through PKA Activation ...... 134 6.3.2 LABAs Do Not Enhance GR Protein Expression or Alter GR-Agonist Affinity ...... 137 6.3.3 Effects of Glucocorticoids and LABAs on GR Translocation ...... 140 6.3.4 LABAs Enhance RU486-Induced 2×GRE Activation Without Affecting GR Localization...... 144 6.3.5 Effects of Glucocorticoids and Formoterol on Expression of CDKN1C, DUSP1, RGS2 and TSC22D3 in BEAS-2B and Primary Lung Cells ...... 146 6.3.6 Budesonide and Formoterol Both Enhance and Repress Gene Expression in BEAS-2B Cells ...... 149 6.4 Discussion ...... 153

CHAPTER SEVEN: GENERAL DISCUSSION ...... 162 7.1.1 GR Transactivation and Induced Hyporesponsiveness ...... 162 7.1.2 Mechanisms Underlying the Modulation of Glucocorticoid Activity ...... 166 7.1.3 Effects of Glucocorticoid Receptor Agonists on Reporter Activation and Gene Expression ...... 170 7.1.4 Development and Implementation of Optimal Therapy ...... 173 7.1.5 Overall Conclusions ...... 177

CHAPTER EIGHT: FURTHER WORK ...... 179

REFERENCES ...... 186

APPENDIX A: LIST OF ANTIBODIES AND PRIMER SEQUENCES...... 243

APPENDIX B: MESH TERMS...... 245

APPENDIX C: COPYRIGHT PERMISSIONS ...... 246

ix List of Tables

Table 1.1 Symptom Severity Index by Clinical Features of Asthma Before Treatment...... 18

Table 3.1. Effects of TNF, IL1B and FCS on the Sensitivity of Glucocorticoid-Induced 2×GRE Reporter Activation...... 73

Table 5.1 Effect of NR3C1 Ligands on BEAS-2B 2×GRE Activation in the Presence and Absence of TNF...... 114

Table 6.1 Effects of Budesonide and Formoterol on Expression of Select Genes...... 158

x List of Figures and Illustrations

Figure 1.1 Glucocorticoid- and LABA-Induced Signalling Pathways and Possible Mechanisms of Enhancement...... 36

Figure 1.2 Signalling Pathway Activation by TNF and IL1B...... 47

Figure 1.3 Modulation of Glucocorticoid-Induced Gene Expression...... 50

Figure 2.1 Cigarette Smoke Extract Preparation Apparatus...... 55

Figure 3.1 Effects of the Cytokines TNF and IL1B on 2×GRE-Reporter Activation...... 68

Figure 3.2 Effects of TNF on Constitutive TATA and SV40 Luciferase Reporters in BEAS- 2B Cells...... 69

Figure 3.3 Effects of Fetal Calf Serum on Dexamethasone-Induced 2×GRE Reporter Activation...... 71

Figure 3.4 Effects of TNF, IL1B and FCS on Dexamethasone-Induced 2×GRE Reporter Activation...... 72

Figure 3.5 Effects of Epidermal Growth Factor on 2×GRE Reporter Activation and Phosphorylation of c-Jun N-Terminal Kinase...... 74

Figure 3.6 Effects of the Gq-Linked GPCR Agonists Carbachol and U46619 on Dexamethasone-Induced 2×GRE Reporter Activation...... 76

Figure 3.7 Effects of PKC Activation by Phorbol 12-Myristate 13-Acetate on Dexamethasone-Induced 2×GRE Reporter Activation...... 77

Figure 3.8 Effects of Cigarette Smoke Extract and Hydrogen Peroxide on Dexamethasone- Induced 2×GRE Reporter Activation...... 78

Figure 3.9 Repression of 2×GRE Reporter Activation by TNF or FCS is Not Dependent on the Glucocorticoid Used...... 79

Figure 3.10 Effects of TNF on Dexamethasone-Induced TSC22D3 Expression in BEAS-2B, Human Bronchial Epithelial and Airway Smooth Muscle Cells...... 81

Figure 3.11 Effects of IL1B on Dexamethasone-Induced Gene Expression...... 83

Figure 4.1 Effect of Short Incubations with Human Rhinovirus on Dexamethasone-Induced 2×GRE Reporter Activation...... 91

Figure 4.2 Effects of Human Rhinovirus on IL-8 Release and Glucocorticoid-Induced 2×GRE Reporter Activation...... 92

xi Figure 4.3 Effects of Poly(I:C) Treatment on Dexamethasone-Induced 2×GRE Reporter Activation in BEAS-2B Cells...... 93

Figure 4.4 Effects of Poly(I:C) Pre-Treatment on BEAS-2B 2×GRE Cell Viability...... 94

Figure 4.5 Effects of Poly(I:C) Treatment on Dexamethasone-Induced 2×GRE Reporter Activation in A549 Cells...... 96

Figure 4.6 Effects of Poly(I:C) on the Activation of cAMP Responsive, Basal and Strong Promoter-Driven Luciferase Reporters...... 97

Figure 4.7 Effects of Poly(I:C) Treatment on NF-κB Reporter Activation in BEAS-2B Cells. .. 99

Figure 4.8 Effects of Poly(I:C), Dexamethasone and Formoterol on CXCL8 and CXCL10 Expression in BEAS-2B Cells...... 100

Figure 5.1 Modulation of Dexamethasone-Induced 2×GRE Activation by Formoterol, TNF and Poly(I:C)...... 109

Figure 5.2 LABAs Functionally Reverse TNF- and Poly(I:C)-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B Cells...... 110

Figure 5.3 Effects of TNF or Poly(I:C), Dexamethasone and Formoterol on CDKN1C and TSC22D3 Expression...... 111

Figure 5.4 Effects of TNF on Glucocorticoid or Glucocorticoid Receptor Agonist-Induced 2×GRE Reporter Activation in BEAS-2B Cells...... 113

Figure 5.5 Effects of TNF or IL1B on Glucocorticoid-Induced 2×GRE Reporter Activation in A549 2×GRE Cells...... 115

Figure 5.6 Effects of TNF and/or Formoterol on 2×GRE Reporter Activation Induced by Various Glucocorticoid Receptor Agonists...... 116

Figure 5.7 Effect of TNF and/or Formoterol on Glucocorticoid Receptor Agonist-Induced 2×GRE Reporter Activation...... 118

Figure 5.9 Effects of Inhibition of NF-κB or MAPK Pathways on TNF-Induced 2×GRE Reporter Repression in BEAS-2B Cells...... 122

Figure 5.10 Effects of Inhibition of the NF-κB, p38 or JNK MAPK Pathways on Repression of Dexamethasone-Induced 2×GRE Activation by Poly(I:C)...... 124

Figure 5.11 Effects of Phosphatidylinositol 3-Kinase (PI3K) Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Reporter Cells...... 125 xii Figure 5.12 Effects of Protein Kinase C Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Cells...... 126

Figure 5.13 Effects of Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Cells...... 127

Figure 6.1 Formoterol Time-Dependently Enhances Dexamethasone-Induced 2×GRE Activation...... 135

Figure 6.2 Formoterol and Forskolin Enhance Dexamethasone-Induced 2×GRE Activation through PKA...... 137

Figure 6.3 Effects of Dexamethasone and the LABAs Formoterol and Salmeterol on GR Protein Expression...... 138

Figure 6.4 Effects of Clinically Relevant Glucocorticoid Plus LABA Combinations and Partial GR Agonists on GR Protein Expression...... 139

Figure 6.5 Effects of Formoterol on GR-Agonist Affinity...... 140

Figure 6.6 Effect of Length of Dexamethasone Treatment on GR Localization...... 141

Figure 6.7 Effect of Length of Salmeterol Treatment on GR Localization...... 141

Figure 6.8 Effect of Dexamethasone and Salmeterol Treatment on GR Localization...... 142

Figure 6.9 Effect of Glucocorticoids and LABAs on GR Translocation...... 143

Figure 6.10 Effects of RU486 Treatment on GR Localization and 2×GRE Activation...... 145

Figure 6.11 Effects of Formoterol on Budesonide-Inducible Putative Anti-Inflammatory Genes in BEAS-2B Cells...... 147

Figure 6.12 Effects of LABAs on Dexamethasone-Inducible Gene Expression in Primary Human Bronchial Epithelial (HBE) Cells...... 148

Figure 6.13 Effects of LABAs on Dexamethasone-Inducible Gene Expression in Primary Human Airway Smooth Muscle (ASM) Cells...... 149

Figure 6.14 Effects of Budesonide and Formoterol on Gene Expression in BEAS-2B Cells. ... 151

Figure 6.15 Effects of Formoterol on Budesonide-Induced Gene Expression...... 152

Figure 7.1 Expression of Genes in Human Lung Biopsies Following a Single Dose of Inhaled Budesonide...... 164

xiii List of Symbols, Abbreviations and Nomenclature

Symbol Definition [Ca2+]i intracellular free calcium concentration AC adenylyl cyclase ACOS asthma-COPD overlap syndrome ACTH adrenocorticotropin hormone

ADRB2 (β2-AR) adrenoceptor beta 2, surface ADRBK/βARK adrenergic β-receptor kinase AF activator function ANOVA analysis of variance AP-1 activator protein-1 AR androgen receptor ASM airway smooth muscle ATF activating transcription factor ATP adenosine triphosphate BAG BCL2-associated athanogene BEGM bronchial epithelial cell growth medium BSA bovine serum albumin Bud budesonide C5 complement component 5 cAMP cyclic 3',5'-adenosine monophosphate CCL chemokine ligand CCL chemokine ligand CDKN cyclin dependent kinase inhibitor CHUK/IKK1 conserved helix-loop-helix ubiquitous kinase CNR1 cannabinoid receptor type 1 COPD chronic obstructive pulmonary disease CRE cAMP-response element CREB cAMP-response element binding CRH corticotropin-releasing hormone CRISPLD2 cytoseine-rich secretory protein LCCL domain-containing 2 CSE cigarette smoke extract CSF colony stimulating factor CXCL chemokine (CXC motif) ligand DAG diacyl glycerol DALY disability-adjusted life year DBD DNA binding domain DC des-ciclesonide DDX58/RIGI DEAD box polypeptide 58 Dex dexamethasone DMEM Dulbecco’s modified Eagle’s medium DMSO dimethyl sulfoxide

xiv DUSP dual specificity phosphatase EDTA ethylenediaminetetraacetic acid EGF epidermal growth factor ELISA enzyme-linked immunosorbent assay ERK extracellular signal-regulated kinase EZR ezrin FCER1 high affinity IgE receptor FCER2 low affinity IgE receptor FCS fetal calf serum FEV1 forced expiratory volume in 1 second FF fluticasone furoate FKBP FK506 binding protein FP fluticasone propionate FVC forced vital capacity G6PC glucose-6-phosphatase GATA GATA binding protein GINA Global Initiative For Asthma GOLD Global Initiative for COPD GPCR G protein-coupled receptors GR/NR3C1 glucocorticoid receptor GRE glucocorticoid response element GRIP GR-interacting protein GSK GSK9027 GW GW870086X

H2O2 hydrogen peroxide HBE human bronchial epithelial HBSS Hank’s balanced salt solution HDAC histone deacetylase HPA hypothalamic-pituitary-adrenal HRV human rhinovirus HSP heat shock protein ICAM intercellular adhesion molecule ICS inhaled corticosteroid IFIH1/MDA5 interferon-induced with helicase c domain 1 IFN interferon Ig immunoglobulin IKBKB/IKK2 inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta IKBKG/NEMO inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase gamma IL interleukin IP3 inositol 1, 4, 5-triphosphate IRF interferon regulatory factor JNK c-jun N-terminal kinase LABA long acting β2-adrenoceptor agonist

xv LBD ligand binding domain LPS lipopolysaccharide MAPK mitogen activated protein kinase MHC major histocompatability complex MKP MAPK kinase phosphatase MLCK myosin light chain kinase MMP matrix metalloproteinase MMTV mouse mammary tumor virus MR mineralocorticoid receptor MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide NCOA nuclear receptor coactivator NCOR nuclear receptor corepressor NFAT nuclear factor of activated T-cells NFKBIA nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 NF-κB nuclear factor-kappa B NLS nuclear localisation signal NOS2 nitric oxide synthase 2, inducible NS not stimulated PAMP pathogen associated molecular patterns PBS phosphate buffered saline PCK phosphoenolpyruvate carboxykinase PCK2 phosphoenolpyruvate carboxykinase 2 PDE phosphodiesterase PEF peak expiratory flow PI3K phosphatidylinositol 3-kinase PIP2 phospholipid phosphatidylinositol (4, 5)-bisphosphate PKA protein kinase A PKB protein kinase B PKC protein kinase C PKIα cAMP protein kinase inhibitor α PMA phorbol 12-myristate 13-acetate poly(I:C) polyinosinic:polycytidylic acid POMC pro-opiomelanocortin PPID/CYP-40 peptidylprolyl isomerase D PPP protein phosphatase PR progesterone receptor PTGER prostaglandin E receptors PTGS2 prostaglandin-endoperoxide synthase RALBP ralA binding protein RGS regulator of G-protein signalling RHD Rel-homology domain RMA robust multi-array averaging RSV respiratory syncytial virus

xvi RU RU24858 SABA short acting β2-adrenoceptor agonist SEGRA selective glucocorticoid receptor agonist SERPIN serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin) SFM serum free medium SLC37A glucose 6 phosphate transporter SYK spleen tyrosine kinase TAT tyrosine aminotransferase TAT tyrosine aminotransferase TBP TATA-binding protein TCID tissue culture infectious dose TGF transforming growth factor TLR toll-like receptor TNF tumor necrosis factor alpha TNFAIP3 TNFα-induced protein 3 TNFR TNF receptor TPR tetratricopeptide repeat TRADD TNFRSF1A-associated via death domain TRE (TPA/PMA)-response element TSC22D3 TSC22 domain family, member 3 TSLP thymic stromal lymphopoietin URTI upper respiratory tract infections VCAM vascular cell adhesion protein VEGF vascular endothelial growth factor (VEGF) ZFP36 ZFP36 ring finger protein

xvii Epigraph

Too often we hold fast to the clichés of our forebears. We subject all facts to a prefabricated set of interpretations. We enjoy the comfort of opinion without the discomfort of thought.

- John F. Kennedy Yale University, June 11th 1962

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xviii 1

Chapter One: Introduction

Glucocorticoids are among the most effective and frequently used medications for inflammatory and autoimmune diseases, including asthma, rheumatoid arthritis, eczema and inflammatory bowel disease (Belgi and Friedmann, 2002; Schäcke et al., 2007). However, some individuals have either partial or no response to glucocorticoid therapy, conditions described as glucocorticoid resistance or insensitivity (Barnes and Adcock, 2009; Keenan et al., 2012; Schaaf and Cidlowski, 2002). Additionally, inflammatory lung diseases, including interstitial pulmonary fibrosis and chronic obstructive pulmonary disease, appear to be inherently resistant to the effects of glucocorticoids (Barnes and Adcock, 2009; Keenan et al., 2012). As asthma severity is now largely defined according to the dose of glucocorticoid needed to control symptoms, resistance to glucocorticoids may contribute to apparent severity (Chaudhuri et al., 2003;

Durham et al., 2011; Livingston et al., 2005; Stapleton et al., 2011). Additionally, smoking or asthma exacerbations can induce resistance in otherwise glucocorticoid responsive asthmatics

(Adcock et al., 2008; Grünberg et al., 2001; Livingston et al., 2005; Papi et al., 2013). Resistance to glucocorticoids in asthma significantly increases suffering and has substantial costs through increased hospitalization and lost productivity (Antonicelli et al., 2004; Lane et al., 2006; Masoli et al., 2004; Serra-Batlles et al., 1998). However, glucocorticoid resistance is not fully understood and therefore cannot be adequately treated.

Despite the above, the most effective approach to controlling asthma symptoms is addition of a long acting β2-adrenoceptor agonist (LABA) to glucocorticoid, as this is more effective than doubling or even quadrupling the dose of glucocorticoid (O’Byrne et al., 2001;

Pauwels et al., 1997). However, the mechanisms underlying the interactions between

2 glucocorticoids and LABAs are not fully understood (Giembycz et al., 2008). Hence, there is a pressing need to understand the mechanisms underlying glucocorticoid resistance and the interactions between glucocorticoids and LABAs, so that improved therapies can be developed.

1.1 Asthma

Asthma, originally from the Greek word for "panting", was recognised as early as the

16th or even 25th century BC by Egyptian and Chinese cultures, respectively (Gordon, 2008).

Asthma is a chronic, inflammatory and heterogeneous disease of the airways, characterised by reversible bronchoconstriction, non-specific airways hyperresponsiveness, increased mucus production and airways remodelling (Bousquet et al., 2000; Gordon, 2008). The chronic inflammation induced in asthma may contribute to remodelling of the airways, including thickening of the basement membrane and increased deposition of extracellular matrix (Bossé et al., 2008; Bousquet et al., 2000; Davies et al., 2003).

Asthma is estimated to affect 4.3% of adults worldwide and can occur in individuals of both sexes and all ages, from childhood through adulthood into old age (Global Initiative for

Asthma, 2014; Masoli et al., 2004). Asthma symptoms typically vary over time, but often increase following exposure to specific environmental stimuli, colloquially known as "triggers"

(Global Initiative for Asthma, 2014; Bartra et al., 2007; D’Amato et al., 2002; Hamid and Tulic,

2009; Weinmayr et al., 2007). Principle triggers for asthma include aeroallergens, which are often small proteins that can be inhaled, including pollens, house dust mite feces, mold and pet dander (Bartra et al., 2007; Hamid and Tulic, 2009). Symptoms of asthma can also increase in response to non-allergens, including industrial pollution, diesel exhaust, cold weather, exercise, strong emotions and certain medications, such as aspirin (Chen and Miller, 2007; D’Amato et al.,

2002; Gordon, 2008; Wong and Lai, 2004). Environmental factors appear to interact with host determinants, including genotype, obesity and sex, in the development of asthma (Global

Initiative for Asthma, 2014; Moore et al., 2010; Wenzel, 2012).

1.1.1 Asthma Diagnosis

A diagnosis of asthma is usually made on the basis of a history of variable respiratory symptoms, physical examination and an assessment of pulmonary function by spirometry

(Enright et al., 1994; Global Initiative for Asthma, 2014; Lemière and FitzGerald, 2012).

Spirometry is commonly used to determine: 1) forced expiratory volume in 1 second (FEV1): the volume of air that can be forcibly exhaled in 1 second, following a maximal inhalation, 2) peak expiratory flow (PEF): maximal airflow, measured in litres per minute or second, achieved during forced expiration, and 3) forced vital capacity (FVC): the volume of air, usually in litres, which can be forced out of the lung after deep inhalation. FEV1 values are usually compared to those predicted based on age, height and gender and expressed alone, as a percentage of expected values, or as a ratio with FVC (FEV1/FVC). A ratio of FEV1/FVC of less than 0.80 indicates airflow limitation (Enright et al., 1994; Global Initiative for Asthma, 2014; Miller et al., 2005b;

Stanojevic et al., 2008). Spirometry is also used to determine reversibility of bronchoconstriction following inhalation of a β2-adrenoceptor agonist bronchodilator. Asthmatics usually have a post bronchodilator increase in FEV1 of greater than 12% and 400 ml from baseline (BTS/SIGN,

2012; Enright et al., 1994; Global Initiative for Asthma, 2014; Lemière and FitzGerald, 2012).

Another test utilized in asthma diagnosis is airway responsiveness, in which changes in spirometry are measured in response to inhalation of increasing concentrations of the bronchoconstrictors, histamine or methacholine (BTS/SIGN, 2012; Enright et al., 1994; Global

Initiative for Asthma, 2014; Lemière and FitzGerald, 2012). Other clinical markers sometimes assessed in asthma diagnosis include allergen sensitivity, sputum cell counts and exhaled nitric oxide (Global Initiative for Asthma, 2014; Hastie et al., 2010; Jayaram et al., 2006). However, the substantial heterogeneity of asthma complicates diagnosis and has led to the suggestion that

"asthma" may in fact comprise a number of different, but overlapping, inflammatory respiratory disease endotypes (Borish and Culp, 2008; Gibson et al., 2001; O’Neil et al., 2011; Peters, 2003;

Wenzel, 2012).

1.1.2 Burden of Asthma

Asthma has a major burden on society in terms of decreased quality of life, treatment, lost productivity and mortality (Bahadori et al., 2009; Masoli et al., 2004; To et al., 2012).

Asthma prevalence has increased in the last half century and now affects an estimated 300 million individuals worldwide (Anandan et al., 2010; Masoli et al., 2004). Asthma prevalence varies dramatically worldwide with 0.2% of adults in China and 21% in Australia having physician diagnosed asthma, with an estimated global prevalence of 4.3% (To et al., 2012). In

Canada, up to 14.1% of the population has asthma (Global Initiative for Asthma, 2014; Masoli et al., 2004). Furthermore, the Global Initiative for Asthma (GINA) has estimated that the number of individuals with asthma world wide may rise to 400 million by 2025 (Global Initiative for

Asthma, 2014; Masoli et al., 2004; To et al., 2012). Although healthcare utilization and deaths from asthma may be in decline in developed nations due to improvements in the quality of care,

GINA estimates suggest that 1 in every 250 deaths is due to asthma, with approximately 3500 and 346000 individuals dying from asthma each year, in the USA and worldwide respectively

(Anandan et al., 2010; Global Initiative for Asthma, 2014; Masoli et al., 2004; Rogers and

Reibman, 2011). However, severe asthma exacerbations requiring admission to intensive care units are more common than death due to asthma and occur in 2-20% of asthmatics (Peters et al.,

2006; Rogers and Reibman, 2011). As a chronic disease that can develop during childhood and last into old age, asthma has large effects on quality of life with an estimated yearly loss of 13.8-

15 million disability-adjusted life years (DALYs) (Global Initiative for Asthma, 2014; Masoli et al., 2004; Peters et al., 2006). This may represent as much as 1.8% of the total global disease burden.

The financial costs of asthma are substantial with a expenditure of $56 billion in the USA in 2007 alone, based on estimates of medical costs, lost productivity and early deaths (Centres for Disease Control, 2011). Since the majority of asthma costs result from hospital admission

(Bahadori et al., 2009; Lane et al., 2006), costs rise dramatically as a consequence of poor control and increasing asthma severity, with a minority of severe asthmatics accounting for between 41% and over half of total asthma health care expenditure, depending on the study

(Antonicelli et al., 2004; Bahadori et al., 2009; Barnes, 2008; Borderías Clau et al., 2005; Ganse et al., 2002; Lane et al., 2006; Serra-Batlles et al., 1998).

1.2 Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is also characterised by chronic lung inflammation, but differs from asthma in that the predominant underlying cause is inhalation of noxious particles and gases (smoke) from cigarettes or other air pollution (Global Initiative for

Asthma, 2014; GOLD, 2014; Pauwels et al., 2001). Furthermore, in asthma, airflow obstruction is generally reversible with bronchodilators, while in COPD airflow limitation is frequently fixed. The global initiative for chronic obstructive lung disease (GOLD) states that: "COPD…is

6 characterized by persistent airflow limitation that is usually progressive and associated with an enhanced chronic inflammatory response in the airways and the lung to noxious particles or gases." (GOLD, 2014). COPD usually affects individuals in mid or late adulthood and is now the fourth leading cause of death worldwide (GOLD, 2014; Hurd, 2000). Symptoms of COPD include chronic coughing, sputum production and shortness of breath (Barnes and Celli, 2009;

Barnes et al., 2003; GOLD, 2014). Lung function in COPD deteriorates at an increased rate relative to that in smokers without COPD and individuals who do not smoke, leading to progressive disability (Fletcher and Peto, 1977). Furthermore, individuals with COPD often suffer from co-morbidities, including heart disease, diabetes, lung cancer and osteoporosis, complicating treatment (Barnes and Celli, 2009; Fabbri et al., 2008). Recurrent inhalation of smoke results in chronic inflammation of the bronchioles (chronic bronchitis), increased mucus production and plugging, fibrosis and destruction of alveolar walls leading to emphysema and air trapping (Barnes, 2000; GOLD, 2014; Spurzem and Rennard, 2005). As in asthma, individuals with COPD experience exacerbations, during which lung function acutely declines for a short period (GOLD, 2014). As COPD is frequently glucocorticoid resistant, reducing lung inflammation is difficult and improved therapies are therefore urgently needed (Ammit, 2013;

Barnes and Adcock, 2009).

1.3 Asthma-COPD Overlap Syndrome

As many as 17-35% of asthmatics smoke (Althuis et al., 1999; Chalmers et al., 2002;

Livingston et al., 2005). Therefore, a potential for the development of COPD on a background of asthma exists and this is referred to as asthma-COPD overlap syndrome (ACOS) (Gibson and

Simpson, 2009; Global Initiative for Asthma, 2014; Papaiwannou et al., 2014). ACOS manifests

7 as a combination of increased airflow variability, sputum eosinophils and incompletely reversible airways obstruction, as measured by spirometry (Gibson and Simpson, 2009; Global Initiative for Asthma, 2014; Papaiwannou et al., 2014). ACOS generally develops in mid to late adulthood in individuals with a history of exposure to cigarette smoke or air pollution. Individuals with

ACOS often have poor quality of life, frequent exacerbations and worse clinical outcomes than those with either asthma or COPD (Gibson and Simpson, 2009; Global Initiative for Asthma,

2014). As ACOS is excluded from the majority of trials investigating pharmaceutical interventions, worse disease outcomes may in part be due to inadequate therapy (Gibson and

Simpson, 2009; Papaiwannou et al., 2014).

1.4 Inflammation in Asthma and COPD

A central feature of both asthma and COPD is chronic inflammation of the airways due to mediator release from a diversity of lung resident and recruited cell types (Barnes, 1996, 2008;

Hamid and Tulic, 2009). Many cell types may contribute to inflammation in asthma, including mast cells, eosinophils, T and B lymphocytes and epithelial cells (Barnes, 2008; Bousquet et al.,

2000; Postma et al., 2014). There is increased production of inflammatory mediators in asthma, including cytokines and eicosanoids, by mast cells, macrophages, dendritic cells, airway smooth muscle or epithelial cells, which induces the upregulation of adhesion molecule expression on endothelial cells (Barnes, 2008; Bentley et al., 1992; Bousquet et al., 2000). Together with inflammatory mediators, this increase in adhesion molecule expression leads to recruitment of granulocytes and lymphocytes to the lung. Recruited or resident cells can produce a variety of cytokines, including interleukins (ILs) 4, 5, 9, 13 and even tumor necrosis factor alpha (TNF) and IL1B (Barnes, 2001; Greenfeder et al., 2001; Hamid and Tulic, 2009; Oboki et al., 2008;

Wong et al., 2001). Likewise, in COPD, macrophages, T lymphocytes, neutrophils, epithelial and other cells may generate mediators contributing to inflammation (Barnes, 2008). At a molecular level in COPD, macrophages and epithelial cells activated by smoke release chemotactic factors, including TNF, leukotriene B4, chemokine (CXC motif) ligand 1 (CXCL1), CXCL8 and

CXCL10, which attract neutrophils and cytotoxic T cells (Tc) to the lung (Barnes, 2000; Barnes et al., 2003; Spurzem and Rennard, 2005). Neutrophils and macrophages release proteases (e.g. neutrophil elastase, proteinase 3), generate matrix metalloproteinases (e.g. MMP1 and 9) and reactive oxygen species (e.g. hydrogen peroxide) and these can increase mucus production and degrade alveolar walls (Barnes et al., 2003; GOLD, 2014). The destruction of alveolar walls

(emphysema) is mediated in part by the apoptosis of type 1 pneumocytes in addition to the effects of neutrophil elastases, which degrade structural components, such as the extracellular matrix (Barnes, 2000, 2008; Spurzem and Rennard, 2005).

Asthma and COPD are often characterised as having eosinophilic and neutrophilic inflammation, respectively. However, neutrophils may also be increased in asthmatic smokers and in more severe asthma, which may bear a closer resemblance to COPD (Gibson et al., 2001;

Jatakanon et al., 1999; Postma et al., 2014). Eosinophilia is less frequently encountered in well controlled COPD, but may be increased in patients with ACOS and potentially during COPD exacerbations (Gibson and Simpson, 2009; Saha and Brightling, 2006). Conversely, the T cell populations in asthma and COPD appear to differ, with primarily T helper 2 (Th2) in asthma and

T helper 1 (Th1) and cytotoxic T cells (Tc) in COPD. The difference in T cells contributes to differences in mediator production with cytokines, including IL4, 5, 9 and 13, predominating in asthma and interferon gamma (IFNγ) in COPD (Barnes, 2008). However, cytotoxic CD8+ T

9 cells are also increased in severe asthma, contributing IFNγ to the cytokine milieu (Barnes, 2008;

Schoenborn and Wilson, 2007; Wong et al., 2001).

1.4.1.1 Epithelial Cells and the Development of Allergy in Asthma

Epithelial cells are amongst the first cell types exposed to inhaled substances, including aeroallergens, smoke, pollution, bacteria, inhaled medications and viruses (Hammad and

Lambrecht, 2008; Lambrecht and Hammad, 2012; Proud and Leigh, 2011). The airway epithelium is made up of Clara, goblet, basal and ciliated cells, which line the airways and provide a barrier between the airways lumen and the underlying cells (Hammad and Lambrecht,

2008; Proud and Leigh, 2011; Rescigno et al., 2001; Xiao et al., 2011). This barrier is maintained by tight junctions consisting of zonula occludens, occludin and claudin proteins that link the epithelial cells together. Dendritic cells are present in the basolateral space below the epithelium, but may express tight junction proteins allowing them to extend long processes between epithelial cells to capture allergen without decreasing barrier function (Chieppa et al., 2006;

Jahnsen et al., 2006; Rescigno et al., 2001; Sung et al., 2006). Alternatively, dendritic cells can be directly exposed to allergen following loss of epithelial integrity in asthma, either because of disruption of tight junction formation, allergen activity or possibly inflammation (Antony et al.,

2002; Hammad and Lambrecht, 2008; Lee et al., 2004; Xiao et al., 2011). For example, allergens from house dust mite (Der p 1 and 9), Aspergillus sp. (Asp f 5, 6 and 11), ragweed (Amb a), birch and cockroach (Bla g) have protease activity, enabling cleavage of tight junctions (Antony et al., 2002; Lee et al., 2004). Cigarette smoke or cockroach allergen induced vascular endothelial growth factor (VEGF) production from epithelial cells may also increase epithelial permeability, potentially enhancing allergen entry (Antony et al., 2002; Kim et al., 2009; Olivera

10 et al., 2007; Tuder et al., 2000). Furthermore, rhinovirus infection and the synthetic dsRNA polyinosinic:polycytidylic acid (poly(I:C)), which models the dsRNA intermediate generated during rhinovirus replication, may decrease the integrity of the airway epithelium (Ohrui et al.,

1998; Rezaee et al., 2011). This may occur through recognition by pathogen associated molecular pattern (PAMP) receptors, such as members of the toll-like receptor (TLR) family,

DEAD box polypeptide 58 (DDX58/RIGI) and interferon-induced with helicase C domain 1

(IFIH1/MDA5), which may enable detection of noxious inhaled matter, including respiratory viruses and allergen (Kato et al., 2006; Proud and Leigh, 2011; Slater et al., 2010; Triantafilou et al., 2011; Wang et al., 2009).

Following uptake by dendritic cells, allergens are fragmented, loaded onto major histocompatability complex (MHC) class II molecules and presented to naïve T-cells in lymph nodes (Lambrecht, 2001). T-cells can then undergo maturation, differentiation and division, before trafficking into the lung and releasing cytokines, including IL4, 5, 9 and 13 (Barnes,

2001; Lambrecht, 2001). Release of IL5 by T cells induces differentiation and proliferation of eosinophil precursor cells in bone marrow (Greenfeder et al., 2001). IL4 and IL13 can also enhance endothelial cell vascular cell adhesion protein (VCAM)-1 expression and eotaxin release from epithelial cells and fibroblasts, enhancing eosinophil recruitment into the lung

(Prussin and Metcalfe, 2003). Eosinophils have granules containing major basic protein, cysteinyl leukotrienes and the cytokines IL-3, 4, 5, 8 and TNF, which may induce hyperresponsiveness and bronchoconstriction (Greenfeder et al., 2001; Prussin and Metcalfe,

2003).

B cells can also capture allergen and present it on class II MHC, either following trafficking to the lung or through antigen acquisition from dendritic cells in lymph nodes (Lindell

11 et al., 2008; Qi et al., 2006). Th2 cells can then promote class switching, IgE production and proliferation of these allergen-presenting B cells, through receptor interactions that include

CD40-CD40L (CD40LG) binding and release of IL4 and 13 (Corry and Kheradmand, 1999;

Lambrecht, 2001; Oettgen and Geha, 1999). The IgE secreted by B-cells binds to high affinity

IgE receptors (FCER1/FcεRI) on mast cells and eosinophils and to low affinity IgE receptors

(FCER2/FcεRII/CD23) on B-cells and macrophages (Corry and Kheradmand, 1999; Lindell et al., 2008; Oettgen and Geha, 1999). When bound by allergen, these receptors cross link to induce the release of inflammatory mediators, including histamine, cysteinyl leukotrienes and prostaglandins, which can induce broncoconstriction (Barnes, 2008). Mast cells may in part mediate airway hyperresponsiveness and can produce cytokines, including IL4, IL5 and IL13, following IgE receptor cross linking (Barnes, 2008; Corry and Kheradmand, 1999; Prussin and

Metcalfe, 2003).

1.5 Inflammatory Signalling in Asthma

A number of inflammatory pathways, including mitogen-activated protein kinase

(MAPK), activator protein (AP)-1 and nuclear factor kappa B (NF-κB), are activated in response to inflammatory mediators and are thought to play important roles in asthma (Barnes, 2006a;

Pelaia et al., 2005).

1.5.1 Gq-Linked G Protein-Coupled Receptor Signalling

Many of the principal mediators in asthma, including acetylcholine, histamine, leukotrienes and prostanoids, cause the contraction of airway smooth muscle and bronchospasm

(Barnes et al., 1998; Rolin et al., 2006). For example, the prostanoid, thromboxane, is elevated in

12 exhaled breath condensate from asthmatics and activates the, Gq-linked G protein-coupled receptor (GPCR), thromboxane A2 receptor (TP) (Dorn and Becker, 1993; Huszár et al., 2005;

Shenker et al., 1991). Likewise, the leukotriene, histamine H1 and muscarinic acetylcholine M1,

M3 and M5 receptors are predominantly Gq-linked GPCRs (Alexander et al., 2011; Bakker et al.,

2001; Caulfield, 1993; Jones et al., 2009). Indeed, anti-cholinergic drugs, including ipratropium

(Atrovent) and tiotropium (Spiriva) bromide, are used in COPD treatment, where they target bronchoconstriction and mucus secretion, principally induced through activation of M1 and M3 receptors present in the lung (Mak and Barnes, 1990; Sales, 2010).

Activation of Gq-linked GPCRs causes phospholipase C to cleave the phospholipid phosphatidylinositol (4, 5)-bisphosphate (PIP2) into inositol 1, 4, 5-trisphosphate (IP3) and diacyl glycerol (DAG) (Bos et al., 2004; Dorn and Becker, 1993). DAG, which can be mimicked by phorbol 12-myristate 13-acetate (PMA), activates certain protein kinase C (PKC) isoforms, while

IP3 can diffuse through the cytosol and bind IP3 receptors on the smooth endoplasmic or sarcoplasmic reticulum, leading to the release of calcium. The increased calcium leads to contraction in smooth muscle cells and is also involved in the activation of some PKC isoforms

(Dempsey et al., 2007; Wright et al., 2013).

1.5.2 Mitogen-Activated Protein Kinases

The MAPK proteins are highly conserved serine, threonine and tyrosine kinases activated in response to a wide variety of stresses and cell membrane receptor-derived signals, including many of the inflammatory cytokines associated with asthma (Chang and Karin, 2001; Johnson and Lapadat, 2002; Pelaia et al., 2005). MAPKs regulate processes, including proliferation, cell survival, apoptosis and cytokine production, through phosphorylation of other kinases,

13 cytoskeletal proteins and activation of transcription factors, such as AP-1 and NF-κB (Chang and

Karin, 2001; Garrington and Johnson, 1999; Johnson and Lapadat, 2002; Pelaia et al., 2005;

Zhang and Liu, 2002).

MAPK cascades are divided into three main branches known as the extracellular signal- regulated kinases (ERK 1, 2 and 5), p38 (α, β, γ and δ) and c-jun N-terminal kinase (JNK 1, 2 and 3), each with a slightly different phosphorylation motif and substrate specificity (Johnson and Lapadat, 2002; Qi and Elion, 2005; Zhang and Liu, 2002). Each cascade exists as a three- tiered kinase cascade held together by scaffold proteins, in which MAPK3Ks are activated and phosphorylate MAP2Ks on specific threonine and serine residues. Subsequently, MAP2Ks phosphorylate MAPKs, on threonine and tyrosine residues, inducing activation (Johnson and

Lapadat, 2002; Qi and Elion, 2005; Zhang and Liu, 2002). MAPKs phosphorylate numerous downstream targets, leading to inflammatory activity, including the stabilisation of prostaglandin-endoperoxide synthase (PTGS) 2, IL-2, 6 and CXCL8 mRNAs and activation of

AP-1 and myocyte-enhancer factor 2, which increases c-jun transcription (Chen et al., 2000b;

Han et al., 1997; Lasa et al., 2000; Winzen et al., 1999). MAPK pathway activation is involved in many aspects of asthma, including inducing the differentiation of naïve T cells into Th2 cells and the production of Th2 cytokines (Chen et al., 2000a; Maneechotesuwan et al., 2007;

Yamashita et al., 2005). MAPK members are regulated and inactivated by phosphatases, including the MAPK kinase phosphatase (MKP) dual specificity phosphatase (DUSP) 1

(Johnson and Lapadat, 2002; King et al., 2009a; Pelaia et al., 2005).

