Studies of HIV and HCV co-infection in the context of haemophilia

A thesis submitted to the University of London for the degree of

Doctor of Philosophy

in the Faculty of Medicine

by

Esteban Herrero-Martinez B.Sc.

Department of Virology and Haemophilia and Haemostasis Centre Royal Free and University College Medical School University of London

October 2002 ProQuest Number: U643503

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11 Abstract

HIV and HCV co-infection is highly prevalent in intravenous drug users and individuals with inherited bleeding disorders treated with clotting factor concentrates prior to the introduction of heat sterilisation in 1985. The presence of HIV accelerates HCV disease progression and the presence of HCV impairs CD4+ T-cell recovery post-HAART, although the underlying mechanisms for these effects remain to be elucidated. The aim of this thesis was to investigate HIV and HCV co-infection in the context of haemophilia.

Initially, a quantitative competitive RT-PCR assay for HCV was developed. This assay was used in a retrospective cohort study of 96 men with haemophilia to determine the prognostic value of a single HCV RNA load measured early post HIV seroconversion. This study showed for the first time, that HCV RNA level early post HIV seroconversion is associated with progression to both AIDS and all-cause mortality over a period of at least 15 years.

The effect of HAART on HCV replication is controversial, with some studies reporting no effect and others increases, reductions and clearances of HCV RNA post­ therapy. I have investigated the effect of HAART on the titre of anti-HCV specific antibodies and on the relationship between these antibodies and HCV RNA level in a cohort of 24 patients with inherited bleeding disorders. A significant inverse correlation between anti-HCV antibodies was observed pre-HAART that disappeared or was obscured post-therapy. I have therefore shown that HAART affects HCV specific humoral immune responses without affecting HCV RNA level.

Finally, I have investigated the effect of HCV co-infection on the expression of a range of memory markers on total CD8+ T-cells in HIV positive and negative patients. Significant differences in memory marker expression were observed in all four cohorts investigated; HIV mono-infected, HCV mono-infected, HIV and HCV co-infected and HIV and HCV negative controls.

I ll Acknowledgements

I would like to express my thanks to my supervisors Professors Vince Emery and Christine Lee for all their help, support and advice throughout my PhD and the writing of this thesis. I would also like to thank Dr Caroline Sabin for her help in the analysis of viral load and immunofluorescence data, Professor Paul Griffiths for giving me the opportunity to write for Reviews in Medical Virology, Dr Helen Devereux for her help and encouragement during the early stages of my PhD and Drs Paul Klenerman, Michaela Lucas and Ana Vargas for their contributions to my work on CD8+ T-cell memory markers. I would also like to thank the Katharine Dormandy Trust and the Royal Free Hospital Virology Department for funding my PhD.

Many thanks to Ms Joyce Beo for the HLA typing of patient samples, to all the staff at the Ian Charleson Day Care Centre and especially to all my colleagues at the Royal Free Virology and Haemophilia Departments for all their help and friendship over the last four years; Aycan, Carol, Chris D, Claire A, Claire SL, Donna, Duncan, Ed, Elaine, Emma, Eva, Frank, Gill, Jacqueline, Jane, Jeremy, Kali, Keirissa, Kuba, Matt, Nigel, Ruth, Shelley, Sly, Ting, Toyin, Ann H, Anne R, Anja, Chris H, Debra, Gillian, Jacqui, Pura, Sarah and Thynn. I would finally like to thank all my friends outside the Royal Free Hospital (you know who you are!) and my family for always being there when I needed a pint of beer or a bottle of wine.

IV Contents

Contents

Abstract iii

Acknowledgements iv

Contents v

List of Figures xii

List of Tables xvi

Abbreviations xviii

Chapter 1 : General introduction 1 1.1 Discovery of HCV 2 1.1 Epidemiology of HCV 3 1.2 Natural History of HCV 4 1.3 HCV Genome organisation 5 1.4.1 The 5’untranslated region 5 1.4.2 Core and F proteins 9 1.4.3 Envelope glycoproteins and p7 protein 10 1.4.4 Non-structural protein 2 (NS2) 11 1.4.5 NS3 and NS4 11 1.4.6 NS5 12 1.4.7 The 3’untranslated region 13 1.5 HCV replication 14 1.6 Genetic variability and genotype 16 1.6.1 Geographical distribution and disease associations 17 1.6.2 HCV genotype and disease associations 20 1.6.3 HCV quasispecies 21 1.6.4 Assigning HCV genotype 22 1.7 HCV diagnosis 22 1.7.1 Serological assays 23 1.7.2 Qualitative and quantitative nucleic acid amplification 23 1.7.3 Chiron TMA qualitative assay 24 1.7.4 Roche AMPLICOR (manual and COBAS assays) 25

V Contents

1.7.5 HCV quantification by branched chain DNA 25 1.7.6 NucliSense quantification of HCV 26 1.8 Associations of HCV RNA load with disease and treatment outcomes 26 1.8.1 Response to treatment 26 1.8.2 Disease progression 27 1.9 HCV therapy 28 1.9.1 Interferon-oj monotherapy 28 1.9.2 Interferon-a and ribavirin combination therapy 29 1.9.3 Pegylated interferon therapy 29 1.9.4 Future therapies for HCV 30 1.9.5 Progress towards the development of a vaccine for HCV 31 1.10 Pathogenesis of HCV 32 1.10.1 Humoral immunity 3 2 1.10.2 Cellular immunity (CD4+ T-lymphocytes) 33 1.10.3 Cellular immunity (CD8+T-lymphocytes) 35 1.10.4 Innate immunity and additional factors 37 1.11 HIV epidemiology 39 1.12 HIV natural history 40 1.13 HIV genome organisation and replication 42 1.14 HIV and HCV co-infection 51 1.14.1 Effect of HIV co-infection on liver disease 51 1.14.2 Mechanisms by which HIV may influence HCV disease progression 52 1.14.3 Effect of HCV co-infection on HIV disease 53 1.15 HIV therapy 54 1.15.1 Novel approaches to HIV therapy 56 1.15.2 HIV therapy in HCV co-infected patients 56 1.15.3 Effect of HIV therapy of HCV 58 1.16 Immune response to HIV 58 1.16.1 Humoral immunity 5 8 1.16.2 Cellular immunity (CD4+T-lymphocytes) 59 1.16.3 Cellular immunity (CD8 + T-lymphocytes) 60 1.18 Aims of thesis 61

VI Contents

Chapter 2: Materials and methods 62 2.1 Development of a quantitative-competitive RT PCR assay (QC RT-PCR) 63 for HCV 2.1.1 Cloning of HCV 5’UTR into pCR2.1 TA cloning vector 63 2.1.2 Mutagenic PCR reactions 64 2.1.3 Agarose gel electrophoresis 66 2.1.4 Annealing and ‘Klenow fill’ of PCR products 66 2.1.5 PCR reactions 67 2.1.6 Purification of the 5’UTR wild type and control inserts 67 2.1.7 Ligation into pGEM T-Easy vector 68 2.1.8 Preparation of transformation competent E.coli JMl 09 cells 68 2.1.9 Transformation into competent JM l09 cells 69 2.1.10 Mini-preparation of plasmid DNA from bacterial cultures 70 2.1.11 Screening of plasmid colonies by restriction enzyme digestion 70 2.1.12 Plasmid sequencing reactions 71 2.1.13 Analysis of sequencing reactions by 7M polyacrylamide urea gel 73 2.1.14 Large-scale preparation of plasmid DNA 74 2.2.15 Linearisation of plasmid prior to transcription 75 2.2.16 In-vitro transcription using T7 RNA polymerase 75 2.1.17 Removal of DNA template with RNase free DNase 1 76 2.1.18 Clean up of RNA 76 2.1.19 MOPS/ formaldehyde gel electrophoresis of RNA transcripts 76 2.2 Optimisation of QC RT-PCR using internal standard RNA transcripts 78 2.2.1 Reverse transcription and PCR amplification of cloned 5’UTR 78 2.2.2 Generation of standard curve for QC RT-PCR assay 79 2.2.3 Hind III digests of amplified DNA 79 2.2.4 Polyacrylamide gel electrophoresis (PAGE) of RT-PCR products 79 2.2.5 Gel scanning and quantification 80 2.2.6 Viral RNA extractions 80 2.3 Routine use of the QC RT-PCR assay for HCV 81 2.4 HCV genotyping assay 84 2.4.1 Reverse transcription of HCV RNA 84 2.4.2 First round PCR 84

V ll Contents

2.4.3 Second round PCR 85 2.4.4 Restriction digests of second round PCR products 86 2.4.5 15% polyacrylamide gel electrophoresis of digested DNA 86 2.5 Immunofluorescence assays for determining HIV and HCV specific 87 antibody titres 2.5.1 Sf-21 cell culture 87 2.5.2 Generation of high titre baculovirus stocks 88 2.5.3 Sf-21 cell plaque assay 88 2.5.4 Baculovirus protein expression time course in Sf-21 cells 90 2.5.5 SDS polyacrylamide gel electrophoresis 91 2.5.6 Western blot analysis 91 2.5.7 Immunofluorescence assay 94 2.6 Effect of HCV co-infection on expression of memory markers on CD8+ 99 T-cells in HIV positive patients 2.6.1 PBMC isolation 100 2.6.2 HLA typing 101 2.6.3 Thawing of frozen PBMCs 101 2.6.4 Phenotyping of CD8+ T-cells using directly conjugated antibodies 101 2.6.5 Unconjugated antibody staining of CCR7 on PBMCs 103 2.6.6 Acquisition of data and flow cytometric analysis 103 2.7 Statistical methods 106 2.7.1 Sign test 106 2.7.2 Wilcoxon signed ranks test 106 2.7.3 Chi squared test 107 2.7.4 Analysis of variance (ANOVA) 107 2.7.5 Pearson’s product moment correlation coefficient 108 2.7.6 Multivariate linear regression model 108 2.7.7 Kaplan-Meier analysis 109 2.7.8 Cox proportional hazards regression analysis 109 2.7.9 Log rank test 109 2.7.10 Spearman’s rank correlation coefficient 110 2.7.11 Paired T-test 110

Vlll Contents

Chapter 3: Development of a QC RT-PCR assay for HCV 111 3.1 Introduction 112 3.2 Materials and methods 114 3.3 Results 114 3.3.1 Generation of the internal standard for the QC RT-PCR assay 114 3.3.2 Optimisation of the QC RT-PCR assay 117 3.3.3 Generation of standard curve and calibration of QC RT-PCR assay 122 3.3.4 Quantification of stored serum samples 122 3.3.5 Evaluation of concordance between the QC RT-PCR assay and the 125 Chiron branched chain (bDNA) assay 3.3.6 Evaluation of quantification in different HCV genotypes 125 3.3.7 Evaluation of QC RT-PCR reproducibility 128 3.3.8 Development of a genotyping assay for HCV 128 3.4 Discussion 132 3.4.1 Development of the QC RT-PCR assay for HCV 132 3.4.2 HCV genotyping assay 133

Chapter 4: The prognostic value of a single HCV RNA load 135 measured early after HIV seroconversion 4.1 Introduction 136 4.2 Materials and methods 138 4.3 Patients studied 138 4.3.1 Study population and samples 138 4.3.2 HIV and HCV therapy 138 4.4 Results 140 4.4.1 Quantitative RT-PCR and HCV genotyping 140 4.4.2 Sample storage assessment 142 4.4.3 Relationship between CD4 count and HCV RNA level in the four 142 initial HCV RNA levels measured 4.4.4 Patient samples excluded from analysis 144 4.4.5 Data analysis 144

IX Contents

4.4.6 Relationship of HCV RNA level with HCV genotype and stratification 150 of viral loads 4.4.7 The prognostic value of a single HCV RNA level for progression to 154 AIDS and death 4.5 Discussion 155