1.5.3 Nuclear Factor-kappa B

NF-κB is a heterodimeric transcription factor that contributes to many key processes in asthma, including inflammation, immune responses, cell adhesion, proliferation and cell death, through enhancing expression of cytokines, chemokines, adhesion molecules, enzymes and growth factors (Bonizzi and Karin, 2004; Wright and Christman, 2003). NF-κB members share an approximately 300 amino acid long N-terminal region known as the Rel-homology domain

(RHD) that is involved in nuclear localisation, DNA binding and dimerization (Bonizzi and

Karin, 2004). NF-κB consists of five proteins divided into two subfamilies, the Rel subfamily containing RelA (p65), RelB, c-Rel, and the NF-κB subfamily consisting of NF-κB1 (p50) and

NF-κB2 (p52) (Bonizzi and Karin, 2004; Perkins, 2007). NF-κB1 and 2 are synthesized as larger precursor proteins known as p105 and p100 respectively that undergo cleavage to generate p50 and p52.

NF-κB can be activated through two main pathways, known as the classical and alternative (Bonizzi and Karin, 2004). The classical pathway is activated by cytokines, including

IL1B and TNF, viruses and PAMPs, through cell membrane and cytoplasmic receptors (Bonizzi and Karin, 2004; Edwards et al., 2009). For example, binding of tumor necrosis factor receptors by TNF, leads to the activation of MAP3K14 (Ahn and Aggarwal, 2005; Jackson-Bernitsas et al.,

2006; Sakurai et al., 2003). MAP3K14 phosphorylates conserved helix-loop-helix ubiquitous kinase (CHUK/IKKα/IKK1) and inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta (IKBKB/IKKβ/IKK2). The IKK complex contains three members, the catalytic proteins CHUK and IKBKB and the regulatory inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase gamma (IKBKG/IKKγ/NEMO) (Ahn and Aggarwal, 2005; Bonizzi and Karin, 2004; Perkins, 2007). After phosphorylation, IKBKB phosphorylates nuclear factor of

15 kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (NFKBIA/IκBα), which partially masks the nuclear localization sequences of nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1/p50)/ v-rel avian reticuloendotheliosis viral oncogene homolog A (RELA/p65). Although the NF-κB complex may shuttle into and out of the nucleus, partial masking of the nuclear localisation sequence predominantly localizes NF-κB in the cytoplasm (Birbach et al., 2002; Yamamoto et al., 2003). However, following phosphorylation,

NFKBIA is ubiquitinated and undergoes degradation by the 26S proteasome, exposing the nuclear localisation sequence of NF-κB and allowing the complex to translocate into the nucleus

(Bonizzi and Karin, 2004). The NF-κB NFKB1/RELA proteins then bind to κB sites (consensus sequence: 5′-GGGAATTTCC-3′) that are often, but not exclusively, found in the 5' upstream region of inflammatory genes, enhancing inflammatory transcription (Bonizzi and Karin, 2004).

The alternative pathway is stimulated through receptors, including CD40 ligand

(CD40LG), leading to the activation of CHUK homodimers (Bonizzi and Karin, 2004; Neumann and Naumann, 2007). The CHUK homodimers phosphorylate two C-terminal subunit sites on

NFKB2 p100, inducing proteosomal degradation that generates NFKB2 p52. RelB/NFKB2 heterodimers can then translocate into the nucleus and enhance gene expression (Bonizzi and

Karin, 2004; Neumann and Naumann, 2007).

1.5.4 Activator Protein-1

A second major transcription factor involved in inflammatory gene expression in asthma is activator protein 1 (AP-1) (Demoly et al., 1995; Rahman and MacNee, 1998). AP-1 proteins are divided into three families known as Jun (JUN (c-Jun), JUNB and JUND), Fos (FOS (c-Fos),

FOSB, FOSL1 (Fra1) and FOSL2(Fra2)) and activating transcription factor ATF (ATF2, ATF3,

BATF (B-ATF)). AP-1 transcription factors share a common basic region leucine zipper protein motif, which enables dimerization and DNA binding following activation by MAPK, protein tyrosine kinases or PKC (Karin et al., 1997). Jun and ATF can form stable homodimers and also heterodimerize with each other and with Fos proteins, while Fos proteins can only heterodimerize. AP-1 proteins bind to consensus response elements that are palindromic and contain an AP-1 half site (Karin et al., 1997). Jun-Jun and Jun-Fos dimers preferentially bind to phorbol 12-O-tetradecanoate-13-acetate (TPA/PMA)-response elements (TRE), which have the consensus sequence "TGACTCA". However, ATF homodimers and Jun-ATF dimers predominantly bind to cyclic 3',5'-adenosine monophosphate (cAMP)-response elements (CRE), which have the consensus sequence "TGA CGT CA" (Karin et al., 1997). The transcriptional activity of AP-1 is regulated at multiple levels through expression, protein stability and phosphorylation. For example, phosphorylation of c-Jun by JNK MAPK on S63 and S73, may enhance gene transactivation (Smeal et al., 1994).

1.6 Therapies for Asthma and COPD

A wide variety of medications have been developed for the treatment of asthma and

COPD, targeting specific features of these diseases, including inflammation and bronchoconstriction (Barnes, 2009; Bousquet et al., 2000; Global Initiative for Asthma, 2014;

GOLD, 2014). Different treatments are utilized according to symptom control and exacerbation risk (Global Initiative for Asthma, 2014; GOLD, 2014; Lemière and FitzGerald, 2012; Taylor et al., 2008). Therefore, treatment intensity is increased with the severity of disease.

1.6.1 Asthma Severity and Control

Consideration of clinical symptoms and spirometry enables division of asthmatics into four categories, intermittent, mild persistent, moderate and severe, showing a spectrum of increasing symptom severity (Table 1) (Global Initiative for Asthma, 2014; Rabe et al., 2004;

Taylor et al., 2008). This indicates that day and night-time asthma symptoms and exacerbation frequency increases with asthma severity, while lung function acutely deteriorates.

Rather than focusing on asthma severity, the latest GINA guidelines emphasize disease control, while minimising the risk of side effects and exacerbations (Global Initiative for

Asthma, 2014). The GINA now encourages asthmatics to be classified into three groups, according to control: 1) well controlled (no limitation of activities and normal lung function), 2) partly controlled (daytime symptoms or rescue inhaler used more than twice a week, any nocturnal symptoms or limitation of activity or reduced lung function) and 3) uncontrolled (three or more features of partially controlled asthma) (Global Initiative for Asthma, 2014). Although many of the parameters are similar, assessment of disease control is simpler and more treatment- focused than determination of disease severity. Additionally, while a newly diagnosed asthmatic may have severe asthma symptoms, these may be highly responsive to therapy, enabling good symptom control. Alternatively, a patient with moderate asthma symptoms may be unable to achieve consistent disease control, due to resistance to standard treatments and may therefore require additional therapies (Global Initiative for Asthma, 2014; Taylor et al., 2008). However, if severity is assessed after treatment initiation, there is usually a good correlation with disease control, as patients with severe asthma tend to have poor disease control due to factors that include substantial lung inflammation and treatment resistance (Global Initiative for Asthma,

2014; Peters et al., 2006; Taylor et al., 2008).

Table 1.1 Symptom Severity Index by Clinical Features of Asthma Before Treatment. Mild Moderate Severe Intermittent Persistent Persistent Persistent

<2 ≥2 times ≤ 2 times ≥3 times Daytime symptoms times/week a week every day every day

<2 times ≥2 times ≥2 times Every/most Night-time symptoms a month a month a week nights

Typical symptom ≤2 3-6 7-20 8-21 frequency (times/week)

Exacerbations Exacerbations Brief Frequent Exacerbations/impact affect activity affect activity exacerbations exacerbations and sleep and sleep

Spirometry (FEV1 or PEF; ≥80%, 60-80%, % of predicted, ≥80%, <20% ≤60%, >30% 20-30% >30% % variability)

The spectrum of asthma severity ranges from very mild intermittent disease through to severe persistent asthma. Note: typical symptoms include cough, wheeze, shortness of breath and chest tightness (Adapted from Rabe et al., 2004; Taylor et al., 2008).

GINA has developed a stepped plan for asthma designed to escalate treatments until control is achieved (Global Initiative for Asthma, 2014). Step 1 recommends “as needed” short- acting β2-adrenoceptor agonists (SABA), which induce bronchodilatation (Global Initiative for

Asthma, 2014). In step 2, a low dose ICS is added as a "controller" treatment. Rather than increasing ICS concentration, a LABA is added to the ICS in step 3, as this provides greater

19 symptom control in adults than doubling or even quadrupling the ICS concentration (Global

Initiative for Asthma, 2014; O’Byrne et al., 2001; Pauwels et al., 1997). In step 4, combination therapy doses are increased so that a medium or high dose ICS/LABA combination is utilised.

Finally, step 5 recommends that the severe asthma patient is referred for add on treatments, including monoclonal antibody therapy against IgE and oral glucocorticoids (Global Initiative for Asthma, 2014).

1.6.2 COPD Pharmacotherapy

Medications for COPD are, as in asthma, prescribed on the basis of symptoms and disease control (GOLD, 2014). Gold recommends COPD patients be divided into four groups on the basis of symptom control and exacerbation risk (GOLD, 2014). Group A patients have few symptoms and little risk of exacerbations; group B includes patients with a low risk of exacerbations, but more significant symptoms than group A; group C have a high risk of exacerbations but few symptoms; finally, group D have both many symptoms and a high risk of exacerbations (GOLD, 2014). The first choice treatment for group A patients are short acting β2- adrenoceptor agonists or anticholinergics, while in group B long-acting bronchodilators are recommended. The recommended initial treatment for patients in group C is combination therapy, comprising an inhaled corticosteroid plus a LABA, or a long-acting anticholinergic.

GOLD recommends that patients in group D initially receive combination therapy and/or a long- acting anticholinergic (GOLD, 2014).

1.6.3 β2-Adrenoceptor Agonists

β2-Adrenoceptor agonists provide relief from bronchoconstriction, irrespective of the constrictor stimulus (Johnson, 1998; Nials et al., 1993). β2-Adrenoceptor agonists can be divided into three groups based on their duration of action (Sears and Lötvall, 2005). SABAs, such as salbutamol (Ventolin), have a rapid onset of action that lasts for ~4 h and are therefore utilised as

“rescue” or “reliever” medications (Johnson, 1998; Sears and Lötvall, 2005). In more severe asthma LABAs, such as salmeterol and formoterol, may be prescribed with a glucocorticoid

(Cazzola et al., 2010; Sears and Lötvall, 2005). LABAs potentiate glucocorticoid activity, while reducing bronchoconstriction and due to ~12 h activity, only need to be taken twice a day.

Although, formoterol and salmeterol have similar durations of action, formoterol is rapidly- acting in vivo allowing use as a reliever medication, while salmeterol has a slower onset of activity (Anderson et al., 1994; Lötvall, 2001; O’Byrne et al., 2005). Recently, ultra long-acting

β2-adrenoceptor agonists, including indacaterol and vilanterol, have been developed with ~24 h duration of action to allow once daily dosing (Cazzola et al., 2010; Spina, 2014).

β2-Adrenoceptor agonists bind to adrenoceptor beta 2, surface (ADRB2), commonly known as the β2-adrenoceptor, located in the cell membranes of many cell types, including airway smooth muscle, myocardiocytes, eosinophils and airway epithelial cells (Anderson, 2006;

Cazzola et al., 2005; Johnson, 2006; Nials et al., 1993). Upon ligand binding, the β2- adrenoceptor, a GPCR, is activated causing the linked Gsα subunit to separate from the βγ subunit (Johnson, 1998). Gsα then activates adenylyl cyclase (AC), enhancing production of cyclic adenosine-3,5-monophosphate (cAMP) from adenosine triphosphate (ATP). Increased cAMP activates the holoenzyme cAMP-dependent protein kinase A (PKA) by decreasing the affinity of the regulatory subunits for the catalytic subunits (Johnson, 1998). PKA then

21 phosphorylates downstream targets, including myosin light chain kinase (MLCK) (Johnson,

1998). PKA also activates Ca2+-Mg+ exchange ATPases, decreasing cytoplasmic Ca2+ (Barnes,

1995; Johnson, 1998). Phosphorylation induces MLCK inactivation, which together with decreased Ca2+, mediates relaxation of airways smooth muscle. PKA also phosphorylates the transcription factor cAMP response element (CRE) binding protein (CREB) at serine 133, enhancing the expression of genes with potentially anti-inflammatory activity, including regulator of G-protein signalling 2 (RGS2) and cytoseine-rich secretory protein LCCL domain- containing 2 (CRISPLD2) (Barnes, 1995; Johnson, 1998). As RGS2 may decrease bronchoconstriction induced by histamine, while CRISPLD2 may decrease IL1B-induced IL6 and 8 expression in airways smooth muscle, increased expression of these genes induced by

LABAs may be beneficial in the treatment of asthma (Himes et al., 2014; Holden et al., 2011,

2014; Xie et al., 2012).

Phosphorylation by PKA and adrenergic β-receptor kinase 1 and 2 (ADRBK1,2; βARK;

GRK2/3), terminates agonist-bound β2-adrenoceptor signalling by enhancing arrestin, beta 1

(ARRB1; β-arrestin) binding and uncoupling from Gαs (Bouvier et al., 1988; Lohse et al., 1990;

Pippig et al., 1993). Following phosphorylation the β2-adrenoceptor can undergo internalisation and degradation (Barak et al., 1994), while sustained stimulation of the β2-adrenoceptor also decreases receptor expression and thereby attenuates signalling (Barnes, 1995; Johnson, 2006;

Lipworth and Aziz, 2000; Nishikawa et al., 1996). The β2-adrenoceptor may also promiscuously couple to Gαi following phosphorylation, leading to activation of MAPK signalling and potentially enhanced inflammation (Adcock et al., 2002; Sears, 2002).

1.6.4 Glucocorticoids

The principle anti-inflammatory "controller" therapy for asthmatics is synthetic inhaled glucocorticoids, referred to clinically as inhaled corticosteroids (ICS) (Barnes, 2006b).

Glucocorticoids act on the glucocorticoid receptor (GR; NR3C1) to improve symptom control, reduce exacerbation frequency and may even reduce mortality in asthmatics, through reducing lung inflammation (Barnes, 2006b; Bousquet et al., 2000). Glucocorticoids reduce inflammation by decreasing inflammatory gene expression and protein production, primarily by inducing the expression of anti-inflammatory genes (transactivation) and by binding to and directly inhibiting the pro-inflammatory transcription factors NF-κB and AP-1 (transrepression) (De Bosscher and

Haegeman, 2009; Newton, 2014).

Therapeutic glucocorticoids mimic the actions of the endogenous glucocorticoid, cortisol, which is normally released in a circadian manner with peak blood levels occurring at around 8 am (Barnes, 2006b; Chen and Miller, 2007; Chrousos, 1995; Perogamvros et al., 2012).

However, stressors, including pain, infection and inflammation, also induce cortisol generation, through hypothalamic-pituitary-adrenal (HPA) axis activation (Busillo and Cidlowski, 2013;

Chen and Miller, 2007). HPA axis activation causes the release of corticotropin-releasing hormone (CRH) from the paraventricular nucleus of the hypothalamus (Barnes, 2006b; Chen and

Miller, 2007; Newton, 2000). CRH travels to the anterior pituitary gland where it induces the release of pro-opiomelanocortin (POMC), a precursor protein that undergoes cleavage to release proteins, including adrenocorticotropin hormone (ACTH), into the circulatory system. ACTH subsequently induces cortisol synthesis and release. Cortisol, and other glucocorticoids, feedback on the hypothalamus and pituitary gland, reducing the production of CRH and ACTH (Newton,

2000). This can suppress cortisol release and, therefore, abrupt withdrawal of high dose

23 glucocorticoids can result in musculoskeletal pain, fatigue and even fever (Barnes, 2006b;

Schäcke et al., 2002). This mirrors features of adrenal insufficiency (e.g. Addison's disease), including fatigue, reduced strength, weight loss, nausea, myalgia, fever, hypotension and hypoglycaemia (Hopkins and Leinung, 2005).

Cortisol is bound by serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 6 (SERPINA6/CBG) in the blood, while most synthetic glucocorticoids instead bind to albumin (Hammond et al., 1991; Lewis et al., 2005; Mendel, 1989; Perogamvros et al., 2012; Pugeat et al., 1981). Protein binding protects the glucocorticoid from inactivation, but may leave only a fraction free to exert effects. However, cleavage of SERPINA6 by neutrophil elastase decreases its affinity for cortisol, potentially increasing free cortisol levels at inflammatory sites (Hammond et al., 1990). Glucocorticoids undergo metabolism by liver enzymes, including cytochrome P450 3A family members and excretion occurs predominantly via the fecal route (Cerasoli, 2006; Moore et al., 2012).

1.6.4.1 Side Effects of Glucocorticoids

As a mediator of the "fight or flight" stress response, cortisol has a variety of actions throughout the body (Alexander et al., 2011; Sapolsky et al., 2000). In conjunction with other hormones, such as epinephrine and norepinephrine, that act on adrenoceptors, including the β2- adrenoceptor, cortisol can increase energy supply, enhance cardiac output and increase blood pressure (Sapolsky et al., 2000; Zhou and Cidlowski, 2005). Cortisol increases blood sugar through inhibition of energy storage, mobilization of stored energy and gluconeogenesis, the production of glucose from non-carbohydrate substrates (Sapolsky et al., 2000). Nevertheless, under the conditions of stress, normally associated with the "fight or flight" response, cortisol

24 and other stress hormone levels are only temporarily raised and so metabolic effects only last for a relatively short duration (Sapolsky et al., 2000).

However, asthmatics commonly take synthetic glucocorticoids once or twice a day to control symptoms (Barnes, 2006b), potentially simulating near continuous stress responses

(Sapolsky et al., 2000). This can result in the development of systemic metabolic responses, particularly when synthetic glucocorticoids are taken at higher doses over prolonged periods, which, because of their detrimental effects in asthma therapy, are known as 'side effects' (Barnes,

2006b). Furthermore, local side effects, including cough, dysponia and oropharyngeal candidiasis can occur in the mouth and throat, due to the large fraction of inhaled glucocorticoid that is swallowed (Barnes, 2006b). Modern inhaled corticosteroids generally only induce mild systemic side effects, but high dose oral or systemic glucocorticoids will generally induce more severe side effects, including skin thinning, delayed wound healing, glaucoma and cataract formation, osteoporosis, diabetes development, hypertension, cognitive and emotional disturbances (Barnes, 2006b; Schäcke et al., 2002). Prolonged high dose glucocorticoid therapy may lead to the development of iatrogenic Cushing's disease, which has features, including central obesity, hypertension, skin thinning, poor wound healing, muscle weakness and increased frequency of infection (Hopkins and Leinung, 2005).

Pharmaceutical companies have focused on minimising side effects associated with glucocorticoid treatment, through a number of innovations in compound design (Biggadike et al.,

2004; Cerasoli, 2006). For example, the clinically prescribed compounds fluticasone furoate, fluticasone proprionate and budesonide have low oral bioavailability and were designed as "soft drugs" that reduce systemic exposure following inhalation, by rapidly undergoing metabolism and deactivation (Biggadike et al., 2004; Cerasoli, 2006). Other novel glucocorticoids, including

25 ciclesonide (active metabolite: des-ciclesonide), butixocort 21-propionate and beclomethasone dipropionate, are synthesized as pro-drugs that predominantly undergo activation in the lung, reducing side effects resulting from systemic exposure (Biggadike et al., 2004; Cerasoli, 2006).

1.6.4.2 The Glucocorticoid Receptor

The glucocorticoid receptor (GR; NR3C1), is a member of the nuclear hormone receptor superfamily and has homology with the mineralocorticoid receptor (MR; NR3C2), progesterone receptor (PR; NR3C3) and androgen receptor (AR; NR3C4) (Beato and Klug, 2000). The GR protein is modular and divided into domains that include an N-terminal domain, a DNA binding domain (DBD), a hinge region, a ligand binding domain (LBD) and a short C-terminal domain

(Zhou and Cidlowski, 2005; Giguère et al., 1986). GR contains two activator function (AF) regions (AF-1 and AF-2), located in the N-terminal domain and near the C-terminus respectively, which can interact with cofactors and basal transcriptional machinery (Heitzer et al., 2007; Lavery and Mcewan, 2005; Zhou and Cidlowski, 2005). GR contains ~64 serine (S) or threonine (T) residues accessible for phosphorylation along its structure, most of which are in the

N-terminal region (Adcock et al., 2002; Ortsater et al., 2012).

The DBD contains two zinc fingers enabling recognition of glucocorticoid response elements (GREs) present in DNA at which GR can bind, potentially enhancing gene transcription

(Zhou and Cidlowski, 2005). GREs are imperfect palindromic sequences of DNA bases with a consensus sequence of "GGT ACA NNN TGT TCT" consisting of two 6 bp conserved sequences separated by a non-conserved 3 bp spacer, containing any (N) bases (Karin et al.,

1984; Reddy et al., 2009). GRE sites appear to be highly varied around the consensus sequence,

26 but individual sites show a high degree of conservation between mammalian species which appears to correlate with occupancy (So et al., 2007, 2008).

Finally, the hinge region of GR joins the DBD to the LBD, which consists of 12 alpha helices arranged into 3 sheets, which is bound by agonists (glucocorticoids and non-steroidal ligands) and antagonists (Lavery and Mcewan, 2005; Zhou and Cidlowski, 2005). The LBD is also important for GR dimerization, interaction with heat shock protein 90 (HSP90), co-activator and co-repressor proteins (Heitzer et al., 2007; Lavery and Mcewan, 2005).

1.6.4.3 The Glucocorticoid Receptor Gene

The gene encoding GR is located on chromosome 5q31-32 and contains 10 exons

(Hollenberg et al., 1985; Zhou and Cidlowski, 2005). The GR gene produces a variety of proteins containing up to 777 amino acid residues, including three major protein isoforms known as GR alpha, beta and gamma. GRβ differs from GRα at its C-termini due to utilization of an alternative splice acceptor site in exon 9, which leads to replacement of the final 50 residues of

GRα with 15 non-homologous residues (Hollenberg et al., 1985; Oakley and Cidlowski, 2011;

Pujols et al., 2007). This shortened form of GR does not contain helices 11 and 12 of the LBD, leading to predominantly nuclear localization, where GRβ may behave as a dominant negative inhibitor of GRα (Bamberger et al., 1995; Oakley et al., 1996). However, mRNA expression of

GRβ is very low in many cells types, including A549, BEAS-2B and primary bronchial cells and as protein often cannot be detected, GRβ may not have biologically meaningful effects in these cells (Gagliardo et al., 2000, 2001; Pujols et al., 2001, 2002, 2007). The GR gene also has a number of alternative translation initiation sites, generating proteins of differing length due to

27 shortened N-terminal domains, which may potentially have differences in function and/or cellular localization (Oakley and Cidlowski, 2011).

1.6.4.4 Glucocorticoid Receptor Translocation

In the absence of glucocorticoid, unliganded GR is bound by proteins, including heat shock protein (HSP) 90, p23 and a tetratricopeptide repeat (TPR) protein, which mask nuclear localization signals (NLS) 1 and 2, present in the DBD/hinge region and LBD respectively

(Heitzer et al., 2007; Tang et al., 1998; Zhou and Cidlowski, 2005). HSP70 may, in conjunction with HSP90, induce a GR conformation that allows ligand binding. TPR proteins identified in complexes with GR are the immunophilin, FK506 binding proteins (FKBP) 4 and 5, formally known as FKBP51 and 52 respectively, peptidylprolyl isomerase D (PPID/CYP-40) and protein phosphatase 5 (PPP5C) (Czar et al., 1995; Heitzer et al., 2007; Oakley and Cidlowski, 2011;

Pratt et al., 2006; Savory et al., 1999). Although unliganded GR may continually traffic between the nucleus and cytoplasm, masking of the NLS ensures that GR is predominantly cytoplasmic

(Vandevyver et al., 2012). Glucocorticoids rapidly diffuse through the cell membrane and bind to

GR present in the cytoplasm. This leads to a conformational change in the receptor, the exchange of FKBP5 for FKBP4 (or PPID or PPP5C) and connection to the dynein-dynactin motor (Czar et al., 1995; Davies et al., 2002; Wochnik et al., 2005). These then rapidly shuttle GR to the nucleus along microtubules (See figure 1.1) (Galigniana et al., 1998; Wochnik et al., 2005). In addition, release from the chaperone complex may also allow GR to diffuse to the nucleus (Pratt et al.,

2006). Once at the nuclear envelop, the GR complex is trafficked through nuclear pores by importin-dependent mechanisms (Echeverría et al., 2009; Savory et al., 1999). In the nucleus, the

HSP90, p23 and TPR protein complex dissociate from GR, allowing GR to interact with other proteins and to bind DNA to modulate gene expression (Heitzer et al., 2007; Pratt et al., 2006).

1.6.5 Transrepression and Transactivation

Ligand-bound GR is believed to modulate gene expression through two principle mechanisms, repressing the expression of genes through transrepression and enhancing the expression of genes by transactivation (Barnes, 2006b; Newton, 2000). Initial studies suggested that transrepression by glucocorticoids occurred through cis-acting, negative GREs (nGREs) associated with genes, including prolactin, osteocalcin and POMC, the precursor for ACTH, where GR could bind and repress transcription, either directly or through blocking the binding of other factors, such as TATA-binding protein (TBP) (Drouin et al., 1989; Meyer et al., 1997;

Sakai et al., 1988). However, with the possible exception of thymic stromal lymphopoietin

(TSLP) (Hudson et al., 2013; Surjit et al., 2011), simple nGREs are not commonly found in the regulatory regions of inflammatory genes (Newton, 2014; Reddy et al., 2009). However, nGREs without homology to consensus GREs have recently been discovered, but their physiological relevance remains to be elucidated (Surjit et al., 2011).

Probably the most widely considered mechanism of transrepression is direct binding or

'tethering' of GR to transcription factors, such as NF-κB, nuclear factor of activated T-cells

(NFAT), interferon regulatory factor 3 (IRF3) and AP-1, to repress gene transcription (De

Bosscher et al., 2003; Caldenhoven et al., 1995; Newton, 2000; Ray and Prefontaine, 1994).

Tethering of GR may mask the transcriptional activation domains of these inflammatory transcription factors, hinder interactions with basal transcriptional machinery or sequester the transcription factor, decreasing its ability to bind DNA and enhance gene expression (Brostjan et

29 al., 1997; Caldenhoven et al., 1995; Scheinman et al., 1995a). Additionally, tethered GR may recruit histone deacetylase (HDAC) 2 to the transcription factor complex, resulting in deacetylation of histones and contraction of chromatin structures, preventing inflammatory gene expression (Ito et al., 2000). Likewise, recruitment of the coregulator protein GR-interacting protein (GRIP) 1, following GR tethering, may be involved in the repression of inflammatory transcription factor activity (Chinenov et al., 2012; Rogatsky et al., 2002).

At the time the mechanisms underlying glucocorticoid activity were first being determined, glucocorticoid inducible gene expression (transactivation) was predominantly thought to induce detrimental or "side" effects, such as gluconeogenesis, which can contribute to the development of diabetes (Krane, 1993). This, coupled with the observation that GRE reporter activation required high glucocorticoid concentrations, contributed to the development of dogma suggesting that beneficial, anti-inflammatory glucocorticoid effects occur predominantly through transrepression (Barnes and Adcock, 2003; De Bosscher and Haegeman, 2009; De Bosscher et al., 2003; Krane, 1993). However, there is emerging data suggesting that transrepression may not be the principle mechanism of glucocorticoid activity (Chang et al., 2001; Chivers et al., 2004,

2006; King et al., 2013; Newton et al., 1998a, 2001). Transrepression is limited to inhibiting the activity of inflammatory transcription factors and gene transcription, but significant repression of inflammatory protein production also occurs posttranscriptionally (Fan et al., 2006; Ing, 2005;

Newton et al., 2001; Ristimaki et al., 1996; Stellato, 2004). Indeed, greater than 50% of the repression of TNF-induced mRNA expression by glucocorticoids may occur through posttranscriptional suppression, which may be mediated by glucocorticoid-inducible genes

(Clark, 2007; Fan et al., 2006). Furthermore, IL1B-induced NF-κB reporter activation is only decreased by <40% by dexamethasone in A549 cells, while NF-κB-dependent nitric oxide

30 synthase 2, inducible (NOS2), PTGS2, and CXCL8 protein production is reduced by 70-90%

(Newton et al., 1998a). Glucocorticoids may also decrease the expression of many other potentially inflammatory proteins, including members of the matrix metalloproteinase family and chemokine ligand 2 (CCL2/MCP1), through posttranscriptional mechanisms (Ing, 2005; Delany and Brinckerhoff, 1992; Poon et al., 1999).

Additional evidence underscoring the potential importance of glucocorticoid-inducible genes is that repression of inflammatory mediator production by glucocorticoids is frequently reduced in the presence of inhibitors of transcription (actinomycin D) or translation

(cycloheximide) (Chang et al., 2001; Chivers et al., 2006; Newton, 2000). Equally, dexamethasone-induced post-transcriptional destabilisation of constitutive CXCL8 (Chang et al.,

2001) or IL1B-induced CXCL8 and PTSG2 (Chivers et al., 2006) mRNAs was blocked by actinomycin D or cycloheximide, suggesting that new gene synthesis was required for inhibition.

Likewise, dexamethasone is unable to fully repress the IL1B-induced expression of genes, including PTGS2, IL6, CCL2, CXCL1/GROα, CXCL2/MIP2α, CXCL8 and colony stimulating factor 2 (CSF2/GM-CSF), in the presence of cycloheximide (King et al., 2013).

1.6.5.1 Glucocorticoid-Inducible Genes

The observation that new gene synthesis appears to be required for the repression of inflammatory gene expression has led to the discovery of a number of glucocorticoid-inducible genes that may inhibit many stages of inflammatory protein production and release (Newton and

Holden, 2007; Vandevyver et al., 2013). For example, IL-1r2 and IL-1ra reduce inflammatory signalling by IL-1, by acting as a decoy receptor and receptor antagonist respectively (Levine et al., 1996; Re et al., 1994). Likewise, the bronchoconstriction induced by mediators, such as

31 histamine, acetylcholine and prostaglandins acting on Gq-linked GPCRs may be reduced by regulator of G-protein signalling (RGS) 2, which acts as a GTPase-activating protein, terminating the activity of the Gαq subunit (Bernstein et al., 2004; Holden et al., 2011; Kehrl and

Sinnarajah, 2002; Xie et al., 2012). Glucocorticoid-inducible genes may also reduce MAPK activity, as cyclin dependent kinase inhibitor 1C (CDKN1C) may inhibit JNK MAPK, in addition to cyclin dependent kinases, while DUSP1/MKP1 dephosphorylates and inactivates p38,

ERK and JNK MAPK (Chang et al., 2003; Heximer et al., 1997; Holden et al., 2011, 2014; King et al., 2009a; Owens and Keyse, 2007; Samuelsson et al., 1999; Xie et al., 2012).

Glucocorticoid-inducible genes also inhibit transcription factors activated downstream of inflammatory signalling pathways, including NF-κB and AP1. NFKBIA, one of the first anti- inflammatory glucocorticoid-inducible genes discovered, binds and sequesters NF-κB in the cytoplasm, reducing transcription of inflammatory genes (Auphan et al., 1995; Deroo and

Archer, 2001; Scheinman et al., 1995b). Additionally, the leucine zipper protein TSC22 domain family, member 3 (TSC22D3/GILZ) reduces the activity of the inflammatory transcription factors NF-κB and AP1 (Ayroldi and Riccardi, 2009; Ayroldi et al., 2001; Mittelstadt and

Ashwell, 2001). Finally, ZFP36 ring finger protein (ZFP36/TTP) induces destabilisation of many inflammatory mRNAs, reducing their translation into inflammatory proteins (King et al., 2009b;

Lai et al., 1999; Mahtani et al., 2001).

Importantly, many of these glucocorticoid-inducible genes are induced in the lungs of individuals taking inhaled corticosteroids (Essilfie-Quaye et al., 2011; Kelly et al., 2012; Leigh et al., 2014). For example, TSC22D3 is induced by glucocorticoids in the lungs of mild asthmatics, while genes, including DUSP1, CDKN1C, RGS2, ZFP36 and NFKBIA, show

32 increased expression in bronchial biopsies taken from volunteers after budesonide inhalation (see discussion) (Kelly et al., 2012; Leigh et al., 2014).

1.6.5.2 Selective Glucocorticoid Receptor Agonists

Due to dogma suggesting that beneficial glucocorticoid activities occur through transrepression, while side effects result from transactivation, pharmaceutical companies have attempted to produce 'dissociated' compounds (also known as selective glucocorticoid receptor agonists (SEGRAs)), which induce transrepression, but not transactivation (De Bosscher and

Haegeman, 2009; De Bosscher et al., 2003; Krane, 1993; Mohler et al., 2007; Schäcke et al.,

2004, 2007; Uings and Farrow, 2005). Initial evidence for the possibility of separating transactivation from transrepression came with the finding that specific mutations of GR, including A458T, prevented receptor dimerization, DNA binding and activation of simple GRE reporter systems (Dahlman-Wright et al., 1991; Heck et al., 1994). Mice containing this GR mutation (known as GRdim) could repress inflammatory gene expression, but induction of metabolic genes, such as tyrosine aminotransferase (TAT) and phosphoenolpyruvate carboxykinase 1 (PCK1), was impaired (Reichardt et al., 1998, 2001; Tuckermann et al., 1999).

Although, the GRdim mutation was thought to repress inflammatory gene expression through transrepression, subsequent studies have demonstrated induction of genes, including phenylethanolamine N-methyltransferase and DUSP1, suggesting that transactivation-dependent repressive effects cannot be ruled out (Abraham et al., 2006; Adams et al., 2003). Additionally, the initial optimism that the initial GRdim findings generated has not yet translated into compounds that show complete uncoupling in vivo (Newton and Holden, 2007). For example, while RU24858 demonstrated dissociated properties in vitro and can repress NF-κB in vivo, it

33 also decreased bone mass and body weight in mice (Belvisi et al., 2001). Additionally, RU24858 does not show full dissociation in vitro and induces the expression of genes with anti- inflammatory properties (Chivers et al., 2006). Furthermore, the repression of CXCL8 and

PTGS2 expression by RU24858 is reduced in the presence of actinomycin D or cycloheximide, demonstrating that the repression of inflammatory genes by this compound occurs, at least in part, through inducing gene expression (Chivers et al., 2006). The continued search for dissociated compounds has lead pharmaceutical companies to explore novel glucocorticoid receptor agonist structures, including the non-steroidal ligand, GSK9027, and the unique

SEGRA, GW870086X (Uings et al., 2013; Yates et al., 2010). Although GSK9027 may not show a dissociated profile, it was generated as a template for the development of novel non- steroidal SEGRAs (Yates et al., 2010). GW870086X activates only a subset of glucocorticoid- inducible genes and shows minimal activation of a mouse mammary tumor virus (MMTV) reporter, while retaining an ability to repress IL6 release (Uings et al., 2013).

1.7 Combination Therapy with Glucocorticoids and LABAs

The first large clinical study investigating interaction between glucocorticoids and

LABAs was performed in 1994 and demonstrated that combination therapy had a greater ability to improve morning PEF than glucocorticoid alone (Greening et al., 1994). Numerous follow-up studies have now demonstrated that addition of a LABA to low dose glucocorticoid therapy is more effective at improving symptom control and reducing exacerbation frequency than doubling or even quadrupling the dose of glucocorticoid (Greening et al., 1994; Masoli et al.,

2005; Miller-Larsson and Selroos, 2006; Noord et al., 1999; O’Byrne et al., 2001, 2005; Pauwels et al., 1997; Pearlman et al., 1999; Shrewsbury et al., 2000). Importantly, these effects are

34 believed to be class specific and occur with all glucocorticoid receptor and β2-adrenceptor agonist combinations tested to date (Caramori et al., 2006; Giembycz et al., 2008). Additionally, having both components in a single, rather than separate, inhalers may lead to further modest improvements in lung function (Li et al., 2007; Nelson et al., 2003a). The finding that combination therapy comprising an ICS and a β2-adrenceptor agonist is more effective than ICS monotherapy has been embraced in international guidelines, including GINA, which now recommends combination therapy in those patients who cannot achieve adequate control on an

ICS alone (BTS/SIGN, 2012; Global Initiative for Asthma, 2014; Lemière and FitzGerald,

2012). Furthermore, the GINA guidelines recommend that patients not adequately controlled on low dose ICS/LABA combination therapies increase both components to medium or high doses

(Global Initiative for Asthma, 2014). Additionally, combination therapy decreases the frequency of exacerbations temporally associated with upper respiratory tract infections (URTI), relative to glucocorticoid monotherapy (Prazma et al., 2010).

1.7.1 Effects of Glucocorticoids on LABA-Dependent Responses

A number of studies have investigated the mechanisms through which glucocorticoids and LABAs may interact in combination therapy, focussing on how glucocorticoids may enhance LABA activity and vice versa (Caramori et al., 2006; Giembycz et al., 2008).

Glucocorticoids appear to potentiate signalling of the β2-adrenoceptor (ADRB2) through a number of mechanisms, including reducing β2-adrenoceptor desensitization, increasing binding site number for β2-adrenoceptor agonists and enhancing Gsα expression (Figure 1.1) (Cooper and

Panettieri Jr., 2008; Hui et al., 1982; Kalavantavanich and Schramm, 2000; Saito et al., 1989;

Taylor and Hancox, 2000). Repeated formoterol inhalation over 2 weeks reduces sensitivity to

35 albuterol as measured by increased FEV1, but this effect is partially reversed by a bolus of systemic or inhaled glucocorticoid (Lipworth and Aziz, 2000). Glucocorticoids double the transcription rate of ADRB2 in human peripheral lung tissue, nasal scrapings and rat lung tissue, potentially because of a GRE site upstream of the ADRB2 gene where GR can bind and enhance mRNA expression (Baraniuk et al., 1997; Mak et al., 1995a, 1995b; Nishikawa et al., 1996;

Profita et al., 2005). This enhanced receptor induction may oppose the decrease β2-adrenoceptor expression induced by β2-adrenoceptor agonists.

However, use of LABAs, as monotherapy in asthma, is also associated with an increased risk of exacerbations, or even death, potentially through masking inflammation and increasing cytokine production, which may be largely negated in the presence of a glucocorticoid (Frois et al., 2009; McIvor et al., 1998; Rodrigo et al., 2009; Weatherall et al., 2010). LABAs are able to mediate bronchodilation despite increasing airways inflammation, potentially masking the symptoms of potentially life threatening exacerbations (McIvor et al., 1998). Furthermore,

LABAs may enhance IL6 and CXCL8 production in vitro by augmenting TNF or IL1B and histamine activity (Holden et al., 2007; Korn et al., 2001; Pang and Knox, 2000). However, cytokine production induced by LABAs was significantly reduced following glucocorticoid addition. These results may therefore contribute to the increased benefit of glucocorticoid plus

LABA combination therapy in asthmatics (O’Byrne et al., 2001; Pauwels et al., 1997;

Shrewsbury et al., 2000), where the beneficial effects of LABAs on bronchoconstriction are maintained, or even potentiated (Cooper and Panettieri Jr., 2008; Kalavantavanich and Schramm,

2000), but the induction of cytokines is inhibited by the glucocorticoid (Holden et al., 2010;

Korn et al., 2001).

Figure 1.1 Glucocorticoid- and LABA-Induced Signalling Pathways and Possible Mechanisms of Enhancement. Glucocorticoids bind to the glucocorticoid receptor (GR), which then translocates into the nucleus where it can bind to and inhibit inflammatory transcription factors such as NF-κB (transrepression) or enhance the expression of genes (transactivation), including the β2- adrenoceptor (ADRB2) and Gsα (GNAS). GR may also reduce β2-adrenoceptor desensitisation. LABAs bind to the β2-adrenoceptor inducing the activation of adenylyl cyclase (AC) by GSα. AC catalyses the conversion of ATP into cAMP and the increased cAMP concentration activates PKA. PKA phosphorylates numerous proteins including myosin-light kinase (MLCK) and cAMP response element binding (CREB). PKA may enhance GR ligand binding, translocation and glucocorticoid-inducible gene expression.

1.7.2 Effects of LABAs on Glucocorticoid-Dependent Responses

LABAs also enhance glucocorticoid activity, but while many potential mechanisms have been proposed, the importance of individual processes are unclear (Figure 1.1) (Caramori et al.,

2006; Giembycz et al., 2008). LABAs may enhance GR activity within the cytoplasm through enhancing GR-ligand binding, cofactor dissociation/association or nuclear translocation.

Alternatively, LABAs may enhance GR DNA binding, transrepression and glucocorticoid-

37 inducible gene expression (Giembycz et al., 2008; Taylor and Hancox, 2000). For example,

LABAs and forskolin, a direct activator of adenylyl cyclase, may enhance the expression of GR mRNA, counteracting the decrease in GR protein expression that occurs following glucocorticoid treatment (Dong et al., 1989; Peñuelas et al., 1998). Additionally, LABAs increase cAMP production and may enhance the sensitivity of GR activation, through inducing

GR phosphorylation (Chen et al., 2008; Haske et al., 1994; Ismaili and Garabedian, 2004; Kumar and Calhoun, 2008). Alternatively, by enhancing DNA binding, LABAs may potentiate GR- inducible gene expression (Korn et al., 1998; Roth et al., 2002). Indeed, LABAs have been shown to enhance the expression of anti-inflammatory genes, including RGS2, CDKN1C and

DUSP1 (Holden et al., 2011, 2014; Kaur et al., 2008).

A major focus of investigations into the mechanism by which LABAs may enhance glucocorticoid activity has been on enhanced translocation (Eickelberg et al., 1999; Profita et al.,

2005; Roth et al., 2002; Usmani et al., 2005). Eickelberg et al. (1999) was the first paper to suggest that β2-adrenoceptor agonists enhanced GR translocation, in experiments performed in vitro in primary human fibroblasts and airway smooth muscle. Likewise, Roth et al. (2002) demonstrated that addition of the LABA, formoterol enhanced budesonide-induced translocation in bronchial smooth muscle cells in vitro and was concentration-sparing, allowing less glucocorticoid to be used to generate a given response. Additionally, experiments by Usmani et al. (2005) demonstrated that translocation of GR ex vivo in sputum cells and in vitro in U937 cells was enhanced by salmeterol (Usmani et al., 2005). Furthermore, Eickelberg et al. (1999) suggested that β2-adrenoceptor agonists could enhance GR translocation in the absence of glucocorticoid, an effect known as ligand-independent translocation. While this has not been demonstrated in follow up studies, ligand-independent activation of other steroid receptors has

38 been suggested to occur (Cenni and Picard, 1999; Weigel and Zhang, 1998). However, enhancement of GR translocation by LABAs and particularly ligand-independent GR translocation remain controversial (Giembycz et al., 2008). For example, ligand-independent translocation of GR does not appear credible, as treatment with LABAs does not produce the anti-inflammatory effects that would be expected if they activated GR (Howarth et al., 2000;

Roberts et al., 1999). Furthermore, there is evidence to suggest that salmeterol and formoterol are unable to induce translocation of GR into the nucleus and that the repression of the expression of genes, including CSF2, by formoterol is GR independent (Lovén et al., 2007). Additionally, at moderate glucocorticoid concentrations, the majority of GR is localised in the nucleus and yet substantial enhancement following LABA addition still occurs (Chivers et al., 2004; Kaur et al.,

2008; Usmani et al., 2005). Consequently, there is a need to conclusively demonstrate the mechanisms through which LABAs enhance glucocorticoid activity.

1.8 Glucocorticoid Resistance

Although asthma is effectively controlled with inhaled glucocorticoids in a majority of individuals, a subpopulation of asthmatics, without confounding factors, such as poor adherence to medication, fail to gain adequate symptom control with even high dose oral or systemic glucocorticoids (Carmichael et al., 1981; Lane et al., 1996; Schwartz et al., 1968). This glucocorticoid resistant asthma, was first described in 1968 in 6 patients who received intravenous cortisol, but had only a modest decrease in blood eosinophils when compared to 19 asthmatic controls (Schwartz et al., 1968). To maintain some asthma control, these patients required more than 15 mg of prednisone a day (or equivalent). In a further study, glucocorticoid- resistant asthmatics were shown not to differ substantially from glucocorticoid-responsive

39 asthmatics, except in having a longer duration of symptoms and a more frequent family history of asthma (Carmichael et al., 1981).

Glucocorticoid resistant asthma can be clinically defined as a lack of improvement of

>15% in morning PEF or FEV1, following 7-14 days of treatment with 40 mg daily prednisolone equivalent (Barnes et al., 1995). Alternatively, glucocorticoid resistance can be broadly defined as a decrease in the maximum response to glucocorticoids (Ammit, 2013; Barnes and Adcock,

2009; Keenan et al., 2012). In the context of this thesis "glucocorticoid resistance" is used to describe situations where individuals show reduced responses to glucocorticoids or where there is a decrease in the repression of inflammatory gene expression by glucocorticoids, which cannot be overcome by increasing the dose or concentration (Adcock and Barnes, 2008; Keenan et al.,

2012). The term ‘glucocorticoid hyporesponsiveness’ will be used where maximal glucocorticoid-inducible gene expression cannot be achieved, for example in the presence of an inflammatory stimulus, despite maximally effective concentrations of glucocorticoids.

The prevalence of glucocorticoid resistance among asthmatics is thought to be low, with estimates ranging from as few as 1:10,000 to 1:1000 or possibly even <1:100 (Barnes and

Woolcock, 1998; Barnes et al., 1995; Yim and Koumbourlis, 2012). However, glucocorticoid resistance is more frequently present in severe asthma, during exacerbations and in asthmatics who smoke (Adcock and Barnes, 2008; Durham et al., 2011; Livingston et al., 2005; Wang et al.,

2010). Glucocorticoid resistant asthmatics do not differ from asthmatic controls in their cortisol secretion or in HPA axis suppression (Lane et al., 1996). Additionally, these asthmatics do not normally have symptoms of Addison's disease or secondary adrenal insufficiency, suggesting that they have normal HPA function (Barnes et al., 1995; Lane et al., 1996). As a consequence, it appears that glucocorticoid-resistant asthmatics may still develop side effects from high dose

40 glucocorticoid therapy, despite gaining little by way of therapeutic benefit (Carmichael et al.,

1981). Many reviews separate glucocorticoid resistance from " insensitivity to glucocorticoids", in which there is a rightward shift in the response curve to glucocorticoid, such that increased glucocorticoid concentrations are required to achieve a maximal response (Ammit, 2013; Barnes and Adcock, 2009; Keenan et al., 2012). Although symptom control may be achievable with a sufficient dose of glucocorticoid in asthmatics with insensitivity, practically the manifestation of significant side effects can limit treatment effectiveness to a similar degree as in resistance

(Woolcock, 1993).

1.8.1 Severe Asthma

Asthmatics with severe disease can often struggle to achieve control of symptoms, despite prolonged treatment with high dose inhaled or even oral glucocorticoids (Wenzel and

Busse, 2007). The prevalence of severe asthma may be as high as 20% and of these 20% of patients may be unable to gain adequate control, potentially due to glucocorticoid resistance

(Durham et al., 2011; Peters et al., 2006). Such patients have a disproportionate requirement for health care support due to significant morbidity and frequent exacerbations. Therefore severe asthma accounts for the majority of asthma expenditure (Antonicelli et al., 2004; Barnes, 2008;

Serra-Batlles et al., 1998; Wenzel and Busse, 2007).

Because of the heterogeneous nature of severe asthma, studies have used techniques, including clustering, to stratify asthma phenotypes (Moore et al., 2010; Wu et al., 2013; Wenzel and Busse, 2007). These studies have identified features associated with severe asthma, including obesity, eosinophilia and neutrophilia. Obesity is associated with an increased severity of asthma and may contribute to the development of glucocorticoid resistance, potentially

41 through induction of a generalised pro-inflammatory state characterized by increased IL6, VEGF and TNF production (Boulet, 2013; Juge-Aubry et al., 2005; Wenzel, 2012). A subset of severe asthmatics have profound eosinophilia, but whether this directly contributes to glucocorticoid resistance or simply reflects poor response to treatment, remains unclear (ten Brinke et al., 2004;

Louis et al., 2000; Moore and Peters, 2006). Likewise, neutrophils are increased in some severe asthmatics (Gibson et al., 2001; Green et al., 2002; Jatakanon et al., 1999; Wenzel et al., 1997).

However, it is unclear whether increased neutrophilia results from the apparently intrinsic resistance of neutrophils to glucocorticoid-induced apoptosis or whether neutrophilic inflammation reduces responses to glucocorticoids. Nevertheless, neutrophilia may increase production of inflammatory mediators, including CXCL8, thromboxane and IL17 production

(Cox, 1995; Cox and Austin, 1997; Gibson et al., 2001; Liles et al., 1995; Wenzel et al., 1997).

Conversely, IL17 may induce CXCL8 production and upregulation of VCAM-1 and ICAM-1, enhancing neutrophil trafficking to the lung, through a phosphatidylinositol 3-kinase (PI3K) dependent mechanism (Roussel et al., 2010; Thomas et al., 2005). Both neutrophilia and IL17 are associated with glucocorticoid resistance and may also be enhanced during asthma exacerbations, particularly those associated with respiratory tract infections (Corrigan and Loke,

2007; Poon et al., 2012; Strickland et al., 2001; Vazquez-Tello et al., 2013).

1.8.2 Asthma Exacerbations

Lung function is variable in asthmatics, but can acutely deteriorate during exacerbations, which vary in their speed of development (from minutes to weeks), duration (from days to weeks) and severity (mild, moderate or severe) (Reddel et al., 2009). Exacerbations are often associated with upper respiratory tract infections (URTI), particularly with human rhinovirus and

42 less commonly from exposure to allergen or other precipitating factors (Barnes, 2008; Proud,

2011). Lung inflammation increases dramatically during exacerbations, with greater numbers of inflammatory cells and higher concentrations of mediators, including IL1B, CXCL8 and TNF

(Laza-Stanca et al., 2006; Terajima et al., 1997; Zhu et al., 1997). Additionally, the inflammatory response during exacerbations is often more neutrophilic and frequently resistant to glucocorticoids (Jatakanon et al., 1999; Wark et al., 2001). Exacerbations substantially increase suffering and medical costs through increased hospitalization and therefore improved therapies that provide greater asthma control are urgently needed (Antonicelli et al., 2004; Borderías Clau et al., 2005; Lane et al., 2006).

1.8.2.1 Upper Respiratory Tract Infections and Human Rhinovirus

As noted above, URTI are associated with up to 85% of asthma exacerbations (Johnston et al., 1995; Nicholson et al., 1993; Teichtahl et al., 1997; Wark et al., 2001). While viruses, including influenza and respiratory syncytial virus (RSV), can infect the upper respiratory tract, human rhinovirus (HRV) is the most common and can be found in almost 66% of asthma exacerbations (Grissell et al., 2005; Jackson and Johnston, 2010; Johnston et al., 1995;

Khetsuriani et al., 2007; Wark et al., 2001). Therefore, strikingly, hospitalizations for asthma peak in September, when the return of children to school increases HRV transmission (Dales et al., 1996; Johnston, 2007; Johnston et al., 2006, 1996; Lincoln et al., 2006). One reason for the increase in exacerbations may be that HRV infections are longer and more severe in asthmatics than non-asthmatics (Corne et al., 2002), as the virus may spread from upper respiratory tract epithelial cells where it normally replicates, to the lower airways in asthmatics (Corne et al.,

2002; Mosser et al., 2005; Papadopoulos et al., 2000). Furthermore, there may be increased

43 recruitment of neutrophils and eosinophils to the lung and enhanced IL4, 5 and 13 production during colds in asthmatics (Message et al., 2008).

The development of childhood asthma has been associated with early recurrent wheeze triggered by URTI (Busse et al., 2010; Gordon, 2008; Proud, 2011). Therefore, the risk of developing asthma by age 6 appears to be significantly increased in children experiencing a wheezing illness, such as RSV broncholitis requiring hospitalization or HRV infection, at age 3

(Busse et al., 2010; Proud, 2011). Furthermore, repeated HRV infections may synergize with aeroallergen exposure during childhood, heightening the risk of asthma development (Jackson et al., 2008).

1.8.3 Smoking

Smoke exposure is a risk factor for COPD and lung cancer, but also contributes to asthma development and exacerbations (Gilliland et al., 2000; Hanrahan et al., 1992; Pattenden et al.,

2006; Pedersen et al., 2007; Piipari et al., 2004; Tomlinson et al., 2005). Surprisingly, cigarette smoking frequency in individuals with asthma does not differ from the general population, with as many as 17-35% of asthmatics smoking (Gibson and Simpson, 2009; Livingston et al., 2005;

Stapleton et al., 2011; To et al., 2012). Smoking has both acute and long-term effects on the lung, increasing airways hyperresponsiveness and dose-dependently accelerating the decline of lung function associated with ageing, respectively (Burrows et al., 1977; Camilli et al., 1987;

Gerrard et al., 1980; Jensen et al., 1998; Lange et al., 1998; Sobol et al., 1977; Taylor et al.,

1985). Furthermore, smoking is associated with hospitalization for asthma, as well as elevated mortality and the induction of glucocorticoid resistance (Chalmers et al., 2002; Marquette et al.,

1992; Pedersen et al., 1996; Prescott et al., 1997; Silverman et al., 2003; Siroux et al., 2000;

Ulrik and Frederiksen, 1995). For example, while non-smoking asthmatics show significantly improved PEF, FEV1 and airway hyperactivity following glucocorticoid treatment, in one study, smokers showed no improvement (Chaudhuri et al., 2003). While the mechanisms by which smoke induces glucocorticoid resistance remain unknown, smoking is associated with increased neutrophilia, lung oxidation, hydrogen peroxide (H2O2) in exhaled breath and expression of cytokines, including IL4, CXCL8 and TNF (Byron et al., 1994; Cameron et al., 2010; Chalmers et al., 2001; Horvath et al., 2004; Ito et al., 2001). Indeed, smoking appears to increase neutrophil elastase in bronchial biopsies and sputum neutrophilia, which is associated with glucocorticoid resistance (Cameron et al., 2010; Chalmers et al., 2001, 2002; St-Laurent et al., 2008). Likewise,

TNF may play crucial roles in the cigarette-induced development of emphysema and inflammation (Churg et al., 2002, 2003, 2004; Ito et al., 2001). Furthermore, smoking appears to increase the risk of development and severity of URTIs, possibly due, in part, to increased

CXCL8 and decreased IFN-β production (Blake et al., 1988; Eddleston et al., 2010; Hudy et al.,

2010; Venarske et al., 2006).

1.8.4 Mechanisms of Glucocorticoid Resistance

A number of molecular mechanisms have been suggested to underlie glucocorticoid resistance, including decreased GRα expression, phosphorylation or translocation, increased

GRβ expression, defective histone acetylation and enhanced pro-inflammatory transcription factor activity (Barnes and Adcock, 2009; Keenan et al., 2012). Indeed, increased production of

IL2 and 4 in asthma may reduce GR expression, translocation, binding affinity and activity, potentially through a p38 MAPK dependent mechanism (Irusen et al., 2002, 2002; Sher et al.,

1994). Likewise, both TNF and transforming growth factor (TGF)β1 have been suggested to

45 decrease GR expression and activity, also via activation of p38, as well as JNK MAPK

(Franchimont et al., 1999; Salem et al., 2012; Szatmáry et al., 2004). Equally, AP-1 activation, which is induced by TNF through JNK MAPK, has been implicated in glucocorticoid resistance, potentially through decreasing GR DNA binding (Adcock et al., 1995; Lane et al., 1998; Loke et al., 2006). Alternatively, TNF may induce expression of GRβ, which has been hypothesised to reduce glucocorticoid-responsiveness by acting as a dominant-negative inhibitor of GRα (Goleva et al., 2006; Hamid et al., 1999; Lewis-Tuffin et al., 2007; Sousa et al., 2000; Webster et al.,

2001). However, expression of GRβ is very low relative to GRα in many cell types and no GRβ protein was detected in A549, BEAS-2B and nasal epithelial cells (Gagliardo et al., 2000; Pujols et al., 2002, 2002). Additionally, dominant-negative activity induced using overexpression constructs appears to be cell type specific, making repression of GRα activity unlikely to be widely biologically relevant (Gagliardo et al., 2001; Pujols et al., 2001, 2002, 2007).

Alternatively, severe inflammation and smoking may reduce the expression and/or activity of

HDACs (Adcock et al., 2005; Hew et al., 2006; Ito et al., 2005). As HDACs may be recruited by glucocorticoids during transrepression to decrease inflammatory transcription, this could contribute to the development of glucocorticoid resistance in severe asthma and COPD (Barnes,

2006b; Ito et al., 2000, 2006).

1.8.4.1 Genetics of Glucocorticoid Resistance

A small number of individuals have primary (familial or sporadic) glucocorticoid resistance, due to point mutations in the glucocorticoid receptor gene (Charmandari et al., 2005;

Hurley et al., 1991; Karl et al., 1996; Malchoff et al., 1993; Vottero et al., 2002). These point mutations reduce responsiveness to glucocorticoids, leading to HPA axis dysregulation, with

46 increased cortisol and often ACTH production. However, screening of 113 asthmatic children found no association of GR polymorphisms with asthma or responsiveness to glucocorticoids

(Szczepankiewicz et al., 2008). Likewise the sequence of NR3C1 was unchanged between glucocorticoid resistant and responsive asthmatics, suggesting that any genetic defects that may exist must lie elsewhere (Lane et al., 1994).

1.8.4.2 Tumor Necrosis Factor Alpha as a Mediator of Glucocorticoid Resistance

TNF is a pleotrophic cytokine released by multiple cell types, including macrophages, dendritic cells, B cells, CD4+ T cells, neutrophils, smooth muscle and epithelial cells (Heffler et al., 2007). TNF is involved in the pathogenesis of inflammatory diseases, such as psoriasis,

Crohn's disease and rheumatoid arthritis (Lin et al., 2008). Similarly, TNF is increased in asthma, where expression appears to correlate with severity, with higher concentrations found in uncontrolled and glucocorticoid resistant disease (Ackerman et al., 1994; Berry et al., 2006;

Bradding et al., 1994; Cembrzynska-Nowak et al., 1993; Goleva et al., 2008; Gosset et al., 1991;

Howarth et al., 2005; Ying et al., 1991). TNF enhances airway hyperresponsiveness, methacholine sensitivity and increases eosinophil and neutrophil recruitment to the lung (Berry et al., 2006; Thomas and Heywood, 2002; Thomas et al., 1995). Finally, TNF may produce glucocorticoid resistance through multiple mechanisms, including increasing sputum neutrophilia, up regulating GRβ and enhancing cytokine production (Berry et al., 2007; Bradding et al., 2006; Bradley, 2008; Franchimont et al., 1999; Heffler et al., 2007).

Figure 1.2 Signalling Pathway Activation by TNF and IL1B. In this simplified diagram binding of tumor necrosis factor α (TNF) to a TNF receptor or IL1B to the IL1 receptor (IL1R1) induces activation of a variety of downstream pathways including protein kinase C (PKC), phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK). The transcription factors nuclear factor-kappa B (NF-κB) and activator protein (AP)-1 are also activated leading to enhanced expression of inflammatory genes.

TNF is translated as a 26 kDa protein that is initially anchored in the cell membrane, but can also be released following cleavage by ADAM metallopeptidase domain 17

(ADAM17/TACE) (Kriegler et al., 1988; Zheng et al., 2004). This generates a free 17 kDa protein, which bind as trimers to the two TNF receptors, TNFRSF1A (TNFR1) and TNFRSF1B

(TNFR2) (Figure 1.2) (Davis et al., 1987; MacEwan, 2002; Smith and Baglioni, 1987). On

48 ligand binding TNFRSF1A exchanges BCL2-associated athanogene 4 (BAG4/SODD) for

TNFRSF1A-associated via death domain (TRADD), which subsequently recruits ralA binding protein 1 (RALBP1/RIP-1) and TNFR-associated factor 2 (TRAF2) (Bradley, 2008; MacEwan,

2002). RALBP1 then acts as a bridge enabling activation of the MAPK and NF-κB pathways through recruitment of MAP3K3/MAP3K7 and IKBKB respectively (Heffler et al., 2007).

Activation of these inflammatory pathways may induce glucocorticoid resistance. Furthermore, activation of NF-κB leads to increased production of numerous inflammatory proteins, including

IL1B and TNF, which may then decrease responses to glucocorticoids. TNF may also activate other pathways, such as protein kinase B (PKB) and PKC, which may then induce glucocorticoid resistance (Berry et al., 2007; Bradley, 2008; MacEwan, 2002).

Development of antibodies against TNF has so far been a focus of biotechnology and pharmaceutical companies, but trials of infliximab (mouse-human chimera monoclonal antibody,

Remicade), etanercept (TNFR2 IgG1 fusion protein) and adalimumab (fully human antibody,

Humira) in asthma have produced mixed results. Some studies have demonstrated improvements in metrics, including asthma quality of life questionnaire, FEV1, reduced exacerbations and AHR

(Berry et al., 2006; Erin et al., 2006; Howarth et al., 2005; Morjaria et al., 2008; Taillé et al.,

2013), while others have found little benefit (Rouhani et al., 2005; Wenzel et al., 2009) and increased risk of adverse effects, such as pneumonia, tuberculosis and cancer (Antoni and Braun,

2002; Rennard et al., 2007). Although the studies to date have been small, there is evidence for greater effects of anti-TNF therapy in severe asthma, suggesting that this treatment may benefit a particular group of severe, potentially glucocorticoid resistant asthmatics (Berry et al., 2006;

Howarth et al., 2005). Furthermore, factors predisposing asthmatics to glucocorticoid resistance, such as smoking, obesity and infection, are associated with increased TNF in sputum samples

(Churg et al., 2002, 2003, 2004; Hotamisligil et al., 1995). However, identifying and treating the subset of asthmatics who are most likely to see symptom improvement is currently limited by a lack of understanding of the mechanisms of TNF-induced glucocorticoid resistance (Berry et al.,

2007; Bradley, 2008; Desai and Brightling, 2010; Heffler et al., 2007).

1.9 Overall Hypothesis and Specific Aims

There is clear evidence to suggest that inflammation, produced by pro-inflammatory stimuli, including the cytokine TNF, cigarette smoke and rhinovirus infection, can induce glucocorticoid resistance (Berry et al., 2006; Chalmers et al., 2002; Franchimont et al., 1999;

Goleva et al., 2006; Grünberg et al., 2001; Siroux et al., 2000; Szatmáry et al., 2004; Webster et al., 2001). Likewise, increasing evidence suggests that the induction of genes (transactivation), with potentially anti-inflammatory activity, is important for glucocorticoid activity (Clark, 2007;

Newton, 2014; Newton and Holden, 2007; Vandevyver et al., 2013). However, it is not clear to what extent inflammatory mediators decrease transactivation, leading to induced glucocorticoid hyporesponsiveness. Glucocorticoid hyporesponsiveness may occur through the activation of inflammatory signalling pathways, which reduce the ability of glucocorticoids to induce transactivation and thereby may decrease the expression of genes with potentially anti- inflammatory properties, including CDKN1C, DUSP1, RGS2 and TSC22D3 (see section on glucocorticoid-inducible genes).

Glucocorticoid activity can also be potentiated by stimuli, including LABAs, which enhance the production of cAMP (Kaur et al., 2008). Furthermore, LABAs increase the expression of genes with anti-inflammatory properties, such as CDKN1C and DUSP1.

Therefore, the effects of glucocorticoids on gene expression can be modulated (Figure 1.3).

Given the probable importance of transactivation in glucocorticoid responses, modulation of glucocorticoid-inducible gene expression could have beneficial or detrimental effects. The overall hypothesis of this project is therefore that:

The ability of glucocorticoids to induce genes can be modulated, with negative regulation by

pro-inflammatory stimuli and positive induction by LABAs

It is possible that repression of inflammatory pathways may be achieved by enhancing

GR activity through LABA addition. Likewise the actions of specific inhibitors in combination with glucocorticoid therapy, may alleviate pro-inflammatory stimuli-induced hyporesponsiveness.

Figure 1.3 Modulation of Glucocorticoid-Induced Gene Expression. GR is modulated in a positive manner by LABAs, leading to increased expression of anti- inflammatory genes including CDKN1C. Likewise, inflammatory mediators may negatively modulate GR, decreasing anti-inflammatory gene transcription.

Working from the hypothesis that glucocorticoid activity can be modulated, the aims of this study are:

1) To identify whether pro-inflammatory stimuli repress glucocorticoid induced 2×GRE reporter activity and gene expression.

2) To examine the effect of rhinovirus and the synthetic dsRNA poly(I:C) on glucocorticoid induced 2×GRE reporter activity.

3) To investigate possible strategies for overcoming glucocorticoid hyporesponsiveness.

4) To examine the mechanisms by which LABAs potentiate glucocorticoid activity.

Chapter Two: Materials and Methods

2.1 Materials and Suppliers

AbD Serotec (Raleigh, NC, USA): Primary antibodies – see table A1.

Affymetrix (Santa Clara, CA, USA): 3’IVT Express Kit, GeneChip 3000 scanner, GeneChip

450 fluidics station, PrimeView human gene expression microarrays.

Agilent Technologies (Mississauga, ON, Canada): 2100 Bioanalyser, RNA 6000 Nano

LabChips.

American Type Culture Collection (Rockville, MD, USA): A549 cells, BEAS-2B cells, human rhinovirus type 16.

AstraZeneca Plc. (Södertälje, Sweden): Budesonide, formoterol fumarate dihydrate.

BD Biosciences (San Jose, CA, USA): 8 chamber tissue culture slides.

Biotium Inc. (Hayward, CA, USA): Luciferase assay kit.

BMG Labtech (Offenburg, Germany): FLUOstar OPTIMA plate reader.

Cayman Chemicals (Ann Arbor, Michigan, USA): U46619.

Cell Signalling Technology (Danvers, MA, USA): Primary antibodies – see table A1.

Corning Inc. (Corning, NY, USA): 1.5 ml eppendorf microcentrifuge tubes, cell lifters, T162 cm flasks, tissue culture 6, 12, 24, 48 and 96 well plates.

Dako (Burlington, ON, Canada): Goat anti-mouse, rabbit anti-goat and goat anti-rabbit HRP- conjugated secondary antibodies.

Electron Microscopy Sciences (Hatfield, PA, USA): 16% paraformaldehyde.

EMD Millipore (Billerica, MA, USA): Glycerol, ethylenediaminetetraacetic acid (EDTA),

MgCl2, NP40 alternative, PD098059, SB203580, SB239063, SB202474, U0126.

Eppendorf (Hauppauge, NY, USA): Temperature controlled microcentrifuge S415R.

Enzo Life Sciences (Farmingdale, NY, USA): Phorbol 12-myristate 13-acetate (PMA).

Evergreen Scientific (Los Angeles, CA, USA): Untreated and ELISA treated 96 well plates.

Fujifilm (Tokyo, Japan): Super RX 100NIF x-ray film.

GE Healthcare Life Sciences (Baie d’Urfe, QC, Canada): Amersham Biosciences Ultraspec

2100 Pro UV/visible spectrophotometer, Hybond blotting membranes.

GlaxoSmithKline Plc. (Brentford, Middlesex, UK): Fluticasone propionate, salmeterol xinafoate.

Kodak (Rochester, NY, USA): X-omat 2000 film processor.

Life Technologies Inc. (Burlington, ON, Canada): 7900HT real-time PCR system, Alexa

Fluor 488 goat anti-rabbit F(ab’)2 fragments, Dulbecco’s modified Eagle’s medium (DMEM),

DMEM-F12, fetal calf serum (FCS), NuPage Novex 4-12% bis-tris pre-cast western blotting gels, l-glutamine, Lipofectamine 2000, MicroAmp Optical 96 and 384 well reaction plates,

NuPage western blotting tanks, penicillin-streptomycin antibiotics, 1x penicillin-streptomycin- amphotericin B antibiotics, ProLong Gold anti-fade fixative, Sequence Detection Systems (SDS) v2.4 and SYBR GreenER RT-PCR mastermix, Ultrapure PCR water.

Olympus Canada Inc. (Richmond Hill, ON, Canada): Olympus IX81 FV1000 confocal microscope.

Partek Inc. (St. Louis, Missouri): Partek Genomics Suite v6.6 (6.13.0731).

PerkinElmer (Waltham, MA, USA): Volocity 3D image analysis software.

Praxair Inc. (Danbury, CT, USA): CO2 gas.

Promega (Madison, WI, USA): 20/20n luminometer, pGL3basic and pGL3control luciferase reporter plasmids.

Quanta BioSciences (Gaithersburg, MD, USA): qScript cDNA synthesis kit.

Qiagen Inc. (Toronto, ON, Canada): QIAshredders, RNase-Free DNase Set, RNeasy mini kit.

R&D Systems Inc. (Minneapolis, MN, USA): DuoSet ELISA kits for CSF2 and IL-8, recombinant human IL1B and TNF.

Roche Diagnostics (Laval, QC, Canada): Complete protease inhibitor tablets.

Sigma-Aldrich (Oakville, Ontario, Canada): 30% acrylamide and bis-acrylamide solution, ammonium persulfate, β-mercaptoethanol, bovine serum albumin (BSA), bromophenol blue,

4',6-diamidino-2-phenylindole (DAPI), dexamethasone, dimethyl sulfoxide (DMSO), dithiothreitol, G418 disulfide salt, glycine, goat serum, 4-(2-hydroxyethyl)-1- piperazineethanesulfonic acid, Hank’s balanced salt solution (HBSS), hydrogen peroxide (H2O2), l-glutamine, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), phenylmethylsulphonylfluoride, phosphate buffered saline (PBS), Ponceau S, potassium chloride

(KCl), sodium bicarbonate (NaHCO3), sodium dodecyl sulphate, sodium fluoride, sodium orthovanadate (Na3VO4), sodium pyrophosphate (Na4O7P2), tetramethylethylenediamine, Triton

X-100, TRIZMA-base, TWEEN 20.

Thermo Fisher Scientific (Ottawa, ON, Canada): 50 ml falcon tubes, black walled 96 well plates, coverslips, enhanced chemi-luminescence western blotting substrate, glacial acetic acid, hydrochloric acid, methanol, NanoDrop 2000, Stericycle CO2 incubator 370, sulphuric acid

(H2SO4), T162 cm flasks.

TotalLab Ltd (Newcastle upon Tyne, UK): TL120 1d v2009 image analysis software.

University of Kentucky-College of Agriculture, Food and Environment (North Lexington,

KY, USA): Research grade cigarettes 3R4F (12/2006).

2.2 Reagents and Cell Lines

2.2.1 Dilution of Drugs and Cytokines

Recombinant human IL1B and TNF were dissolved in PBS containing 0.1% BSA. H2O2 and fetal bovine serum were diluted in serum free media. Dexamethasone was dissolved in

HBSS, while all other compounds, including budesonide, formoterol, fluticasone propionate, salmeterol, U46619 and PMA, were dissolved in DMSO (final DMSO concentration <0.1%).

2.2.2 Preparation of Cigarette Smoke Extract

Cigarette smoke extract (CSE) was prepared by bubbling the smoke from 1 research grade cigarette (University of Kentucky) through 4 ml of serum-free medium using an apparatus

Figure 2.1 Cigarette Smoke Extract Preparation Apparatus. Cigarette smoke extract (CSE) was generated by drawing smoke from a lit cigarette up into the syringe. The three-way valve was then rotated and the smoke pushed out and bubbled through 4 ml of media in the 50 ml falcon tube. (Courtesy of Dr. Magda Hudy, Proud laboratory, University of Calgary (Hudy et al., 2010)).

56 consisting of a syringe, three way valve and tubing (Fig. 2.1) (Hudy et al., 2010). Optical density at 320 nM (OD320) was measured and the extract diluted in fresh serum free medium to give an initial OD320 of 1 (Rider et al., 2011). This was then diluted in half logarithms to OD320 0.3, 0.1 and 0.03.

2.2.3 Human Rhinovirus (HRV) Serotype 16 Preparation

HRV propagation and assessment of viral titres were performed by members of the Proud and Leigh laboratories, according to standard procedures.

2.2.4 Cell Culture Methods

2.2.4.1 A549 Cell Culture

The human type 2 pneumocyte cell line, A549 (American Type Culture Collection), was grown in submersion culture in T162 cm flasks in DMEM supplemented with 2 mM l-glutamine

o and 10% FCS at 37 C with 5% CO2 (Praxair) (Giard et al., 1973; Lieber et al., 1976). Cells were passaged when ~95% confluent and plated into 6, 12 or 24 well plates. Prior to experiments, cells were incubated overnight in serum free medium (SFM) consisting of DMEM supplemented with 2 mM L-glutamine.

2.2.4.2 BEAS-2B Cell Culture

The adenovirus12-SV40 virus hybrid-transformed, human bronchial epithelial BEAS-2B cell line (American Type Culture Collection) was grown in submersion culture in T162 cm flasks

o in DMEM/F12 supplemented with 14 mM NaHCO3, 2 mM l-glutamine and 10% FCS at 37 C with 5% CO2 (Reddel et al., 1988). Cells were passaged when ~95% confluent and plated into 6,

12, 24, 48 or 96 well plates. Prior to experiments, cells were incubated overnight in SFM consisting of DMEM/F12 supplemented with 14 mM NaHCO3 and 2 mM L-glutamine.

2.2.4.3 Primary Cell Culture

Airway smooth muscle (ASM) and human bronchial epithelial (HBE) cells were isolated from non-transplanted normal human lungs obtained through a tissue retrieval service, as previously described (Hudy et al., 2010; Kaur et al., 2008). ASM cells were grown in submersion culture in DMEM supplemented with 10% fetal calf serum, 2 mM L-glutamine, 20 μg/ml penicillin/streptomycin and 2.5 μg/ml amphotericin B and used for experiments at passages 3 to

8. HBE cells were grown in submersion culture in bronchial epithelial cell growth medium

(BEGM) containing SingleQuots supplements. HBE and ASM were cultured in supplement free

BEGM and serum free medium respectively, overnight prior to experiments.

2.2.4.4 HRV-16 Infection of BEAS-2B Cells

BEAS-2B cells were infected at log TCID50/ml of ~3.1, 3.6, 4.1 and 4.6 (MOI = ~0.7) in

o SFM and cultured at 34 C in 5% CO2.

2.2.4.5 Reporter Cell Lines

A number of previously developed reporter cell lines were utilised during the research for this thesis. These reporters were generated from Promega's pGL3-basic luciferase reporter plasmid (Promega, 2008). This consists of a backbone containing an enhanced luciferase gene

(luc+) modified from Photinus pyralis with an SV40 derived late poly(A) signal, Escherichia coli and phage F1 origins of replication, an amphicilin resistance gene for bacterial selection and

58 a variety of restriction enzyme sites for cloning. The pGL3-Control plasmid additionally contains an SV40 promoter and enhancer, flanking the luc+ gene. Both reporters were modified by inclusion of a neomycin gene expression cassette, resulting in the generation of pGL3basic.neo and pGL3control.neo (Bergmann et al., 2000). The pGL3control.neo plasmid was further modified to produce pGL3.neo.TATA through the inclusion of a modified minimal β-globin promoter, upstream of the luc+ expression cassette (Catley et al., 2004). The 2×GRE containing reporter pGL3.neo.TATA.2GRE was cloned through the addition of two consensus GRE sites

(consensus sites underlined: 5'-GCT GTA CAG GAT GTT CTA GGC TGT ACA GGA TGT TC

TAG-3') upstream of the TATA promoter in pGL3.neo.TATA (Chivers et al., 2004). The NF-κB responsive reporter 6NF-κBtkluc.neo consists of three repeats of a sequence containing two consensus NF-κB binding sites (NF-κB binding sites underlined: 5′-AGC TTA CAA GGG ACT

TTC CGC TGG GGA CTT TCCAGG GA-3′) upstream of a luciferase gene, while pGL3.neo.TATA.3κBu contains three copies of the prostaglandin-endoperoxide synthase 2

(PTGS2/COX2) promoter upstream NF-κB site (Bergmann et al., 2000; Holden et al., 2007).