Chapter 5: The effect of HAART on HCV specific humoral 157 immunity 5.1 Introduction 158 5.2 Materials and methods 161 5.3 Immunofluorescence assays for determining antibody titres to 161 baculovirus expressed virus derived proteins 5.3.1 Introduction to baculovirus protein expression 161 5.3.2 Generation of high titre stocks of FL and E1E2 baculovirus constructs 162 and determination of optimal time point for protein expression in Sf-21 cells 5.3.3 Assessment of protein expression by western blot 163 5.4 Patients studied 165 5.4.1 Study population 165 5.4.2 HIV and HCV therapy 165 5.5 Results 167 5.5.1 Measurement of HIV and HCV loads 167 5.5.2 Measurement of anti-HCV FL/E1E2 and anti-HIV env antibodies 167 5.5.3 Data analysis 168 5.5.4 Effect of HAART on HCV and HIV RNA level and antibody titre 168 5.5.5 Relationships between anti-HCV antibody titres and HCV RNA loads 174 in a cohort of HAART treated patients 5.5.6 Relationships between anti-HIV antibody env titres and HCV RNA 174 loads in a cohort of HAART treated patients 5.5.7 Effect of successful interferon and ribavirin combination therapy on 178 anti-HCV antibody titres and RNA load 5.5.8 Relationships between anti-HCV antibodies and HCV RNA load in a 178 cohort of patients treated with interferon and ribavirin combination therapy 5.6 Discussion 183

X Contents

Chapter 6: The expression of memory markers on CD8+ T-cells 185 in HIV and HCV co-infected patients 6.1 Introduction 186 6.2 Materials and methods 191 6.3 Patients studied 191 6.3.1 Study population and samples 191 6.3.2 HIV and HCV therapy 193 6.4 Results 194 6.4.1 Expression of perforin, CD95 and CD45RO 194 6.4.2 Expression of CD27 and CD28 197 6.4.3 Expression of CD62L and CCR7 197 6.4.4 Effect of CD4 count on expression of memory markers 201 6.6 Discussion 206

Chapter 7: General discussion 209 7.1 Development of a QC RT-PCR assay for HCV. 210 7.2: Prognostic value of a single HCV RNA load measured early after HIV 211 seroconversion. 7.3: An effect of HAART on anti-HCV specific humoral immunity 213 7.4: An investigation into the expression of memory markers on CD8+ T-cells 215 in HIV and HCV co-infected patients.

Chapter 8: References 218

Publications 259

XI List o f figures

List of Figures

Figure 1.1 : Schematic representation of the HCV genome, including polyprotein 6 cleavage products and gene functions.

Figure 1.2: Proposed secondary and tertiary structure of the 5’UTR of HCV. 7

Figure 1.3: Worldwide geographical distribution of HCV genotypes and 19 subtypes.

Figure 1.4: How interactions between cellular and humoral responses may affect 34 viral escape.

Figure 1.5: Immunopathogenic mechanisms potentially involved in 38 hepatocellular damage in chronic HCV infection.

Figure 1.6: Natural history of HIV infection in an untreated patient, from initial 41 HIV infection to death at 10 to 11 years post infection.

Figure 1.7: Genetic organisation of HIV-1 and functions of encoded proteins 44

Figure 1.8a: Schematic representation of early events occurring after HIV 47 infection of a susceptible target cell.

Figure 1.8b: A summary of late events in the HIV infected cell culminating in 48 the assembly of new infectious virions.

Figure 1.8c: Late steps in the assembly of new HIV virions. 50

Figure 2.1 : Schematic diagram of site-directed mutagenesis methodology used 65 for introducing a Hindlll restriction site into the HCV wt 5’UTR sequence.

Figure 2.2: Set-up of CL-6B sepharose column for purifying annealed DNA. 72

Figure 2.3: Macintosh screen display of the stages involved in analysis of the 82 QC RT-PCR assay PAGE gel photographic image.

Figure 2.4a: 1.5% agarose gel of qualitative RT-PCR (sample number 599 to 83 624).

Figure 2.4b: 10% DNA PAGE gel for the quantification of five HCV positive 83 RNA samples extracted from patient serum.

Figure 2.5: Neutral red stained plaque assay of high titre stock of full-length 89 HCV baculovirus construct.

Figure 2.6: Set-up of western blot apparatus for the transfer of proteins from 93 a polyacrylamide gel to a PVDF membrane.

X ll List of figures

Figure 2.7a: 24, 48, 72 and 96-hour time course of full-length baculovirus 95 construct at an initial moi of 5.

Figure 2.7b: 24, 48, 72 and 96-hour time course of E1E2 baculovirus construct 95 at an initial moi of 5.

Figure 2.8: Layout of a single baculovirus immunofluorescence assay slide. 96

Figure 2.9: HCV-FL, HCV-E1E2 and HIV-env baculovirus 98 immunofluorescence assay with a 1/160 dilution of HIV and HCV positive patient serum.

Figure 2.10: Representative stainings for all memory markers assessed in 104 Chapter 6.

Figure 2.11 : Isotype control staining of CCR7 and perforin. 105

Figure 3.1: 1% agarose gel of PCR amplification of pCR2.1 HCV 5’UTR 115 constructs with the mutagenic primers HCVMUT and HCVMUTB coupled with M l3 reverse and forward primers respectively.

Figure 3.2: 1 % agarose gel of 233bp putative mutagenised internal standard 115 fragment.

Figure 3.3: 1 % agarose gel of restriction enzyme digests of putative internal 116 standard cloned into pGEM T-Easy vectors and control unmutagenised wt 5’UTR inserts cloned into pCR2.1 vectors.

Figure 3.4: 1% agarose gel of restriction enzyme digests of unmutagenised HCV 116 wt 5’UTR cloned into pGEM T-Easy vectors.

Figure 3.5: 8% urea sequencing gels showing location of engineered Hindlll 118 restriction site in IS fragment and its absence in the wt fragment.

Figure 3.6: pGEM T-Easy vector (redrawn from www.nromega.com) and 119 schematic representation of cloned IS fragment.

Figure 3.7: 0.8% agarose gel showing linearisation of pGEM T-Easy vector 120 contatining IS with Spel.

Figure 3.8: 1% MOPS/formaldehyde agarose gel of purified IS RNA 120 transcript (287nt).

Figure 3.9: 1% agarose gel of PCR reactions to verify lack of DNA in wt and 121 IS RNA transcripts.

Figure 3.10: 10% polyacrylamide gel of lO"^ copies of IS transcript mixed in triplicate with 5x10^, 10"^ and 5x10 copies of wt transcripts, RT-PCR amplified 123 and Hindlll digested.

Xlll List of figures

Figure 3.11 : Calibration of the HCV quantitative-competitive RT-PCR assay. 124

Figure 3.12: Linear regression performed on HCV RNA loads from 45 HCV 126 positive serum samples quantified for HCV RNA by using the Chiron version 2.0 assay and the QC RT-PCR assay.

Figure 3.13: Alignments of 5’UTR nt sequences of different genotype with 127 QC RT-PCR assay primer sequences.

Figure 3.14: Restriction fragment length polymorphisms of the 174bp fragment 130 amplified from the 5’UTR region used to identify HCV genotypes and subtypes.

Figure 3.15: 15% polyacrylamide gels of different digestion patterns diagnostic 131 of various HCV genotypes.

Figure 4.1 : Median HCV RNA load for each measurement post HIV 141 seroconversion. Median years post Hf\^ seroconversion: Measurement 1: 2.17, Measurement 2: 3.12, Measurement 3: 4.12 and Measurement 4: 5.24.

Figure 4.2: Relationship between first HCV RNA level at least four years post 151 HIV seroconversion and HCV genotype.

Figure 4.3 : Kaplan-Meier plot showing relationship between HCV RNA level 152 measured approximately four years post HIV seroconversion and progression to AIDS.

Figure 4.4: Kaplan-Meier plot showing relationship between HCV RNA level 153 measured approximately four years post HIV seroconversion and progression to all-cause mortality.

Figure 5.1: 10% bis-tris NuPAGE gel and western blot of 24, 48, 72 and 96 164 hour time points of protein expression for the FL and E1E2 baculovirus constructs. A 1:10 dilution of anti-HCV positive serum from four separate patients was used as the primary antibody.

Figure 5.2a: Antiretroviral therapy for HIV has no effect on HCV RNA load. 170

Figure 5.2b: A significant decrease in HIV RNA load is observed as a result 170 of successful antiretroviral therapy.

Figure 5.3: Correlation between anti-HCV FL and anti-HCV E1E2 antibody 171 titres.

Figure 5.4: Antiretroviral therapy for HIV has no effect on anti-ElE2, but 172 results in a significant decrease in anti-FL antibody titres.

Figure 5.5: Antiretroviral therapy for HIV significantly reduces anti-HIV env 173 antibody titres.

XIV List of figures

Figure 5.6: Relationship between anti-HCV FL antibody titre and HCV RNA 175 load pre- and post-HAART. An inverse correlation of borderline significance disappears post-tberapy.

Figure 5.7: Relationship between anti-HCV E1E2 antibody titre and HCV RNA 176 load pre- and post-HAART. A significant inverse correlation pre-HAART disappears post-tberapy.

Figure 5.8: Trend towards a positive correlation in the top panel due to increase 177 in HIV RNA level and anti-HIV antibody titres post-HAART. There is no significant relationship between the two parameters pre-HAART.

Figure 5.9: Significant decreases in both anti-HCV FL and anti-HCV E1E2 179 antibody titres after successful interferon and ribavirin combination therapy for HCV.

Figure 6,1 : The expression of memory markers on different subsets of memory 189 CD8+ T-cells.

Figure 6.2: Expression of intracellular perforin in human CD8+ T-lympbocytes 195 from four different cohorts.

Figure 6.3: Expression of CD95 on the surface of human CD8+ T-lympbocytes 196 from four different cohorts.

Figure 6.4: Expression of CD45RO on the surface of human CD8+ 198 T-lympbocytes from four different cohorts.

Figure 6.5: Expression of CD27 on the surface of human CD8+ T-lympbocytes 199 from four different cohorts.

Figure 6.6: Expression of CD28 on the surface of human CD8+ T-lympbocytes 200 from four different cohorts.

Figure 6.7: Expression of CD62L on the surface of human CD8+ T-lymphocytes 202 from four different cohorts.

Figure 6.8: Expression of CCR7 on the surface of human CD8+ T-lymphocytes 203 from four different cohorts.

XV List o f tables

List of Tables

Table 1.1: Comparative sequence analysis among HCV subtypes of a 222 18 nucleotide segment at nucleotide positions 7975 and 8196 of the prototype virus NS5 region.

Table 1.2: USA AIDS case definitions for adults and adolescents. 43

Table 1.3: Established antivirals for HIV therapy and their liver related adverse 55 effects.

Table 2.1 : Components of stacking and resolving gels for SDS-polyacrylamide 92 gel electrophoresis.

Table 2.2: Conjugated antibodies used for direct staining of human T-lymphocyte 102 memory markers.

Table 2.2b: Primary and secondary antibodies used for indirect staining of CCR7 102 on human T-lymphocytes.

Table 3.1: Assay reproducibility data. 17 HCV positive serum samples 129 quantified on two separate occasions on the QC RT-PCR assay. There was no significant difference between the viral loads obtained (p= 0.76, paired t-test).

Table 4.1 : Sample storage assessment data. 10 HCV positive serum samples 141 that had been previously quantified in 1994 on the branched DNA (bDNA) version 2.0 assay (Bayer) were requantified in 2001 using the same assay.

Table 4.2: Comparison of the 15 haemophilic men who were excluded from the 145 analysis because they did not have an HCV RNA level at 4 years after HIV seroconversion, and the 96 men who were included in the analysis.

Table 4.3: Laboratory values of patients at time of first sample. 147

Table 4.4: Results from univariate and multivariate analyses of progression to 148 AIDS.

Table 4.5: Results from univariate and multivariate analyses of progression to 149 death.

Table 5.1 : Western blot band sizes and HCV proteins expressed from the FL 163 and E1B2 baculovirus constructs.

XVI List o f tables

Table 5.2: Summary of data values before and after HAART, and changes 169 during treatment.

Table 5.3: Correlations between all measured parameters in the HAART 180 treated cohort. Correlations (r. p-value) between variables measured using Pearson correlation on transformed data.

Table 5.4: Summary of data values before and after interferon and ribavirin 181 combination for HCV and changes during treatment.

Table 5.5: Correlations (r. p-value) between variables in the cohort successfully 182 treated with interferon and ribavirin combination therapy for HCV.

Table 6.1: Demographic data of patient cohorts studied. All values shown are 192 median (range) unless stated.

Table 6.2: Relationship between CD4 counts and memory marker expression, 204 significant correlations are in bold.

Table 6.3: Summary of the effect of individual virus infections on the expression 207 of memory markers on CD8+ T-cells.

xvii Abbreviations

Abbreviations

A adenine aa amino acid AcMNPV autographa califomica multiple nuclear polyhedrosis virus ADCC antibody-dependent cellular cytotoxicity AIDS acquired immune deficiency syndrome ANOVA analysis of variance AP alkaline phosphatase APC antigen presenting cell APC allophycocyanin APS ammonium persulphate ART anti-retroviral therapy ATP adenosine triphosphate AZT azido-thymidine/ zidovudine BAF barrier to autointegration protein BCR B-cell receptor bDNA branched chain DNA bp base pair BSA bovine serum albumin BVDV bovine viral diarrhoea virus C cytosine CCR- chemokine receptor CD- cluster of differentiation Cdk9 cellular dependent kinase 9 cDNA complementary DNA CFG clotting factor concentrate CHC chronic hepatitis C c m chimpanzee infectious dose CmE-B cell death-inducing DFF45-like effector-B protein CMV cytomegalovirus CNS central nervous system CTP cytosine triphosphate

X V lll Abbreviations

Da Dalton DC dendritic cell DC-SIGN dendritic cell-specific intracellular adhesion molecule 3- grabbing nonintegrin DC-SIGNR endothelium expressed homologue of DC-SIGN ddATP dideoxyadenosine triphosphate ddCTP dideoxycytosine triphosphate ddGTP dideoxyguanosine triphosphate ddTTP dideoxythymidine triphosphate DEPC diethyl pyrocarbonate DHHS Department of Health and Human Services (USA) DNA deoxyribonucleic acid dsDNA double stranded DNA dsRNA double stranded RNA dsRNA/DNA double stranded RNA/DNA heteroduplex DTT dithiothreitol E1E2 baculovirus construct expressing the GST fusions of the immunodominant envelope glycoproteins of HCV, El and E2. ECMV encephalomyocarditis virus

ELA enzyme immunoassay EIF eukaryotic initiation factor EDTA ethylenediaminetetraacetic acid ELISA enzyme linked immunosorbent assay Eq genome equivalent ER endoplasmic reticulum ESLD end-stage liver disease EVR early viral response FACS fluorescence activated cell sorter FasL Fas ligand FCH fibrosing cholestatic hepatitis FCS foetal calf serum FDA Food and Drug Administration FITC flourescein isothiocyanate

XIX Abbreviations

FL ’full-length’ baculovirus construct expressing all 10 HCV proteins G guanine 0418 neomycin phosphotransferase GAGs glycosaminoglycans gP glycoprotein GST glutathione-S-transferase GTP guanosine triphosphate HAART highly active antiretroviral therapy HAI histological activity index HAV Hepatitis A virus HBV Hepatitis B virus HCC hepatocellular carcinoma HCV Hepatitis C virus HDV Hepatitis delta virus HIV Human immunodeficiency virus HLA human leukocyte antigen HMGI(Y) high mobility binding group DNA binding-protein Y HVR hypervariable region ICS intracellular cytokine staining IBM immunogold electron microscopy IFN interferon

Ig immunoglobulin IL interleukin IMPDH inosine monophosphate dehydrogenase IN HIV integrase (p32) IPTG isopropylthiogalactoside 1RES internal ribosome entry site IS internal standard ISDR interferon sensitivity determining region i.v. intravenous IVDU intravenous drug user Kb kilobase kDa kilo-Dalton

XX Abbreviations

LB Luna Bertani broth LCMV lymphocytic choriomeningitis virus LDL low density lipoprotein LIPA line probe assay L-SIGN liver-specific intracellular adhesion molecule 3-grabbing nonintegrin LTNP long-term non-progressor LTR long terminal repeat mA milliamp MA HIV matrix protein (pi7) MAb monoclonal antibody MAP kinase mitogen activated protein kinase mg milligram MHC major histocompatibility complex min minute M IP-la macrophage inflammatory protein-la MIP-ip macrophage inflammatory protein-1/3 ml millilitre MNPV multiple nuclear polyhedrosis virus moi multiplicity of infection MOPS 4-morpholinopropanesulphonic acid MuLV Murine Leukaemia Virus MVB multi-vesicular body MWU Mann-Whitney U-test NANBH non-A non-B hepatitis NASBA nucleic acid sequence-based amplification NC HIV nucleocapsid (gag p7) NCR non-coding region Nef HIV negative effector (p24) NES nuclear export signal

NF-k B nuclear factor k B ng nanogram NKcell natural killer cell

XXI Abbreviations

NKT cell natural killer T cell NLS nuclear localisation signal nm nanometer NNRTI non-nucleoside reverse transcriptase inhibitor NRTI nucleoside reverse transcriptase inhibitor NS non-structural nt nucleotide NTP nucleoside triphosphate NTPase nucleoside triphosphatase dNTP deoxynucleotide triphosphate ddNTP dideoxy nucleotide triphosphate OD optical density ORF open reading frame PAGE polyacrylamide gel electrophoresis PBS phosphate buffered saline PBMC peripheral blood mononuclear cells PCR polymerase chain reaction PDV polyhedra derived virus PE phycoerythrin PEG polyethylene glycol PerCP peridinin chlorophyll-a protein pfu plaque-forming unit PI protease inhibitor pi post-infection PIC preintegration complex PKR RNA-activated protein kinase (IFN induced protein kinase) PMB pMelBae vector (Invitrogen) pmol picomole PTB polypyrimidine tract-binding protein PTFE poly-tetra-fluoro-ethylene P-TEFb positive transcription elongation factor b complex PVDF polyvinylidine difluoride membrane QC-RTPCR quantitative competitive reverse transcription polymerase chain

XXll Abbreviations

Q-RNA competitor internal standard RNA (NucliSense assay) RIO RPMI 1640 media at 10% FCS RanGAP RanGTPase protein RANTES regulated upon activation normal T cell expressed and secreted (chemokine) RBV ribavirin RCCl Ran nucleotide exchange factor RdRp RNA-dependent RNA polymerase Rev HIV regulator of viral gene expression (pi 9) RFLP restriction fragment length polymorphism RIBA recombinant immunoblot assay RNA ribonucleic acid RNA pol II RNA polymerase II RNP ribonucleoprotein RPMI Roswell Park Memorial Instiute RRE Rev response element RT reverse transcriptase SDS sodium dodecyl sulphate SDW sterile distilled water sec second SEM standard error of the mean SIV simian immunodeficiency virus SEC secondary lymphoid tissue chemokine SOD superoxide dismutase ssRNA single stranded RNA STI structured treatment interruptions SU HIV surface envelope protein (gp 120) SV40 simian virus 40 SVR sustained virologie al response T thymine TAE Tris-acetate-EDTA buffer TAB transfusion associated hepatitis Taq Thermus aquaticus TAR transcriptional response (element)

X X lll Abbreviations

Tat HIV transcriptional activator (pi4) TBE Tris-borate-EDTA buffer Tc Cytotoxic T-cell (response) ICR T-cell receptor IE Tris-EDTA TEMED N,N,N’ ,N’ tetramethylethylenediamine Tfa tubule forming agent Tfbl transformation buffer I Tfbll transformation buffer II Th T-helper (cell or response) TM HIV transmembrane envelope protein (gp 41) TMA transcription mediated amplification TNF-a tumour necrosis factor alpha tRNA transfer RNA TSGlOl tumour suppressor gene product 101 TTP thymine triphosphate UEV ubiquitin E2 variant (domain on TSGlOl) UTR untranslated region u v ultraviolet UTP uracil triphosphate V volt Vpr HIV viral protein R (pl5) Vpu HIV viral protein U (pl6) VR variable region (of HCV 3’UTR) v/v volume to volume ratio wt wild-type w/v weight to volume ratio

XXIV Chapter 1: General Introduction

Chapter One

General Introduction Chapter 1: General Introduction

1.1 Discovery of HCV

Serological tests for hepatitis A and B viruses (HAV and HBV) were developed in 1974. These allowed the role of these agents in transfusion associated hepatitis (TAH) to be evaluated and it was found that about 90% of cases were caused by an unknown agent. This resulted in TAH being termed non-A non-B hepatitis (NANBH) (Feinstone et al, 1975).

NANBH was initially perceived as a mild disease, but studies in the 1970’s revealed that it had a high propensity to cause chronic hepatitis, which could progress to cirrhosis and liver failure (Berman et al, 1979). After this discovery, much effort was put into discovering the causative agent. A chimpanzee model of infection was established in the late 1970’s which was used to demonstrate that NANBH could be transmitted by intravenous (i.v.) administration of human inocula (Wyke et al, 1979).

In the early 1980’s, this model was used to determine that rechallenge with different inocula resulted in sequential episodes of NANBH, suggesting that there were multiple NANBH agents (Hollinger et al, 1980). In chimpanzee hepatocytes, one NANBH agent induced 150-300nm membranous tubules in the cytoplasm, which led to it being called the tubule-forming agent (tfa). In 1983 it was shown that chloroform treatment of infectious inocula rendered them non-infectious, whilst subsequent filtration experiments revealed that the tfa infectivity could be retained by a 50nm filter. These results were consistent with tfa being a small enveloped virus (Bradley et al, 1983;Feinstone er a/, 1983).

Hepatitis B virus (HBV) and hepatitis delta virus (HDV) were known to be enveloped viruses and a prevalent view at the time was that NANBH was related to these. Some groups showed serological and hybridisation cross-reaction between NANBH and HBV whilst others did not. However, NANBH failed to cross hybridise even at low stringency with the HDV genome (characterised in 1986) (Weiner et al, 1987). In 1985, it was noted that the Togaviridae (which included the flavivirus genera) were small enveloped viruses that could induce tfa-like ultrastructural alterations in Chapter 1: General Introduction infected cells which suggested that tfa may be togalike or a novel virus (Bradley 1985;Fields et al, 2001).

However, with the continuing failure of conventional immunological and virological techniques to identify the NANBH agent, it was the use of recombinant DNA technology in 1989 that resulted in identification of the causative agent of NANBH. Choo et al. pooled plasma from infected chimpanzees and by titrating infectivity in other animals obtained a 10^ CED ml'^ (chimpanzee infectious dose) titre plasma pool. Nucleic acid was extracted from this pool and used to create a cDNA expression library by cloning random fragments. The library was then screened with serum from patients with NANBH. Over a million clones were screened before one was found that reacted with serum from patients with NANBH and infected chimpanzees post hepatitis (clone 5-1-1). This clone was used as a hybridisation probe to screen the original expression library and a 1089 nucleotide open reading frame was reconstructed (Choo et al, 1989;Booth et al, 1998). The whole HCV genome was then rapidly characterised (Choo et al, 1991) and it is now known that HCV is the major causative agent of NANBH, accounting for at least 80% of cases. However, it was not until 1994 that HCV virus particles were first visualised by immunoelectron microscopy (Kaito et al, 1994), and to this day it cannot be readily grown in tissue culture.