Finally, a cAMP responsive reporter was constructed containing 6 cAMP response elements

(CREs) upstream of a luciferase gene (Catley et al., 2004; Himmler et al., 1993).

In order to construct cell lines stably expressing reporters, A549 or BEAS-2B cells at 60-

70% confluence were transfected in T162 flasks for 6 h, with 8 µg of reporter plasmid DNA mixed with 20 µl of Lipofectamine 2000, in a final volume of 10 ml of the appropriate SFM. The medium was then replaced with serum containing medium supplemented with 0.1-0.4 mg/ml

(dependent on cell line and selection strength) of G418, allowing selection. The resultant cell foci were passaged as normal and allowed to reach confluence, before being suspended in freezing medium (10% DMSO, 90% FCS) and frozen as aliquots.

2.3 Assays

2.3.1 Calcium Assay

Confluent BEAS-2B cells in black walled 96 well plates were loaded for 2 h with Fluo-4

(Life Technologies) at 37oC, according to the manufacturer's guidelines. Using excitation at 494 nm, basal fluorescence (F0) was measured at 516 nm for 1.6 seconds in a plate reader (BMG

Labtech). The thromboxane receptor agonist, U46619, (Cayman) was injected and fluorescence

(F) measured for a further 48.4 seconds. Values were expressed as F/F0, which is a proxy for intracellular calcium concentration.

2.3.2 Immunofluorescence Staining and Confocal Microscopy

Cells plated onto 8 well microscropy slides were treated with glucocorticoid, RU486 or

o LABA and incubated at 37 C in 5% CO2 for between 5 min and 6 h, prior to being placed on ice for harvest. After aspiration of medium, cells were fixed with 4% paraformaldehyde for 15 mins, permeabilized (0.3% Triton-X/HBSS) for 10 min and then blocked overnight with 10% goat serum at 4oC. Slides were incubated with primary antibody (See table A1) for 1 h followed by a further 1 h incubation with Alexa Fluor 488 goat anti-rabbit F(ab’)2 fragment secondary antibody containing 1 µM DAPI. Following removal of the wells from slides, coverslips were mounted using ProLong Gold antifade reagent. Slides were visualised using an Olympus IX81 FV1000 laser scanning confocal microscope with 40X magnification at 405 (blue) and 488 (green) nm.

2.3.3 Cytoplasmic and Nuclear Extract Preparation

2.3.3.1 Preparation of Cytoplasmic Extracts

Cells in 6-well plates were harvested by scraping, transferred into 1.5 ml microcentrifuge tubes and centrifuged at 14,000g for 2 min at 4oC to pellet cells. Cell pellets were resuspended for 15 min in 190 µl of Buffer A (10 mM HEPES pH 7.9, 1.5 mM MgCl2, 10 mM KCl, 0.5 DTT,

0.1% NP-40, 1×protease inhibitors) on ice before centrifugation at 14,000g for 5 min at 4oC to pellet nuclei. The supernatant containing cytoplasm was transferred to fresh 1.5 ml microcentrifuge tubes and frozen at -20oC.

2.3.3.2 Preparation of Nuclear Extracts for Western Blotting

Pelleted nuclei were resuspended for 5 min in 15 µl of Buffer C (20 mM HEPES pH 7.9,

25% glycerol, 0.42 M NaCl, 1.5 mM MgCl2, 0.2 mM EDTA pH 8.0, 0.5 mM PMSF, 0.5 mM

DTT, 1×protease inhibitors). The microcentrifuge tubes were then vigorously scrapped across microcentrifuge racks to break up the nuclei, every 10 min for 40 min. Finally, 30 µl of Buffer D

(20 mM HEPES pH 7.9, 20% glycerol, 50 mM KCl, 0.2 mM EDTA pH 8.0, 0.5 mM PMSF, 0.5 mM DTT) was added and the tubes centrifuged at 14,000g for 10 min. The lysate was aspirated, transferred into fresh 1.5 ml microcentrifuge tubes and frozen at -20oC.

2.3.4 Enzyme-Linked Immunosorbent Assay

Supernatants were collected and frozen at -20oC. Capture antibody was added to treated

96 well enzyme-linked immunosorbent assay (ELISA) plates and incubated overnight, before being aspirated and the plate washed with wash buffer (PBS, 0.1% Tween). Plates were blocked with reagent dilutent (1% BSA in PBS) for 1 h and samples and serially diluted (1:1) standards

61 added in duplicate to wells of the plate. After a 1 h incubation, primary antibody was added and incubated for 2 h. Plates were then incubated with biotinylated dectection antibody for 2 h before addition of streptavidin-HRP. Following a 20 min incubation protected from light, substrate solution was added and plates incubated until they developed color. The reaction was stopped by the addition of 2N H2SO4 and absorbance at 450 nm measured in a plate reader. The standards were curve fitted and a quadratic equation generated, allowing the concentrations of samples to be determined.

2.3.5 Luciferase Assay

Cells in 24 or 48 well plates were harvested by addition of 100 µl of reporter lysis buffer

(Biotium) prior to being frozen at -20oC. Plates were thawed and 25 µl of lysate mixed with 50

µl of luciferase reporter solution, in clear 1.5ml microcentrifuge tubes. Luminescence was measured in a 20/20n luminometer.

2.3.6 Microarray Sample Preparation and Scanning

The concentration and quality (expressed as RNA integrity number) of prepared RNA was determined using RNA 6000 Nano LabChips measured on a 2100 Bioanalyser. Samples were prepared for hybridisation to microarrays using GeneChip 3’ IVT kits (Affymetrix). Poly-A

RNA controls (polyadenyated B. subtilis gene transcripts) were diluted and spiked into ~50 or

100 ng samples of total RNA. First strand buffers were added and samples underwent reverse transcription to synthesize first-strand cDNA using oligo-dT primers with attached T7 promoter sequences, before synthesis of complementary second-strands. This DNA underwent linear amplification for 16 h using T7 RNA polymerase, generating biotinylated amplified RNA

(aRNA). The aRNA was purified using RNA binding metal beads (proprietary coating) with a magnetic plate and 12 µg aliquots of each sample fragmented. Samples were subsequently hybridised to PrimeView microarray chips overnight. The microarray chips were washed and stained in groups of 4 on a GeneChip 450 fluidics station and scanned using a GeneChip 3000 scanner.

2.3.7 MTT Cell Viability Assay

Cell viability was assessed using the tetrazolium dye 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide (MTT) assay, which measures reduction by cellular reducing enzymes, indicating viability of cells (Berridge et al., 2005; Mosmann, 1983). Following aspiration, 200 µl of MTT solution (1 mg/ml in HBSS) was added to each well and the plate incubated at 37oC for 30 min, to allow development of purple (formazan) stain in cells. Wells were aspirated and 200 µl of DMSO added to each well. Optical density was measured at 584 nm using a plate reader.

2.3.8 RNA Isolation, cDNA Generation and Real Time PCR

Total RNA was extracted from cells in 6, 12 or 24-well plates using an RNeasy mini kit, quantified with a NanoDrop and cDNA prepared using a qScript cDNA synthesis kit from 0.5 µg aliquots of RNA, before being diluted 1:4 in PCR quality water. Real-time PCR was performed on a 7900HT instrument with 2.5 µl aliquots of cDNA in a 10 µl reaction volume using SYBR

GreenER chemistry. Amplification conditions of 50ºC: 2 min; 95ºC: 10 min; then 40 cycles of

95ºC: 15 sec; 60ºC: 1 min were used, prior to dissociation (melt curve) analysis to confirm primer specificity. Primers were as detailed in Table A1.

2.3.9 Western Blotting

Cells were lysed in luciferase lysis buffer (supplemented with 1×protease and phosphatase inhibitors) and then diluted in Laemmli buffer or lysed directly in 1×Laemmli buffer

(supplemented with 1×protease and phosphatase inhibitors) and frozen at -20oC. After transfer to

1.5 ml microcentrifuge tubes, samples were heated to ~95oC for 5-10 min and sonicated for 30-

60 min at 4oC. Cell lysates were size fractionated by gel electrophoresis on either 12% tris- glycine SDS-polyacrylamide gels or on NuPage 4-12% Bis-Tris gels, before transfer to Hybond-

ECL membranes. After Ponceau staining (5% acetic acid with 1 g/l Ponceau S), membranes were blocked in 5% milk, before being probed with primary antibodies (See table A2). Following incubation with horseradish peroxidise-conjugated anti-rabbit, anti-goat or anti-mouse immunoglobulins, immune complexes were detected using Pierce enhanced chemiluminescent western blotting substrate with Fuji x-ray film and developed on a Kodak Xomat developer.

2.4 Data Analysis and Statistics

2.4.1 Densitometry of Western Blots

Films were scanned at a resolution of ≥300 dpi and saved as TIFF files, before being analysed using 1D gel analysis. Lanes were detected, the baseline corrected by “Rolling Ball” subtraction, bands detected and a value for band volume determined. Band volumes for the protein of interest were normalised to GAPDH and expressed as fold or as a percentage of a treatment.

2.4.2 Analysis of RT-PCR Data

Exported .sds files were analysed using SDS 2.4 (Life Technologies) by setting the threshold on a ΔRn/Cycle plot to a midpoint on the exponential portion of the curve. Relative cDNA concentrations were obtained from a standard curve of log or half log serial dilutions prepared from control samples and analysed at the same time as experimental samples. The mean quantity was determined from duplicates of each sample for each gene of interest, normalised to

GAPDH and expressed as fold or a percentage of a treatment.

2.4.3 Microarray Analysis

Partek Genomics Suite was used to analyse .CEL microarray files. Background was corrected by robust multi-array averaging (RMA) using quantile normalization and probesets log

2 transformed and median polished (Bolstad et al., 2003; Irizarry et al., 2003). Probeset analysis was performed by 1 way analysis of variance (ANOVA) with discrimination by Fisher’s least significant difference using a false discovery rate, with step up, of <0.05 and fold changes of ≥2 or ≤0.5 fold (Curran-Everett, 2000; Eisenhart, 1947). Subsequent merging of probes based on gene names and identification of genes showing substantial fold changes were performed using custom Python scripts, as indicated in figure legends.

2.4.4 Confocal Microscopy Image Analysis

Exported .oif files were analysed using Volocity software and Pearson product-moment correlation coefficient used to enumerate the colocalization between the green (GR) and blue

(DAPI) image channels.

2.4.5 Statistics

Statistical analysis was performed in GraphPad Prism v5.01 (GraphPad Software, La

Jolla, CA, USA) using either paired Student's t-tests or repeated measures one-way or two-way

ANOVA with Bonferroni’s correction for multiple analyses or Dunnett’s test, as appropriate.

Group means were assumed to be significantly different where: P < 0.05 (*), P < 0.01 (**) or P

< 0.001 (***).

Chapter Three: Pro-Inflammatory Stimuli Reduce Glucocorticoid-Induced 2×GRE Reporter Activation and Gene Expression

Material included in this chapter has been published as:

Rider, C.F., King, E.M., Holden, N.S., Giembycz, M.A., and Newton, R. (2011). Inflammatory stimuli inhibit glucocorticoid-dependent transactivation in human pulmonary epithelial cells: rescue by long-acting beta2-adrenoceptor agonists. J. Pharmacol. Exp. Ther. 338, 860–869. Drs.

Neil S. Holden, Joanna E. Chivers and Robert Newton performed some of the experiments detailed in this chapter, as specifically noted in individual figure legends.

3.1 Rationale

The dominant feature of asthma is chronic lung inflammation resulting from increased expression and release of inflammatory mediators (Bousquet et al., 2000; Murdoch and Lloyd,

2010). Glucocorticoids are prescribed for all, but the mildest, asthmatics, to reduce lung inflammation by decreasing inflammatory gene expression (Barnes, 2006b; Newton, 2000;

Vandevyver et al., 2013). Although dogma states that transrepression decreases inflammation, through direct inhibition of NF-κB and AP-1, while transactivation mediates side effects (Barnes and Adcock, 2003), there is increasing evidence that the transcription of anti-inflammatory genes by glucocorticoids is critical for glucocorticoid activity (King et al., 2013; Newton, 2014;

Vandevyver et al., 2013).

Lung inflammation correlates with asthma severity, is often variable and increases during periodic exacerbations (Chang et al., 2002; Hastie et al., 2010; Louis et al., 2000; Suzuki et al.,

2008). Likewise, inflammation increases with asthma severity and in asthmatics who smoke

(Barnes, 2010; Braganza et al., 2008; Chaudhuri et al., 2003; Jayaram et al., 2006; Thomson et al., 2013). Reduced responses to glucocorticoids are often encountered during exacerbations and in those who smoke or have severe, often neutrophilic, asthma, suggesting that inflammation decreases glucocorticoid activity (Gibson et al., 2001; Green et al., 2002; Grünberg et al., 2001;

Livingston et al., 2005; Papi et al., 2013).

3.2 Hypothesis

The overall hypothesis tested in this chapter is that inflammatory mediators reduce glucocorticoid-dependent transcriptional activity leading to decreased expression of anti- inflammatory genes i.e. glucocorticoid hyporesponsiveness. Glucocorticoid-inducible gene expression was modeled using a 2×GRE reporter and directly tested by RT-PCR and microarray analysis of gene expression.

3.3 Results

3.3.1 Effects of the Pro-Inflammatory Cytokines TNF and IL1B on Dexamethasone-Induced 2×GRE Reporter Activation

Bronchial epithelial, BEAS-2B, cells stably transfected with a 2×GRE reporter (BEAS-

2B 2×GRE cells) were treated with a maximally effective concentration of TNF (10 ng/ml), added up to 18 h before and 2 h after 1 μM dexamethasone addition (Figure 3.1A). TNF pre- treatment for 0 - 2 h significantly decreased dexamethasone-induced 2×GRE reporter activation, with maximal repression of ~46% produced at 1 h. However, no significant effect on 2×GRE activation was induced by longer, 6 or 18 h, TNF incubations. This effect was dependent on concentration, as TNF induced a concentration-dependent decrease in reporter activation with an

EC50 of ~1.25 ng/ml, with significant repression occurring at concentrations as low as 0.1 pg/ml

(Figure 3.1B).

Figure 3.1 Effects of the Cytokines TNF and IL1B on 2×GRE-Reporter Activation. A) BEAS-2B 2×GRE cells were treated with TNF (10 ng/ml) for up to 18 h before and 2 h after the addition of dexamethasone (Dex; 1 μM) (time = 0), as indicated in the left panel. Cells were harvested 6 h after the addition of Dex for luciferase assay. B) BEAS-2B 2×GRE or C) A549 2×GRE cells were either not stimulated (NS) or were pre-treated with the indicated concentrations of TNF for 1 h before the addition of Dex (1 μM) and harvested after 6 h for luciferase assay. D) A549 cells were NS or were pre-treated with the indicated concentrations of IL1B for 1 h before addition of Dex (1 μM). Cells were harvested 6 h later for luciferase assay. Data (n = 6, 4, 6, 4 respectively), expressed as fold activation are plotted as means ± S.E. Statistical analyses, versus the Dex control, were performed by ANOVA with a Dunnett's test. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2011).

Pulmonary A549 2×GRE cells were pre-treated for 1 h with 0.1 pg/ml to 100 ng/ml of

TNF, to evaluate whether the response to TNF was specific to BEAS-2B cells (Figure 3.1C).

Increasing concentrations of TNF decreased dexamethasone-induced reporter activation by 40% from 15 to 9 fold, with an EC50 of ~0.3 ng/ml. Pre-treatment with IL1B likewise reduced reporter activation induced by dexamethasone from 17.4 to 9.5 fold, with an EC50 of ~0.1 ng/ml (Figure

3.1D). Thus, TNF and IL1B reduce 2×GRE reporter responses to dexamethasone in airway epithelial cell lines.

To determine whether the effects of TNF were specific to the 2×GRE reporter, two constitutively driven reporter systems were utilized, one containing the weak TATA promoter and a second the strong SV40 promoter (Figure 3.2). Treatment of BEAS-2B TATA and SV40 reporter cells with TNF for 7 h had no significant effect on reporter activation, suggesting that the effects of TNF may be specific to the 2×GRE reporter system.

Figure 3.2 Effects of TNF on Constitutive TATA and SV40 Luciferase Reporters in BEAS-2B Cells. BEAS-2B cells stability transfected with luciferase reporters driven by constitutive weak TATA and strong SV40 promoters, were either not stimulated (NS) or were treated for 7 h with the indicated concentrations of TNF before harvest for luciferase assay. Data (n = 4, 5 respectively), expressed as fold activation are plotted as means ± S.E.

3.3.2 Effects of Fetal Calf Serum on Dexamethasone-Induced 2×GRE Reporter Activation

Serum is an established mitogen and contains a mixture of growth factors, hormones and cytokines, which may activate various signaling cascades (Dang and Lowik, 2005; Xia et al.,

2000; Yujiri et al., 1998). BEAS-2B 2×GRE cells were treated with 10% FCS for up to 18 h before and 2 h after the addition of dexamethasone (Figure 3.3A). FCS reduced dexamethasone- induced reporter activation following pre-treatments of 18, 2 or 1 h. However, there was no significant effect of 6 h pre-treatment and FCS enhanced 2×GRE reporter activation when added simultaneously with, or 1 h after, dexamethasone. The effects of FCS were concentration- dependent, as increasing concentrations from 0.1 to 30% reduced dexamethasone-induced reporter activation from ~8 to 2 fold, with an EC50 of ~2% (Figure 3.3B). Similar outcomes were produced in A549 2×GRE cells, with activation reduced from ~14 to 6 fold (Figure 3.3C). These results demonstrate that FCS time- and concentration-dependently reduced 2×GRE activation.

To examine the possibility of combinatorial effects between TNF and FCS, BEAS-2B

2×GRE cells were pre-treated for 1 h with various concentrations of TNF, in the presence or absence of 10% FCS, before the addition of dexamethasone (Figure 3.3D). TNF concentration- dependently reduced reporter activation by >55% from ~6.5 to 2.8 fold, while 10% FCS reduced reporter activation by ~40%. In the presence of increasing concentrations of TNF, FCS decreased reporter activation to a level similar to that seen with the maximally effective concentration of

TNF, suggesting that FCS and TNF may act through a shared mechanism.

Figure 3.3 Effects of Fetal Calf Serum on Dexamethasone-Induced 2×GRE Reporter Activation. A) BEAS-2B 2×GRE cells were treated with 10% fetal calf serum (FCS) for up to 18 h before and 2 h after the addition of dexamethasone (Dex; 1 μM). B) BEAS-2B 2×GRE cells or C) A549 2×GRE cells were either not stimulated (NS) or pre-treated for 1 h with 0.1 - 30% FCS, before the addition of 1 μM Dex. D) BEAS-2B 2×GRE cells were NS or were pre- treated for 1 h with 10% FCS and/or the indicated concentrations of TNF before addition of Dex (1 μM). Data (n = 8, 6, 6, 8 respectively), expressed as fold activation are plotted as means ± S.E. A-C) Statistical analyses, versus the Dex control, were performed by ANOVA with a Dunnett's test. D) Statistical analyses were performed by paired t-tests, with comparisons made for each concentration of TNF in the presence or absence of FCS. ** P < 0.01, *** P < 0.001. Includes experiments performed by Dr. Robert Newton (Rider et al., 2011).

3.3.3 Effect of Glucocorticoid Concentration on the Repression of 2×GRE-Reporter Activation by TNF, IL1B or FCS

A549 2×GRE cells were pre-incubated for 1 h with maximally effective concentrations of

TNF, IL1B or FCS, before the addition of various concentrations of dexamethasone (Figure 3.4).

Figure 3.4 Effects of TNF, IL1B and FCS on Dexamethasone-Induced 2×GRE Reporter Activation. A549 2×GRE cells were either NS or were pre-treated for 1 h with TNF (10 ng/ml), IL1B (1 ng/ml) or 10% FCS, before addition of the indicated concentrations of dexamethasone (Dex). Cells were harvested 6 h after Dex addition for luciferase assay. Data (n = 6-8), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by paired t-tests between each concentration of Dex with comparisons made between reporter activation in the presence or absence of TNF or FCS. Reporter activation induced by >10 nM of Dex was significantly repressed, to at least P < 0.05, following TNF, FCS or IL1B treatment. Includes experiments performed by Dr. Robert Newton (Rider et al., 2011).

Pre-treatment with each stimuli reduced dexamethasone-induced reporter activation, by 36, 35 and 55% respectively, irrespective of the concentration of dexamethasone used. TNF and FCS treatment modestly, but significantly, increased the EC50 for dexamethasone, while IL1B had no significant effect (Table 3.1). However, the changes in EC50 were very small and therefore, despite being significant, may not be biologically meaningful.

Table 3.1. Effects of TNF, IL1B and FCS on the Sensitivity of Glucocorticoid-Induced 2×GRE Reporter Activation.

Data was taken from figures 3.4 and 3.9 and concentration-response curves individually analyzed. EC50 values were calculated and mean ± SE derived for each glucocorticoid in the absence or presence of 10 ng/ml TNF, 10% FCS or 1 ng/ml IL1B. Significance between means was tested by paired t-tests. * P < 0.05, ** < 0.01 (Rider et al., 2011).

3.3.4 Effects of Epidermal Growth Factor on 2×GRE Reporter Activation

It was hypothesized that the presence of growth factors, such as epidermal growth factor

(EGF), may contribute to the decrease in 2×GRE reporter activation induced by FCS (van der

Valk et al., 2010; Zheng et al., 2006). Therefore, BEAS-2B cells were pretreated with various concentrations of epidermal growth factor (EGF), which acts on the receptor tyrosine kinase

EGFR, for 1 h, prior to addition of dexamethasone. However, EGF had no significant effect on dexamethasone-induced reporter activation at any concentration tested (Figure 3.5A), despite increasing JNK MAPK phosphorylation after 15 min (Figure 3.5 B).

Figure 3.5 Effects of Epidermal Growth Factor on 2×GRE Reporter Activation and Phosphorylation of c-Jun N-Terminal Kinase. A) BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with the indicated concentrations of epidermal growth factor (EGF) before addition of 1 μM dexamethasone (Dex). Cells were harvested 6 h later for luciferase assay. Data (n = 8), expressed as fold activation, are plotted as means ± S.E. B) BEAS-2B 2×GRE cells were treated with TNF (10 ng/ml), 10% FCS or the indicated concentrations of EGF. After 15 min, cells were harvested for western blotting and probed for phospho-JNK and GAPDH. Blots representative of 4 such experiments are shown (Rider et al., 2011).

3.3.5 Effects of Agonists of Gq-Linked G Protein-Coupled Receptors and Activation of Protein Kinase C on Dexamethasone-Induced 2×GRE Reporter Activation

Many of the principal mediators in asthma, including leukotrienes, histamine and prostanoids (e.g. thromboxane A2), activate Gq-linked GPCRs, increasing the intracellular free

2+ calcium concentration ([Ca ]i) and often inducing smooth muscle contraction (Barnes et al.,

1998). As thromboxane A2 is very unstable (Hamberg et al., 1975), BEAS-2B were treated with various concentrations of the stable synthetic thromboxane receptor agonist, U46619, and effects on intracellular calcium release detected using Fluo4. At 0.3 and 1 μM, U46619 induced substantial, but transient, increases in calcium release as monitored by fluorescence (F/F0), while

0.1 μM induced only modest effects (Figure 3.6A). Nevertheless, pre-treatment with 1 μM

U46619 for 1 h had no effect on dexamethasone-induced reporter activation in BEAS-2B

2×GRE cells (Figure 3.6B). However, pre-treatment for 2 - 18 h with U46619 significantly decreased dexamethasone-induced 2×GRE reporter activation (Figure 3.6C). A second GPCR agonist, carbachol, which activates muscarinic receptors, including the Gq-linked M3 receptor, also concentration-dependently induced calcium release (Figure 3.6D), but had no significant effect on dexamethasone-induced 2×GRE activation at any time tested (Figure 3.6E).

BEAS-2B 2×GRE cells were also pre-treated for 0 – 2 h with 100 nM of phorbol 12- myristate 13-acetate (PMA), a diacylglyerol (DAG) mimetic that directly activates PKC

(Castagna et al., 1982), before addition of 1 μM dexamethasone (Figure 3.7A). PMA pre- treatment for 1 or 2 h significantly reduced dexamethasone-induced reporter activation with an

EC50 of ~70 nM (Figure 3.7B).

Figure 3.6 Effects of the Gq-Linked GPCR Agonists Carbachol and U46619 on Dexamethasone-Induced 2×GRE Reporter Activation. A) BEAS-2B cells were loaded with Fluo-4 dye for 2 h at 37oC and transferred to a plate reader. Baseline fluorescence (F0) was measured for 1.6 s before injection of U46619 to the indicated concentration and fluorescence (F) measured for a further 48.4 s. Data (representative of 3 experiments), are shown as a trace of F/F0, a proxy for intracellular 2+ calcium concentration [Ca ]i. B) BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated with the indicated concentrations of U46619 for 1 h prior to the addition of 1 μM dexamethasone (Dex). C) BEAS-2B 2×GRE cells were treated with U46619 for up to 18 h before and 2 h after the addition of 1 μM Dex. Data (n = 6, 6 respectively), expressed as fold activation, are plotted as mean ± S.E. D) BEAS-2B cells were prepared as in A, carbachol injected to the indicated concentrations and fluorescence measured. Data (representative of 4 experiments), is shown as a trace of F/F0. E) BEAS-2B 2×GRE cells were treated with carbachol (100 μM) for up to 18 h before and 2 h after addition of 1 μM Dex. Data (n = 4-6), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnett's test relative to the Dex control. ** P < 0.01, *** P < 0.001. Calcium assays were performed by Dr. Neil S. Holden (Rider et al., 2011).

A 8 B 10 NS Dex 6 8

*** *** 6

4 *** (Fold) (Fold) 4 *** ***

GRE activityGRE *** 

2xGRE activity 2xGRE 2 2 2

0 0 Dex - - + + + + + -10 -9 -8 -7 -6 PMA addition (h) 0 -2 -1 1 0 NS Dex 2 log [PMA (M)]

Figure 3.7 Effects of PKC Activation by Phorbol 12-Myristate 13-Acetate on Dexamethasone-Induced 2×GRE Reporter Activation. A) BEAS-2B 2×GRE cells were pre-treated with phorbol 12-myristate 13-acetate (PMA) (100 nM) for between 2 and 0 h, prior to addition of dexamethasone (Dex; 1 μM). B) BEAS- 2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with 100 nM PMA prior to the addition of Dex (1 μM). Cells were harvested 6 h after Dex addition for luciferase assay. Data (n = 10, 6 respectively), expressed as fold activation, are plotted as mean ± S.E. Statistical analyses were performed by ANOVA with a Dunnett's test relative to the Dex control. *** P < 0.001 (Rider et al., 2011).

3.3.6 Effects of Cigarette Smoke Extract and Hydrogen Peroxide on 2×GRE Reporter Activation

Cigarette smoking is associated with decreased anti-inflammatory responses to glucocorticoids in asthmatics (Chalmers et al., 2002; Chaudhuri et al., 2003; Pedersen et al.,

1996, 2007; Spears et al., 2013; Tomlinson et al., 2005). BEAS-2B and A549 2×GRE cells were therefore exposed to medium containing cigarette smoke extract (CSE) for 1 h before the addition of dexamethasone. CSE concentration-dependently reduced dexamethasone-induced

2×GRE activation in both cell types (Figure 3.8). However, the highest concentration of CSE (1

OD320) significantly decreased BEAS-2B cell viability (Figure 3.8A bottom panel), while both 1 and 0.3 OD320 decreased viability in A549 cells. Nevertheless, in both cell lines, dexamethasone-

78 induced 2×GRE activation was reduced at concentrations of CSE that did not decrease cell viability. Thus cigarette smoke can decrease glucocorticoid responsiveness independently of any effects on cell viability. In contrast, treatment of BEAS-2B 2×GRE cells with hydrogen peroxide

(H2O2) repressed 2×GRE reporter activity in parallel with reduced cell viability, suggesting that decreased reporter activation was predominantly due to cell death (Figure 3.8C).

Figure 3.8 Effects of Cigarette Smoke Extract and Hydrogen Peroxide on Dexamethasone-Induced 2×GRE Reporter Activation. A) BEAS-2B or B) A549 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with the indicated concentrations of cigarette smoke extract (CSE) (expressed as OD320), before the addition of dexamethasone (Dex; 1 μM). C) BEAS-2B 2×GRE cells were either NS or were pre-treated for 1 h with the indicated concentrations of H2O2, before addition of 1 μM Dex. Cells were harvested 6 h after Dex addition for either luciferase assay (top panels) or MTT viability assay on log, but not half log, values (bottom panels). Data (n = 10, 7, 9 (top panels) and n = 5, 7, 5 (bottom panels) respectively) expressed as fold (top panels) or as OD584 (bottom panels), are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnett's test relative to Dex (top panels) or untreated/Dex controls (bottom panels). * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2011).

3.3.7 Effect of TNF and FCS on 2×GRE Reporter Activation Induced by the Glucocorticoids Dexamethasone, Fluticasone Propionate and Budesonide

BEAS-2B 2×GRE cells were pre-treated with TNF or FCS for 1 h prior to the addition of the clinically relevant glucocorticoids, budesonide and fluticasone propionate, as well as dexamethasone (Fig 3.9). TNF and FCS induced a 40 - 60% repression of the maximal 2×GRE activation induced by all three glucocorticoids, without significantly altering the EC50 for each glucocorticoid (see table 3.1).

8 NS 150 NS 150 NS 6 TNF TNF TNF

100 100

M Dex) M Dex) M 

4 

(Fold)

GRE GRE activity GRE activity

GRE GRE activity

 

 50 50

2 2

(% of 1 (% of 1

0 0 0 -10 -9 -8 -7 -6 -5 -10 -9 -8 -7 -6 -10 -9 -8 -7 -6 NS NS NS TNF log [Dex (M)] TNF log [Bud (M)] Dex TNF log [FP (M)] Dex

10 150 150 NS NS NS 8 FCS FCS FCS 100 100

M Dex) M

 

(Fold) 4

GRE GRE activity GRE GRE activity

GRE GRE activity 50 50



 

2 2 (% of 1 2 (% of 1

0 0 0 -10 -9 -8 -7 -6 -5 -10 -9 -8 -7 -6 -10 -9 -8 -7 -6 NS NS Dex NS FCS log [Dex (M)] FCS log [Bud (M)] FCS log [FP (M)] Dex

Figure 3.9 Repression of 2×GRE Reporter Activation by TNF or FCS is Not Dependent on the Glucocorticoid Used. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with TNF (10 ng/ml) or 10% FCS, prior to the addition of the indicated concentrations of the glucocorticoids dexamethasone (Dex), budesonide (Bud) or fluticasone propionate (FP). Cells were harvested 6 h after glucocorticoid addition for luciferase assay. Data (n = 4-8) expressed as either fold or a percentage of Dex treatment, are plotted as means ± S.E. Statistical analyses were performed by paired t-tests on each concentration of glucocorticoid with comparisons made between reporter activation in the presence and absence of TNF or FCS. Reporter activation induced by ≥10 nM of each glucocorticoid was significantly repressed, to at least P < 0.05, following TNF or FCS treatment (asterisks not shown) (Rider et al., 2011).

3.3.8 Effects of Pro-Inflammatory Stimuli on Dexamethasone-Induced Gene Expression

To determine whether treatment with a pro-inflammatory stimulus reduced bone fide glucocorticoid-inducible gene expression, the effect of TNF or IL1B on dexamethasone induced gene expression was evaluated in BEAS-2B, HBE and ASM cells (Figure 3.10). In BEAS-2B cells, TNF significantly reduced dexamethasone-induced CDKN1C mRNA expression by 62%, but had no effect on DUSP1 and RGS2 expression. Dexamethasone induced a 74 fold increase in

TSC22D3 mRNA expression, which was significantly repressed to 48 fold by TNF (Figure

3.10A). Dexamethasone also enhanced DUSP1 expression in HBE cells, but this was unaffected by IL1B or TNF treatment. However, both TNF and IL1B decreased dexamethasone-induced

RGS2 expression at 1 and 2 h, while TNF also significantly repressed expression at 6 h. Both

TNF and IL1B decreased dexamethasone-induced TSC22D3 expression at 1, 6 and 18 h, but not

2 h, with maximal repression of 60 and 62% occurring at 1 and 18 h for TNF and IL1B respectively (Figure 3.10B). Expression of CDKN1C was not materially increased by dexamethasone in HBE cells (data not shown). As in BEAS-2B and HBE cells, TNF and IL1B treatment had no effect on dexamethasone-induced DUSP1 expression in ASM cells. TSC22D3 expression was significantly enhanced by dexamethasone and decreased by TNF or IL1B pre- treatment at both 2 and 6 h (Figure 3.10C). CDKN1C and RGS2 were not substantially glucocorticoid-inducible in ASM cells (data not shown). Thus, pro-inflammatory cytokines repress gene expression in a time-dependent manner in multiple cell types relevant to asthma pathogenesis.

Figure 3.10 Effects of TNF on Dexamethasone-Induced TSC22D3 Expression in BEAS- 2B, Human Bronchial Epithelial and Airway Smooth Muscle Cells. A) BEAS-2B, human bronchial epithelial and airway smooth muscle cells were either not stimulated (NS) or were pre-treated with 10 ng/ml of tumor necrosis factor (TNF) for 1 h prior to addition of 1 μM dexamethasone (Dex). Cells were harvested 6 h after Dex addition. B) Primary human bronchial epithelial (HBE) cells were pre-treated for 1 h with 10 ng/ml of TNF or 1 ng/ml of interleukin 1β (IL1B), before addition of 1 μM dexamethasone (Dex). Cells were harvested at 1, 2, 6 and 18 h after Dex addition. C) Airway smooth muscle (ASM) cells were pre-treated for 1 h with 10 ng/ml of TNF or 1 ng/ml of IL1B, before addition of 1 μM Dex. Cells were harvested at 2 and 6 h after Dex addition. Total RNA was extracted, reverse transcribed to cDNA and RT-PCR performed for: regulator of G-protein signaling 2 (RGS2), TSC22 domain family member 3 (TSC22D3; GILZ), dual specificity phosphatase 1 (DUSP1; MKP1) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Data (n = 4-5), normalized to GAPDH, are expressed as fold and plotted as means ± S.E. Significance was tested using repeated measures, one-way analysis of variance (ANOVA) with Bonferroni’s 81 correction for multiple comparisons. *, P <0.05; **, P <0.01; ***, P <0.001.

Data from a previously conducted microarray study were re-examined to determine the effects of IL1B on dexamethasone-induced gene expression (Joanna Elizabeth Chivers, 2005). In this study, A549 cells were pre-treated with IL1B for 2 h, before addition of dexamethasone for either 2 or 4 h. Total RNA was extracted and analyzed using Affymetrix microarrays. The 86 and

221 genes induced by ≥2 fold by dexamethasone at 2 and 4 h, respectively were selected and fold inductions by dexamethasone normalized to 1, allowing the relative effect of dexamethasone plus IL1B to be evaluated (Figure 3.11). IL1B pre-treatment time-dependently decreased the expression of a majority of dexamethasone-inducible genes (Figure 3.11A). To determine the percentage of dexamethasone-induced genes whose expression was enhanced, unchanged or repressed by IL1B pre-treatment, a cut-off representing no significant effect of IL1B treatment relative to dexamethasone of 1.25 to 0.75 fold was chosen. This enabled separation of genes into three groups, based on the effect of IL1B pre-treatment on dexamethasone-induced expression at each time point; 1) genes with enhanced expression, 2) genes whose expression was unchanged and 3) genes whose expression was decreased (Figure 3.11B). While the expression of just over a quarter of genes was unchanged (1.25 - 0.75 fold) by dexamethasone plus IL1B treatment, relative to dexamethasone alone at each time point, the expression of 16% and 5% of genes was enhanced at 2 and 4 h respectively (Figure 3.11B). However, the vast majority of genes were repressed with 58% and 67%, at 2 and 4 h respectively, showing a decrease in expression relative to dexamethasone alone. A total of 31 genes were induced by greater than 2 fold by dexamethasone at both 2 and 4 h (Figure 3.11C).

Figure 3.11 Effects of IL1B on Dexamethasone-Induced Gene Expression. A549 cells were either not stimulated (NS) or were pre-treated for 2 h with IL1B (1 ng/ml) before addition of 1 μM dexamethasone (Dex). Total RNA (n = 3) was extracted and subjected to microarray analysis on U95 Av2 and B Affymetrix chips. After data normalization, probe sets corresponding to the same gene were merged and then ranked by fold induction following Dex treatment. A) All genes induced by ≥2 fold by Dex at 2 or 4 h were plotted according to induction by Dex+IL1B (red lines), as a percentage of Dex treatment (green line), on a log scale. B) Genes were separated into three groups according to fold induction by Dex+IL1B at each time point and are plotted as fold of Dex treatment. C) Genes induced by Dex at both 2 and 4 h are plotted as a percentage of Dex treatment, on a log scale. Samples were prepared by Dr. Joanna A. Chivers and the microarray performed by Aventis Pharmaceuticals.