1.2 HCV Epidemiology

175 to 300 million people are infected with HCV worldwide. The prevalence of HCV antibodies is variable, ranging from 0.1-0.3% in Canada/ Northern Europe, to 1-2% in the USA/ Japan and up to 19.5% in Egypt (Hibbs et al, 1993). 10,000 people die per year in the USA from liver failure and HCV is the leading cause (Williams, 1999). The rate of new HCV infections has been reduced by over 50% in the last 15 years as a result of screening for surrogate markers of HCV, excluding HIV positive blood donors, the availability of more sensitive antibody testing and safer needle using practices (Alter, 1993;Schreiber et al, 1996). Injecting drug use accounts for the bulk of HCV transmission in the USA with seroprevalence reaching 80% within one year of injecting (Williams, 1999). Sexual transmission appears to be infrequent (Donahue Chapter 1: General Introduction et al, 1991;Hisada et al, 2000;Leruez-Ville et al, 2000) and maternal (vertical) transmission frequency is around 5% (Conte et al, 2000). Increased risk of HCV transmission has been associated with HIV co-infection, multiple sexual partners and a longer duration of marriage (Sanchez-Quijano et al, 1990;Eyster et al, 1991;Akahane et al, 1994). Currently, the patient groups with the greatest prevalence of HCV are intravenous drug users (IVDU) and people with inherited bleeding disorders (Ockenga et al, 1997). In the USA, 15-30% of HIV positive individuals are also HCV infected (Sherman et al, 2000).

1.3 Natural history of HCV

The majority of individuals who develop acute HCV are unaware of the fact and disease onset is usually identified by assumption. Originally, progression from acute to chronic hepatitis was defined as the persistence of increased aminotransferases for 6 months or more but it is now defined by persistence of HCV RNA in the blood. Failure to clear the virus occurs in 54-86% of cases depending on the study (Seef, 2002). The predicted outcome of infection also varies greatly between different studies and it is very difficult to assemble an unbiased patient cohort. However an important observation with these data is that mortality increases in infected persons only if they develop cirrhosis (Niederau et al, 1998). Prospective studies with up to 14 years of follow-up detected cirrhosis in approximately 20% of patients, with hepatocellular carcinoma (HCC) being rare and liver disease responsible for death in 3% of patients (Hopf et al, 1990;Tremolada et al, 1992;Koretz et al, 1993;Mattsson et al, 1993). Relatively short follow up and small patient numbers were limitations in these studies. In retrospective studies, frequencies of 30-46% for cirrhosis and 11- 19% for HCC after 4-11 years follow-up have been reported. Disease outcomes are more severe because these studies selected patients with well-established liver disease (Takahashi et al, 1993;Tong et al, 1995Yano et al, 1996). These results contrast with those of a retrospective-prospective study of 62,667 Irish women infected with contaminated anti-D immunoglobulin (Kenny-Walsh, 1999). This study found only 2% had cirrhosis after 17 years, an outcome possibly associated with their low alcohol intake. A further retrospective cohort study of US military recruits with 45 years of follow-up found less than 15% had suffered from or died as a result of liver disease Chapter 1: General Introduction

(Seeff et al, 2000). There is clearly great variation in the progression of HCV disease. Progression in HCV mono-infection is usually very slow, but influenced by other factors such as age, HCV genotype, alcohol consumption and HIV co-infection (Eyster et al, 1993;Sabin et al, 2000b;Yee et al, 2000;Westin et al, 2002).

1.4 HCV Genome organisation

HCV has been classified as the sole member of a distinct genus called hepacivirus within the Flaviviridae (Murphy et al, 2001). Homology with other members of the Flaviviridae family is low although they share a similar genomic organisation. HCV is composed of a positive sense single stranded RNA genome of -9600 nucleotides in length that encodes a single open reading frame (ORE). The genome codes for a single polyprotein of -3000 amino acids in length that is proteolytically cleaved by host and virally encoded proteases into eleven viral proteins, see Figure 1.1.

1.4.1 The 5’ untranslated region

Two highly conserved untranslated regions (UTR) flank the HCV ORF; these may also be referred to as non-coding regions (NCR). The 5’UTR and adjacent core region are the most highly conserved regions of the virus. HCV does not encode a methyl transferase activity and so translates its viral RNA by a cap-independent mechanism. The 341nt 5’UTR forms a highly ordered stem loop secondary structure (see Figure 1.2) which possibly together with a small portion of the core region functions as an internal ribosome entry site (1RES) (Smith et al, 1995;Hellen & Pestova, 1999). The 1RES is a mechanism that allows cap-independent translation that was first described for poliovirus (a picomavirus) in 1988 (Pelletier & Sonenberg, 1988).

Translation of most eukaryotic mRNAs is usually dependent on the 5’ modified m^G terminal ‘cap’. The process is initiated by the binding of a eukaryotic initiation factor (elF) elF2, OTP and a Met-tRNA to a 40S ribosomal subunit to form a 43S complex. elF4F then binds to the 5’ cap and together with elF4A and elF4B, unwinds the mRNA, creating a binding site for the 43 S complex; a variety of elFs interact to Chapter 1: General Introduction

O 1RES

Structural Non-Structura! (NS) 5’UTR 3’UTR / /

VO r— — (N / —' CO — r- / 0\ oo s VC r - OV AÎ & RNA binding j 4A 4B 5A 5B nucleocapsid I— El E2

I I NS3-pro. metallo/Cys serine protease cofactor R NA-dependent envelope proteinase (NS3) replication replication RNA-polymerase glycoproteins Ca2+ interferon resistance channel?

Figure 1.1: Schematic representation o f the HCV genome (top). 5’ and 3’ UTR’s are not drawn

to scale. Individual cleavage products are given below. Cleaved by (|) host cell signalases, (]J ) the

NS2-3 proteinase, (jj ) the NS3/4A proteinase complex and (j ) host signal peptidase. Numbers on

arrows correspond to PI positions of the corresponding cleavage sites. Functions of the given

proteins are shown at the bottom. The F protein is a novel protein encoded in an overlapping

reading frame indicated under the capsid protein, adapted from Bartenschlager & Lohmann 2000

and Dubuisson et al,2002. Chapter I: General Introduction

U Û

U A 3 C G C 3 C

ac

I , Ae A c ccÛ A Ilia

J CACCGG U r GU ^ : lilC

G jH-* C Q A u Q C CG G * U A ^ G C G U A CG c c U,,U 1 GC U C ^ iid-uG-J«9 1RES

■J . 5 GCCA,. „OAGAU,’CCACCAlA5AA^CACCCC‘f ^ACCCCCCCUCCCGGQ* ^GCCU Ilia GGACGGCCC-^UGC^^^ '" 6

C G \ ; c Z L A lllf

Q ^^UAAACCOCAAA jCAAAAAÆCAAACCUAAC 'A I*' 3J J S - J V ii aCû * IV

Figure 1.2: Secondary and tertiary RNA structure within the complete 5 ’UTR of HCV and immediate downstream open reading frame. The region comprising the 1RES extends from domain II to domain IV. The initiator AUG codon is highlighted, Honda et al, 1999. Chapter 1: General Introduction promote this binding. The 43 S complex then scans downstream and forms a stable 48S complex with the first AUG triplet encountered. The OTP is then hydrolysed via eIF5, elFs are released and the Met-tRNA is left at the P site of the 40S subunit. The 40s subunit now joins with the 60S ribosomal subunit allowing protein synthesis to begin.

The HCV 5’UTR forms four highly structured domains (see Figure 1.2). Domain I forms a single stem loop between nucleotides 5 and 20 that has been shown to be dispensable for translation activity, but essential for replication (Honda et al, 1996). The 5’ border of the 1RES has been mapped to between nucleotides 38 and 46. Oligopyrimidine tracts are found in the apical loop of domain III and between domain III and domain II. Domain IV consists of a small stem loop containing the polyprotein start codon at nucleotide position 342 and forms a pseudoknot by base pairing with a loop in domain III. Mutagenesis or insertion of upstream AUG codons has little effect on 1RES activity and 40S ribosomal subunits appear to bind to the initiator AUG with little or no scanning (Reynolds et al, 1996). The mapping of the 3’ end of the 1RES is still a matter of debate. Most experimental evidence suggests that sequences of the core-coding region, but not core itself, are needed for full 1RES activity. However, whether this sequence is a true component of the 1RES or just needed to prevent unfavourable base pairings is unknown. In fact, purified 40S ribosomal subunits can bind directly to an HCV 1RES lacking core sequences without requiring any additional transcription factors. This is a property unique among eukaryotic RNA’s that resembles the interaction between the prokaryotic 3OS ribosomal subunit and the Shine-Dalgamo sequence (Pestova et al, 1998;Hellen & Pestova, 1999;Bartenschlager & Lohmann, 2000).

1RES activity is influenced by several factors. The X-tail in the HCV 3’UTR enhances 1RES dependent translation by an unknown mechanism and several cellular factors bind the 1RES. These stimulate translation in most cases and include PTB (polypyrimidine tract-binding protein), the La antigen, heterogeneous nuclear ribonucleoprotein L and as yet unidentified proteins of 120, 87 and 25 kDa (Bartenschlager & Lohmann, 2000). Using cell lines stably expressing bicistronic reporter constructs with a cap-dependently expressed upstream reporter and a downstream reporter translated from the HCV 1RES, it was found that IRES-

8 Chapter 1: General Introduction dependent translation was greatest in mitotic and lowest in quiescent (Go) cells (Honda et al, 2000). Cellular proteins whose abundance is regulated by the cell cycle may therefore regulate HCV translation.

1.4.2 Core and F proteins

The core protein is the most conserved structural protein of HCV, it forms the nucleocapsid that surrounds the HCV RNA genome and has numerous functional activities. Encoded in the first 191aa of the HCV polyprotein, it is the first protein cleaved from it in a process mediated by an unknown cellular enzyme. The 21kD core protein contains a C-terminal basic region that is essential for its membrane dependent processing and which also acts as a signal for the translocation of El to the ER. Recombinant core protein has been shown to multimerise in the cytoplasm, and probably associates with El and E2 by budding through the ER membrane where El and E2 co-localise. It is also immunogenic, containing several linear B-cell epitopes (Ray & Ray, 2001). Translation of HCV genotype la core protein in the presence of microsomal membranes gives rise to three protein products of -21, 19 and 16kD, whilst genotype lb core results in a single -21 or -21 and 19kD species. A -16kD product is expressed if missense mutations are present at codons 9-11 (Lo et al, 1994;Yeh et al, 2000). Genotype la core is predominantly cytoplasmic whilst lb core accumulates in the nuclei and mitochondria of transgenic mice where core has been shown to be oncogenic (Moriya et al, 1998). It is possible that the ratio and subcellular localisation of different core protein species may have an effect on HCV replication and pathogenesis, although the nuclear localisation of core may be an artefact of the expression system used as it has not been observed in vivo.

The core protein has features of a gene regulatory protein; it contains phosphorylation sites, nuclear localisation signals and locates to the cytoplasm and possibly the nucleus. It transactivates the IL-2 promoter, human c-myc promoter, SV40 early promoter and Rous sarcoma virus LTR as well as suppressing c-fos promoter and HIV-1 LTR promoter activities (Bergqvist & Rice, 2001 ;Ray & Ray, 2001). Activation or repression of promoters probably depends on promoter structure. Core does not appear to directly bind DNA and probably modulates gene expression via its Chapter 1: General Introduction ability to interact with many host proteins (Ray & Ray, 2001). The function of core in vivo remains unclear. It directly interacts in vitro with the tumour suppressor gene p53, NF-kB and components of the MAPK pathways, suggesting it can both promote and inhibit cell growth (Shrivastava et al, 1998;Lu et al, 1999;Fukuda et al, 2001). The core protein also both inhibits and blocks apoptosis: an important mechanism for the regulation of cell survival and immune evasion (Zhu et al, 1998;Marusawa et al, 1999;Ray & Ray, 2001;0tsukaet al, 2002).