While a few genes showed a time-dependent increase in expression following Dex+IL1B treatment, the majority underwent greater repression relative to dexamethasone at 4 h. Thus a majority of glucocorticoid-inducible genes are repressed by pre-treatment with a pro- inflammatory cytokine.

3.4 Discussion

The above data indicate that the ability of glucocorticoids to induce 2×GRE reporter activation can be attenuated by prior or simultaneous addition of various pro-inflammatory stimuli. For example, both TNF and IL1B pre-treatment concentration and time-dependently reduced dexamethasone-induced reporter activation. This demonstrates that cytokines, including

IL1B and TNF, which are potentially relevant to severe asthma pathogenesis (Berry et al., 2007,

2006; Sousa et al., 1996; Ying et al., 1991), can induce glucocorticoid hyporesponsiveness.

These findings are consistent with studies in which inflammatory cytokines, including IL2, IL4,

IL1A, IL1B, IL17, IFN-γ and CSF2, either alone or in combination, also decreased glucocorticoid activity (Goleva et al., 2002; Kam et al., 1993; Pariante et al., 1999; Raddatz et al., 2001; Sher et al., 1994; Tliba et al., 2008; Wang et al., 2004b). This may, in part, explain the increase in glucocorticoid resistance found in severe asthma (Durham et al., 2011; Peters et al.,

2006).

Similarly, FCS induced a time-dependent decrease in 2×GRE reporter activation (Figure

3.3). However, unlike TNF, which only reduced reporter activation following -2 - 0 h pre- treatment, the response to FCS appeared biphasic, with repression induced by 1, 2 and 18 h of pre-treatment, but not by 6 h. Conversely, FCS enhanced GRE reporter activation when added either 1 h after or simultaneously with dexamethasone. As FCS constitutes a complex mixture of

85 compounds, it is possible that individual components may elicit effects at different times

(Lagarde et al., 1984; Marazzi et al., 2011; van der Valk et al., 2010; Zheng et al., 2006).

Surprisingly, addition of FCS either simultaneously or 1 h after dexamethasone treatment enhanced 2×GRE reporter activity. While the mechanism underlying this effect is unclear, FCS may contain a compound that, like a LABA, increases cAMP and thereby enhances 2×GRE reporter activity (see Chapter 6) (Kaur et al., 2008).

Likewise, understanding the effect of CSE may be complex, as cigarette smoke contains over 4000 components (Hoffmann et al., 1997). However, unlike hydrogen peroxide, CSE did not simply decrease cell viability, demonstrating that CSE contains chemicals that induce glucocorticoid hyporesponsiveness (Figure 3.8). These results may, in part, explain the decreased glucocorticoid activity found in many asthmatics who smoke and in individuals with COPD

(Braganza et al., 2008; Cameron et al., 2010; Thomson et al., 2013). However, responses to glucocorticoids may also be reduced through other mechanisms, such as enhanced production of inflammatory cytokines (Spears et al., 2013). Additionally, there may be chronic effects of cigarette smoking on responses to glucocorticoids, which were not examined in the acute experiments performed in this chapter.

Differences in 2×GRE repression were found between U46619, a thromboxane A2 (TP) receptor agonist, and the non-selective acetylcholine receptor agonist carbachol, despite a shared ability to enhance calcium release (Figure 3.5A and D). This may reflect differences in downstream signaling, as U46619 predominantly activates Gq signaling and may therefore repress 2×GRE reporter induction through activation of PKC (Alexander et al., 2011; Shenker et al., 1991). However, carbachol can also act on receptors that couple to Gi (Alexander et al.,

2011) and may also stimulate cAMP production through Gs-coupling (Michal et al., 2007).

Likewise, while PMA and FCS decreased 2×GRE reporter activation (Figures 3.7 and 3.3), EGF had no effect, reflecting differences in signaling pathways. For example, PMA and serum, but not EGF, have been shown to activate ERK MAPK, through a scaffold protein, mitogen- activated protein kinase organizer 1 (Vomastek et al., 2004).

TNF pre-treatment reduced 2×GRE reporter activation induced by two clinically relevant glucocorticoids budesonide and formoterol, as well as dexamethasone, suggesting that such repression is a class-specific effect common to all glucocorticoids. TSC22D3, a gene with putative anti-inflammatory properties, was significantly induced by 6 h of dexamethasone treatment, but TNF pre-treatment decreased expression in BEAS-2B, HBE and ASM cells

(Figure 3.10) (Eddleston et al., 2007). Dexamethasone-induced TSC22D3 expression was also reduced at 2 h following IL1B+dexamethasone treatment (60% of dexamethasone treatment alone) in a microarray performed on A549 cells (Figure 3.11, top panel, group 3). Likewise, the majority of dexamethasone-induced genes were repressed following IL1B pre-treatment, demonstrating that the effects of this pro-inflammatory cytokine were widespread (Figure 3.11).

This is supported by a microarray study demonstrating that simultaneous treatment with TNF and dexamethasone repressed a majority of genes (Lannan et al., 2012). However, the relative time of addition of glucocorticoid and TNF may substantially affect gene expression (Lannan et al., 2012; Rao et al., 2011).

Although the molecular pathways that induce glucocorticoid hyporesponsiveness remain to be determined, cytokines have been shown to decrease glucocorticoid activity through a number of mechanisms, including reducing GR translocation, transactivation and binding affinity

(Barnes, 2010; Biola et al., 2001; Pariante et al., 1999). Furthermore, IL1B treatment of intestinal epithelial cell lines and IL1A pre-treatment in mouse fibroblasts or L929 cells has been shown to

87 decrease GR translocation and/or GRE reporter activation (Pariante et al., 1999; Raddatz et al.,

2001; Wang et al., 2004c). Furthermore, a combination of TNF and IFN-γ reduces glucocorticoid-inducible reporter activation in airway smooth muscle cells (Tliba et al., 2008).

These results demonstrate that numerous cytokines reduce glucocorticoid responsiveness and therefore approaches to reverse cytokine-induced glucocorticoid hyporesponsiveness are urgently needed. Chapter 5 therefore investigates strategies to overcome TNF-induced glucocorticoid resistance.

Chapter Four: Rhinovirus and Poly(I:C) Modulate Glucocorticoid-Dependent and Other Transcriptional Responses

Much of the material in this chapter was published as:

Rider, C.F., Miller-Larsson, A., Proud, D., Giembycz, M.A., and Newton R. (2013). Modulation of transcriptional responses by poly(I:C) and human rhinovirus: Effects of long-acting β2- adrenoceptor agonists. Eur. J. Pharmacol. 708, 60-67.

4.1 Rationale

Asthma exacerbations are debilitating, expensive to treat and sometimes fatal (Borderías

Clau et al., 2005; Krishnan et al., 2006; Lane et al., 2006). Although exacerbations can be precipitated by allergen exposure, environmental pollution or certain medications, the most common cause is viral infection of the airways (Dales et al., 1996; Johnston et al., 1995, 1996;

Kistler et al., 2007; Nicholson et al., 1993; Teichtahl et al., 1997; Wark and Gibson, 2006). In this respect, human rhinovirus (HRV) is the predominant respiratory virus detected during exacerbations of asthma (Corne et al., 2002; Johnston et al., 1995; Proud, 2011; Venarske et al.,

2006). Indeed, HRV infections underlie the ‘September epidemic’ of asthma exacerbations, as measured by visits to emergency departments or hospitalization (Dales et al., 1996; Johnston et al., 2005, 2006, 1996; Teichtahl et al., 1997). The return to school enhances HRV transmission, leading to a greater number of asthma exacerbations in juvenile asthmatics. Adult asthma exacerbations subsequently peak a few weeks later, as infected children transmit HRV to their parents and other adults (Johnston et al., 2006, 1996).

HRV is a member of the genus Enterovirus in the Picornaviridae family and frequently infects individuals causing a common cold (Fields et al., 2007; Palmenberg et al., 2010; Proud,

2011). HRV is small, with a protein capsid diameter of ~27 nm and has a positive-sense single- stranded RNA genome of ~7.2kb. Over 100 strains of HRV have been classified using genetic sequence homology into three clades known as HRV A, B and the recently discovered, HRV C

(Fields et al., 2007; Palmenberg et al., 2010; Proud, 2011). The majority of HRV clade A and all of B use intercellular adhesion molecule-1 (ICAM1) to gain cellular entry, while the remaining members of clade A use the low density lipoprotein receptor (Proud, 2011). The receptor for

HRV clade C is yet to be identified.

Binding to ICAM1, in rhinoviruses that use this receptor, results in association with ezrin

(EZR) and spleen tyrosine kinase (SYK) and also induces endocytosis allowing rhinovirus to enter the cell (Fields et al., 2007; Lau et al., 2008; Wang et al., 2006b). SYK association may also activate the p38 MAPK and PI3K pathways enhancing CXCL8 production (Lau et al., 2008;

Wang et al., 2006b). In the cell cytoplasm, the RNA genome is translated as a single entity by host ribosomes and then cleaved generating viral proteins (Fields et al., 2007; Palmenberg et al.,

2010). This is facilitated by 3' polyadenylation and a small protein known as viral protein genome-linked (VPg) that acts as a 5' cap and primer. Translation generates a viral RNA- dependent RNA polymerase and accessory proteins that can copy the positive-sense RNA, forming a negative-stranded intermediate that is used as a template for the generation of many positive stranded viral genomes (Fields et al., 2007; Palmenberg et al., 2010). These can then assemble with coat proteins to form infectious viral particles. During replication dsRNA is generated, which may be recognised by host PAMP receptors, including TLR3, DEAD box

90 polypeptide 58 (DDX58/RIGI) and interferon induced with helicase C domain 1 (IFIH1/MDA5)

(Proud, 2011; Slater et al., 2010; Wang et al., 2009).

As previously noted, the primary anti-inflammatory therapy for all, but the mildest, asthmatics are inhaled glucocorticoids (Barnes, 2006b). However, the inflammation associated with rhinovirus infection is often glucocorticoid resistant in asthmatics, decreasing symptom control, which can lead to an exacerbation (Grünberg et al., 2001; Papi et al., 2013). This study investigated the effects of human rhinovirus infection on transactivation, in lung epithelial cells, using the 2×GRE reporter to model glucocorticoid-inducible gene expression. Additionally, intra-cellular responses to infection were modelled using the TLR3 agonist polyinosinic:polycytidylic acid (poly(I:C)), a synthetic mimetic of the double-stranded RNA that is generated during rhinovirus replication.

4.2 Hypothesis

The hypothesis explored in this chapter was that human rhinovirus 16 (Clade A/ICAM-1 binding) infection, or poly(I:C) as a viral mimetic, reduces glucocorticoid-induced gene expression.

4.3 Results

4.3.1 Effects of Rhinovirus on 2×GRE Reporter Activation in BEAS-2B Cells

To investigate whether HRV type 16 affected 2×GRE reporter activation, BEAS-2B cells were treated with 4.1 log TCID50/ml of HRV, added 1 h before, simultaneously, or 1 h after addition of various concentrations of dexamethasone (Figure 4.1). Dexamethasone

91 concentration-dependently induced 2×GRE reporter activation, but these short incubations with

HRV were without effect.

Figure 4.1 Effect of Short Incubations with Human Rhinovirus on Dexamethasone- Induced 2×GRE Reporter Activation. BEAS-2B 2×GRE cells were left naive or were treated with 4.1 log TCID50/ml of human rhinovirus for A) 1 h before, B) simultaneously with, or C) 1 h after, addition of the indicated concentrations of dexamethasone (Dex). Cells were harvested for luciferase assay 6 h after Dex addition. Data (n=3), expressed as fold activation, are plotted as means ± S.E.

BEAS-2B 2×GRE cells were therefore pre-treated for 18 h with log median tissue culture infective doses (TCID50/ml) of 3.1 - 4.6 of HRV, before addition of dexamethasone (1 μM)

(Figure 4.2). Plates were harvested 6 h later for luciferase and MTT viability assays.

Dexamethasone induced 2×GRE reporter activation and this was significantly reduced by up to

42% following HRV infection (Figure 4.2A). However, cell viability, as measured by MTT viability assays performed, in parallel, on identically treated cells, was modestly decreased at the highest log TCID50/ml of rhinovirus (Figure 4.2A). Nevertheless, at 4.1 log TCID50/ml dexamethasone-induced 2×GRE activity was reduced, but there was no effect on cell viability, indicating that HRV can significantly reduce glucocorticoid-inducible reporter activity without affecting cell viability (Figure 4.2).

Figure 4.2 Effects of Human Rhinovirus on IL-8 Release and Glucocorticoid-Induced 2×GRE Reporter Activation. BEAS-2B 2×GRE reporter cells were either not stimulated (NS) or were pre-treated for 18 h with TNF (10 ng/ml) or the indicated log TCID50/ml (3.1, 3.6, 4.1, 4.6) of human rhinovirus, before addition of 1 μM dexamethasone (Dex). After 6 h, a plate was A) harvested for luciferase assay, and B) a parallel plate was harvested for MTT viability assay. Data (n = 4), expressed as, A) fold 2×GRE activity, or B) OD584, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnett's test versus the Dex control. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013)

4.3.2 Effects of Poly(I:C) on Dexamethasone-Induced 2×GRE Reporter Activation in BEAS- 2B and A549 Cells

To examine whether 2×GRE activation was repressed by poly(I:C) treatment, BEAS-2B

2×GRE reporter cells were transfected (using lipofectamine 2000) for 0 - 72 h with various concentrations of poly(I:C), before dexamethasone addition (Figure 4.3A).

Figure 4.3 Effects of Poly(I:C) Treatment on Dexamethasone-Induced 2×GRE Reporter Activation in BEAS-2B Cells. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated with the indicated concentrations of A) poly(I:C) plus 1 μl/ml lipofectamine 2000 (Lipo), or B) Lipo alone, for between 0 and 72 h, before addition of 1 µM dexamethasone (Dex). Plates were harvested 6 h after Dex addition for luciferase assay. Data (n = 7), expressed as a percentage of Dex, are plotted as means ± S.E. Statistical analyses, versus Dex control, were performed by repeated measures two-way ANOVA with Bonferroni’s correction for multiple comparisons. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013).

Poly(I:C) had no effect on 2×GRE reporter activity when added for up to 2 h before dexamethasone, but pre-treatments of 6, 24, 48 and 72 h induced significant repression of up to

~58%. The EC50 of the response to poly(I:C) in inhibiting 2×GRE activation underwent a sinistral shift, from ~65 ng/ml at 6 h (the earliest time point where an EC50 was measurable) to

~0.34 ng/ml at 48 h, with increasing time of incubation. Addition of the transfection reagent lipofectamine 2000, alone or in the presence of dexamethasone, had no effect on 2×GRE reporter activation at any time tested (Figure 4.3B).

Figure 4.4 Effects of Poly(I:C) Pre-Treatment on BEAS-2B 2×GRE Cell Viability. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for A) 24 h, B) 48 h, or C) 72 h, with poly(I:C) plus 1 μl/ml lipofectamine 2000 (Lipo) at the indicated concentrations, prior to addition of 1 μM dexamethasone (Dex). Cells were harvested 6 h after Dex addition for MTT viability assay. Data (n = 4), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnett’s test versus NS. * P < 0.05, ** P < 0.01 (Rider et al., 2013).

To determine whether poly(I:C) treatment affected viability, BEAS-2B 2×GRE cells were treated for 24, 48 or 72 h with poly(I:C), before addition of 1 μM dexamethasone and cells harvested for MTT viability assays (Figure 4.4). Treatment with 100 or 1000 ng/ml of poly(I:C) for 24, 48, but not 72 h, modestly, but significantly reduced cell viability by <18%. However, 10 or 1 ng/ml poly(I:C) had no effect on viability, despite significantly reducing dexamethasone- induced 2×GRE reporter activation at 24 and 48 h respectively (Figure 4.3A). Therefore,

95 poly(I:C) pre-treatment reduced dexamethasone-induced 2×GRE activation at concentrations that did not affect cell viability.

A549 2×GRE cells were also pre-treated with poly(I:C) for up to 72 h, before the addition of 1 μM dexamethasone (Figure 4.5). As in BEAS-2B cells, poly(I:C) concentration- and time- dependently reduced 2×GRE reporter activation in A549 cells. Treatment with poly(I:C) for up to 6 h before dexamethasone addition had no effect on 2×GRE reporter activation. However, following longer incubations with poly(I:C), dexamethasone-induced 2×GRE activation was repressed by ~81% at 24 h and 91% at 72 h. Because poly(I:C) treatment had no significant effect at 6 h, the apparent change in EC50 in A549 cells was smaller than in BEAS-2B cells, but decreased from ~0.43 ng/ml at 24 h to 0.11 ng/ml at 48 h. Again, there was no significant effect of lipofectamine 2000, either alone or in the presence of dexamethasone, at any time point investigated (Figure 4.5B).

Figure 4.5 Effects of Poly(I:C) Treatment on Dexamethasone-Induced 2×GRE Reporter Activation in A549 Cells. A549 2×GRE cells were either not stimulated (NS) or were pre-treated with the indicated concentrations of A) poly(I:C) plus 1 μl/ml lipofectamine 2000 (Lipo), or B) Lipo alone, for between 0 and 72 h, before addition of 1 µM dexamethasone (Dex). Plates were harvested 6 h after Dex addition for luciferase assay. Data (n = 5), expressed as a percentage of 1 μM Dex, are plotted as means ± S.E. Statistical analyses, versus Dex control, were performed by repeated measures two-way ANOVA with Bonferroni’s correction for multiple comparisons. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013).

4.3.3 Effects of Poly(I:C) on cAMP-Induced and Constitutive Reporter Systems

The specificity of inhibition by poly(I:C) was examined using three additional reporter systems (Fig 4.6). BEAS-2B 6×cAMP response element (CRE) reporter cells were pre-treated for 24 h with poly(I:C), before addition of the LABA formoterol (10 nM), which stimulates cAMP production, or formoterol plus dexamethasone (Figure 4.6A). Formoterol induced substantial CRE reporter activity, which was concentration-dependently reduced by poly(I:C) treatment. Although the combination of formoterol plus dexamethasone mediated CRE reporter activation, this was reduced compared to formoterol alone. Poly(I:C) treatment repressed by 93%

CRE reporter activation induced by dexamethasone plus formoterol treatment, with an EC50 of

6.6 ng/ml.

Figure 4.6 Effects of Poly(I:C) on the Activation of cAMP Responsive, Basal and Strong Promoter-Driven Luciferase Reporters. A) BEAS-2B cells stably transfected with a cAMP response element (CRE) driven lucferase reporter were either not stimulated (NS) or were pre-treated for 24 with the indicated concentrations of poly(I:C) plus 1 μl/ml lipofectamine 2000 (Lipo), before the addition of 10 nM formoterol (Form) either alone or with 1 μM dexamethasone (Dex) (DF = Dex+Form). Cells were harvested after 6 h for luciferase assay. Data (n = 5), expressed as fold activation, are plotted as means ± S.E. B) BEAS-2B cells stably transfected with either B) a basal TATA promoter, or C) a strong simian virus 40 (SV40) driven luciferase reporter, were either NS or were pre-treated with the indicated concentrations of poly(I:C) plus 1 μl/ml Lipo or Lipo alone for 24 h, before being harvested for luciferase assay. Data (n = 8), expressed as fold activation, are plotted as means ± S.E. Statistical analyses, versus A) Form, or B) and C) NS, were performed by ANOVA with a Dunnett’s test. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013).

Poly(I:C) treatment also concentration-dependently reduced, by 46 and 60% respectively, the basal activity of constitutive TATA and SV40 reporters (Figure 4.6B and C). The EC50s of the responses were comparable to the CRE reporter, at 4.4 and 5.6 ng/ml for the TATA and

SV40 reporter respectively. These results demonstrated that poly(I:C)-induced repression was not specific to the glucocorticoid-inducible 2×GRE reporter.

4.3.4 Effects of Poly(I:C) on NF-κB Activated Reporter Systems in BEAS-2B and A549 Cells

As CXCL8 was induced following 24 h of rhinovirus infection (data not shown) and

CXCL8 production is, at least in part, NF-κB dependent, the effects of poly(I:C) on NF-κB reporter activation were determined (Holden et al., 2007; Neuschäfer-Rube et al., 2013; Profita et al., 2008). BEAS-2B 3κBu (contains the upstream NF-κB site from the prostaglandin- endoperoxide synthase 2 (PTGS2/COX2) promoter), 6κbtk (contains 6 consensus NF-κB sites) and A549 6κBtk NF-κB reporter cell lines were pre-treated for 24 h with various concentrations of poly(I:C), before stimulation with TNF for 6 h (Fig 4.7).

Figure 4.7 Effects of Poly(I:C) Treatment on NF-κB Reporter Activation in BEAS-2B Cells. BEAS-2B cells stably transfected with, A) NF-κB 3κBu, or B) NF-κB 6κbtk driven luciferase reporters were pre-treated for 24 h with the indicated concentrations of poly(I:C) plus 1 μl/ml lipofectamine 2000, before the addition of 10 ng/ml TNF. Plates were harvested 6 h after TNF addition for luciferase assay. Data (n = 8), expressed as fold activation, are plotted as means ± S.E. C) A549 cells stably transfected with the 6κbtk NF-κB luciferase reporter were pre-treated for 24 h with the indicated concentrations of poly(I:C) plus 1 μl/ml lipofectamine 2000, before addition of 10 ng/ml TNF. Plates were harvested 6 h after TNF addition for luciferase assay. Data (n = 8), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnett’s test versus TNF control. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013).

Poly(I:C) treatment induced modest BEAS-2B 6κbtk reporter activation to a maximum of

1.6 fold, in the absence of TNF, but had no significant effect on the 3κBu or A549 6κbTK reporters (Fig. 4.7 B). By contrast, TNF induced substantial activation of all three NF-κB reporters, but this induction was concentration-dependently repressed by poly(I:C) to a maximum of >80%. The EC50s of poly(I:C) repression in the BEAS-2B 3κBu and A549 6κBtk reporter systems were comparable to those obtained with the CRE, TATA and SV40 reporters, at

3 and 1.6 ng/ml respectively (Fig. 4.7 A&C). However, the EC50 of the BEAS-2B 6κBtk reporter was substantially higher at 50 ng/ml, potentially reflecting the enhanced activation induced by poly(I:C) treatment (Fig. 4.7 B). These results demonstrate that poly(I:C) pre-treatment represses

TNF-induced NF-κB reporter activation.

100

4.3.5 Effect of Poly(I:C), Dexamethasone and Formoterol on Inflammatory Cytokine Expression

BEAS-2B cells were pre-treated with poly(I:C) for 24 h, before addition of dexamethasone and/or formoterol (Fig. 4.8). Cells were harvested after 6 h for real-time PCR analysis of the cytokines CXCL8 and CXCL10 (interferon gamma-induced protein (IP)-10).

Figure 4.8 Effects of Poly(I:C), Dexamethasone and Formoterol on CXCL8 and CXCL10 Expression in BEAS-2B Cells. BEAS-2B cells were pre-treated for 24 h with 100 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000, before addition of 1 μM dexamethasone (Dex) and/or 10 nM formoterol (Form). Cells were harvested 6 h after Dex or Form addition, total RNA extracted, cDNA generated and RT-PCR for CXCL8, CXCL10 and GAPDH performed. Data (n = 4), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons. * P < 0.05, ** P < 0.01, *** P < 0.001 (Rider et al., 2013).

Rather than repressing expression, poly(I:C) significantly induced CXCL8 and CXCL10 mRNA production by 32 and ~12,500 fold respectively. Dexamethasone significantly reduced

100

101 poly(I:C)-induced CXCL8 and CXCL10 mRNA induction. However, formoterol significantly attenuated CXCL8, but not CXCL10 expression. Furthermore, dexamethasone plus formoterol significantly decreased poly(I:C)-induced CXCL8 expression, relative to formoterol alone (Fig.

4.8 A). Thus, despite repressing the activation of a variety of reporter systems, poly(I:C) significantly induces pro-inflammatory gene expression. Additionally, although 2×GRE reporter activation was repressed by poly(I:C) pre-treatment (Fig 4.2), dexamethasone retained the ability to significantly repress poly(I:C)-induced gene expression.

4.4 Discussion

These data demonstrated that human rhinovirus TCID50-dependently induced glucocorticoid hyporesponsiveness in 2×GRE BEAS-2B cells. Likewise, poly(I:C) concentration-dependently induced glucocorticoid hyporesponsiveness in 2×GRE lung epithelial cell reporter systems, but also repressed the activation of 6×CRE, TATA, SV40 and NF-κB reporters. As the 2×GRE reporter systems model glucocorticoid-inducible gene expression, this may, at least in part, explain the glucocorticoid resistance induced during HRV infection

(Grünberg et al., 2001; Papi et al., 2013). Inflammation may be difficult to control in asthmatics with glucocorticoid resistance, increasing the risk of developing an asthma exacerbation following HRV infection (Corne et al., 2002; Johnston et al., 1995; Message et al., 2008).

Rhinovirus infection decreased 2×GRE reporter activation by a maximum of 42%, a concentration that reduced cell viability, while poly(I:C) induced ~60% and ~91% repression of dexamethasone-induced 2×GRE activity in BEAS-2B and A549 cells respectively. One possible explanation for the high concentrations of rhinovirus required to induce modest responses, is low

ICAM-1 expression on BEAS-2B cells (Atsuta et al., 1997), which may decrease rhinovirus

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102 binding and infection. ICAM-1 expression is very low in not stimulated cells (Holden et al.,

2004) and in BEAS-2B cells incubated in serum free medium overnight (data not shown).

Therefore, infection efficiency may have been low during experiments. Additionally, glucocorticoids and LABAs may decrease ICAM1 expression (Spoelstra et al., 2000), which could contribute to the decreased exacerbation rate induced during URTI, by decreasing infection of individual lung cells in asthmatics taking combination therapy (O’Byrne, 2011;

Pauwels et al., 1997; Prazma et al., 2010).

Both rhinovirus and poly(I:C) treatment time-dependently decreased cell viability.

However, the reductions in cell viability were modest and significant repression of 2×GRE reporter activation occurred at concentrations and TCID50s that did not induce cell death.

Furthermore, poly(I:C) pre-treatment appeared to decrease cell viability at 24 and 48 h, but not at

72 h (Fig. 4.4). Cells in which viability was decreased by 72 h of pre-treatment with poly(I:C) may have had sufficient time to recover, or underwent apoptosis and were replaced by dividing cells by 72 h. Indeed, HRV-14 has previously been shown to time-dependently induce apoptosis in human epithelial cells (Deszcz et al., 2005).

The delay before rhinovirus, or poly(I:C), reduced 2×GRE activation argues against rapid activation of signalling pathways, such as the p38 MAPK and PI3K pathway activation mediated by SYK, following binding of rhinovirus to ICAM-1 (Lau et al., 2008; Wang et al., 2006b), directly inducing glucocorticoid hyporesponsiveness. Instead, cells may have initiated a slower protein expression program following, for example, detection of dsRNA replication intermediates by PAMP receptors, such as Toll-like receptor 3 (Slater et al., 2010). However, experiments comparing live, with replication deficient, UV-irradiated virus were not performed.

Therefore, responses to the single stranded viral genome and/or rhinovirus proteins, rather than

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103 the double stranded RNA replication intermediate that poly(I:C) mimics, cannot be ruled out

(Grünberg and Sterk, 1999; Slater et al., 2010; Wang et al., 2009). Indeed, repression of glucocorticoid-inducible reporter activation following respiratory syncytial virus (HSV) infection may be dependent on non-structural viral proteins (Webster Marketon et al., 2014).

Poly(I:C) treatment induces substantial transcription of antiviral genes, including

CXCL10 and beta-defensin (Proud et al., 2004; Spurrell et al., 2005). In my experiments expression of CXCL8 and CXCL10 were increased by ~30 and >12,000 fold respectively, following poly(I:C) treatment (Fig. 4.8 B). In addition to the 2×GRE reporter, poly(I:C) decreased activation of TATA, SV40 and even NF-κB and CRE reporters, after induction by

TNF and formoterol respectively, suggesting that repression occurs through a generic mechanism. For example, substantial transcription of antiviral genes could monopolize cell transcriptional machinery, including the core transcriptional factor polymerase II, potentially leading to squelching effects on other gene expression programs and reporter activation (Cahill et al., 1994; Lin et al., 2007). Similar effects on transcription have also been demonstrated following over-expression of glucocorticoid or estrogen receptors, due to competition for transcriptional factors and machinery (Hoeck et al., 1992; Meyer et al., 1989). However, there are alternative generic mechanisms by which poly(I:C) could repress 2×GRE induction, including a reduction in GR nuclear translocation, affinity for DNA or ability to induce gene transcription, as observed following respiratory syncytial virus infection, potentially resulting from activation of the NF-κB and/or MAPK pathways (Bellettato et al., 2003; Hinzey et al.,

2011; Papi et al., 2013).

The inability of poly(I:C) to substantially potentiate the NF-κB reporters was unexpected, as poly(I:C) had previously been shown to activate NF-κB (Alexopoulou et al., 2001; Offermann

104 et al., 1995). However, it is possible that poly(I:C) activated NF-κB at shorter incubation times, but that by 24 h feedback mechanisms, such as enhanced NFKBIA expression, had reduced NF-

κB activity and therefore luciferase production (Le Bail et al., 1993; Hoffmann et al., 2002; Scott et al., 1993). Conversely, poly(I:C) may activate the alternative NF-κB pathway, which may not be effectively measured as the reporter systems utilized appear to be largely IKBKB-dependent

(Newton et al., 2007).

Despite poly(I:C) reducing 2×GRE reporter activity, dexamethasone treatment significantly reduced mRNA expression of the inflammatory genes CXCL8 and CXCL10.

CXCL8 expression was also decreased by formoterol alone. Additionally, the combination of dexamethasone and formoterol significantly reduced CXCL8 expression, compared to formoterol alone. In support of these results, a combination of the glucocorticoid, fluticasone propionate, and the LABA, salmeterol, may significantly decrease rhinovirus-induced CXCL8 mRNA and protein expression, in BEAS-2B and primary epithelial cells (Edwards et al., 2006). This indicates that glucocorticoids and LABAs retain activity despite rhinovirus infection and suggests that these medications may be beneficial during virally-induced asthma exacerbations

(O’Byrne, 2011; Pauwels et al., 1997; Prazma et al., 2010; Skevaki et al., 2009). Furthermore, clinical data indicate that patients taking combination therapy, consisting of a glucocorticoid and a LABA, have fewer virally-induced asthma exacerbations (O’Byrne, 2011; Pauwels et al., 1997;

Prazma et al., 2010). However, it is unclear if: 1) these therapies have a protective effect leading to a reduced frequency of infection, or 2) whether asthma exacerbations are not recognised, despite an ongoing infection, because of maintenance of symptom control.

In summary, HRV reduced the ability of glucocorticoids to induce 2×GRE reporter activation. Likewise, poly(I:C) repressed activation of 2×GRE activation, but also repressed the

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105 activity of other reporter systems, suggesting that repression occurs through a generic mechanism. These findings may explain the reduced effectiveness of glucocorticoid treatment during viral exacerbations. Additionally, this study details a system that models the effects of viral infection on the response to glucocorticoids, which may enable investigation into approaches to overcoming virally-induced glucocorticoid hyporesponsiveness.

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Chapter Five: Approaches to Overcoming Induced Glucocorticoid Hyporesponsiveness

Much of the data in this chapter was previously published in the following papers:

Rider C.F., King E.M., Holden N.S., Giembycz M.A. and Newton R. (2011). Inflammatory stimuli inhibit glucocorticoid-dependent transactivation in human pulmonary epithelial cells: rescue by long-acting β2-adrenoceptor agonists. J. Pharmacol. Exp. Ther. 338, 860–869 (Rider et al., 2011).

Rider C.F., Miller-Larsson A., Proud D., Giembycz M.A. and Newton R. (2013). Modulation of transcriptional responses by poly(I:C) and human rhinovirus: Effects of long-acting β2- adrenoceptor agonists. Eur. J. Pharmacol. 708, 60-67 (Rider et al., 2013).

Rider C.F., Shah S., Miller-Larsson A., Giembycz MA and Newton R (Submitted). Cytokine- induced loss of glucocorticoid function: Effect of kinase inhibitors, long-acting β2-adrenoceptor agonist and glucocorticoid receptor ligands. PloS ONE.

Suharsh Shah and David Gaunt performed some of the experiments detailed in this chapter, as specifically noted in individual figure legends.

5.1 Rationale

Glucocorticoid resistance is sometimes encountered in severe asthma, during rhinovirus- induced exacerbations and in asthmatics who smoke (Chaudhuri et al., 2003; Grünberg et al.,

2001; Sher et al., 1994; Tomlinson et al., 2005). By decreasing symptom control, glucocorticoid resistance may increase suffering, mortality and medical expenses in asthma (Antonicelli et al.,

2004; Godard et al., 2001; Keenan et al., 2012; Nelson et al., 2003b). Therefore, approaches to

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107 overcome glucocorticoid resistance are urgently needed. Glucocorticoid resistance could theoretically be overcome by identifying or developing a GR agonist that was not subject to resistance or by inhibiting signalling pathways that decrease glucocorticoid responsiveness

(Adcock et al., 2008; Keenan et al., 2012). Although many novel GR agonists have recently been developed, none have as yet been shown to be invulnerable to resistance (Biggadike et al., 2004;

Schäcke et al., 2007, 2008; Uings et al., 2013; Yates et al., 2010). A better approach could be the inhibition of the inflammatory signalling pathways that may underlie glucocorticoid resistance.

Thus, inhibition of pathways with a potential role in reducing responses to glucocorticoids, including MAPK, PI3K, PKC and NF-κB, were investigated (Edwards et al., 2009; Irusen et al.,

2002; Lee et al., 2006; Marwick et al., 2010; Mercado et al., 2011; Tsitoura and Rothman, 2004;

Wang et al., 2004b). Finally, LABAs are an established adjunct therapy that potentiates glucocorticoid activity in addition to reducing bronchoconstriction. Indeed, addition of a LABA is more effective than doubling the glucocorticoid dose (Greening et al., 1994; O’Byrne et al.,

2001; Shrewsbury et al., 2000). By enhancing the effects of glucocorticoids in asthmatics and potentiating the induction by glucocorticoids of genes with anti-inflammatory properties, LABAs may prove efficacious in combating glucocorticoid hyporesponsiveness (Holden et al., 2014;

Kaur et al., 2008; O’Byrne et al., 2001; Shrewsbury et al., 2000).

Genes with potentially anti-inflammatory properties that may contribute to glucocorticoid activity, including TSC22D3, CDKN1C and RGS2, are induced, by inhaled glucocorticoids, in mild asthmatics and normal volunteers (Heximer et al., 1997; Holden et al., 2011; Kelly et al.,

2012; Leigh et al., 2014; Vandevyver et al., 2013). Additionally, pro-inflammatory stimuli, including TNF and poly(I:C) decrease glucocorticoid-induced expression of TSC22D3 and

CDKN1C, potentially reducing the effectiveness of glucocorticoids (Rider et al., 2011, 2013).

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Therefore, potential approaches to reversing the repression of glucocorticoid-inducible gene expression by inflammatory stimuli were investigated, including addition of a LABA, novel glucocorticoids and inhibition of inflammatory pathways.

5.2 Hypothesis

In this chapter the following hypotheses will be tested: 1) that potentiating glucocorticoid activity through the addition of a LABA will reverse induced glucocorticoid hyporesponsiveness; 2) that specific novel GR agonists may not be susceptible to induced hyporesponsiveness, and; 3) that inhibition of specific inflammatory signalling pathways will reverse the repression of glucocorticoid-inducible gene expression induced by pro-inflammatory stimuli. These hypotheses will be tested using a 2×GRE reporter system, which models glucocorticoid-induced gene transcription and is repressed by treatment with specific inflammatory agents, as demonstrated in chapters 3 and 4.

5.3 Results

5.3.1 Effects of Long-Acting β2-Adrenoceptor Agonists on Glucocorticoid Hyporesponsiveness Induced by TNF or Poly(I:C)

Pre-treatment with 10 ng/ml TNF for 1 h reduced, by ~40%, 2×GRE reporter activation induced by 6 h of dexamethasone treatment, in A549 and BEAS-2B cells (Figures 5.1A and B).

Addition of formoterol had no significant effect on 2×GRE activation alone, in either cell type and on dexamethasone treatment in A549 cells. However, in BEAS-2B cells, formoterol functionally reversed TNF-induced repression of the 2×GRE reporter, through significantly potentiating dexamethasone activity (Fig 5.1 B). Likewise, formoterol significantly reversed the

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5.1 C).

Figure 5.1 Modulation of Dexamethasone-Induced 2×GRE Activation by Formoterol, TNF and Poly(I:C). A) A549 or B) BEAS-2B 2×GRE cells were pre-treated for 1 h with 10 ng/ml TNF, before addition of 10 nM formoterol (Form) and/or the indicated concentrations of dexamethasone (Dex). C) BEAS-2B 2×GRE cells were pre-treated for 24 h with 100 ng/ml of poly(I:C) plus 1 μl/ml lipofectamine 2000, before addition of 10 nM Form and/or the indicated concentrations of Dex. Cells were harvested 6 h after Dex addition for luciferase assay. Data (n = 6-8), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons made between treatments at each Dex concentration (6 comparisons). Significance versus Dex: a, P < 0.05; b, P < 0.01; c, P < 0.001. Significance versus Dex+TNF: d, P < 0.05; e, P < 0.01; f, P < 0.001.

BEAS-2B 2×GRE cells were pre-treated with 10 ng/ml of TNF for 1 h, or 100 ng/ml poly(I:C) for 24 h, prior to addition of 1 μM dexamethasone and various concentrations of either formoterol or salmeterol (Figure 5.2). Pre-treatment with TNF or poly(I:C) reduced dexamethasone-induced 2×GRE activation by ~45%. However, treatment with either formoterol or salmeterol concentration-dependently enhanced reporter activation, thereby functionally reversing the repression induced by TNF or poly(I:C) treatment. This reversal was functional, as

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110 the LABAs did not directly combat the repression induced by TNF or poly(I:C) and instead simply potentiate dexamethasone-induced reporter activation.