1.4.3 Envelope glycoproteins and p7 protein

El (31kD) and E2 (70kD) are the two envelope glycoproteins of HCV. They are both type I transmembrane proteins with C-terminal domains that are probably important for membrane anchoring. Inefficient cleavage at the E2-p7 junction leads to the production of two species, E2 and E2-p7. The function of both E2-p7 and p7 remain unknown, although p7 has recently been shown to cross-link into hexamers in vivo. In vitro, p7 hexamers have been shown to act as calcium ion channels, the function of which can be inhibited by amantadine (Griffin et al, 2003). In vivo, El and E2 are thought to exist largely as stable non-covalent heterodimers embedded within the lipid layer of the HCV virion (Dubuisson et al, 1994). E2 is highly variable and contains two regions of extreme variability termed the hypervariable regions 1 and 2 (HVR-1 and HVR-2). HVR-1 is immunogenic and antibody responses to it block binding to cells in vitro, whilst both CTL and antibody responses directed against HVR-1 are thought to be neutralising (Hijikata et al, 1991;Farci et al, 1994;Lechner et al, 1998). E2 interacts with CD81, which is now thought to be a putative HCV receptor, although it is not known whether binding to CD81 is sufficient for virus internalisation (Pileri et al, 1998). It has recently been shown in vitro that E2 binds strongly to DC-SIGN and L-SIGN (dendritic cell and liver-specific intracellular adhesion molecule 3-grabbing nonintegrin). Additionally, a separate group has found that both El and E2 bind to DC-SIGN and DC-SIGNR (an endothelial cell expressed DC-SIGN homologue) (Lozach et al, 2003;Pohlmann et al, 2003). High affinity interactions between HCV glycoproteins and oligomeric lectins may be a strategy by which HCV targets and concentrates in certain target sites such as the liver. Soluble E2 can also bind to the human scavenger receptor class B type I (SR-BI) in hepatoma

10 Chapter 1: General Introduction cell lines independently of CD81 (Scarselli et al, 2002). Finally, E2 inhibits the interferon inducible RNA-activated protein kinase (PKR), blocking its antiviral inhibitory effect on cell growth and protein synthesis and this is a possible mechanism by which HCV may become interferon resistant (Taylor et al, 1999).

1.4.4 Non-structural protein 2 (NS2)

NS2 (23kD) is a hydrophobic transmembrane protein that together with NS3 (70kD) forms a zinc dependent protease responsible for NS2/NS3 cleavage. The enzymatic activity of NS3 is not required for this process. The processing is thought to be an autocatalytic cis cleavage, but the exact mechanistic details of this process remain elusive, making the design of antivirals to target the NS2/3 protease very difficult at present (Bartenschlager & Lohmann, 2000;De Francesco et al, 2000).

It has recently been shown in a yeast two-hybrid screen that NS2 also interacts with the pro-apoptotic factor CIDE-B (cell death-inducing DFF45-like effector-B). In vitro, NS2 has been shown to counteract CIDE-B induced cytochrome-c release and inhibit apoptosis (Erdtmann et al, 2003).

1.4.5 NS3 and NS4

The NS3 protein is multifunctional, and contains sequences for a serine protease at its N-terminus and for a nucleoside triphosphatase (NTPase) and RNA dependent RNA helicase at the C-terminus. The serine protease is involved in four of the five maturation cleavage events that occur during the maturation of HCV non-structural proteins (see Figure 1.1). The formation of non-covalent heterodimeric complexes between NS3 and NS4A (8kD) is essential for cleavage at the NS3/4A and NS4B/5A sites, as well as enhancing cleavage of NS5A/5B. NS4A increases the stability of NS3 and targets it to the ER membrane. Crystal structure analysis of the NS3 protease has revealed a highly conserved tetrahedrally coordinated structural zinc- binding site opposite the active site (Love et al, 1996;Suzuki et al, 1999).

11 Chapter 1: General Introduction

The NS3 RNA helicase is a member of the DEXH helicase family, so named because of an invariant Asp-Glu-Xaa-His (DEXH) motif found in its active site (Gorbalenya et al, 1989). It is thought to unwind duplex RNA in a reaction coupled to the hydrolysis of nucleoside triphosphates (NTP) (De Francesco et al, 2000). It has some unique properties in that it can unwind dsRNA, dsDNA and dsRNA/DNA heteroduplexes in a 3’ to 5’ direction. Recombinant NS3 protein binds to poly(U) sequences in E.coli and its NTPase activity is enhanced by the addition of poly (U) to the reaction mixture, supporting the theory that NS3 binds to the 3’ region of HCV (Tai et al, 1996). Interestingly, NS4A mediated NS3 stabilisation downregulates the unwinding but not the NTPase activity (Gallinari et al, 1998;Gallinari et al, 1999). The role of the NS3 helicase is thought to be the separation of the HCV genomic RNA (+) strand from the (-) strand during viral replication, and compounds capable of interfering with the helicase function would have antiviral activity. NS3 may also be oncogenic as its expression in NIH 3T3 cells transforms the cells and causes tumours in nude mice (Sakamuro et al, 1995). NS3 may also be cleaved into two species, NS3A (49kD) and NS3B (23kD). The cleavage occurs within the helicase motif but, it has yet to be observed in vivo (Shoji et al, 1999).

NS4A acts as a cofactor for NS3 (see above). It is also associated with NS5A where it is involved in the hyperphosphorylation of NS5A. NS4B (26kD) is a hydrophobic protein that has recently been shown in tetracycline regulated cell lines to induce a structure termed a membranous web, consisting of vesicles in a membranous matrix. Immunogold electron microscopy (lEM) in experiments expressing the complete HCV polyprotein found that all HCV proteins associated with the NS4B induced membranous web to form a membrane associated multiprotein complex that may be a candidate replication complex (Suzuki et al, 1999;Egger et al, 2002).

1.4.6 NS5

NS5A exists as two phosphorylated proteins of 56 and 58 kD, with the 58kD species being a hyperphosphorylated version of the 56kD protein. Although the function of NS5A remains unknown, a Japanese group has found that it contains a feature termed the interferon sensitivity determining region (ISDR) located between aa 2209 and

12 Chapter 1: General Introduction

2248 (Enomoto et al, 1995). A portion of the ISDR interacts with PKR, and interferon sensitive HCV has mutations which disrupt the binding of PKR to NS5 (Gale, Jr. et al, 1998). However, European groups have found the ISDR to be a stable sequence element (Rispeter et al, 1998) and differences between the sequence of Japanese and non-Japanese (or Asian and non-Asian) HCV isolates may be responsible for this difference (Nakano et al, 1999;Chung et al, 1999). Recent microarray analysis of Huh-7 cells has revealed that interferon treatment upregulates 50 genes and NS5A expression reduces the induction of 9 of them. Additionally, NS5A induced IL-8 production, which inhibits the antiviral effect of interferon and similarly reduces the expression of interferon-induced genes (Girard et al, 2002).

NS5B is a highly conserved 65kD membrane associated protein and it contains the GDD catalytic sequence motif of an RNA-dependent RNA polymerase (RdRp). The RdRp catalyses the synthesis of both plus and minus strand HCV RNA and there are three strategies that the enzyme may use to initiate RNA synthesis. In vitro, the enzyme prefers primer-dependent initiation, either by elongation of a primer bound to an RNA homopolymer or by a ‘copy back’ mechanism when using heteropolymeric templates; a function probably performed by the 3’UTR in vivo. The RdRp of bovine viral diarrhoea virus (BVDV) can also initiate RNA synthesis de novo and this mechanism may also operate in vivo during HCV infection (Lohmann et al, 1998;Suzuki et al, 1999; Bartenschlager & Lohmann, 2000). An unresolved question remains how template specificity is achieved as in most studies the RdRp was found to bind and utilise virtually every RNA and DNA template (although with different specificities). Interactions with viral and cellular proteins are likely to be important in regulating RNA synthesis (Bartenschlager & Lohmann, 2000). As the RdRp enzyme is only used in the replication of RNA viruses, it is an ideal target for novel antivirals .

1.4.7 The 3’ untranslated region

The individual steps underlying HCV replication are unknown. However, the NS5B (RdRp) is important in the catalysis of both plus and minus strand HCV RNA. In vitro, the enzyme prefers primer dependent initiation of RNA synthesis either by the elongation of a primer hybridised to an RNA homopolymer or by a ‘copy-back

13 Chapter 1: General Introduction mechanism when using heteropolymeric templates. It is likely that in vivo, the 3’UTR can fold back intramolecularly to generate a 3’ end that can be used to initiate negative strand RNA synthesis, resulting in a product approximately double the length of the input template (Ito et al, 1998;Bartenschlager & Lohmann, 2000).

The 3’UTR of HCV is divided into three domains. A highly conserved 3’ terminal 98 nt segment (3’X region), an upstream poly(U)-poly(UC) or poly(U/UC) tract and a variable region (VR) located at the 5’ end. Each of these domains contributes to efficient viral RNA replication in transfected hepatoma cells. Replication is abolished if any of the three stem loops in the 3’X region is deleted. Complete deletion of the poly (U/UC) tract also abolishes replication, with a minimal 50 to 62 nt of poly (U/UC) required for detectable RNA replication. Longer tracts and possibly pure poly (U) tracts may be associated with more efficient RNA replication. Finally, although multiple deletions can be tolerated in the VR, each leads to a partial loss of replicative capacity (Yi & Lemon, 2003).

Various cellular proteins also bind to the 3’UTR. The 3’X region binds PTB, and it has been suggested that the 3’UTR may regulate translation by interacting with the 5’UTR via PTB. Mutations that abolished PTB binding to the 3’X region reduced but did not abolish in vitro translation of HCV RNA, suggesting PTB as a mediator of in vitro HCV RNA translational enhancement by the 3’UTR (Ito & Lai, 1997;Ito et al, 1998). Additionally, glyceraldehyde-3-phosphate dehydrogenase binds to the poly(U/UC) sequence and two cellular proteins identified by UV cross-linking (p87 and pl30) bind the 3’X region (Inoue et al, 1998;Petrik et al, 1999).

1.5 HCV Replication

Initially, HCV enters the host cell using an as yet unidentified primary receptor, although a variety of molecules have been described as putative receptors. It is probable that the virus uses various different receptors in vivo for internalisation and additionally, the mechanisms of viral fusion, binding and entry, remain to be elucidated. CD81 is a member of the tetraspanin family and both the hypervariable regions of the E2 protein interact with it to promote attatchment. However, CD81

14 Chapter 1: General Introduction binding is relatively weak and not sufficient for internalisation of the virus. HCV particles have been shown to interact more strongly with both the low-density lipoprotein receptor (LDL receptor) and glycosaminoglycans (GAGs) as well as SR- Bl. (Pileri et al, 1998;Agnello et al, 1999;Monazahian et al, 1999;Meola et al, 2000;Germi et al, 2002;Scarselli et al, 2002;Roccasecca et al, 2003). Once inside the cell, the (+) strand RNA is released into the cytoplasm and transcribed into a BOOOaa polyprotein via the 1RES cap-independent mechanism regulated by a combination of host cell proteins and the HCV 3’UTR. Translation occurs at the rough ER and the polyprotein is processed by a combination of host and viral enzymes. Most or all of the cleavage products (in particular NS3 to NS5) associate with intracellular membranes to form a replication complex that probably includes some host proteins, with NS4B induced membrane alterations possibly facilitating this process (Egger et al, 2002). The NS5B RdRp catalyses the synthesis of (+) and (-) strand RNA with the NS3 helicase unwinding stable RNA structures to facilitate replication. NS3 unwinding, NS5A phosphorylation and host proteins may regulate NS5B. It is possible that particle formation may be initiated by the interaction of core with the (+) RNA. Using baculovirus constructs expressed in insect cells, it was found that core interacts with itself and forms HCV-like particles. In this system, the HCV-like particles selectively incorporated short HCV derived RNA sequences in preference to host RNA (Baumert et al, 1998). HCV envelope glycoproteins are retained in the ER via signals in their transmembrane domain, suggesting that the above nucleocapsids become enveloped via ER budding. It is possible that the virus particles are then exported via the constitutive secretory pathway. Clearly, many individual steps in the HCV replicative pathway remain unknown (Bartenschlager & Lohmann, 2000).