Figure 5.2 LABAs Functionally Reverse TNF- and Poly(I:C)-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B Cells. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated with 10 ng/ml TNF for 1 h (top panels) or with 100 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000 for 24 h (bottom panels), before addition of the indicated concentrations of formoterol (Form) or salmeterol (Salm) and/or 1 μM dexamethasone (Dex). Cells were harvested 6 h after Dex addition for luciferase assay. Data (n = 4-7), expressed as a percentage of Dex treatment, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with a Dunnet’s test against Dex+TNF or Dex+Poly(I:C), *, P < 0.05; **, P < 0.01; ***, P < 0.001.

BEAS-2B cells were pre-treated with TNF or poly(I:C) before addition of dexamethasone and/or formoterol and harvested for analysis of CDKN1C and TSC22D3 mRNA and protein expression, by RT-PCR and western blotting respectively (Figure 5.3).

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Figure 5.3 Effects of TNF or Poly(I:C), Dexamethasone and Formoterol on CDKN1C and TSC22D3 Expression. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated with A, B, D, E) 10 ng/ml TNF for 1 h, or C) 100 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000 for 24 h, prior to addition of 1 μM dexamethasone (Dex) and/or 10 nM formoterol (Form). Cells were harvested 6 h after Dex or Form addition, for total RNA extraction and reverse transcription to cDNA (A, B, C) or western blotting (D, E). RT-PCR and western blotting were performed for CDKN1C, TSC22D3 and GAPDH expression. Densitometry was performed to generate data in lower panels of D and E. Data (n = 3 - 4), expressed as fold activation relative to GAPDH, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons. a, P < 0.05 compared to control; c, P < 0.001 compared to control; d, P < 0.05 compared to Dex; f, P < 0.001 compared to Dex; g, P < 0.05 compared to Dex+Form; i, P < 0.001 compared to Dex+Form. (Rider et al., 2011, 2013).

Dexamethasone significantly induced expression of both CDKN1C and TSC22D3.

However, pre-treatment with TNF or poly(I:C) significantly reduced dexamethasone-induced

CDKN1C mRNA expression by ~70 and ~30% respectively. Although TNF reduced TSC22D3 expression by 32%, this was not statistically significant in these experiments. Formoterol significantly potentiated dexamethasone-induced CDKN1C mRNA expression by ~3 fold and functionally reversed the repression induced by TNF and poly(I:C) (Figure 5.3B and C).

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However, formoterol only enhanced dexamethasone induced TSC22D3 mRNA expression by

~1.2 fold and therefore, although there was a trend towards reversal of TNF mediated glucocorticoid resistance, this did not reach significance. Similar results were obtained with western blotting to those seen with RT-PCR (Figure 5.3D and E). These results indicate that glucocorticoid-inducible gene expression can be repressed by TNF or poly(I:C) pre-treatment and that this may be countered by addition of formoterol to dexamethasone treatment.

5.3.2 Effects of Different Glucocorticoid Receptor Agonists on Cytokine-Induced Glucocorticoid Hyporesponsiveness

To determine the susceptibility of structurally dissimilar, steroidal and non-steroidal GR agonists to repression by TNF, BEAS-2B 2×GRE cells were pre-treated for 1 h with 10 ng/ml

TNF, before addition of various concentrations of the glucocorticoids dexamethasone, fluticasone furoate, fluticasone propionate, budesonide, des-ciclesonide, RU24858 and

GW870086X or the non-steroidal glucocorticoid receptor agonist GSK9027, for 6 h (Figure 5.4).

Relative to a maximally effective 1 μM concentration of dexamethasone, certain GR ligands acted as full agonists (fluticasone furoate, fluticasone propionate and budesonide), producing similar EMax values to dexamethasone (Table 5.1). However, other GR ligands acted as partial agonists (des-ciclesonide, RU24858, GSK9027 and GW870086X) on the 2×GRE reporter system. Nevertheless, TNF pre-treatment reduced the EMax produced by each GR agonist by

~50% (Table 5.1) and the effect was not surmountable even at the highest GR agonist concentrations (Figure 5.4). In addition, a trend towards modest reductions in the EC50s were noted and these reached significance with dexamethasone, RU24858 and GW870086X (Table

5.1).

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Figure 5.4 Effects of TNF on Glucocorticoid or Glucocorticoid Receptor Agonist- Induced 2×GRE Reporter Activation in BEAS-2B Cells. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with 10 ng/ml TNF, before addition of 1μM dexamethasone (Dex), the indicated concentrations of the glucocorticoids Dex, fluticasone furoate (FF), fluticasone propionate (FP), budesonide (Bud), des-ciclesonide (DC), RU24858 (RU) and GW870086X (GW) or the non-steroidal glucocorticoid receptor agonist, GSK9027 (GSK). Cells were harvested 6 h after glucocorticoid or glucococorticoid receptor agonist addition for luciferase assay. Data (n = 3- 6), expressed as fold activation or as a percentage of Dex activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons. At least the top 5 concentrations of each glucocorticoid or glucocorticoid receptor agonist had statistical significance of P < 0.001 when naive versus in the presence of TNF. Suharsh Shah performed some of the experiments in generating this figure.

A549 2×GRE cells were likewise pre-treated with 10 ng/ml TNF or 1 ng/ml IL1B, before addition of 1 μM dexamethasone and various concentrations of fluticasone furoate, budesonide, des-ciclesonide and GW870086X for 6 h (Figure 5.5). As in BEAS-2B cells, fluticasone furoate and budesonide behaved as full agonists, while des-ciclesonide was a partial agonist and

GW870086X a weak partial agonist. However, partial agonists appeared to induce lower EMax values in A549 than in BEAS-2B cells, relative to full agonists.

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Table 5.1 Effect of NR3C1 Ligands on BEAS-2B 2×GRE Activation in the Presence and Absence of TNF.

BEAS-2B cells harbouring a 2×GRE reporter were either not treated (naive) or were pre- treated with tumor necrosis factor (TNF; 10 ng/ml) for 1 h, prior to addition of a maximally effective concentration of the indicated NR3C1 ligands. After 6 h, cells were harvested for luciferase assay. Data are from Fig. 5.4 and are expressed as a percent of 1 µM dexamethasone treatment (Naïve: EMax = 6.3 ± 0.2 fold; +TNF: EMax = 3.7 ± 0.2 fold). Statistical analyses, comparing the EC50s of the ligand in the presence and absence of TNF, were conducted by paired Student's t-tests: P < 0.05 *.

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Figure 5.5 Effects of TNF or IL1B on Glucocorticoid-Induced 2×GRE Reporter Activation in A549 2×GRE Cells. A549 2×GRE cells were either not stimulated (NS) or were pre-treated for 1 h with 10 ng/ml TNF or 1 ng/ml IL1B, before addition of 1 μM dexamethasone (Dex) and the indicated concentrations of the glucocorticoids fluticasone furoate (FF), budesonide (Bud), des- ciclesonide (DC) and GW870086X (GW). Cells were harvested 6 h after glucocorticoid addition for luciferase assay. Data (n = 4-6), expressed as a percentage of Dex activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons. At least the top 4 concentrations of FF, Bud and DC had statistical significance of P < 0.001, when naive versus in the presence of TNF or IL1B.

Addition of a LABA was previously shown to functionally reverse poly(I:C) or TNF- induced repression of 2×GRE reporter activation, by potentiating dexamethasone activity (Figure

5.2). To determine whether LABA addition would also potentiate the activity of all the GR agonists, BEAS-2B 2×GRE cells were pre-treated for 1 h with TNF, before addition of 10 nM formoterol and a maximally effective concentration of each GR agonist (Figure 5.6 A), upper panel). Reporter activation by each GR agonist was significantly repressed by 44-55% after TNF treatment and significantly enhanced by ~2 fold following formoterol addition. Addition of formoterol to each GR agonist also functionally reversed TNF-induced 2×GRE reporter

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116 hyporesponsiveness, so that, with the exception of dexamethasone, there was no longer any significant difference from GR agonist alone. Similar results were obtained following treatment with each GR agonist and poly(I:C) in the absence, or presence, of formoterol (Figure 5.6 B, upper panel).

Figure 5.6 Effects of TNF and/or Formoterol on 2×GRE Reporter Activation Induced by Various Glucocorticoid Receptor Agonists. BEAS-2B 2×GRE cells were pre-treated for, A) 1 h with 10 ng/ml TNF, or B) 24 h with 10 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000, before addition of maximally effective concentrations of fluticasone furoate (FF; 100 nM), fluticasone propionate (FP; 100 nM), budesonide (Bud; 100 nM), dexamethasone (Dex; 1 μM), GSK9027 (GSK; 1 μM), RU24858 (RU; 1 μM), des-ciclesonide (DC; 100 nM) or GW870086X (GW; 100 nM), in the presence, or absence, of 10 nM formoterol (Form). After 6 h cells were harvested for luciferase assay. Data (n = 9, 6), expressed as fold activation (top panels) or as fold of NR3C1 agonist alone (X axis) against fold of NR3C1 agonist plus TNF and/or Form (Y axis), are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Dunnett’s test versus each NR3C1 agonist alone. * P < 0.05, ** P < 0.01, *** P < 0.001.

To quantify the effect of modulation with TNF and formoterol, activation of the 2×GRE reporter by each GR agonist alone was plotted against GR agonist in the presence of TNF and/or formoterol and linear regression used to produce lines of 'best fit' (Figure 5.6 A, lower panel).

The lines intersected at approximately 1/1 on the graph, showing that 2×GRE reporter activation

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2 TNF (r = 0.67), was linear and proportional to the EMax for each GR agonist. Hence, full agonists were strongly potentiated by formoterol and repressed by TNF pre-treatment, while partial agonists showed reduced modulation.

Likewise, the effects of poly(I:C) and formoterol on GR agonist-induced 2×GRE activation were determined (Figure 5.6B, upper panel). The GR agonists induced differing levels of 2×GRE reporter activation dependent on intrinsic activity, which was enhanced by formoterol and reduced by poly(I:C) pre-treatment. When the fold activity induced by each GR agonist was plotted against GR agonist in the presence of poly(I:C) and/or formoterol, a clear linear trend was produced, as in figure 5.6A, with the lines for GR agonist with formoterol, poly(I:C) and formoterol plus poly(I:C) intersecting at approximately 1/1 on the graph (Figure 5.6B, lower panel). These results demonstrate that glucocorticoid hyporesponsiveness induced by both poly(I:C) and TNF is functionally reversed by formoterol and that the magnitude of repression or enhancement of 2×GRE reporter activation is dependent on the GR agonist used.

5.3.3 Effects of TNF and Formoterol on GR Agonist-Induced Gene Expression

To determine whether TNF and formoterol also modulate gene expression induced by GR ligands showing full or various levels of partial agonism, BEAS-2B cells were pre-treated for 1 h with TNF, before addition of formoterol and/or a maximally effective concentration of dexamethasone, fluticasone furoate, des-ciclesonide or GW870086X (Figure 5.7). Formoterol and/or TNF had no effect on the mRNA expression, normalized to GAPDH, of the four genes tested, CDKN1C, DUSP1, RGS2 and TSC22D3. Although all four agonists had an equivalent ability to promote CDKN1C and DUSP1 mRNA expression, there was a trend towards reduced

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GW870086X, relative to the full agonists dexamethasone and fluticasone furoate. Indeed,

TSC22D3 induction by GW870086X was significantly decreased relative to induction by dexamethasone. CDKN1C and TSC22D3 mRNA expression induced by all four GR agonists was substantially repressed by TNF, while DUSP1 and RGS2 were minimally affected.

Figure 5.7 Effect of TNF and/or Formoterol on Glucocorticoid Receptor Agonist- Induced 2×GRE Reporter Activation. BEAS-2B 2×GRE reporter cells were pre-treated for 1 h with 10 ng/ml of TNF, before addition of formoterol and/or maximally effective concentrations of the glucocorticoid receptor agonists (GRAs) dexamethasone (1 μM; Dex), fluticasone furoate (100 nM; FF), des- ciclesonide (100 nM; DC) or GW870086X (100 nM; GW). Cells were harvested 6 h after addition of formoterol and/or GRAs, total RNA extracted, cDNA generated and RT-PCR performed for DUSP1, TSC22D3, CDKN1C, RGS2 and GAPDH. Data (n = 5), expressed as fold activation relative to GAPDH, are plotted as means ± S.E.

Formoterol significantly enhanced GR-induced CDKN1C and RGS2 expression, but had little effect on TSC22D3 and DUSP1. However, the level of enhancement of RGS2 by formoterol was affected by the GR agonist, with both des-ciclesonide and GW870086X inducing

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119 significantly lower mRNA expression than dexamethasone. These differences were maintained in the presence of formoterol plus TNF. Therefore, the level of mRNA expression achieved by different GR agonists is dependent on the agonist efficacy for some genes (e.g. RGS2,

TSC22D3), but not others (e.g. CDKN1C, DUSP1). However, the enhancement produced by formoterol and repression induced by TNF occurred irrespective of the GR agonist utilized.

5.3.4 Effects of Full and Partial Glucocorticoids on NF-κB Reporter Activation and CXCL8 Production

As it was unclear whether a partial agonist on the 2×GRE reporter would also have a reduced ability to repress inflammatory transcription, the effects of the dexamethasone and

GW870086X, the weakest partial agonist tested, were determined on IL1B-induced 6κBtk NF-

κB reporter activation and CXCL8 production, which is at least in part NF-κB dependent

(Holden et al., 2007; Neuschäfer-Rube et al., 2013; Profita et al., 2008) (Figure 5.8). While dexamethasone modestly, but significantly, reduced IL1B-induced NF-κB reporter activation,

GW870086X had no significant effect at any concentration tested (Figure 5.8A and B respectively). However, both dexamethasone and GW870086X significantly repressed IL1B- induced CXCL8 release, by ~78% and ~67% respectively. Therefore, despite the difference between full and partial agonists on the 2×GRE reporter, the weak partial agonist GW870086X repressed CXCL8 release by a similar, though slightly lower, degree to dexamethasone.

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Figure 5.8 Effects of the Full and Partial Glucocorticoid Receptor Agonists Dexamethasone and GW870086X, on IL1B-Induced 6κbtk NF-κB Reporter Activation and IL-8 Release from A549 Reporter Cells. A549 6κbtk cells were either not stimulated (NS) or were treated with the indicated concentrations of A & C) dexamethasone (Dex) and/or 1 ng/ml IL1B or B & D) GW870086X (GW) and/or 10 ng/ml IL1B or 1 μM Dex and/or IL1B. Cells were harvested after 6 h for A & B) luciferase assay or C & D) CXCL8 ELISA. Data (n = 3-5), expressed as fold activation (A & B), or as CXCL8 release (C & D), are presented as means ± S.E. Statistical analyses were performed by ANOVA with Dunnett’s test versus the IL1B controls. * P < 0.05, ** P < 0.01, *** P < 0.001.

5.3.5 Effects of Inhibition of NF-κB and MAPK Signalling Pathways on TNF or Poly(I:C) Mediated Repression of Dexamethasone-Induced 2×GRE Reporter Activation

As TNF treatment activates inflammatory pathways, including NF-κB and MAPK, we investigated whether inhibition of these pathways would reverse TNF-induced glucocorticoid hyporesponsiveness. To examine the effect of PS-1145 and JNK inhibitor VIII, on their

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5.9A and B). PS-1145 concentration-dependently decreased TNF-induced NFKBIA phosphorylation with an EC50 of ~1 μM. Likewise, JNK inhibitor VIII reduced TNF-induced

JUN phosphorylation in a concentration-dependent manner, with an EC50 of ~0.3 μM.

BEAS-2B 2×GRE cells were pre-treated for 30 min with maximally effective concentrations of the IKBKB inhibitor, PS-1145, or the MAPK inhibitors PD098059

(extracellular signal-regulated kinase (ERK)), SB203580 (p38 MAPK) or JNK inhibitor VIII (c- jun N-terminal kinase (JNK)) prior to addition of TNF (Dudley et al., 1995; Holden et al., 2014;

King et al., 2009a; Newton et al., 2007; Shah et al., 2014; Szczepankiewicz et al., 2006).

Dexamethasone was added 1 h after TNF and cells harvested for luciferase assays 6 h later

(Figure 5.9C). Reporter activation induced by dexamethasone was reduced by 41% following

TNF treatment. Pre-treatment with PS-1145 partially reversed the repression induced by TNF, restoring reporter activation to 73% of the level induced by dexamethasone. Likewise, JNK inhibitor VIII restored reporter activity to 77% of that induced by dexamethasone. However,

PD098059 significantly reduced dexamethasone-induced reporter activation, while SB203580 had no significant effect on reporter activation induced by dexamethasone in the presence, or absence, of TNF (Figure 5.9C).

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Figure 5.9 Effects of Inhibition of NF-κB or MAPK Pathways on TNF-Induced 2×GRE Reporter Repression in BEAS-2B Cells. A) BEAS-2B cells were pre-treated for 30 min with the indicated concentrations of PS-1145 (PS), before addition of TNF. Cells were harvested after 2 min for western blotting and probed for phospho nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (pNFKBIA; pIκBα), NFKBIA and GAPDH. Blots representative of 4 such experiments shown. B) BEAS-2B cells were pre-treated for 30 min with the indicated concentrations of JNK inhibitor VIII (JNK), before addition of 10 ng/ml TNF. Cells were harvested after 15 min for western blotting and probed for phospho jun proto-oncogene (pJUN) and glyceraldehyde 3- phosphate dehydrogenase (GAPDH). Blots representative of 3 such experiments shown. C) BEAS-2B 2×GRE cells were pre-treated for 30 min with 10 μM of the NF-κB or MAPK pathway inhibitors: PS-1145 (PS; IKBKB), PD098059 (PD; MAP2K1/2), SB203580 (SB; p38 MAPKs) or JNK inhibitor VIII (JNK; JNK MAPKs), before addition of 10 ng/ml of TNF. After 1 h, 10 μM dexamethasone (Dex) was added and cells harvested 6 h later for luciferase assay. Data (n = 7), expressed as a percentage of Dex activation, are plotted as means ± S.E. BEAS-2B 2×GRE cells were pre-treated for 30 min with the indicated concentrations of D) PS or JNK, or E) JNK in the presence or absence of 10 μM PS, before addition of 10 ng/ml TNF. After 1 h, 10 μM Dex was added and cells were harvested 6 h later for luciferase assay. Data (n = 4-8), expressed as fold activation, are plotted as means ± S.E. Significance was tested using repeated measures, one-way analysis of variance (ANOVA) with Bonferroni’s correction for multiple comparisons. *, P < 0.05; **, P < 0.01; ***, P < 0.001. D+T indicates Dex plus TNF treatment.

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The effect of various concentrations of PS-1145 or JNK inhibitor VIII were tested on the

2×GRE reporter. PS-1145 had no effect on the 2×GRE reporter either alone or in the presence of dexamethasone, but concentration-dependently reversed the repression by TNF, restoring reporter activation from ~60% to 76% of the level induced by dexamethasone alone (Figure

5.9D). Likewise, JNK VIII concentration-dependently reversed TNF-induced repression to 87% of the level of dexamethasone alone, but also modestly enhanced dexamethasone-induced reporter activation at 30 μM, the highest concentration. To investigate whether simultaneous inhibition of IKBKB and JNK MAPK could more fully reverse repression by TNF of dexamethasone-induced 2×GRE reporter activation, a concentration response curve of JNK inhibitor VIII was generated in the absence and presence of 10 μM PS-1145, a maximally effective concentration (Figure 5.9E). While the combination of JNK inhibitor VIII and PS1145 decreased the TNF-induced repression of 2×GRE activation by dexamethasone, no additional effect of PS-1145 was obvious at concentrations of up to 10 μM JNK inhibitor VIII. These results indicate that repression of dexamethasone-induced 2×GRE activation by TNF occurs, at least in part, through NF-κB and JNK MAPK pathway activation.

To determine whether the NF-κB or MAPK pathways were also involved in poly(I:C) mediated repression of dexamethasone-induced 2×GRE activation, BEAS-2B cells were pre- treated for 30 min with maximally effective concentrations of PS1145, SB239063 (p38 MAPK inhibitor) or JNK inhibitor VIII, prior to addition of 100 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000. After 24 h dexamethasone was added and cells were harvested for luciferase assay 6 h later (Figure 5.10A). Poly(I:C) repressed dexamethasone-induced 2×GRE reporter activation by ~70%. Modest reversals of poly(I:C)-induced repression were apparent following

PS-1145 and JNK inhibitor VIII addition. The effects of various concentrations of PS-1145 and

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JNK inhibitor VIII were therefore assessed on the 2×GRE reporter system (Fig 5.10 B & C).

However, neither inhibitor had any significant effect on poly(I:C) induced repression at any concentration tested.

Figure 5.10 Effects of Inhibition of the NF-κB, p38 or JNK MAPK Pathways on Repression of Dexamethasone-Induced 2×GRE Activation by Poly(I:C). A) BEAS-2B 2×GRE cells were pre-treated for 30 min with 10 μM PS1145, SB239063 or JNK inhibitor VIII, before addition of 100 ng/ml poly(I:C) plus 1 μl/ml lipofectamine 2000. After 24 h, 1 μM dexamethasone (Dex) was added and plates were harvested 6 h later. Data (n = 6), expressed as a percentage of Dex activation, are plotted as means ± S.E. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 30 min with the indicated concentrations of, B) the JNK inhibitor VIII, or C) the IKBKB inhibitor PS1145, before addition of 100 ng/ml poly(I:C) plus 1 μl/ml. After 24 h, 1 μM dexamethasone (Dex) was added and cells were harvested 6 h later for luciferase assay. Data (n = 3-6), expressed as fold activation, are plotted as means ± S.E.

5.3.6 Effect of Phosphatidylinositol 3-Kinase and Protein Kinase C Inhibitors on TNF- Induced Glucocorticoid Hyporesponsiveness As PI3K inhibitors have been shown to reduce glucocorticoid resistance in mice and human cells treated with cigarette smoke or hydrogen peroxide (Lee et al., 2006; Marwick et al.,

2009, 2010; Mercado et al., 2011; Rossios et al., 2012), the effects of LY294002, PI103 and wortmannin were investigated on TNF-induced repression of glucocorticoid activity (Figure

5.11) (Hayakawa et al., 2006; Powis et al., 1994; Vlahos et al., 1994). LY294002, PI103 and wortmannin blocked phosphorylation of v-Akt murine thymoma viral oncogene homolog 1

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(AKT1), a downstream target of PI3K, at concentrations lower than 10 μM with EC50 values of

~900, 70 and 20 nM respectively (Figure 5.11 A - C). However, all three PI3K inhibitors concentration-dependently reduced 2×GRE reporter activation induced by dexamethasone, both in the absence, or presence, of TNF. These data do not therefore support a role for PI3K in TNF- induced glucocorticoid hyporesponsiveness.

Figure 5.11 Effects of Phosphatidylinositol 3-Kinase (PI3K) Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Reporter Cells. BEAS-2B 2×GRE cells were pre-treated with the indicated concentrations of, A) LY29404 (LY), B) PI103 (PI), or C) wortmannin (W) for 30 min before addition of TNF. Cells were harvested after 30 min and western blotting performed for phospho protein kinase B (pPKB), PKB and glyceraldehydes 3-phosphate dehydrogenase (GAPDH). Blots representative of 4-5 experiments are shown. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre- treated for 30 min with the indicated concentrations of the PI3K inhibitors, D) LY29404, E) PI103, or F) wortmannin, before addition of 10 ng/ml TNF. After 1 h, 1 μM dexamethasone (Dex) was added and 6 h later cells were harvested for luciferase assay. Data (n = 3-4), expressed as fold activation, are plotted as means ± S.E. Suharsh Shah and David Gaunt performed many of the experiments in this figure.

To determine whether PKC activation was involved in TNF mediated repression of dexamethasone-induced reporter activation, BEAS-2B cells were pre-treated with various concentrations of Ro31-8220, Gö6976 or GF109203X for 30 min, prior to addition of TNF.

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After 1 h, dexamethasone was added and cells were harvested 6 h later for luciferase assays

(Figure 5.12). The PKC inhibitors tested had no effect on reporter activation in the presence of dexamethasone or dexamethasone plus TNF at concentrations below 1 μM, but at higher concentrations both Ro31-8220 and Gö6976 reduced dexamethasone-induced 2×GRE activity

(Figure 5.12 B and C). Conversely, GF109203X enhanced dexamethasone-induced reporter activation in the presence, and absence, of TNF. These data do not suggest a clear role for PKC in the TNF mediated repression of dexamethasone-induced 2×GRE activation.

Figure 5.12 Effects of Protein Kinase C Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Cells. BEAS-2B 2×GRE cells were either not stimulated (NS), or were pre-treated for 30 min with the indicated concentrations of the PKC inhibitors, GF103203X, Gö6976 or Ro318220, before addition of 10 ng/ml TNF. After 1 h, 1 μM dexamethasone (Dex) was added and 6 h later cells were harvested for luciferase assay. Data (n = 3-4), expressed as fold activation, are plotted as means ± S.E. David Gaunt performed some of the experiments in generating this figure.

5.3.7 Effects of NF-κB and JNK Pathway Inhibitors on the Repression of Glucocorticoid- Inducible Gene Expression by TNF

BEAS-2B cells were pre-treated for 30 min with PS-1145 or JNK inhibitor VIII, before

TNF addition and cells harvested after 6 h for mRNA expression analysis of CDKN1C, DUSP1,

RGS2, TSC22D3 and GAPDH (Figure 5.13). TNF and formoterol had no effect on the four genes tested, either alone or in combination. However, TNF pre-treatment had little effect on

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DUSP1 and RGS2 expression, but repressed dexamethasone-induced CDKN1C and TSC22D3 mRNA expression. Neither PS1145 or JNK inhibitor VIII (at 3 or 10 μM) had any significant effect on dexamethasone-induced mRNA expression of the four genes, in the presence, or absence, of TNF.

Figure 5.13 Effects of Inhibitors on TNF-Induced Glucocorticoid Hyporesponsiveness in BEAS-2B 2×GRE Cells. BEAS-2B 2×GRE cells were either not stimulated (NS) or were pre-treated for 30 min with the indicated concentrations of PS1145 (PS) or JNK inhibitor VIII (JNK), before addition, or not, of 10 ng/ml TNF. After 1 h, 1 μM dexamethasone (Dex) was added and 6 h later cells were harvested for luciferase assay. Data (n = 3-4), expressed as fold activation, are plotted as means ± S.E. Significance was tested using repeated measures, one-way analysis of variance (ANOVA) with Bonferroni’s correction for multiple comparisons. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Formoterol addition significantly enhanced dexamethasone-induced CDKN1C and RGS2 mRNA expression, but did not substantially affect DUSP1 or TSC22D3 induction (Fig 5.13).

Addition of either JNK inhibitor VIII or PS-1145 had no significant effect on expression of the

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However, addition of PS-1145 to dexamethasone plus TNF plus formoterol treatment significantly enhanced DUSP1 mRNA expression, but had no effect on the other three genes tested. With the exception of PS-1145 on DUSP1 expression, inhibition of the NF-κB or JNK

MAPK pathways did not significantly affect dexamethasone-induced expression of the genes tested in the absence, or presence, of TNF.

5.4 Discussion

A number of approaches to overcoming TNF-induced glucocorticoid hyporesponsiveness were tested using a 2×GRE reporter system and bone fides glucocorticoid-inducible genes. While

TNF may activate signalling pathways, including PI3K, PKC, MAPK and NF-κB, no clear role for either PI3K or PKC was identified on TNF-induced glucocorticoid hyporesponsiveness. PI3K inhibition has previously been shown to reduce glucocorticoid resistance induced by inflammatory stimuli, including IL17A, lipopolysaccharide (LPS) and cigarette smoke (Marwick et al., 2009, 2010; Zijlstra et al., 2012). However, the three structurally dissimilar inhibitors used all concentration-dependently prevented AKT1 phosphorylation, yet failed to reverse TNF mediated glucocorticoid hyporesponsiveness. Likewise, two of the three PKC inhibitors tested repressed dexamethasone-induced reporter activation, while the third enhanced activation at the highest concentrations. This may reflect inhibition of novel PKC isoforms, as GF109203X is selective for classical and novel, while Gö6976 is more selective for classical (Goekjian and

Jirousek, 1999). However, as Ro31-8220 is a relatively generic inhibitor of PKC isoforms, a likely explanation for GF109203X-induced enhancement of reporter activity is off target effects

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129 and these data do not therefore support a role for PKC in TNF mediated glucocorticoid hyporesponsiveness.

Inhibition of p38 and ERK MAPK were likewise unable to reverse TNF-mediated glucocorticoid hyporesponsiveness, despite reports suggesting that these signalling pathways may contribute to glucocorticoid resistance induced by IL1α, IL2 plus IL4 or TNF (Irusen et al.,

2002; Onda et al., 2006; Szatmáry et al., 2004; Wang et al., 2004c). Conversely, inhibition of

JNK MAPK significantly reversed TNF mediated hyporesponsiveness. While the mechanism is unclear, phosphorylation of GR by JNK may attenuate glucocorticoid-induced gene expression by promoting export from the nucleus and therefore inhibition of JNK may maintain GR activity

(Chen et al., 2008; Itoh et al., 2002; Rogatsky et al., 1998). Likewise inhibition of the NF-κB pathway by PS-1145 partially reversed TNF mediated glucocorticoid hyporesponsiveness.

However, simultaneous inhibition of both IKBKB and JNK failed to produce any additional reversal of repression by TNF, possibly reflecting crosstalk between the JNK and NF-κB pathways (Papa et al., 2004). Additionally, PS-1145 and JNK inhibitor VIII were unable to decrease poly(I:C) mediated repression of dexamethasone-induced 2×GRE activation, despite data suggesting that inhibition of IKBKB and JNK reverses HRV16-induced glucocorticoid resistance (Papi et al., 2013).

Nevertheless, inhibition of the NF-κB and JNK MAPK pathways did not significantly reverse the TNF mediated repression of dexamethasone-induced CDKN1C and TSC22D3 expression. However, given the clear reversal of 2×GRE reporter repression induced by these inhibitors, we predict that inhibition of the NF-κB or JNK MAPK signalling cascades will reduce the TNF mediated repression of other glucocorticoid-inducible genes, not examined in the current study. Furthermore, as the NF-κB and MAPK pathways are activated by multiple

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130 inflammatory stimuli, their inhibition is likely to be beneficial in reducing inflammatory mediator expression and may therefore partially compensate for reduced GR activity.

A more effective approach to overcoming glucocorticoid hyporesponsiveness may be the development of novel GR agonists that are unaffected by inflammatory stimuli. Nevertheless, all the GR agonists tested in this study were affected by TNF and poly(I:C) pre-treatment, suggesting that development of an invulnerable agonist may not be possible. However, this study indicated that repression by TNF and conversely enhancement by formoterol was dependent on the relative efficacy of the GR agonist. Therefore, the full agonists fluticasone furoate, fluticasone propionate, budesonide and dexamethasone showed a greater ability to induce

2×GRE activity than partial agonists and this advantage was maintained following TNF treatment. Therefore, if control of inflammation in the asthmatic lung is dependent on gene expression and gene expression behaves like the 2×GRE reporter system, the development of fuller GR agonists could prove valuable. In fact, pharmaceutical companies have recently developed compounds which appear to act as superagonists, such as fluticasone furoate and

AZD5423 (R. Newton, personal communication) (Biggadike et al., 2008; Norman, 2013;

O’Byrne et al., 2013; Salter et al., 2007). However, expression of some genes (RGS2,

TSC22D2), but not others (CDKN1C, DUSP1), was dependent on agonist efficacy in BEAS-2B cells (Figure 5.7). Therefore, if TSC22D3 and RGS2 were only partially induced by a low efficacy agonist, increased inflammation and broncoconstriction may be experienced relative to treatment with a fuller agonist (Ayroldi and Riccardi, 2009; Ayroldi et al., 2001; Heximer et al.,

1997; Holden et al., 2011; Mittelstadt and Ashwell, 2001; Xie et al., 2012). Conversely, if genes responsible for the side effects of glucocorticoids were induced in an agonist efficacy-dependent manner, a partial or dissociated GR agonist may provide a better overall therapeutic outcome. A

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131 possible caveat is that the effectiveness of full and partial agonists may be dependent on the output measured. For example, in figure 5.8, GW870086X was unable to significantly repress

NF-κB reporter activation, but showed an equivalent ability to repress CXCL8 production to dexamethasone.

Despite the above discussion, the most effective approach to overcoming TNF mediated glucocorticoid hyporesponsiveness was addition of a LABA, as this potentiated glucocorticoid- inducible 2×GRE reporter system activation and the expression of potentially anti-inflammatory genes, such as CDKN1C and RGS2. LABA addition enhanced glucocorticoid activity, functionally reversing TNF- and poly(I:C)-induced repression of the 2×GRE reporter system.

Indeed, addition of a LABA to glucocorticoid treatment frequently improves control in severe asthma and during exacerbations (Ducharme et al., 2010; Giembycz et al., 2008; Rabe et al.,

2006). However, the mechanisms by which LABAs enhance glucocorticoid activity are not fully understood.

In summary, TNF or poly(I:C) treatment reduced 2×GRE activation induced by GR agonists in proportion with agonist efficacy. Furthermore, none of the GR agonists tested was immune to glucocorticoid hyporesponsiveness. Full and partial GR ligands had various degrees of agonism on TSC22D3 and RGS2 mRNA expression, but were equally effective in inducing

CDKN1C and DUSP1. However, none of the GR agonists tested had any effect on the repression of CDKN1C and TSC22D3 mRNA expression induced by TNF. TNF-induced glucocorticoid hyporesponsiveness could be partially reversed by PS-1145 and JNK inhibitor VIII, inhibitors of the NF-κB and JNK MAPK pathways, respectively. Nevertheless, neither inhibitor had any effect on repression of dexamethasone-induced CDKN1C and RGS2 mRNA expression by TNF.

The most effective approach to overcoming TNF- or poly(I:C)-induced repression of 2×GRE

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Chapter Six: Enhancement of Glucocorticoid-Inducible Gene Expression by Long-Acting β2-Adrenoceptor Agonists

6.1 Rationale

In asthmatics not properly controlled on glucocorticoid alone, the addition of a LABA to an ICS is more effective at reducing asthma symptoms and exacerbation frequency than doubling, or even quadrupling, the concentration of glucocorticoid (Bateman et al., 2008;

Condemi et al., 1999; Greening et al., 1994; Masoli et al., 2005; Matz et al., 2001; O’Byrne et al., 2001; Pauwels et al., 1997; Pearlman et al., 1999; Shrewsbury et al., 2000). Thus, by reducing the concentration of glucocorticoid needed to achieve asthma control, addition of a

LABA may be 'steroid sparing' and this may potentially minimise side effects associated with higher ICS concentrations (Busse et al., 2003; Gibson et al., 1996). Furthermore, the use of

ICS/LABA combination therapies is also associated with a reduction in health care utilization and therefore asthma treatment costs (Delea et al., 2008; Lundbäck et al., 2000; Markham et al.,

2000).

Despite well established clinical benefits, the mechanisms by which LABAs enhance ICS activity are currently unclear and this prevents the rational development of optimal glucocorticoid plus LABA combination therapies (Giembycz et al., 2008). For example, LABAs have been proposed to augment glucocorticoid activity through multiple mechanisms, including increased GR expression, ligand and DNA binding, as well as enhanced GR translocation (Dong et al., 1989; Eickelberg et al., 1999; Korn et al., 1998; Peñuelas et al., 1998; Roth et al., 2002;

Usmani et al., 2005). Thus, LABAs may enhance GR translocation in human fibroblasts, smooth muscle, U937 and even sputum cells ex vivo (Eickelberg et al., 1999; Roth et al., 2002; Usmani

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134 et al., 2005). Furthermore, it has been suggested that LABAs can enhance GR translocation even in the absence of a GR agonist, through "ligand-independent" activation (Eickelberg et al., 1999).

However, LABAs do not effect the potency of glucocorticoids and do not demonstrate anti- inflammatory activity in vivo, but enhance GRE reporter activity in the presence of concentrations of glucocorticoids that induce translocation of all GR to the nucleus (Chivers et al., 2004; Howarth et al., 2000; Kaur et al., 2008; Lewis-Tuffin et al., 2007; Roberts et al., 1999).

Additionally, most of the proposed mechanisms by which LABAs enhance glucocorticoid activity do not explain how glucocorticoid-inducible genes can show substantially different patterns of enhancement following LABA addition (Holden et al., 2014; Kaur et al., 2008). The mechanisms by which LABAs enhance glucocorticoid activity were therefore investigated.

6.2 Hypothesis

The primary hypothesis of this chapter is that LABAs enhance glucocorticoid-inducible gene expression via mechanisms that do not involve generic effects, such as GR translocation, ligand binding or expression. Instead, mechanisms of enhancement that allow for gene-specific control are hypothesised to occur.

6.3 Results

6.3.1 Enhancement of Glucocorticoid Activity by Formoterol is Time-Dependent and Occurs through PKA Activation

BEAS-2B 2×GRE cells were treated with various concentrations of dexamethasone in the presence of 10 nM formoterol, a concentration that was maximally effective in enhancing

6×CRE reporter activation (Figure 6.1A) and cells were harvested 6 h later for luciferase assay

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(Figure 6.1B). Dexamethasone concentration-dependently enhanced 2×GRE activation to a maximum of ~18 fold. Formoterol had no significant effect on 2×GRE activation alone, but in combination with dexamethasone, synergistically enhanced reporter activation to ~340% of the dexamethasone response, i.e. a maximum of ~60 fold (Figure 6.1B).

Figure 6.1 Formoterol Time-Dependently Enhances Dexamethasone-Induced 2×GRE Activation. A) BEAS-2B 6×CRE cells were treated with the indicated concentrations of formoterol (Form) for 6 h and harvested for luciferase assay. B) BEAS-2B 2×GRE cells were treated with the indicated concentrations of dexamethasone (Dex) in the absence, or presence, of formoterol and harvested after 6 h for luciferase assay. C) BEAS-2B 2×GRE cells were treated with 10 nM formoterol, added at the indicated times relative to 1 μM dexamethasone (Dex) added at time 0. Cells were harvested 6 h after dexamethasone addition for luciferase assay. Data (n = 2-5), expressed as A & B) fold activation, or C) as a percentage of Dex activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with, B) Bonferroni’s correction for multiple comparisons made between treatments at each Dex concentration, or C) Dunnett's test versus Dex control. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

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To examine the effect of time of formoterol addition, BEAS-2B 2×GRE cells were treated with formoterol for up to 6 h before and 4 h after dexamethasone (1 μM) addition. In each case, cells were harvested 6 h after the dexamethasone addition for luciferase assay (Figure

6.1C). Dexamethasone-induced 2×GRE reporter activation was not significantly potentiated if formoterol was added more than 2 h before or after dexamethasone. However, formoterol addition 1 h before or 1 h after dexamethasone produced a significant 2 fold enhancement.

Nevertheless, maximal enhancement of ~300%, relative to dexamethasone alone, was achieved when formoterol was added within 15 min of dexamethasone (Figure 6.1C).

BEAS-2B 2×GRE cells were pre-treated for 30 min with H-89, to inhibit PKA, before addition of various concentrations of dexamethasone in the presence, or absence, of formoterol

(Figure 6.2A). H-89 had no effect on reporter activation alone, but completely reversed the enhancement of dexamethasone-induced 2×GRE activation by formoterol, suggesting a requirement for PKA activation. However, as H-89 may directly inhibit the β2-adrenoceptor

(Penn et al., 1999), BEAS-2B 2×GRE cells were pre-treated for 30 min with H-89, before addition of various concentrations of dexamethasone in the presence, or absence of forskolin, a direct activator of adenylyl cyclase (Seamon et al., 1981) (Figure 6.2B). H-89 reversed the dexamethasone-induced 2×GRE activation enhanced by forskolin, suggesting that reporter activity is potentiated by LABA through a PKA-dependent mechanism.

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Figure 6.2 Formoterol and Forskolin Enhance Dexamethasone-Induced 2×GRE Activation through PKA. BEAS-2B 2×GRE cells were left naïve or were pre-treated with 10 μM of the PKA inhibitor H-89, before addition of the indicated concentrations of dexamethasone (Dex) in the presence, or absence, of A) 10 nM formoterol (Form), or B) 10 μM forskolin (Forsk), a direct activator of adenylyl cyclase. Cells were harvested 6 h after Dex addition for luciferase assay. Data (n = 3), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons made between treatments at each Dex concentration. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

6.3.2 LABAs Do Not Enhance GR Protein Expression or Alter GR-Agonist Affinity

BEAS-2B cells were treated for 1, 2, 6 or 18 h with dexamethasone in the presence, or absence, of formoterol or salmeterol and total GR protein expression evaluated by western blot

(Figure 6.3). Dexamethasone had no effect at 1 and 2 h, but significantly decreased GR expression by approximately 50 and 80% at 6 and 18 h respectively. This effect was not modulated by LABAs, which had no significant effect on GR expression, either alone or in combination with dexamethasone.

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Figure 6.3 Effects of Dexamethasone and the LABAs Formoterol and Salmeterol on GR Protein Expression. A) BEAS-2B cells were either not stimulated (NS), or were treated with 1 μM dexamethasone (Dex) and/or 10 nM formoterol (Form) or 0.1 μM salmeterol (Salm). Cells were harvested after 1, 2, 6 and 18 h and western blotting for GR and GAPDH performed. Blots representative of 6 such experiments are shown. Densitometry was performed to generate data in lower panels. Data (n = 6), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by one-way ANOVA with Dunnett's tests versus NS at each time point. **, P < 0.01; ***, P < 0.001.

To examine the effects of clinically relevant glucocorticoid/LABA combinations on GR protein expression, BEAS-2B cells were treated with maximally effective concentrations of budesonide plus formoterol or fluticasone propionate plus salmeterol, for 6 h (Figure 6.4A)

(Holden et al., 2014; Kaur et al., 2008). Budesonide and fluticasone propionate reduced GR protein expression by 40-50%, but the LABAs had no significant effect either alone or on the repression of GR expression induced by the glucocorticoids. To examine the effects of partial glucocorticoid receptor agonists on GR protein expression, BEAS-2B cells were treated with

GW870086X or RU486 for 6 h (Figure 6.4B). GW870086X and RU486 only repressed GR

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139 protein expression by ~28 and 10% respectively and unlike the budesonide control, which decreased GR protein expression by ~40%, this did not reach significance (Figure 6.4B).

Figure 6.4 Effects of Clinically Relevant Glucocorticoid Plus LABA Combinations and Partial GR Agonists on GR Protein Expression. A) BEAS-2B cells were treated with 0.1 μM budesonide and/or 10 nM formoterol or 0.1 μM fluticasone propionate and/or 0.1 μM salmeterol, harvested after 6 h and western blotted for GR and GAPDH. B) BEAS-2B cells were treated for 6 h with 1 μM RU486, 0.1 μM GW870086 or 0.1 μM budesonide and western blotted for GR and GAPDH. Blots representative of A) 6-9, or B) 8, such experiments are shown. Densitometry was performed to generate graphs in lower panels. Data (n = 6-9, 8), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Dunnett's tests versus naïve controls. **, P < 0.01; ***, P < 0.001.

To investigate whether formoterol altered GR-agonist affinity, BEAS-2B 2×GRE cells were pre-treated for 30 min with dexamethasone-21-mesylate, an irreversible alkylator that covalently inactivates GR (Simons and Thompson, 1981), prior to addition of 1 μM dexamethasone or various concentrations of budesonide in the absence, or presence, of formoterol (Figure 6.5). Dexamethasone-21-mesylate had no effect on 2×GRE activation alone, but significantly decreased dexamethasone or budesonide induced reporter activation in the

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2010).

Figure 6.5 Effects of Formoterol on GR-Agonist Affinity. BEAS-2B 2×GRE cells were either not stimulated (NS) or were treated for 30 min with 10 nM dexamethasone-21-mesylate (DM), an irreversible alkylator that inactivates GR, prior to addition of the indicated concentrations of budesonide (Bud) or 1 μM dexamethasone (Dex), in the absence, or presence, of 10 nM formoterol (Form). Cells were harvested after 6 h for luciferase assay. Data (n = 5), expressed as fold, are plotted as means ± S.E. Most of the experiments were performed by Robert Newton.

6.3.3 Effects of Glucocorticoids and LABAs on GR Translocation

BEAS-2B cells were treated with dexamethasone for between 0.25 and 6 h and GR localization, relative to DAPI staining of the nucleus, determined using immunofluorescence microscopy (Figure 6.6). GR was predominantly cytoplasmic in untreated cells, but modest staining of the nucleus was also detected. However, following treatment with dexamethasone for between 0.25 and 6 h, GR immunofluorescence was predominantly localised to the nucleus.

These results are consistent with dexamethasone treatment rapidly inducing GR nuclear translocation, which is sustained for at least 6 h. Conversely, salmeterol did not induce nuclear

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Figure 6.6 Effect of Length of Dexamethasone Treatment on GR Localization. BEAS-2B cells were either not stimulated (NS) or were treated for between 0.25 and 6 h with 1 μM dexamethasone (Dex). Cells were harvested, fixed, stained with DAPI and an antibody against GR and subjected to confocal microscopy. Images representative of 3 such experiments are shown.

Figure 6.7 Effect of Length of Salmeterol Treatment on GR Localization. BEAS-2B cells were either not stimulated (NS) or were treated for between 0.25 and 6 h with 0.1 μM salmeterol (Salm) or for 1 h with 1 μM dexamethasone (Dex). Cells were harvested, fixed, stained with DAPI and an antibody against GR and subjected to confocal microscopy. Images representative of 3 such experiments are shown.

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To determine whether salmeterol affected dexamethasone-induced GR translocation,

BEAS-2B cells were treated for 1 h with maximally effective concentrations of dexamethasone, salmeterol or dexamethasone plus salmeterol (Figure 6.8). GR was localized throughout the cell in not-stimulated and salmeterol-treated cells, but was predominantly nuclear following dexamethasone or dexamethasone plus salmeterol treatment. The overlay between GR and DAPI staining was assessed in 5 images obtained from each treatment and quantified using Pearson product-moment correlation coefficient (Figure 6.8). There was no significant difference between not-stimulated and salmeterol-treated cells, but in dexamethasone and dexamethasone plus salmeterol treated cells GR and DAPI localization were significantly correlated.

Nevertheless, there was no significant difference in GR localization between dexamethasone and dexamethasone plus salmeterol treated cells, indicating that this LABA had no effect on GR translocation.

Figure 6.8 Effect of Dexamethasone and Salmeterol Treatment on GR Localization. BEAS-2B cells were either not stimulated (NS) or were treated for 1 h with 0.1 μM salmeterol (Salm) and/or 1 μM dexamethasone (Dex). Cells were harvested, fixed, stained with DAPI and an antibody against GR and subjected to confocal microscopy. Images representative of 3 such experiments are shown. Images were analysed using Volocity 3D image analysis software and pearsons correlation used to determine the overlap between GR (green) and DAPI (blue) staining. Pearson product-moment correlation coefficient values are plotted as means ± S.E. Significance versus NS: *** P < 0.001.

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Figure 6.9 Effect of Glucocorticoids and LABAs on GR Translocation. BEAS-2B cells were treated with 0.1 μM fluticasone propionate and/or 0.1 μM salmeterol or 0.1 μM budesonide and/or 10 nM formoterol for 1 h. A sample that was not fractionated was used as a control. Cytoplasmic and nuclear extracts were prepared and subjected to western blotting for GR, CREB (nuclear) and GAPDH (cytoplasmic). Blots representative of 6-7 such experiments are shown. Densitometry was performed on the cytoplasmic (GR/GAPDH) and nuclear (GR/CREB) extracts to generate the figures shown in lower panels. Data (n = 6-7), expressed as fold, are plotted as means ± S.E. Some experiments were performed by Dong Yan.

Cytoplasmic and nuclear fractions were isolated from cells treated with fluticasone propionate and/or salmeterol or budesonide and/or formoterol and assessed by western blotting for GR, CREB (nuclear protein control) and GAPDH (cytoplasmic protein control) (Figure 6.9).

CREB was only present in the nuclear fraction, while GAPDH protein was predominantly in the cytoplasmic fraction, suggesting successful fractionation. In naïve and LABA treated cells the majority of GR protein was in the cytoplasmic fraction. However, in cells treated with glucocorticoid or glucocorticoid plus LABA there was a substantial increase in GR within the nuclear extracts. This GR localization was not significantly altered in samples from LABA plus

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6.3.4 LABAs Enhance RU486-Induced 2×GRE Activation Without Affecting GR Localization

BEAS-2B cells were treated for 1 h with salmeterol, RU486 or RU486 plus salmeterol and GR localization assessed by immunofluorescence microscopy (Figure 6.10). GR localized throughout naïve and salmeterol treated cells, but accumulated in the nucleus of cells treated with RU486. However, nuclear localization did not increase following salmeterol addition to

RU486 treatment. Despite inducing apparently complete GR translocation into the nucleus,

RU486 alone was unable to significantly enhance 2×GRE reporter activity, inducing 1.45 fold activation at concentrations as high as 10 μM (Figure 6.10B). However, addition of 0.1 μM salmeterol significantly potentiated RU486 activity on the 2×GRE reporter, inducing up to 3.3 fold activation, an increase of ~220%. Likewise, RU486-induced 2×GRE reporter activation was significantly enhanced by treatment with formoterol (10 nM), the short acting β2-adrenoceptor agonist, salbutamol, or the direct adenylyl cyclase activator forskolin. Therefore, despite apparently inducing complete translocation of GR into the nucleus, RU486 activity on the

2×GRE reporter system was substantially enhanced by addition of a LABA or other cAMP inducing compound. These results suggest that LABAs do not potentiate glucocorticoid activity through enhancing GR translocation.

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Figure 6.10 Effects of RU486 Treatment on GR Localization and 2×GRE Activation. A) BEAS-2B cells were either not stimulated (NS) or were treated for 1 h with 0.1 μM salmeterol (Salm) and/or 1 μM RU486. Cells were harvested, fixed, stained with DAPI and an antibody against GR and subjected to confocal microscopy. Images representative of 2 such experiments are shown. B) BEAS-2B 2×GRE cells were treated with the indicated concentrations of RU486 in the absence, or presence, of 10 nM formoterol (Form). C) BEAS- 2B 2×GRE cells were either not stimulated (NS), or were treated with 1 μM RU486 and/or 10 nM Form, 0.1 μM Salm, 1 μM salbutamol (Salb) or 10 μM forskolin (Forsk). After 6 h cells were harvested for luciferase assay. Data (n = 6, 8), expressed as fold activation, are plotted as means ± S.E. Statistical analyses were performed by ANOVA, with B) Bonferroni’s correction for multiple comparisons made between treatments at each RU486 concentration, or C) Dunnett's tests versus NS. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

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6.3.5 Effects of Glucocorticoids and Formoterol on Expression of CDKN1C, DUSP1, RGS2 and TSC22D3 in BEAS-2B and Primary Lung Cells

BEAS-2B cells were treated for 1, 2, 6 or 18 h with budesonide and/or formoterol and harvested for RT-PCR analysis of CDKN1C, DUSP1, RGS2 and TSC22D3 mRNA expression

(Figure 6.11). Budesonide had no substantial effect at 1 or 2 h, but significantly enhanced

CDKN1C mRNA expression at 6 and 18 h. Formoterol did not induce CDKN1C mRNA expression at any time point, but significantly enhanced budesonide-induced CDKN1C expression at 2 and 6 h. Conversely, DUSP1 mRNA expression was time-dependently induced by both budesonide and formoterol, with formoterol significantly enhancing expression at 1 h and budesonide at 2, 6 and 18 h. Budesonide and formoterol appeared to additively induce

DUSP1 at 1 and 2 h, but expression was predominantly budesonide-dependent by 18 h. Although formoterol significantly enhanced RGS2 mRNA expression at 1 h, at 1, 2 and 6 h, budesonide plus formoterol synergized in inducing RGS2. However, formoterol had little effect on

TSC22D3 expression, which was primarily budesonide dependent at all times tested.

Similar results were obtained when the effects of dexamethasone and formoterol on gene expression were investigated in primary human bronchial epithelial (HBE) and airway smooth muscle (ASM) cells (Figures 6.12 and 6.13). However, although RGS2 was significantly potentiated by combination treatment, in ASM cells expression was predominantly driven by formoterol (as in BEAS-2B cells), while in HBE cells dexamethasone-induced significant expression at early time points. These results indicate that formoterol has different effects on various glucocorticoid-inducible genes and that the effects of glucocorticoid and LABA treatment on specific genes can differ between lung cell types.

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Figure 6.11 Effects of Formoterol on Budesonide-Inducible Putative Anti-Inflammatory Genes in BEAS-2B Cells. BEAS-2B cells were left naïve or were treated with 0.1 μM budesonide (Bud) and/or 10 nM formoterol (Form). Cells were harvested after 1, 2, 6 and 18 h and RT-PCR performed for CDKN1C, DUSP1, RGS2, TSC22D3 and GAPDH. Data (n = 6), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons, with comparisons made against naïve controls at each time point, as indicated. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

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Figure 6.12 Effects of LABAs on Dexamethasone-Inducible Gene Expression in Primary Human Bronchial Epithelial (HBE) Cells. HBE cells were left naïve or were treated with 1 μM dexamethasone (Dex) and/or 10 nM formoterol (Form) or 0.1 μM salmeterol (Salm). Cells were harvested after 1, 2, 6 and 18 h and RT-PCR performed for CDKN1C, DUSP1, RGS2, TSC22D3 and GAPDH. Data (n = 7), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons, with comparisons made against naïve controls at each time point, as indicated. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

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Figure 6.13 Effects of LABAs on Dexamethasone-Inducible Gene Expression in Primary Human Airway Smooth Muscle (ASM) Cells. ASM cells were left naive or were treated with 1 μM dexamethasone (Dex) and/or 10 nM formoterol (Form) or 0.1 μM salmeterol (Salm). Cells were harvested after 1, 2, 6 and 18 h and RT-PCR performed for CDKN1C, DUSP1, RGS2, TSC22D3 and GAPDH. Data (n = 8-9), expressed as fold, are plotted as means ± S.E. Statistical analyses were performed by ANOVA with Bonferroni’s correction for multiple comparisons, with comparisons made against naïve controls at each time point, as indicated. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

6.3.6 Budesonide and Formoterol Both Enhance and Repress Gene Expression in BEAS-2B Cells

Microarray analysis was performed on mRNA extracted from BEAS-2B cells treated for

1, 2, 6 or 18 h with budesonide and/or formoterol (Figure 6.14). An initial analysis indicated that a total of 1299 unique genes had ≥2 fold enhancement or ≤0.5 repression following treatment

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150 with budesonide, formoterol or the combination, at 1, 2, 6 or 18 h. All treatments induced a greater number of genes than they repressed at 1, 2 and 6 h, but the kinetics of gene expression for each treatment differed (Figure 6.14A). The greatest effects of formoterol on gene expression were apparent at 2 h, while modulation of gene expression by budesonide was maximal at later time points, with the highest levels of repression and induction seen at 6 and 18 h respectively.

Budesonide plus formoterol induced more genes by ≥2 fold than either of the monotherapies at each time point, with the number of genes induced peaking at 363 at 6 h. Likewise, budesonide plus formoterol treatment repressed the greatest number of genes at 18 h. The gene with the greatest induction by dexamethasone at 2 h was TSC22D3, but the expression of other potentially anti-inflammatory genes, including DUSP1, CRISPLD2, TNFα-induced protein

(TNFAIP)3, RGS2 and CDKN1C, was also significantly enhanced (Figure 6.14B).

To examine the effect of formoterol on budesonide-induced gene expression, induction by budesonide at each time point was normalized to 1 and the relative effect of formoterol addition assessed. Genes were then separated into three groups according to the effect of formoterol plus budesonide treatment relative to budesonide alone: "enhanced", "unchanged" and

"repressed" (Figure 6.15). The expression of greater than 50% of the genes induced by ≥2 fold by budesonide was enhanced by formoterol addition at 1 h. This percentage of enhanced genes subsequently decreased, though the absolute number peaked at 6 h. Conversely, the number of budesonide-inducible genes whose expression was repressed following formoterol addition was low at 1 h, highest at 2 h and declined at 6 and 18 h. The number of budesonide-inducible genes that were unchanged by formoterol addition increased with time, peaking at 18 h. The fact that the budesonide-induced expression of many genes was unchanged following formoterol addition

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151 argues against a generic mechanism of enhancement, such as translocation, which would be expected to, essentially universally, enhance gene expression.

Figure 6.14 Effects of Budesonide and Formoterol on Gene Expression in BEAS-2B Cells. BEAS-2B cells were left naïve or were treated with 0.1 μM budesonide (Bud) and/or 10 nM formoterol (Form). Cells were harvested after 1, 2, 6 and 18 h and subjected to microarray analysis using Affymetrix PrimeView chips. Data analysis was performed by robust multi- array averaging and ANOVA with a false discovery rate of ≤ 0.05. Probe sets induced or repressed by ≥2 fold at 1, 2, 6 or 18 h, by any treatment, were selected and merged according to gene name (total = 1299). A) Genes were plotted by fold value, with the mean and SD calculated for each treatment at each time point (upper panel). Genes induced or repressed by greater than 2 fold with each treatment and time point are plotted in the lower panel. B) A heat map was generated of genes induced or repressed by ≥8 fold (122 genes) by any treatment, at any time tested and ranked according to the effect of Bud treatment at 2 h. A magnified image of a selection of the top genes is shown.

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Figure 6.15 Effects of Formoterol on Budesonide-Induced Gene Expression. Genes from figure 6.14 induced by ≥2 fold following budesonide (Bud) treatment, were normalized to Bud and grouped according to the relative effect of Bud plus formoterol (Form) addition within each time point, as indicated. Genes were plotted as fold induction normalized to Bud treatment. 152

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6.4 Discussion

The results in this chapter suggest that LABAs enhance glucocorticoid-induced 2×GRE activation through a time-dependent mechanism, involving PKA, which does not affect GR expression, ligand binding or translocation. The requirement for close temporal stimulation with both a glucocorticoid and LABA to obtain maximal 2×GRE reporter activation, combined with the need for PKA activation, suggests a rapid and direct signalling effect, such as phosphorylation of one or more target proteins, rather than an indirect process (e.g. one involving the synthesis of new proteins). The PKA inhibitor, H-89, reduces phosphorylation of downstream targets of PKA, including CREB and ATF1 (Meja et al., 2004). Furthermore, a role for PKA in enhancement is supported by a study demonstrating that inhibition with cAMP protein kinase inhibitor (PKI)α reduced formoterol enhanced 2×GRE reporter activation by budesonide (Kaur et al., 2008). However, PKA phosphorylates a large number of protein substrates and the protein(s) whose phosphorylation enhances glucocorticoid activity have yet to be identified (Shabb, 2001).

The need for close temporal stimulation with both glucocorticoid and LABA to obtain maximal reporter activation supports the use of single asthma inhalers, containing both components, such as Advair and Symbicort (Giembycz et al., 2008). These devices increase the probability of both compounds being simultaneously delivered to individual cells and may have other advantages, such as increased patient compliance and reduced overall medical cost (Delea et al., 2008; Lundbäck et al., 2000; Markham et al., 2000; Stoloff et al., 2004).

Decreased GR expression following glucocorticoid treatment has been shown in numerous in vitro and in vivo studies and is suggested to occur through both transcriptional and post-transcriptional mechanisms (Brönnegård, 1996; Dong et al., 1988; Knutsson et al., 1996;

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Korn et al., 1997; Okret et al., 1986; Pujols et al., 2001; Ramamoorthy and Cidlowski, 2013). In the experiments detailed in this chapter, the decrease in GR expression appeared to be dependent on the intrinsic efficacy of the agonist, with reduced and no repression, relative to dexamethasone, induced by GW870086X and RU486 respectively (Figures 3 and 4). Likewise, treatment with TNF or PMA has been shown to have no effect on GR expression (Adcock et al.,

1996; Verheggen et al., 1996). Furthermore, in contrast with data suggesting that terbutaline, a

SABA, can enhance GR expression (Korn et al., 1998), addition of the LABAs formoterol or salmeterol had no effect on GR expression. This western blot data is supported by the microarray data, which revealed no effect of formoterol on budesonide induced repression of GR at 6 and 18 h (Table 1). Likewise, formoterol did not affect the affinity of budesonide for GR, as the EC50 of budesonide was not significantly affected by formoterol addition, but the EMax was reduced in line with the decreased number of functional GRs present following dexamethasone-21-mesylate treatment. Therefore, operational modeling indicated that the affinity of budesonide for GR was unchanged by formoterol (Black and Leff, 1983; Black et al., 2010).

In the immunofluorescence microscopy experiments, dexamethasone treatment appeared to increase GR fluorescence, potentially due to enhanced access of the primary antibody following a conformation change of the receptor and/or changes in cofactor protein binding.

However, these and the cell fractionation experiments collectively demonstrated that LABAs did not induce GR translocation, nor did they enhance the translocation induced by glucocorticoids.

The observation that LABAs do not affect GR translocation in this chapter, are not consistent with studies suggesting that LABAs enhance translocation (Eickelberg et al., 1999; Haque et al.,

2013; Roth et al., 2002; Usmani et al., 2005). While some discrepancy may be explained by the differences in cell type used, Usmani et al. 2005 used BEAS-2B cells in part of their study.

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Usmani et al. showed a significant increase in fluticasone propionate-induced GR translocation, following salmeterol addition, by western blot after cytoplasmic and nuclear fractionation of

BEAS-2B cells (Usmani et al., 2005). However, as in their experiments a significant amount of

GR was present in the nucleus in untreated cells, the nuclear loading control histone H1 band was very overexposed and no cytoplasmic control was provided, assessing the validity of these data is difficult (Usmani et al., 2005). Furthermore, despite these authors’ ability to generate immunofluorescence images showing GR localisation in the cytoplasm and nucleus, images showing enhanced translocation in the presence of combination treatments were not included in the paper. This is a significant omission and therefore, to the best of my knowledge, there is, at present, no credible evidence indicating that glucocorticoid-induced GR translocation is enhanced by LABAs in BEAS-2B cells.

Furthermore, my data shows that RU486 induced essentially complete GR translocation into the nucleus, as measured by immunofluorescence (Figure 6.10) (Chivers et al., 2004), but addition of the LABA formoterol mediated a ~2.3 fold increase in 2×GRE reporter activity

(Figure 6.10). This substantial increase in RU486-induced reporter activation following LABA addition cannot be explained by enhanced translocation, as there was already substantial amounts of inactive GR localised to the nucleus. Therefore, logic would suggest, rather than enhancing the translocation of those few GRs that were remaining in the cytoplasm, pathways activated by

LABAs may act on proteins associated with the cell transcriptional machinery to enhance transactivation by the ligand-bound GR that was present in the nucleus. Thus these data do not appear to support an enhancement of RU486-induced GR translocation by LABA.

In considering the changes in genes expression observed following glucocorticoid and/or

LABA treatment of BEAS-2B, HBE and ASM, enhanced translocation is also unlikely to explain

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156 the different patterns of enhancement of genes (Holden et al., 2014; Kaur et al., 2008). For example, DUSP1 showed apparently additive enhancement, while CDKN1C, which generally behaves like the 2×GRE reporter, and RGS2 were synergistically induced. However, TSC22D3 was predominately glucocorticoid-inducible and not significantly enhanced following LABA addition in BEAS-2B cells at 6 h (Figure 6.11). The patterns of enhancement of CDKN1C,

DUSP1, RGS2 and TSC22D3 seen in RT-PCR experiments, were similar to those in the budesonide/formoterol microarray study (Figure 6.14B). However, fold inductions on the microarray were substantially lower than those obtained by RT-PCR, as microarrays are subject to ratio compression (compare figures 6.11 and 6.14B) (Dallas et al., 2005; Wang et al., 2006c).

Therefore genes with fold values a little below the ≥2 fold or above the ≤0.5 cut offs on the microarray may, in fact, be significantly induced when measured by RT-PCR.

The microarray study revealed a number of budesonide-inducible genes, including

FKBP5, NFKBIA and SERPINE1, whose expression was unaffected by formoterol addition

(Figure 6.14B and Table 6.1). Importantly, CDKN1C, TSC22D3, FKBP5 and RGS2, have been demonstrated to be primary GR target genes in A549 cells (Wang et al., 2004a). These data are therefore not consistent with glucocorticoid activity being enhanced by LABAs through a global effect on translocation.

Many of the genes induced by budesonide in the microarray study have previously been shown to be induced by glucocorticoids in other microarray studies, including some genes that are proposed to have anti-inflammatory activity, such as NFKBIA, TNFAIP3 (A20) and ZFP36

(Table 6.1) (Altonsy et al., 2014; King et al., 2009a, 2013; Masuno et al., 2011; Misior et al.,

2009; Vandevyver et al., 2013). TNFAIP3 and NFKBIA inhibit NF-κB activation and activity respectively, while ZFP36 destabilises inflammatory mRNAs (Anderson, 2008; Auphan et al.,

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1995; Lai et al., 1999; Scheinman et al., 1995b; Verstrepen et al., 2010). Others, including the β2- adrenoceptor (ADRB2) and the prostaglandin E receptors 2 and 4 (PTGER2; PTGER4), showed modest induction, at least at early time points (Table 6.1) (Alexander et al., 2011). As PTGER2 and PTGER4 are, like the β2-adrenoceptor, Gs-linked GPCRs, activation by PGE2 in smooth muscle may induce bronchodilatation (Alexander et al., 2011; Benyahia et al., 2012; Buckley et al., 2011). Indeed, selective EP4 agonists induce bronchodilation of human lung samples following contraction with histamine or carbachol (Benyahia et al., 2012; Buckley et al., 2011).

Expression of PTGS2, which catalyzes the conversion of arachidonic acid to PGH2, was modestly induced by budesonide or formoterol treatment, but was synergistically enhanced by budesonide plus formoterol treatment (Table 6.1) (Ricciotti and FitzGerald, 2011). However, glucocorticoids can also repress PTGS2 expression induced by inflammatory mediators, including IL1B (Newton et al., 1998b). Whether increased PTGS2 activity is inflammatory or anti-inflammatory in asthma remains unclear (Ricciotti and FitzGerald, 2011). Nevertheless, budesonide inducible expression of many potentially anti-inflammatory genes, including

TNFAIP3, PTGER2/4 and ZFP36, was enhanced following formoterol addition (Figure 6.15,

Table 6.1). Likewise, formoterol induced expression of RGS2 and CRISPLD2, which decrease

Gq-linked GPCR-induced bronchoconstriction and IL1B-induced IL6 and CXCL8 expression respectively, was enhanced following budesonide addition (Table 6.1) (Himes et al., 2014;

Holden et al., 2011, 2014; Xie et al., 2012).

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Table 6.1 Effects of Budesonide and Formoterol on Expression of Select Genes.

Select genes were chosen from the microarray data presented in figure 6.14B. Values presented are fold on the microarray.

The microarray study also identified a number of genes, with potentially inflammatory properties, which were enhanced by LABA treatment (Figure 6.14 and Table 6.1). For example, the inflammatory cytokines IL6, chemokine ligand 2 (CCL2/MCP1) and chemokine (C-X-C motif) ligand 2 (CXCL2/MIP2α) were substantially formoterol inducible, but time-dependently

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159 repressed by dexamethasone (Al-Alwan et al., 2013; Wong et al., 2001). Likewise, the AP-1 transcription factor gene FOS, which has been associated with glucocorticoid resistance (Lane et al., 1998), was induced by formoterol, while both FOS and JUN were time-dependently repressed by budesonide (Table 6.1). The repression of LABA-induced inflammatory gene expression following addition of glucocorticoid may, in part, contribute to the reduced morbidity found in COPD patients taking glucocorticoid plus LABA combinations, compared to LABA monotherapy (Aaron, 2013; Kew et al., 2014; Nannini et al., 2012). However, glucocorticoids are not universally immunosuppressive and may act to prime the immune system for responses to pathogens (Galon et al., 2002; Sapolsky et al., 2000). For example, TLR4 and complement component 5 (C5), which detect lipopolysaccharide (LPS) and are involved in the complement cascade respectively, were induced at 18 h, potentially enabling enhanced immune responses to pathogens (Table 6.1) (Galon et al., 2002; Sapolsky et al., 2000).

Likewise, a number of genes with potentially detrimental effects on asthma control were induced following budesonide treatment, including cannabinoid receptor type 1 (CNR1), phospodiesterase 3A, cGMP-inhibited (PDE3A) and phosphodiesterase 4D, cAMP-specific

(PDE4D) (Table 6.1). Increased expression of PDE3A and PDE4D, which hydrolyse cAMP, may decrease cAMP concentrations in lung cells, potentially reducing the ability of LABAs to enhance glucocorticoid activity and decrease LABA-induced bronchodilation of ASM. Likewise,

CNR1 is a predominantly Gi-linked GPCR and was the gene with greatest induction by budesonide and budesonide plus formoterol at 6 and 18 h (Table 6.1) (Alexander et al., 2011;

Howlett et al., 2002). As Gi-linked GPCRs inhibit AC (Billington and Penn, 2003), activation of

CNR1 by endogenous agonists, such as anandamide and 2-arachidonoylglycerol, may reduce cAMP generation following β2-adrenoceptor activation. However, cannabinoids decrease LPS-

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160 induced cytokine production and mediate bronchodilation in vivo and in vitro, suggesting that they may couple to Gsα in the lung and hence may be beneficial in asthma treatment (Duncan et al., 2013; Grassin-Delyle et al., 2014; Howlett et al., 2002; Tetrault JM et al., 2007). Therefore, the effects of CNR1 agonists on LABA and glucocorticoid activity should be explored in subsequent experiments (Chapter 8).

A number of genes associated with glucocorticoid side-effects were not significantly induced by budesonide treatment on the budesonide/formoterol microarray, potentially because they are predominantly active in other tissues, such as the liver, including tyrosine aminotransferase (TAT), glucose-6-phosphatase (G6PC), glucose 6 phosphate transporters

(SLC37As) and PCK1 (data not shown) (Clark, 2007; Schäcke et al., 2002). Indeed, although

PCK1 expression may be increased by both glucocorticoids and cAMP elevating agents, including glucagon, which acts on a Gαs-linked GPCR, treatment with budesonide and/or formoterol did not mediate significant induction in BEAS-2B cells (data not shown) (Short et al.,

1986; Waltner-Law et al., 2003). This may reflect the differences in gene expression patterns in various cell types, potentially mediated by distinct splice forms of the glucocorticoid receptor

(Oakley and Cidlowski, 2011).

In summary, these data demonstrate that LABAs time-dependently enhance dexamethasone-induced 2×GRE activation through a mechanism that requires PKA activation.

Furthermore, LABAs do not appear to enhance glucocorticoid activity through effects on GR expression, ligand binding or translocation. Instead the data support mechanisms of enhancement that allow for gene specific control. Indeed, expression of individual glucocorticoid-inducible genes can be enhanced, unchanged and even repressed following formoterol addition. Further

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LABA is therefore warranted.

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Chapter Seven: General Discussion

7.1.1 GR Transactivation and Induced Hyporesponsiveness

Dogma states that glucocorticoids decrease anti-inflammatory gene transcription through transrepression, the direct inhibition of inflammatory transcription factors, while transactivation is responsible for inducing genes that contribute to side effects (Barnes, 2006b). However, there is mounting evidence for a significant role for anti-inflammatory genes induced through transactivation in glucocorticoid activity (De Bosscher and Haegeman, 2009; Clark et al., 2008;

King et al., 2013; Newton, 2014; Vandevyver et al., 2013). For example, IL1B-induced NF-κB reporter activation was only decreased by <40% by dexamethasone in A549 cells, while NF-κB- dependent nitric oxide synthase 2, inducible (NOS2), PTGS2, and CXCL8 protein production was reduced by 70-90% (Newton et al., 1998). Likewise, in BEAS-2B cells, NF-κB reporter activation was repressed by 13% following dexamethasone treatment, but CXCL8 release was repressed by 78% (Figure 5.8). Furthermore, repression of MAPK activation by glucocorticoids is reduced by inhibitors of transcription (actinomycin D) and translation (cycloheximide), demonstrating roles for post-transcriptional repression and new gene expression (King et al.,

2009a; Lasa et al., 2001; Newton et al., 2010). Indeed, greater than ~50% of the repression of

TNF-induced mRNA expression by glucocorticoids may occur through posttranscriptional suppression, to which glucocorticoid inducible proteins, such as ZFP36 (TTP), may contribute

(Clark, 2007; Fan et al., 2006). Likewise, repression of inflammatory gene expression by glucocorticoids occurs in part through enhanced DUSP1 expression and MAPK repression by dexamethasone is reduced in DUSP1 knockout mice (Abraham et al., 2006; Cho and Kim, 2009;

Diefenbacher et al., 2008; Jang et al., 2007; Joanny et al., 2012; Kang et al., 2008; King et al.,

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2009a). Other glucocorticoid inducible genes, including TSC22D3, CDKN1C and NFKBIA, have also been shown to contribute to the repression of MAPK, AP-1 and NF-κB activity

(Ayroldi et al., 2001, 2002; Chang et al., 2003; Eddleston et al., 2007; Marco et al., 2007;

Mittelstadt and Ashwell, 2001; Yang et al., 2008). Indeed, proving the impact of an individual gene on inflammation is often hampered by the considerable redundancy between glucocorticoid-inducible genes, which, while contributing to the effectiveness of glucocorticoids, makes demonstrating the importance of transactivation difficult (Abraham et al., 2006; Newton et al., 2010a; Yang et al., 2008). Nevertheless, many genes with potentially anti-inflammatory activity, including CDKN1C, DUSP1, NFKBIA, RGS2, TSC22D3 and ZFP36, were induced by budesonide in vivo, in bronchial biopsy samples taken from human volunteers (Figure 7.1)(Leigh et al., 2014), corroborating the findings of earlier studies in asthmatics (Essilfie-Quaye et al.,

2011; Kelly et al., 2012). Conversely, genes with potentially inflammatory activity, including

MMP13 and CCL2, were significantly repressed following inhalation of budesonide (Leigh et al., 2014; Mariani et al., 1998; Rose et al., 2003).

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Figure 7.1 Expression of Genes in Human Lung Biopsies Following a Single Dose of Inhaled Budesonide. A) Following screening, 12 volunteers were randomized to study Arm A or B, as indicated. On their first visit volunteers received either budesonide (Bud) or placebo, as indicated, and 5-6 h later a bronchoscopy was performed and lung biopsies obtained. Following a 2-3 week washout period, volunteers returned and received the second treatment, before a second bronchoscopy. B) Good quality RNA was extracted from 11 pairs of biopsy samples and analysed on Affymetrix PrimeView microarrays. Following robust multi-array averaging, statistical analysis was performed by one-way ANOVA, with a false discovery rate correction of P ≤0.05. A volcano plot, showing fold change of budesonide treatment versus placebo, against significance for each probe was generated and the position of selected probes marked with their gene name. C) Probes with a fold value of ≥2 or ≤0.05 were standardised across all volunteers by normalizing to a mean of zero and a standard deviation of one and a heatmap generated. Rows representing selected probes were marked with gene names. (Leigh et al., 2014). Bronchial biopsies were performed by Richard Leigh; Elizabeth M. King froze the biopsies and extracted some of the RNA used in the microarray; Curtis Dumonceaux screened study volunteers and coordinated the study.