The propagation of HCV in a reliable cell culture system would greatly help in understanding both the viral life cycle and in the development of new antivirals for HCV. Both primary human hepatocytes and PBMCs have been shown to support a limited amount of HCV replication. However, the amount of HCV RNA detected after ~28 days (the longest these cells can be cultured) is low, ranging from -1000 to -60,000 gEq/ml in the supernatants from 10^ cells. Human hepatoma cell lines (HepG2, Huh-7 and PH5CH) and human B- and T-cell lines (Daudi, MOLT-4 and MT-2) have also been used. Infectivity was again low in these cells, but a human B- cell line (Daudi) supported low titres of HCV replication for over 1 year (Nakajima et

15 Chapter 1: General Introduction al, 1996;Bartenschlager & Lohmann 2001). An alternative method is the culturing of hepatocytes or PBMCs from persistently infected patients. A variety of systems have been set up, but the level of viral replication in these cells is also very low (Sung et al, 2003). Transfection of cells with cloned viral DNA or transcripts generated from this template has proved difficult, possibly because many of these constructs lacked most of the 3’UTR (Bartenschlager & Lohmann 2001). A system has been set up involving the replication of engineered HCV minigenomes in Huh-7 cells. These bicistronic molecules were derived from an HCV consensus genome, and consisted of the selectable marker neomycin phosphotransferase (G418) under the control of the HCV 1RES and HCV NS3-NS5B under the control of the encephalomyocarditis virus (ECMV) 1RES. G418 selected Huh-7 cells transfected with these constructs, contained these autonomously replicating constructs at titres of up to -5000 positive strand RNA copies per cell, with negative strand RNA being 5 to 10 fold less abundant. Under continuous G418 selection, these replicons have been propagated for >2 years, during which they also acquired some cell culture adaptive mutations, mainly in the NS5A region. As these cells carry high levels of replicating RNAs containing all the known viral enzymes, and can be stably replicated for years, they are useful tools for drug development and evaluation (Bartenschlager & Lohmann 2001). However, more research is needed in order to produce a system that efficiently produces infectious virus and to find a permissive cell line that can produce high titres of infectious virus. The important recent development of mice with chimeric human livers that can synthesise and release infectious HCV particles should also greatly aid HCV research (Mercer et al, 2001), but at present this system remains prohibitively expensive for most researchers.

1.6 Genetic variability and genotype

The HCV genome is highly variable as a result of the highly error prone RdRp, and different isolates are significantly different. In the past, HCV has been classified into genotypes using a variety of methods including sequencing of the first 1700 nt of the HCV genome and RFLP (restriction fragment length polymorphism analysis) of NS5. However, a consensus nomenclature was proposed in 1994 based on the phylogenetic analysis of sequences derived from the NS5 region (Nakao et al, 1991;Cha et al.

16 Chapter 1: General Introduction

1992;Simmonds et al, 1993;Simmonds et al, 1994). It is now accepted that HCV has evolved into major genetic groups or genotypes that share 65.7-68.9% nucleotide similarity. Genotypes 1 to 6 are the major genotypes and each new genotype is numbered in order of its discovery. Each genotype is divided into subtypes sharing 76.9-80.1% nucleotide similarity. Finally, HCV exists as a complex of genetic variants within individual isolates, these share 90.8-99% nucleotide similarity and are called quasispecies (Martell et al, 1992;Simmonds et al, 1993;Simmonds et al, 1994;Zein, 2000). The nucleotide similarities between different genotypes and subtypes are shown in Table 1.1.

1.6.1 Geographical distribution and disease associations

The geographical distribution of the six major HCV genotypes is shown in Figure 1.3. The clinical significance of HCV genotypes was predominantly investigated in Europe the USA and Japan. Therefore, we know most about genotypes 1, 2 and 3 (Zein, 2000).

The distribution of different HCV genotypes varies widely. Subtypes la and lb are most common in the USA and Europe. In Japan, subtypes lb, 2a and 2b are most prevalent. Subtype 3a is most prevalent in IVDUs from Europe and the USA. Genotype 4 is most prevalent in North Africa and the Middle East and 5 and 6 in South Africa and Hong Kong respectively. Genotypes 7 to 9 were found in Vietnam and 10 and 11 in Indonesia (Tokita et al, 1998;Tokita et al, 1996) although investigators now consider these to be subtypes of genotypes 3 or 6. In fact, the difficulties encountered with the classification of these Asian HCV isolates, suggests that HCV heterogeneity may in fact be a continuum. However, the categorical grouping of isolates remains very useful in the study of HCV epidemiology, disease progression and transmission (Simmonds et al, 1993;Farci & Purcell, 2000). The geographical distribution and diversity of different HCV genotypes also provide information on the historical origin of HCV. There are numerous and often unclassifiable subtypes in Africa and South East Asia suggesting that HCV has been endemic in those regions for a long time. Conversely, there are only a limited number of subtypes seen in the USA and Europe suggesting that HCV was a more recent

17 Chapter 1: General Introduction

% Similarity to: Subtype la lb Ic 2a 2b 2c 3a 3b 4a 5a 6a la 100 81 85 65 66 63 67 66 68 69 64 lb 100 77 64 67 64 67 71 64 70 65 Ic 100 68 70 67 65 70 64 61 61 2a 100 82 77 67 67 66 66 68 2b 100 81 64 69 65 67 66 2c 100 64 65 65 66 65 3a 100 79 65 67 64 3b 100 66 68 61 4a 100 66 66 5a 100 68 6a 100

Table 1.1: Comparative sequence analysis among HCV subtypes of a 222 nucleotide segment at nucleotide positions 7975 to 8196 of the prototype virus NS5 region, taken from Simmonds et al, 1993.

18 Chapter I: General Introduction

Figure 1.3: Worldwide geographic distribution of HCV genotypes and subtypes. ‘Others’ indicate unclassified sequences, taken from Tokita et al, 1996.

19 Chapter 1: General Introduction introduction (Smith & Simmonds, 1997). Curiously, sustained responses to IFNa therapy are more common in Asian patients than those of African or Caucasian descent (Reddy et al, 1999).

1.6.2 HCV genotype and disease associations

Although many studies have evaluated the clinical significance of different HCV genotypes, the results have been controversial. This is because there has been a lack of consistency between the different studies, especially as regards response to interferon therapy. Depending on the study, severity of liver disease was determined by histology, development of cirrhosis or hepatocellular carcinoma. In addition, prior to 1995, response to interferon had been defined as normalisation of liver transaminases after therapy and now it is defined by the disappearance of detectable serum HCV RNA, as well (Zein, 2000). There has also been selection bias in different studies i.e: haemophiliac or dialysis cohorts reflect the HCV genotype prevalence in blood products whilst IVDU cohort studies do not (Puoti et al, 1997). At present, the role of HCV genotype in HCV disease progression is a controversial area of research.

Subtype lb has been often associated with more severe liver disease including development of HCC (Dusheiko & Simmonds, 1994;Sabin et al, 1997;Isaacson et al, 1997;Bruno et al, 1997). For example, in one study, after acute exposure, 92% of patients infected with subtype lb progressed to chronicity whilst the rate for other subtypes was 33-50% (Amoroso et al, 1998). Studies to investigate the mechanism by which subtype lb is associated with a poor response to interferon therapy have focused on the ISDR region, located in the NS5A gene (Enomoto et al, 1995). The Japanese prototype lb strain, HCV-J, contains the ‘wild-type’ ISDR sequence, which does not respond well to therapy. One to three mutations in the ISDR constitute ‘intermediate’ and three or more, ‘mutant’ ISDR types. Japanese patients infected with these strains appear to be responders to IFNa therapy (Enomoto et al, 1995;Fukuma et al, 1998). However, there appears to be no association between ISDR sequence and response to IFNa therapy in American patients (Chung et al, 1999) and the role of the ISDR in response to therapy remains unclear in non- Japanese patients. Subtype lb may also be associated with allograft cirrhosis post

20 Chapter 1: General Introduction transplantation (Prieto et al, 1999), although this is controversial and may relate to longer duration of disease in patients with genotype lb (Poynard et al, 1997;Mihm et al, 1997). Subtypes la and lb are also associated with more rapid progression to ADDS and death in HIV co-infected patients (Sabin et al, 1997). Subtype 3a infection is associated with a significantly higher incidence of steatosis and bile duct lesions than subtype la and higher ALT levels than subtypes la and lb (Trepo, 2000) as well as being associated with impaired CD4 T-cell recovery on HAART (Greub et al, 2000). However, patients with genotype 3 appear to have more vigorous HCV specific CD4 T-lymphocyte proliferative responses, which are associated with sustained viral responses (SVR) post interferon therapy for HCV (Legrand et al, 2002). SVR is defined as the absence of detectable HCV RNA in serum, as shown by qualitative HCV RNA assay with a lower limit of detection of 50 lU/mL or less, 24 weeks after the end of treatment. Patients infected with either HCV genotypes 2 or 3 are also more likely to achieve an SVR than patients infected with genotype 1 or 4 (NIH consensus statement 2002).

1.6.3 HCV quasispecies

The concept of quasispecies was first postulated in 1971 as a model for the rapid evolution of a biological system under selective pressure (Eigen, 1971). It is possible that increased quasispecies complexity in acute HCV infection may correlate with progression to chronicity (Ray et al, 1999). The most important implication of the quasispecies nature of HCV however, is probably its role in the establishment of persistent infection as the host immune response may not be able to contain the wide spectrum of viral genomes (Farci et al, 1997). Some quasispecies types may also not be cytotoxic, modulating wild-type virus replication and possibly facilitating persistence through reduction of cell death (Gomez et al, 1999). Neutralising antibody responses are directed against the HVR-1 of E2 and immune pressure is the likely driving force behind HVR-1 variation (Domingo, 1998;Domingo et al, 1998). In particular, HVR-1 variation may prevent the development of a humoral response that can recognise all HCV variants, which may have implications for both response to antiviral therapy and vaccine development (Trepo, 2000).

21 Chapter 1: General Introduction

HCV quasispecies may also have a role in cellular tropism as the quasispecies distribution from HCV in the liver, circulation and PBMCs differ from each other (Hadida et al, 1998). This suggests that quasispecies groups from different compartments in the body may be able to use different host cell receptors (Maggi et al, 1999). The role of HCV quasispecies in liver disease progression remains controversial however and some studies have found relationships with histological markers of liver damage (Honda et al, 1994), whilst others have not (Brambilla et al, 1998). Inverse correlations have been found between response to interferon treatment and both the number of dominant quasispecies and single strand conformation polymorphism bands in the HVR-1 (Mizokami et al, 1994;Le Guen et al, 1997;Pawlotsky eM/, 1998).

1.6.4 Assigning HCV genotype

The most accurate basis for assigning HCV genotype is clearly the sequencing of the entire genome, but this is impractical. Therefore, portions of the genome have been selected for this type of analysis; in particular a 222bp region of the NS5b gene (Simmonds et al, 1993;Mellor et al, 1995). The six major genotypes of HCV have well conserved polymorphisms in the 5’UTR and a variety of assays have therefore been developed that make use of this, including PCR and restriction fragment length polymorphism (RFLP) based assays (Davidson et al, 1995; Pohjanpelto et al, 1996;Harris et al, 1999), and the line probe assay (LIPA), which is commercially available (Stuyver et al, 1996).

1.7 HCV diagnosis

Antibodies to HCV antigens are present in the vast majority of individuals chronically infected with HCV and most diagnostic tests screen for detectable anti-HCV serum antibody. These assays however, are of limited use in acute infections as they fail to detect HCV infected patients during the window period between viral contact and appearance of antibody, which can last from seven to eight weeks up to several months (Pawlotsky, 1997; Boyer & Marcellin, 2000). More sensitive RT-PCR or

22 Chapter 1: General Introduction viral RNA detection-based assays can be used in acute HCV infection and to accurately quantify the amount of viral RNA in blood or serum.

1.7.1 Serological Assays

The expression of clone 5-1-1 as a fusion polypeptide with superoxide dismutase (SOD) in yeast (antigen c l00-3) was used as the basis for the first generation enzyme- linked immunosorbent assay (ELISA) test (see Section 1.1) (Kuo et al, 1989). Second and third generation serological tests including other antigens were subsequently developed (Yuki et al, 1992;Barrera et al, 1995) and these are the tests most often used for laboratory diagnosis of HCV infection. Although these assays are sensitive and specific, they are prone to giving occasional false negative and positive results. Despite the fact that serological assays are of little use during acute infection, this is an infrequent clinical setting. These assays are useful in ascertaining whether a patient has been exposed to HCV if they are PCR negative, and are also much cheaper than HCV RNA detection based tests, which makes them an important diagnostic tool.

An Irish study of a cohort of women accidentally exposed to HCV 18-20 years previously found that humoral immune responses had become undetectable in many patients, although anti HCV cellular responses persisted. If serology alone is used as a marker of previous HCV infection however, the actual prevalence of the infection may be underestimated (Takaki et al, 2000).

1.7.2 Qualitative and quantitative nucleic acid amplification

Qualitative and quantitative HCV nucleic acid amplification tests are the most sensitive tests for the diagnosis of HCV infection. They can detect HCV viraemia one to three weeks after initial infection and are important in the confirmation of an HCV diagnosis, especially if a patient is a low-risk individual.

23 Chapter 1: General Introduction

1.7.3 Chiron TMA qualitative assay

The Versant HCV RNA qualitative assay (Bayer, Emeryville) is a qualitative assay that can detect down to 10 HCV RNA lU/ml. The assay consists of three steps, target capture, target amplification and target detection. This procedure is abbreviated to TMA, for transcription mediated amplification. Briefly, an internal control is added to each 500pl sample of plasma or serum. HCV RNA is released from the viral particles and stabilised by incubation with a lysis reagent. The viral RNA and control are hybridised to specific capture oligonucleotides and these hybrids bind to magnetic microparticles, allowing several washing and aspiration steps to remove potential assay inhibitors and other interfering substances. HCV RNA is reverse transcribed into cDNA by an RT with RNaseH activity and two primers. The first primer contains a T7 promoter and is used for initial RNA-DNA duplex synthesis. Following RNaseH degradation of the RNA, the second primer binds to the cDNA to form dsDNA. An RNA polymerase is then used that recognises the T7 promoter and synthesises numerous antisense RNA transcripts, which re-enter the above process causing exponential amplification of the target RNA.

RNA amplicons are detected by amplicon specific acridinium ester labelled DNA probes. Unbound probes are inactivated by an alkaline reagent and a detection reagent (Dioxetan) is added. Chemiluminescence from the acridinium ester label is measured in a luminometer. Differentiation between the control and target is achieved by using two different modified acridinium esters. On addition of Dioxetan the internal control probe emits a short intense flash of light (‘flasher’) whilst the target probe emits a longer lasting light (‘glower’) measured shortly afterwards. The ‘flasher’ indicates successful amplification and the ‘glower’ the presence of HCV RNA in the sample. The assay sensitivity is reportedly HCV genotype independent and it is 96 and 100% sensitive to HCV RNA at 5 and 10 lU/ml respectively (Sarrazin, 2002).

24 Chapter 1: General Introduction

1.7.4 Roche AMPLICOR Monitor (manual and COB AS assays)

The HCV AMPLICOR Monitor test (Roche Belleville NJ) is an RT-PCR based assay that involves the isolation of patient sample RNA by guanidine thiocyanate lysis and isopropanol precipetation. An internal standard of known copy number is added to the guanidine thiocyanate buffer and carried through with each patient sample and control throughout the whole procedure. This is especially important in this assay as a control for the RT step, which is inefficient (5-20% efficiency). The internal standard is amplified with the same primers as the patient sample but contains a unique probe-binding site; this does not bind the probe that captures the patient sample PCR product, thus allowing differentiation of the two products. Quantification is based on a comparison of the amplification of the internal standard versus the patient sample and the limit of detection is 400 copies/ml for the standard assay and 50 copies/ml for the Ultrasensitive version of the test. The Ultrasensitive assay achieves increased sensitivity by increasing input plasma volume by a factor of 2.5, concentrating virus particles from plasma by ultracentrifugation, and reducing the final resuspension volume of the recovered virus by a factor of 4. Assuming a 100% recovery of virus, these modifications improve sensitivity 10-fold over the original assay (Sun et al, 1998). The COB AS AMPLICOR HCV Monitor assay is a semi­ automated version of the above where the COBAS instrument performs the amplification, detection and result calculation steps (Martinot-Peignoux et al, 2000; Podzorski, 2002).

1.7.5 HCV quantification by branched chain DNA

The branched chain DNA (bDNA) assay was the first commercially developed quantitative assay for HCV. The QUANTIPLEX HCV version 2.0 (Bayer, Emeryville) is the most frequently used version, although version 3.0 is now available. The bDNA procedure uses a variety of capture probes coupled with multiple reporter molecule constructs to create an amplified signal from captured HCV RNA. Non-specific hybridisation is reduced in version 3.0 by the use of artificial bases (isocytidine and isoguanosine) in the preamplifier and amplifier probes. RNA standards are run with patient samples and constitute a standard curve

25 Chapter 1: General Introduction against which patient viral loads can be determined. The sensitivity of the version 2.0 assay is 200,000 copies/ml and that of the version 3.0 is 3200 copies/ml (Martinot- Peignoux et al, 2000;Podzorski, 2002;).

1.7.6 NucliSens quantification of HCV

The NucliSens system (Biomerieux, Marcy-TEtoile, France) uses an isothermal RNA target amplification procedure that does not require reverse transcription. lOO-lOOOpl of patient serum is used and extracted using a silica bead nucleic acid isolation process. Three competitor internal standard RNAs (Q-RNAs) are added per sample before extraction and followed by single tube co-amplification. Resultant co­ amplified products are captured by a DNA probe attached to paramagnetic beads. Products are distinguished by hybridisation with ruthenium labelled probes and detected by electrochemiluminescence. HCV RNA load is calculated from an internal standard curve obtained from the three Q-RNAs (Podzorski, 2002).

Run-to-run precision is estimated at between 15 and 35% for all three quantitative assays. HIV-1 RNA is quantified commercially by similar methodologies from the same companies (Chew et al, 1999;Anastassopoulou et al, 2001).

1.8 Associations of HCV RNA load with disease and treatment outcomes

The association between HCV RNA levels and aspects of liver disease progression such as steatosis, fibrosis, cirrhosis, HCC and liver decompensation remains controversial. HCV RNA load is however an important determinant of response to IFNa therapy.

1.8.1 Response to treatment

HCV genotype and viral load are most clearly associated with response to treatment. Patients with elevated HCV RNA load (over 2x10^ gEq/mL) respond more poorly to IFNa therapy and are treated for twice as long, as are those with genotype 1 (see

26 Chapter 1: General Introduction

Section 1.9.2) (Hayashi et al, 1998;Davis et al, 1998;McHutchison et al, 1998). Additionally, the rate of decline of HCV RNA during weeks 2 to 12 of interferon therapy is predictive of treatment efficacy (Hayashi et al, 1998;Zeuzem et al, 1998).

1.8.2 Disease progression

It is a well-established fact that HIV RNA load is predictive of HIV disease progression (Mellors et al, 1995;MeIIors et al, 1996), but whether HCV RNA load is predictive of disease progression for either HIV or HCV remains controversial. It is possible that HCV replication can occasionally be directly cytopathic such as in the case of fibrosing cholestatic hepatitis (FCH) post-transplantation (Boletis et al, 2000), although FCH has occurred in HIV co-infected patients without elevated HCV RNA load (Rosenberg et al, 2002). In cirrhotic patients, elevated HCV RNA load (>lxl0^gEq/ml) is predictive for the development of HCC, amongst other factors (Ishikawa et al, 2001). Elevated HCV RNA (>3xl0^gEq/ml) also correlates with elevated histological activity index (HAI) score, fibrosis and steatosis in persons with CHC (Adinolfi et al, 2001). In HCV positive liver transplant recipients; elevated HCV RNA load correlates significantly with both graft rejection and death (Deshpande et al, 2001). Patients infected with HCV genotype 1 have elevated HCV RNA load and progress to both AIDS and liver disease faster than other patients (Sabin et al, 1997). Individuals with haemophilia also have elevated HCV RNA load compared to patients with post-transfusion hepatitis although whether it is associated with a worse prognosis for this patient group has yet to be determined (Cohen & Fauci, 2002). In a cohort of 207 co-infected patients, each 10-fold increase in HCV RNA load correlated with a 1.66 (95% Cl) increased relative risk of clinical progression to AIDS. However, a recent study found no association between either HCV RNA load or HCV genotype and progression to end-stage liver disease (ESLD) in HIV co-infected patients (Goedert et al, 2001). Factors other than HCV RNA load also associated with a poorer prognosis include older age (<40 years) at start of infection, alcohol consumption, and both HIV and HBV co-infections (Poynard et al, 1997;Seeff, 1999).

27 Chapter 1: General Introduction

1.9 HCV therapy

HCV is theoretically a good target for antiviral therapy because of its long chronic phase of infection during which treatment can be administered. The virus encodes various enzymatic activities not common to humans and these present viable targets for antiviral therapy. These targets include HCV encoded proteases (at the NS2/3, NS3/4A and NS4B/5A junctions), the NS3 viral helicase and the NS5B RdRp (Kwong et al, 1998; Bartenschlager, 1999;Major et al, 2002). Although current advances in interferon-based therapy have greatly improved response rates to therapy, the treatment remains expensive, difficult to tolerate and ineffective in a large proportion of patients. Novel therapeutic strategies are therefore clearly needed.

1.9.1 Interferon-a monotherapy

Interferon-a monotherapy (IFNa therapy) has been commercially available for the last 12 years and was the first antiviral drug available to treat chronic HCV. Therapy consists of three million units injected subcutaneously three times weekly and SVR are infrequent. In initial trials, ALT levels normalised (a biochemical response) in an average of 24%-28% of patients after 24 or 48 weeks of therapy, decreasing to 11%- 16% respectively after a ftirther 24 weeks without treatment (Davis et al, 1998;McHutchison et al, 1998). Racial differences may also be important, as long­ term sustained responses are more frequent in Asian or Caucasian patients than those of African descent (Reddy et al, 1999).

However, it appears that IFNa monotherapy administered during the acute phase of infection can result in undetectable HCV RNA in 98% of patients independent of HCV genotype (Patel & Germer, 2002;Tocci et al, 2002;Seligman & Fox, 2002;Muir & Rockey, 2002). The vast majority of acute HCV infections are not reported or are subclinical however, so despite its effectiveness, this treatment is likely to be of use only in a small minority of infected persons.

2 8 Chapter 1: General Introduction

1.9.2 Interferon-a and ribavirin combination therapy

IFNa and ribavirin (RBV) combination therapy was introduced in 1998 and is more effective than IFNa monotherapy. It consists of standard IFNa therapy (see Section 1.9.1) in combination with 1000 or 1200mg/day of RBV (depending on weight). Therapy leads to ALT normalisation in 58%-65% of patients after 24 or 48 weeks of treatment, decreasing to 32-36% respectively 24 weeks post treatment. An SVR of 31% (increasing to 38% is seen after 24 and 48 weeks of therapy (Davis et al, 1998;McHutchison et al, 1998). HCV genotype and to a lesser degree, HCV RNA load prior to treatment both affect the response rate to combination therapy. For this reason, initial therapy is recommended for six months, with extension to one year in patients with bridging fibrosis or necrosis, HCV genotype 1 or HCV RNA loads of over 2x10^ gEq/mL (Davis, 2000). Interestingly, there appears to be no relationship between race and response to combination therapy (De Maria et al, 2000). RBV is thought to act by both shifting the T-helper cell response in a Thl direction and by increasing the frequency of mutations in the HCV genome (Hultgren et al, 1998;Contreras et al, 2002). However, monotherapy with RBV is not effective for HCV.