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This thesis demonstrated that a number of genes with potentially anti-inflammatory activity, including CDKN1C, RGS2 and DUSP1, were induced by glucocorticoids in lung epithelial cells and airway smooth muscle (Chang et al., 2003; Holden et al., 2011; King et al.,

2009a, 2009a). However, the ability of glucocorticoids to induce activation of a 2×GRE reporter, which models the induction of potentially anti-inflammatory genes, was reduced by inflammatory mediators associated with glucocorticoid resistance (Creed et al., 2009; Grünberg et al., 2001; Papi et al., 2013; Pariante et al., 1999; Szatmáry et al., 2004; Tliba et al., 2006,

2008; Webster et al., 2001), including TNF, IL1B, poly(I:C) and human rhinovirus. Furthermore, cytokine pre-treatment reduced the expression of glucocorticoid-inducible genes, including

CDKN1C, RGS2, ZFP36, DUSP1 and TSC22D3. However, proving that reduced expression of glucocorticoid-inducible genes contributes to glucocorticoid resistance is difficult.

Glucocorticoid resistance in vitro is typically shown by treating cells with inflammatory stimuli and then demonstrating that induced inflammatory gene expression is not repressed by glucocorticoid addition (Salem et al., 2012; Tliba et al., 2006; Zijlstra et al., 2012). However, to demonstrate a role for transactivation a second inflammatory stimulus is needed that does not affect the inflammatory gene transcription output, but decreases glucocorticoid-inducible gene expression. Unfortunately, we have not identified an experimental system allowing this study to be performed. Therefore, the impact of induced glucocorticoid hyporesponsiveness is currently difficult to quantify and in need of further investigation. However, studies indicating the importance of glucocorticoid-inducible genes in glucocorticoid activity (Abraham et al., 2006;

Auphan et al., 1995; Ayroldi et al., 2001; Chivers et al., 2004, 2006; Holden et al., 2011; Lai et al., 1999; Xie et al., 2012), suggest that glucocorticoid hyporesponsiveness may have detrimental effects in conditions such as asthma.

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7.1.2 Mechanisms Underlying the Modulation of Glucocorticoid Activity

Substantial differences in the timing of repression of the 2×GRE reporter system were seen with different inflammatory stimuli (Chapters 3 and 4). For example, TNF or PMA treatment induced a rapid decrease in dexamethasone-induced reporter activation, with pre- treatment for 0-2 and 1-2 h respectively, inducing repression. U46619 induced significant repression after pre-treatment for between 2 and 18 h. However, short (1-2 h) pre-treatment with rhinovirus or poly(I:C) treatment had no effect on reporter activity induced by glucocorticoid and significant repression was only seen following 18 and 6 or 24 h pre-treatment respectively. The time required for HRV to induce glucocorticoid hyporesponsiveness suggests that, rather than the rapid activation of signalling pathways, host cell recognition of the viral genome and/or replication are required. Likewise, the long incubation time of poly(I:C) prior to repression of reporter activation suggests a need for slow, stimulus-dependent changes. For example, rhinovirus or poly(I:C) may induce the production of secondary inflammatory mediators, such as

TNF (Cui et al., 2013; Laza-Stanca et al., 2006), which then induce glucocorticoid hyporesponsiveness in an autocrine manner. Alternatively, substantial transcription of host defence or inflammatory genes, including CCL5, CXCL10 or CXCL8 (Figure 4.8) (Edwards et al., 2006; Skevaki et al., 2009; Spurrell et al., 2005), could result in transcriptional squelching, through competition for core transcriptional proteins, such as RNA polymerase II (Cahill et al.,

1994; Lin et al., 2007; Meyer et al., 1989). This may, in part, explain the results obtained in figure 4.6, where 30 h of poly(I:C) incubation repressed the activation of the constitutive SV40 and TATA driven reporter systems.

Inflammatory mediators shown to induce glucocorticoid hyporesponsiveness may also induce activation of transcription factors and substantial gene expression. For example, IL1B and

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TNF activate transcription factors, including AP-1 and NF-κB, leading to substantially enhanced gene expression (Ammit et al., 2002; Holden et al., 2004; King et al., 2013). The increase in cytokine-induced gene expression may monopolise core transcription factors such as RNA polymerase II (Cahill et al., 1994; Lin et al., 2007; Meyer et al., 1989), reducing their availability for transcription of glucocorticoid-inducible genes. Therefore, transcriptional squelching could, at least in part, contribute to glucocorticoid resistance or hyporesponsiveness induced by many inflammatory mediators, by reducing glucocorticoid-inducible gene expression. If squelching was the mechanism underlying induced hyporesponsiveness, the response to glucocorticoids would be expected to vary between different cell types depending on the expression of GR, polymerase II and other co-regulatory proteins (Biola et al., 2001; Szapary et al., 1999). Indeed,

GR expression in cells affects sensitivity to glucocorticoids (Gehring et al., 1984). Nevertheless, transcriptional squelching may not contribute to all induced hyporesponsiveness, as incubation with TNF for 7 h had no effect on TATA or SV40 reporter activation (Figure 3.2). However, it is unclear whether longer incubations with TNF would affect the TATA or SV40 reporter systems

(e.g. 30 h as was tested with poly(I:C), figure 4.6) and hence whether transcriptional squelching has a role in TNF-induced hyporesponsiveness.

Alternatively, transrepression of activated transcription factors, such as NF-κB and AP1 by GR, could lead to sequestration of GR, reducing the amount of free ligand-bound GR available for transactivation (Schüle et al., 1990; Verheggen et al., 1996). Inhibition of transcription factors, such as NF-κB, could reduce inflammatory gene transcription, potentially freeing transcriptional machinery for induction of genes by GR. Indeed, inhibition of NF-κB and

JNK MAPK, which can activate AP-1, partially reversed induced hyporesponsiveness following

TNF treatment (Figure 5.9). Alternatively, the modest reversal induced by inhibition of these

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168 transcription factors may simply indicate that NF-κB and JNK MAPK are directly involved in mediating TNF-induced glucocorticoid hyporesponsiveness. However, NF-κB and JNK MAPK inhibition had no effect on poly(I:C)-induced hyporesponsiveness (Figure 5.10), suggesting that hyporesponsiveness may also be induced through mechanisms that do not require activation of these transcription factors.

Another mechanism of glucocorticoid resistance in asthma may be increased expression of GRβ, which is proposed to act as a dominant negative inhibitor of GRα, through mechanisms potentially including competing for GRE binding sites and/or forming heterodimers with GRα, that are less transcriptionally active (Bamberger et al., 1995; Christodoulopoulos et al., 2000;

Goleva et al., 2006; Hamid et al., 1999; Tliba et al., 2006; Webster et al., 2001). GRβ expression may be increased by inflammatory stimuli associated with glucocorticoid resistance, including

TNF, IL1B and IL17 (Vazquez-Tello et al., 2010, 2013; Webster et al., 2001). However, consistent with published reports, initial studies suggest that GRβ expression is very low in

BEAS-2B cells relative to GRα (Pujols et al., 2001). Furthermore, the GR antibody used in this thesis is raised against an epitope consisting of residues 346-367 in the N-terminal domain of GR and will therefore recognise both GRα and β. RT-PCR using N-terminal domain directed primers and western blotting reveal a modest increase in GR expression following treatment with IL1B or TNF, but this is abrogated in the presence of dexamethasone at 6 h (C. Rider and B.

Borthakur, unpublished observations). Additionally, studies demonstrating dominant negative activity of GRβ, utilized expression constructs and may therefore reflect transcriptional squelching effects (Bamberger et al., 1995; Oakley et al., 1996). Given the low expression level of GRβ and controversy surrounding its dominant negative activity, it is unlikely that GRβ

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169 contributes to induced glucocorticoid hyporesponsiveness (Gagliardo et al., 2000, 2001; Hecht et al., 1997; Pujols et al., 2001).

GR activity can be affected by modifications, including acetylation, ubiquitination and

SUMOlation, but most research has focused on phosphorylation (Beck et al., 2009; Le Drean et al., 2002; Ito et al., 2006; Wang and DeFranco, 2005). Phosphorylation may contribute to repression of glucocorticoid activity induced by factors, such as MAPK activation or treatment with TNF and IFNγ (Bouazza et al., 2012; Irusen et al., 2002; Itoh et al., 2002; Kino et al., 2007;

Miller et al., 2005a; Rogatsky et al., 1998). For example, JNK MAPK has been suggested to phosphorylate GR, decreasing glucocorticoid activity (Chen et al., 2008; Itoh et al., 2002;

Rogatsky et al., 1998). Since inhibition of JNK MAPK partially reversed TNF-induced glucocorticoid hyporesponsiveness (Figure 5.9), the mechanism underlying repression of glucocorticoid activity may involve modulation of GR phosphorylation. Indeed, in addition to effects on reporter activation, GR phosphorylation has been reported to affect recruitment to the

TSC22D3 gene promoter (Blind and Garabedian, 2008). Thus altered phosphorylation could potentially underlie the repression of dexamethasone-induced TSC22D3 expression following

TNF treatment (Figures 3.10 and 5.7). However, phosphorylation does not affect RSV-induced repression of GR transactivation, suggesting that other mechanisms capable of inducing hyporesponsiveness may exist (Webster Marketon and Corry, 2013).

Although limited to a single inflammatory stimulus, the microarray results presented in figure 3.11 indicate a variety of effects of IL1B treatment on individual dexamethasone-induced genes. This suggests that repression of glucocorticoid activity by IL1B may be gene dependent, as was found for enhancement of glucocorticoid activity by LABA (Chapter 6). The mechanisms underlying the PKA-dependent enhancement of glucocorticoid-induced 2×GRE activation by

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LABAs are unclear, but are likely to take place in the nucleus, potentially through phosphorylation of co-regulators (coactivators or co-repressors) and/or core transcriptional machinery. For example, PKA may phosphorylate nuclear receptor coactivator 2 (NCOA2;

GRIP1) enhancing transactivation by the estrogen receptor (Fenne et al., 2008). Likewise, activation of PKA indirectly leads to phosphorylation of nuclear receptor coactivator 1 (NCOA1;

SRC-1), which enhanced progesterone receptor (PR) mediated reporter activation, through interaction with CREB binding protein (Rowan et al., 2000). Conversely, the stable cAMP analog 8-bromo-cAMP enhances PR transcriptional activity, through decreasing interactions between PR and the co-repressors nuclear receptor corepressor 1 (NCOR1) and 2 (NCOR2;

SMRT) (Wagner et al., 1998). Conceivably, differences in recruitment of co-regulator proteins to particular GREs, following phosphorylation by PKA, could, therefore, lead to gene specific enhancement of GR mediated transcription.

The most effective approach to overcoming TNF-mediated repression of glucocorticoid- induced 2×GRE activation was addition of a LABA, which potentiated reporter activation, functionally reversing the cytokine-induced glucocorticoid hyporesponsiveness (Figure 5.2).

However, TNF still decreased reporter activation relative to the level induced by glucocorticoid plus LABA. This suggests that the effects of LABAs and TNF may occur through different mechanisms.

7.1.3 Effects of Glucocorticoid Receptor Agonists on Reporter Activation and Gene Expression

The effects of various glucocorticoid receptor agonists were examined on the 2×GRE reporter system (Chapter 5). The major finding was that despite variations in the intrinsic activity

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171 of the agonists on the 2×GRE reporter system, activity was universally repressed by TNF.

Indeed, the repression mediated by TNF was proportional to the EMax of reporter activation by the agonist (Figure 5.6). However, differences in intrinsic activity were only apparent on the mRNA expression of RGS2 and to a lesser extent TSC22D3 (Figure 5.7). While the mechanisms underlying differences in expression of particular genes is currently unclear, they may result from differences in the transcriptional complexes that assemble at the promoters of individual genes. This suggests that it may be possible to tailor glucocorticoid receptor agonists, such that a subset of genes are expressed (van der Laan and Meijer, 2008; Wang et al., 2006a). For example, if expression of genes associated with the side effects of glucocorticoid treatment were dependent on the efficacy of the agonist, then lower efficacy agonists may be preferable.

Conversely, if expression of potentially anti-inflammatory or anti-asthma genes, such as RGS2 and TSC22D3, was dependent on agonist efficacy, then agonists with higher efficacy may be preferable. Many compounds recently developed by pharmaceutical companies, including fluticasone furoate and AZD5423, appear to behave as very full agonists on 2×GRE reporter systems (Chapter 5 and R. Newton unpublished data) (Biggadike et al., 2008; Norman, 2013;

O’Byrne et al., 2013; Salter et al., 2007). This suggests that pharmaceutical companies may have data indicating improved outcomes with fuller agonists and indeed trials of non-lipophilic indazole SEGRAs, which may have reduced efficacy, by GSK appear to have been halted (Diallo et al., 2011; Norman, 2013).

The activity of glucocorticoid receptor agonists on the 2×GRE reporter was potentiated by LABA addition in line with intrinsic activity (Figure 5.6). Likewise, although enhanced by

LABA addition, mRNA expression of RGS2 and TSC22D3 was dependent on agonist efficacy, indicating that LABA plus glucocorticoid combination therapy may be most effective when

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172 fuller agonists are used (Figure 5.7). LABA addition also enhanced glucocorticoid-induced gene expression in primary human bronchial epithelial and airways smooth muscle cells (Figures 6.12 and 6.13). Likewise, in induced sputum samples taken from asthmatics, a combination of 80 μg budesonide plus 4.5 μg formoterol induced significantly enhanced GRE activity relative to 200

μg budesonide (Essilfie-Quaye et al., 2011). The combination also significantly enhanced DUSP-

1 expression (as did 400 μg budesonide), while 200 μg budesonide alone was not significant compared to placebo. This indicates that addition of LABA to a low dose glucocorticoid is more effective at enhancing the expression of DUSP1 in vivo than doubling the dose of glucocorticoid.

This is consistent with the results of clinical studies on combination therapy, which indicate that addition of a LABA is more effective than doubling glucocorticoid dose (Bateman et al., 2008;

O’Byrne et al., 2001; Pauwels et al., 1997).

Formoterol addition enhanced, repressed or had no substantial effect on the expression of different genes induced by budesonide, as measured by microarray, indicating that LABAs do not simply potentiate all aspects of glucocorticoid activity (Figures 6.14 and 6.15). Both budesonide and formoterol induced greater fold induction than repression of genes, while the greatest effects on gene expression at each time point were produced by budesonide plus formoterol treatment (Figure 6.14A). Budesonide treatment induced an expanded number of genes by ≥2 fold with increasing time. However, while greater than 90 genes were induced by ≥2 fold following formoterol treatment at 1, 2 and 6 h, only 10 were enhanced at 18 h. Likewise, the number of genes induced by budesonide plus formoterol decreased at 18 h, relative to 6 h. At 1 h, expression of 56% of budesonide-induced genes was enhanced by formoterol, but this decreased to 35% at 6 h and 17% at 18 h (Figure 6.15). The number of budesonide-induced

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173 genes whose expression was decreased by formoterol peaked at 17% at 2 h, before decreasing to

10% at 18 h.

Repression of gene expression increased over time and by 18 h more genes were repressed than were enhanced by budesonide treatment (Figure 6.14). While this may reflect decreased transactivation due to feedback mechanisms, such as decreased GR expression, GR may also bind to nGREs decreasing gene expression (Dong et al., 1988; Knutsson et al., 1996;

Surjit et al., 2011). However, such nGRE sites appear to have sequences unrelated to GREs, potentially explaining why GREs are not normally associated with repressed genes (So et al.,

2007, 2008; Surjit et al., 2011). Nevertheless, an analysis of GR binding and gene expression previously indicated that down-regulation of genes occurred independently of proximal GR-

DNA binding and was delayed relative to gene activation (Reddy et al., 2009). This is consistent with the finding that in A549 cells pre-treated for 2 h with IL1B, prior to dexamethasone addition for 2 or 4 h, the number of genes repressed by dexamethasone increased with time

(Figure 3.11).

7.1.4 Development and Implementation of Optimal Therapy

The data in this thesis are potentially relevant to the development of optimal asthma therapy. For example, data in chapter 5 indicate that the development of dissociated compounds, otherwise known as SEGRAs, may be inadvisable (Newton and Holden, 2007). Firstly, it is questionable whether true dissociation can be achieved, as at least the early dissociated compound RU24858 appeared to induce transactivation, enhancing MMTV and GRE reporter activation and inducing genes, such as TSC22D3, DUSP1 and metallothionein 1X (Chapter 5)

(Belvisi et al., 2001; Eberhardt et al., 2005; Janka-Junttila et al., 2006; Newton et al., 2010;

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Tanigawa et al., 2002). Likewise the anti-inflammatory activity of two newer SEGRAs also appears to be, at least in part, mediated through DUSP1 activation (Joanny et al., 2012). The induction of genes is likely to reflect the limitations of negatively screening compounds using

GRE reporters, or a limited repertoire of glucocorticoid-inducible genes (Clark and Belvisi,

2012). GRE reporters do not adequately model the complexity of real glucocorticoid inducible genes, as considerable variation exists in the sequence and distribution of GR binding sites relative to induced genes (Reddy et al., 2009; So et al., 2007, 2008; Wang et al., 2004a).

Additionally, gene expression may be effected by other factors, which may differ between cell types, such as chromatin structure (Hakim et al., 2009; John et al., 2008, 2011; Wiench et al.,

2011).

The majority of dissociated compounds developed to date appear to be partial agonists on the glucocorticoid receptor (Chapter 5) (Clark and Belvisi, 2012; Joanny et al., 2012). While this partial agonism may be intentional, reflecting the screening strategies used, these compounds may have reduced anti-inflammatory activity relative to full agonists (Figure 5.8) (Joanny et al.,

2012; Rider et al., 2014). This is likely to reflect the reduced ability of these compounds to induce the expression of genes with anti-inflammatory properties (Chapter 5). Furthermore, the use of these compounds in combination therapy may be suboptimal, as activity in combination with a LABA appears to be linearly related to GR agonist efficacy (Figure 5.6).

Recently pharmaceutical companies have developed a range of non-steroidal glucocorticoid receptor agonists (Diallo et al., 2011; Joanny et al., 2012; Mohler et al., 2007;

Norman, 2013; O’Byrne et al., 2013; Schäcke et al., 2008). While many of these compounds are designed as SEGRAs, with the limitations described above, at least AZD5423 appears to behave as a full agonist, possibly even a super agonist (R. Newton, unpublished data). The development

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175 of non-steroidal full GR agonists appears promising, as this may enable greater tailoring of interactions with co-factors and selective gene expression. This could potentially lead to the development of compounds that show differential partial activity on different sets of genes. If expression of different sets of genes could be tailored, this may allow optimal treatment of specific inflammatory diseases. The tailoring of compounds may be enhanced by screening strategies incorporating transcriptomics (microarray/RNA seq) and proteomics based secondary screening of compounds in multiple cell types. Furthermore, incorporating analysis of effects on gene expression and inflammation in combination with LABAs may facilitate the development of optimal combination therapy for asthma and COPD (Giembycz et al., 2008). Compound development could be improved by a greater understanding of the beneficial and potentially detrimental effects of glucocorticoid inducible genes in the context of specific diseases (Newton,

2014). Furthermore, an improved understanding of gene and protein expression in "normal" lungs, may at some point enable personalized medicine aimed at restoring "normal" protein signatures. Another approach to improve therapy may be the development of novel combination therapies, comprising a glucocorticoid and a compound that enhances cAMP production, such as selective prostacyclin (PGI2), E2/4 (PTGER2, 4), adenosine A2B receptor agonists or PDE inhibitors (Giembycz and Maurice, 2014; Greer et al., 2013; Kaur et al., 2008; Moodley et al.,

2013). Indeed, a selective A2B receptor agonist and the prostacyclin mimetic taprostene, enhanced glucocorticoid-inducible gene expression (Greer et al., 2013; Wilson et al., 2009).

Likewise, roflumilast, which inhibits PDE4 reducing the breakdown of cAMP, potentiated glucocorticoid-induced 2×GRE activation and significantly enhanced RGS2 and CDKN1C expression induced by fluticasone propionate plus formoterol (Moodley et al., 2013).

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Work presented in this thesis indicated that specific small molecule inhibitors of the NF-

κB and JNK MAPK pathways may be beneficial in reversing TNF-induced glucocorticoid hyporesponsiveness (Figure 5.9). Inhibition of these pathways has also been shown to partially reverse glucocorticoid resistance induced by rhinovirus (Papi et al., 2013). As the NF-κB and

JNK MAPK pathways are activated by multiple inflammatory stimuli, their inhibition is likely to be independently beneficial in reducing inflammatory mediator expression (Holden et al., 2007,

2008; Neuschäfer-Rube et al., 2013; Sakurai et al., 2003; White et al., 2008; Xia et al., 2000). As well as decreasing inflammatory responses, this may reduce glucocorticoid hyporesponsiveness

(Birrell et al., 2005; Papi et al., 2013; Wang et al., 2004b). Therefore, short term inhibition of

NF-κB and/or MAPK pathways in lung cells may be beneficial during exacerbations. However, inhibition of these pathways may induce side effects, increase inflammation due to dysregulation of feedback mechanisms and may suppress the induction of interferons, which may be beneficial during viral infections (Contoli et al., 2006; Lavon et al., 2000; Lawrence et al., 2001; Wark et al., 2005). As induction of IFNβ and γ appears to be NF-κB- and potentially JNK MAPK- dependent, this could potentially increase the duration and/or severity of infection (Chu et al.,

1999; Thanos and Maniatis, 1995).

The data in this thesis have implications for the treatment of chronic inflammatory diseases, including asthma and COPD. For example, the finding that close temporal stimulation with both glucocorticoid and LABA is needed to obtain maximal reporter activation, supports the use of single asthma inhalers containing both components, such as Advair and Symbicort

(Barnes, 2002; Giembycz et al., 2008). These inhalers increase the probability of both glucocorticoid and LABA being simultaneously delivered to individual cells and may have other advantages, including increased patient compliance and reduced overall cost (Delea et al., 2008;

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Lundbäck et al., 2000; Markham et al., 2000; Stoloff et al., 2004). Furthermore, the data presented supports the use of fast acting LABA plus glucocorticoid therapies, such as SMART

(Symbicort for Maintenance and Reliever Therapy), as by providing extra glucocorticoid and

LABA during the initial stages of exacerbations, such therapy may decrease inflammation and hence the likelihood of developing glucocorticoid resistance (Edwards et al., 2010; Kuna et al.,

2007; Lundborg et al., 2006; Peters, 2009). Furthermore, while step down from combination to glucocorticoid monotherapy is encouraged by current guidelines in patients with good asthma control, the data in this thesis provide a rationale for the decreased disease control found in studies of patients who step down to glucocorticoid monotherapy (Brozek JL et al., 2012;

Hagiwara et al., 2010; Koenig et al., 2008). Instead, treating uncontrolled asthmatics with higher dose combination therapy and then stepping-down to lower dose combinations may be more effective (Cheng et al., 2013; Papi et al., 2012). Substantially decreasing lung inflammation with the initial aggressive therapy may combat induced hyporesponsiveness and thereby increase responsiveness to the lower doses of glucocorticoid in the subsequent combination therapy.

Furthermore, providing patients with higher dose combination therapy (in addition to lower dose regular therapy) "step-up, short term" or encouraging greater inhaler use "adjustable maintenance dosing" during exacerbations, may prove beneficial (Aalbers et al., 2004; Ind et al., 2004;

Thomas et al., 2011).

7.1.5 Overall Conclusions

In summary, the data in this thesis indicate that inflammatory mediators reduce the ability of glucocorticoids to induce 2×GRE reporter activation and the expression of genes with putative anti-inflammatory properties, a situation referred to as glucocorticoid hyporesponsiveness. As

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178 there is increasing evidence demonstrating that transactivation is important for glucocorticoid activity, repression of glucocorticoid-inducible gene expression by inflammatory mediators may decrease glucocorticoid activity and potentially contribute to glucocorticoid resistance. However, the data in this thesis also suggest a number of avenues for overcoming TNF-induced glucocorticoid hyporesponsiveness, including inhibition of the NF-κB or JNK MAPK pathways and addition of LABAs, which potentiate glucocorticoid activity. While the mechanisms underlying the enhancement of glucocorticoid-inducible gene expression by LABAs remain unclear, the data in this thesis support a nuclear mechanism allowing for gene specific control.

Furthermore, conclusions drawn from the data in this thesis may contribute to the development of improved strategies for combating glucocorticoid resistance during exacerbations and in severe asthma. Additionally, this work may contribute to an improved understanding of how

LABAs and glucocorticoids interact, paving the way for further studies.

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Chapter Eight: Further Work

The data and analysis highlighted in this thesis presents several areas for further experimentation.

1. A prominent limitation of this thesis is that much of the work was performed in the immortalized BEAS-2B and A549 cell lines. A number of key experiments, for example to demonstrate repression of glucocorticoid-inducible gene expression by TNF or enhancement by formoterol, were therefore repeated in primary human bronchial epithelial or airway smooth muscle cells. Nevertheless, further experiments could be performed in primary cells, including those investigating the effects of rhinovirus or poly(I:C) on glucocorticoid-inducible gene expression. Further experiments could also be performed in a more physiologically relevant system, for example using multiple lung cell types in an air-liquid interface culture. However, experiments conducted in isolated cell types do not fully recapitulate the complexity of living systems and therefore ideally key experiments would, ethics permitting, be performed in model animals and/or humans.

2. The results obtained using poly(I:C) suggest that the generation of dsRNA during rhinovirus replication may induce glucocorticoid hyporesponsiveness (Chapter 4). Cells could be treated with synthetic single-stranded RNA or DNA mimetics to confirm whether glucocorticoid hyporesponsiveness was specific to dsRNA. Furthermore, the specific receptors involved in the response to dsRNA could potentially be determined through siRNA mediated knockdown. To confirm that rhinovirus replication was necessary for induction of glucocorticoid

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180 hyporesponsiveness, experiments could be conducted using UV irradiated rhinovirus (Wang et al., 2009).

3. Rhinovirus and poly(I:C) induced GR hyporesponsiveness only after many hours of pre- incubation (Chapter 4). One possible mechanism, which could contribute, is the generation of factors, such as cytokines, which can act in an autocrine manner to reduce dexamethasone- induced 2×GRE activation. The effects of soluble factors could be determined by generating

'conditioned medium' from cells incubated with rhinovirus or poly(I:C) and adding this to

2×GRE cells prior to dexamethasone treatment. If glucocorticoid activity was unaffected by treatment with conditioned medium, this could suggest that transcription, protein expression or other processes induced by rhinovirus or poly(I:C) induces glucocorticoid hyporesponsiveness.

However, if treatment with conditioned medium reduced 2×GRE activation, the medium could be screened to determine the factors present using ELISAs or a multiplex technique, such as

Luminex cytokine panels (www.luminexcorp.com/). Alternatively, the conditioned medium could be screened using mass spectrometry, potentially enabling detection of novel factors not currently included in Luminex screens. Specific antibodies could be used to deplete the conditioned medium of particular mediators, prior to addition to 2×GRE cells, to determine whether removal reduced glucocorticoid hyporesponsiveness.

4. Experiments using the inhibitors PS1145 and JNK inhibitor VIII suggested roles for NF-κB and JNK MAPK respectively in TNF-induced glucocorticoid hyporesponsiveness (Figure 5.9).

However, the inhibitors had no effect on the TNF-induced repression of CDKN1C or TSC22D3 expression (Figure 5.13). The effects of these inhibitors could be evaluated on the expression of

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181 other glucocorticoid-inducible genes showing repression by TNF or potentially IL1B, using either RT-PCR or further microarrays.

5. Numerous variants of the glucocorticoid receptor protein are generated due to the presence of alternative start and splicing sites in the glucocorticoid receptor gene (NR3C1) (Oakley and

Cidlowski, 2011; Pujols et al., 2007; Zhou and Cidlowski, 2005). However, with the possible exception of GRβ (Bamberger et al., 1995; Oakley et al., 1996), little is known about this diversity of GR proteins. The expression of different GR proteins could potentially be examined in different cell types using western blotting with antibodies raised against various GR epitopes or possibly using mass spectrometry. Expression of distinct GR receptors in different cell types may alter interactions with individual GREs, potentially contributing to variation in gene expression. Differences, and similarities, in gene expression between cell types could be examined by microarray, but may be complicated by differences in the expression of other proteins, miRNAs or epigenetic modifications. Therefore, an alternative approach could be to express modified GR gene sequences in a particular cell type and examine the effects on gene expression using RT-PCR, microarrays or sequencing.

Expression of multiple GR proteins simultaneously in individual cells may also alter gene expression. For example, inflammatory stimuli, including TNF, may decrease the activity of

GRα by increasing GRβ expression (Tliba et al., 2006; Webster et al., 2001). The effects of TNF on GRβ expression in BEAS-2B cells could be determined using GRβ specific RT-PCR primers and antibodies. If GRβ expression was shown to be increased by inflammatory treatment, the impact on glucocorticoid activity could be determined using techniques such as GRβ overexpression and knockdown. Likewise, the effect of TNF on translocation of GR could be

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182 assessed using immunofluorescence microscopy or cellular fractionation with regular or GRβ specific antibodies.

Changes in GR phosphorylation may also, at least in part, underlie the glucocorticoid hyporesponsiveness induced by inflammatory stimuli, such as TNF, and the enhancement of glucocorticoid activity following LABA addition (Blind and Garabedian, 2008; Bouazza et al.,

2012; Haske et al., 1994; Kumar and Calhoun, 2008). Commercial antibodies have been developed against the three most studied GR phosphorylation sites, S203, 211 and 226. Western blotting could be performed using these phospho-specific antibodies to determine whether any changes in GR phosphorylation were induced by treatment with glucocorticoids, LABAs or inflammatory stimuli. The effects of these phosphorylation sites on GR activity could then be tested, through techniques including mutating the sites. Alternatively, GR could be immunoprecipitated and then subjected to phosphorylation analysis by mass spectroscopy. If chemical crosslinking were performed prior to immunoprecipitation, this may allow identification of co-immunoprecipitated proteins associated with different treatments.

6. Microarray studies examining glucocorticoid-inducible gene expression in A549 and BEAS-

2B cells demonstrated that numerous genes were either upregulated or repressed following glucocorticoid treatment (Chapters 3 and 6) (Joanna Elizabeth Chivers, 2005). While the activities of a number of glucocorticoid-induced genes are, at least partially, understood, the functions and impact on asthma of many genes remain to be fully elucidated. For example, the microarray identified genes, including PTGER2, PTGER4 and CNR1, whose expression was enhanced by budesonide plus formoterol treatment, which may have an ability to enhance, or decrease, glucocorticoid activity. Expression of the EP receptors PTGER2 and 4 was enhanced

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183 by glucocorticoids and as these are Gs-coupled GPCRs, specific agonists may act in a similar manner to β2-adrenoceptor agonists, inducing bronchodilatation and potentially enhancing glucocorticoid activity (Buckley et al., 2011). The effects of specific EP2 or EP4 receptor agonists on glucocorticoid activity in the absence, or presence, of a LABA could therefore be determined on the 2×GRE reporter and gene expression. Additionally, CNR1 expression was substantially enhanced by budesonide plus formoterol treatment (Chapter 6). Although, CNR1 has been proposed to be predominantly coupled to Gαi (Alexander et al., 2011; Howlett et al.,

2002), data indicates that binding of agonists to this receptor in the lung induces bronchodilatation (Grassin-Delyle et al., 2014; Tetrault JM et al., 2007) . Therefore, CNR1 may couple to the Gsα in the lung, allowing specific agonists to induce cAMP production. The effects of CNR1 agonists in BEAS-2B cells could be investigated, to determine whether they enhance cAMP production, activate PKA and thereby enhance the induction of genes by glucocorticoids.

Likewise, budesonide inhalation enhanced, or repressed, the expression of various genes in human biopsy samples (Essilfie-Quaye et al., 2011; Kelly et al., 2012; Leigh et al., 2014).

Further biopsy studies could be performed to investigate the relative effects of LABA treatment, alone or in combination with a glucocorticoid on gene expression, potentially enabling insight into the genes that may be most relevant for gene function studies and how glucocorticoid plus

LABA combinations may improve asthma control. Additional biopsy studies comparing glucocorticoid-inducible gene expression between asthmatic and normal volunteers may indicate differences in gene expression relevant to the treatment of this disease. Further microarray studies using NR3C1 agonists, including GSK9027, RU24858 or GW870086X, may indicate if different agonists induce expression of identical or different sets of genes. Likewise, variation in gene expression following treatment with distinct glucocorticoid plus LABA combinations could

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184 be investigated. Such studies may enable the development of agonists designed to induce expression of an “optimal” set of genes, tailored for the treatment of particular diseases, such as asthma or COPD.

7. The degree of 2×GRE reporter activation was shown to be dependent on the relative time of addition of dexamethasone and formoterol (Chapter 6). However, it is not clear whether gene expression is similarly affected by the relative addition times of glucocorticoid and LABA. There is some evidence for improved clinical efficacy and a reduction in exacerbation frequency and

SABA use in asthmatics receiving glucocorticoid plus LABA treatment using a single, rather than two separate inhalers (Chan et al., 2007; Nelson et al., 2003a). Assessment of the time dependence of gene expression may provide additional insights into the mechanism by which

LABAs enhance glucocorticoid activity. Likewise, the requirement for PKA activation in LABA mediated enhancement of 2×GRE activity demonstrated using H89 has not been tested on glucocorticoid-inducible gene expression (Meja et al., 2004).

8. The experiments in chapter 6 indicate that LABAs are likely to enhance glucocorticoid- inducible gene expression in a gene dependent manner. Chromatin immunoprecipitation (ChIP) studies could be performed to investigate the interaction of GR with the GRE elements of the

2×GRE reporter or the promoters of glucocorticoid inducible genes, following treatment with glucocorticoids in the presence, and absence, of a LABA. Analysis could be performed by RT-

PCR or by higher throughput approaches, such as microarrays (ChIP on chip) or next generation sequencing (ChIP-Seq). Related, but potentially complex, investigations could be performed using variants of the chromosome conformation capture, ChiP loop or Hi-C techniques (van

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Berkum et al., 2010). In these techniques DNA is crosslinked using formaldehyde and then digested with restriction enzymes to produce small fragments. Intramolecular ligation is then performed and the small fragments of DNA produced analysed using RT-PCR, microarrays or sequencing (van Berkum et al., 2010). This could enable insight into the interactions between

DNA elements separated by large distances in the genome. Combined with gene expression analysis, such techniques may enable analysis of long range interactions between GR binding sites and enhanced gene transcription.

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Appendix A: List of antibodies and primer sequences

Table A1 Sequences of primers used for RT-PCR. Target Gene Accession Number Primer Sequences GAPDH 2597 F: 5'-TTCACCACCATGGAGAAGGC-3' R: 5'-AGGAGGCATTGCTGATGATCT-3' TSC22D3 1831 ACTTACACCGCAGAACCACCA GGCCATAGACAACAAGATCG DUSP1 1843 F: 5'-GCTCAGCCTTCCCCTGAGTA-3' R: 5'-GATACGCACTGCCCAGGTACA-3' CDKN1C 1028 F: 5'-CGGCGATCAAGAAGCTGTC-3' R: 5'-GGCTCTAAATTGGCTCACCG-3' RGS2 5997 F: 5'-CCTCAAAAGCAAGGAAAATATATACTGA-3' R: 5'-AGTTGTAAAGCAGCCACTTGTAGCT-3'

List of forward (F) and reverse (R) sequences of primers used in this thesis with their corresponding targets and accession numbers.

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Table A2 List of antibodies used for western blotting and immunofluorescence staining. Secondary Cat. Number Primary Antibody Antibody Dilution Source or Reference Cell CREB Rabbit 1:1,000 Signalling 9197 Thermo Fisher GR/NR3C1 Rabbit 1:1,000 Scientific PA1-511A Cell pC-Jun (Ser 73) Rabbit 1:1,000 Signalling 9164 Eddleston et al., TSC22D3/GILZ Rabbit 1:1,000 Bruce Zuraw 2007 GAPDH Mouse 1:80,000 AbD Serotec 4699-9555(ST) Cell CDKN1C/p57KIP2 Rabbit 1:1,000 Signalling 2557 Cell pNFKBIA/pIκBα Mouse 1:1,000 Signalling 9246 Santa Cruz NFKBIA/IκBα Rabbit 1:1,000 Biotechnology SC-371 (C-21) Santa Cruz NF-κB p65 Goat 1:1000 Biotechnology SC-372(C-20)

The list of antibodies includes the relevant secondary antibodies, working dilution and source details.

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Appendix B: MeSH terms

To ensure coverage of the relevant literature PubMed searches for specific topics in the introduction were performed using medical subject headings (MeSH)

(http://www.ncbi.nlm.nih.gov/mesh), as indicated below. Searches were limited to articles published in English before July 2014. Additionally, articles to which the University of Calgary library does not have online access were not reviewed. At least the abstract of each article returned by searches was reviewed for relevancy. Many additional papers were reviewed based on knowledge of the literature, collected references and further searches. Together these were used in writing relevant sections of this thesis.

Glucocorticoid Resistance in Asthma and COPD

The closet mesh term for the concept "Resistance" was: "Drug Resistance"[Mesh].

"Glucocorticoids"[Mesh] AND "Drug Resistance"[Mesh] AND "Asthma"[Mesh] - 129 papers

"Glucocorticoids"[Mesh] AND "Drug Resistance"[Mesh] AND "Pulmonary Disease, Chronic

Obstructive"[Mesh] - 14 papers

Glucocorticoid and LABA in Asthma and COPD

"Adrenergic beta-2 Receptor Agonists"[Mesh] AND "Glucocorticoids"[Mesh] AND

"Asthma"[Mesh] - 52 papers

"Adrenergic beta-2 Receptor Agonists"[Mesh] AND "Glucocorticoids"[Mesh] AND "Pulmonary

Disease, Chronic Obstructive"[Mesh] - 34 papers

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Appendix C: Copyright permissions

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