1.9.3 Pegylated interferon therapy

There are two pegylated interferons on the market. IFNa 2a attached to a Mr 40000 PEG (polyethylene glycol) moiety, called Pegasys (Hoffinann-La Roche) and PEG- Intron (Schering-Plough), consisting of IFN- 2b attached to an Mr 12000 PEG moiety (Zeuzem et al, 2000;Bamard, 2001). PEG addition increases the half-life of the drug in the body (54h for pegylated interferon versus 8h for IFNa) allowing for once weekly administration and making it a more tolerable treatment than standard interferon. To date, the highest response rates to therapy for HCV have been achieved with pegylated interferon and ribavirin combination therapy.

Three large trials have examined the efficacy of pegylated interferon and ribavirin in the treatment of chronic HCV infection. These trials excluded patients with decompensated cirrhosis and comorbid conditions. Pegylated interferon and ribavirin was more effective than pegylated interferon alone or interferon and ribavirin

29 Chapter 1: General Introduction combination therapy. However, SVR rates were similar between both forms of pegylated interferon (alpha 2a and alpha 2b). Factors associated with successful therapy included genotypes other than 1, lower baseline HCV RNA levels, less inflammation on liver biopsy and lower body weight or surface area. For patients with genotypes 2 or 3, SVRs with standard interferon and ribavirin were similar to those obtained with pegylated interferon and ribavirin so the former treatment may be used for these patients. In two trials of 48 weeks of pegylated interferon and ribavirin, patients with genotype 1 achieved SVRs of 42-46%, whilst those with genotype 2 or 3 achieved SVRs of 76-82% after 24 weeks. This suggests (as in section 1.9.2), that 6 months of treatment appears to be sufficient for genotypes 2 or 3, while patients with genotype 1 should be treated for 1 year. A third study suggested that higher doses of ribavirin, 1000 to 1200 mg/day versus 800 mg/day may slightly increase SVR (NIH consensus statement 2002).

An early viral response (EVR) defined as a minimum 2 log decrease in HCV RNA during the first 12 to 24 weeks of therapy is predictive of SVR and should be a part of routine patient monitoring. If patients fail to achieve an EVR after 12 or 24 weeks of treatment, they are unlikely to achieve an SVR even after 1 year of therapy. Treatment can therefore be discontinued after 12 or 24 weeks in these patients (NIH consensus statement 2002).

1.9.4 Future therapies for HCV

A new approach involves the use of synthetic nuclease-resistant ribozymes that inhibit viral replication by cleaving the HCV 1RES. Cell culture studies have revealed potent inhibition that is additionally potentiated by IFN (Usman & Blatt, 2000;Macejak et al, 2001). Ribozyme therapy also appears to be well-tolerated (Sandberg et al, 2000). Immunomodulatory agents such as IL-2 appear to upregulate anti-HCV immune responses and could be used therapeutically, although this is controversial (Schlak et al, 1999;Thibault et al, 2002). RBV is an inhibitor of inosine monophosphate dehydrogenase (IMPDH), an enzyme essential for the modulation of host cellular pathways. Inhibition leads to a depletion of intracellular GTP levels, and a small orally bioavailable IMPDH inhibitor drug, VX-497 (Vertex Pharmaceuticals), has a

30 Chapter 1: General Introduction broad spectrum of antiviral activity and is active against HCV. Phase I and II studies in CHC patients suggest that it is 20-fold more potent than RBV and may be used in combination with IFN (Di Bisceglie et al, 2002). Amantadine is a compound that decreases ALT levels in CHC patients, but with no corresponding decrease in viraemia. It may be of use in combination with interferon or interferon and ribavirin in patients that fail interferon therapy (Yagura & Harada, 2001). Max amine (Maxim Pharmaceuticals) is a histamine inhibitor with anti-HCV activity and studies are currently ongoing to evaluate its usefulness in conjunction with pegylated IFN (Barnard, 2001). Research is also ongoing to develop NS3 protease and helicase inhibitors, as well as inhibitors of the NS5 RdRp. Such novel agents could be used alone or in combination with IFN (Di Bisceglie et al, 2002). A histological amelioration of HCV related pathology is observed even in patients that do not achieve an SVR after IFN, pegylated IFN or combination therapy with ribavirin (McHutchison et al, 1998;Manns et al, 2001), suggesting that pegylated IFN maintenance therapy in these patients might be of clinical benefit. Additionally, adjuvant therapy such as iron removal by phlebotomy may increase sustained responses in patients (Fargion et al, 2002). It has recently been found that patients who did not achieve an SVR to interferon and ribavirin combination therapy had significantly higher median s-ferritin values than those who did respond to therapy (130pg/L vs 75pg/L, p= <0.001) (Distante et al, 2002).

1.9.5 Progress towards the development of a vaccine for HCV

The development of an effective vaccine for HCV is proving problematic. The genetic diversity of HCV and high mutation rate complicate vaccine development, as does the lack of a suitable in vitro cell culture system to produce vaccine quantities of virus. A vaccine based on the El and E2 glycoproteins was tested in chimpanzees in 1994 (Choo et al, 1994). It produced a strong but short-lived antibody response that needed frequent boosting. Protection was only seen if the animals were challenged with very low doses of the same strain of virus as that used to make the vaccine. An effective vaccine would probably be required to elicit more non-classical functions, such as the development of strong CD4+ T-helper and CD8+ T-cell responses (Major et al, 2002).

31 Chapter 1: General Introduction

1.10 Pathogenesis of HCV

HCV is not usually directly cytopathic and hepatic damage appears to arise from the destruction of infected hepatocytes (Ferrari et al, 1999). The release of lytic granules or Fas/FasL interactions by CD8+ CTLs can kill uninfected bystander cells as well as infected hepatocytes. The rate of viral replication versus the generation of immune responses is crucial. Early vigorous T-cell responses to a few infected cells does not lead to hepatitis whereas a few days delay can result in fulminant hepatitis due to the increase in the number of targets killed (Ehl et al, 1998). Many studies of both T-cell and B-cell immunity to HCV have measured immune parameters in patient sera, however relatively few have also investigated these parameters in the liver. This is important, as it is the primary site of infection and compartmentalisation of immune responses does occur i.e. there is enrichment of both anti-HCV CD4+ and CD8+ T- cells in the liver (He et al, 1999;Schirren et al, 2001). Additionally, there are only a small number of HCV epitopes mapped for both CD4 and CD8+ T-cells and most studies of CTL responses have focussed on HLA-A2 restricted peptides due to the high prevalence of this haplotype in the general population. HLA-A2 restricted peptides may not be the most crucial for viral clearance, and the response to many other peptides of all possible HLA types must be examined, in order to get a truer picture of the overall cellular immune response to HCV (Lauer et al, 2002b).

1.10.1 Humoral immunity

The humoral immune response plays a part in the resolution of acute HCV infection, although it may be less important than that of the cellular immune response. E2 contains the HVR-1 region and antibodies to it are neutralising. E2 binds to the putative HCV receptor CD81 and antibodies to it have been shown to block this interaction (Piled et al, 1998). Mutations in the HVR-1 region are associated with viral escape and progression to chronicity (Farci et al, 2000). Antibody responses to structural proteins during the acute phase however, are transient, weak and not associated with viral clearance (Baumert et al, 2000).

Chronic infection is associated with elevated anti-HCV titres (Baumert et al, 2000), but the role of antibodies in CHC remains to be elucidated. In contrast to acute

32 Chapter 1: General Introduction infection, mild disease is associated with an accumulation of non-synonymous amino acid substitutions within the E2 HVR-1; whilst the virus population in severe progressive liver disease remains more stable (Curran et al, 2002). Anti-HCV antibodies eventually become undetectable in between 2% and 20% of patients (depending on the study). This usually correlates with the disappearance of HCV viraemia, which suggests that the anti-HCV humoral response requires antigenic stimulation in order to be maintained (Simon et al, 1994;Osella et al, 1997;Seeff et al, 2001;Kondili et al, 2002). HCV infected individuals with congenital immunoglobulin defects suffer more severe liver disease, suggesting that the humoral immune response plays an important role in controlling HCV infection (Bjoro et al, 1994). Additionally, in vivo infection of an HCV naïve chimpanzee can be prevented by preincubating HCV with serum from an infected animal, which suggests the presence of effective neutralising antibodies (Farci et al, 1994). The interaction of both humoral and cellular responses to HCV is likely to be important in disease progression and outcome (Klenerman et al, 2000), see Figure 1.4.

1.10.2 Cellular immunity (CD4+ T-lymphocytes)

Acute HCV infection is resolved in patients during a bout of self-limited (usually subclinical) hepatitis. Resolution is also associated with a strong, multispecific and long lasting CD4+ T-cell response (Diepolder et al, 1995;Gerlach et al, 1999;Rosen et al, 1999;Harcourt et al, 2001). In fact, HCV specific cellular immune responses can persist for 20 years or more (Takaki et al, 2000). The most frequently recognised CD4+ T-cell epitopes are core amino acid positions 21 to 40, NS4 1767 to 1786, NS4 1909 to 1929 and NS3 1251 to 1272 (Diepolder et al, 1996;Lamonaca et al, 1999;Tabatabai et al, 1999). These epitopes are highly immunodominant and conserved between different HCV genotypes, making them possible candidates for a prophylactic or therapeutic T-cell anti-HCV vaccine.

Patients able to resolve HCV infection also develop a predominantly Thl response in peripheral blood (Tsai et al, 1997). Thl cytokines (i.e. IFNy, TNF-a and IL-2) are

33 Chapter I: General Introduction

. low Ab selection pressure cm strong viral viral control clearance

high Ab selection pressure weak viral viral control persistence immune escape

loss of CTL activity no generation of new Ab specificities loss of T help

• CD4 no generation of new CTL specificities

Figure 1.4: How interactions between cellular and humoral immune responses may affect viral escape. Redrawn from Klenerman et al, 2000.

34 Chapter 1: General Introduction important in the development of host antiviral immune responses involving CD8+ T lymphocytes and NK cells, whilst Th2 responses (i.e. IL-4 and IL-10) downregulate the Thl response and enhance antibody production. One of the mechanisms by which RBV is thought to enhance IFN-a therapy is by shifting the T-helper cell response in a Thl direction (Hultgren et al, 1998). There is also an association between class II MHC haplotype (HLA-Z)R67*7707 in linkage disequilibrium with HLA-Dg^7 *0301) and resolution of acute infection. The mechanism behind this is unclear, but patients with the above haplotype have a greater number of CD4+ T-cell responses to a greater number of epitopes (Thursz et al, I999;Harcourt et al, 2001).

Defective, weak or transient CD4+ T-cell function is found in patients that progress to CHC (Gerlach et al, I999;Takaki et al, 2000;Chang et al, 2001). CD4+ T-helper cell responses in peripheral blood are shifted in a Th2 direction and become almost undetectable in the -80% of patients that progress to chronic infection; the appearance of serum HCV RNA coincides with this disappearance in some cases (Gerlach et al, 1999). There also appears to be a further Thl to Th2 switch during chronic infection (Eckels et al, 2000;Klenerman et al, 2002).

1.10.3 Cellular immunity (CD8+ T lymphocytes)

A strong multispecific CD8+ T-cell response mainly directed against NS proteins develops in patients who resolve acute HCV infection (Lechner et al, 2000b). Additionally, the CD8+ T-cells express high levels of CDS 8 and class II MHC indicating that they are activated, and the proportion of activated cells correlates with serum ALT levels (a surrogate measure of liver inflammation) (Lechner et al, 2000a); a correlation that is not seen in chronic infection. However, the ability of CD8+ T- cells to secrete antiviral Thl cytokines is impaired in some patients regardless of the level of antigen (Lechner et al, 2000b;Gruener et al, 2001). The class I HLA allele Cw*04 is associated with persistence, with two copies being more associated than one, but it has no relation to HCV RNA load. The reason behind this is not clear at present (Thio et al, 2002).

35 Chapter 1: General Introduction

CD8+ T-cell cytotoxicity to fewer epitopes results in progression to chronic infection (Lechner et al, 2000b;Lechner et al, 2000a;Takaki et al, 2000;Chang et al, 2001). Progression to chronicity probably depends to an extent on the balance between activated T-cells induced primarily in lymphoid tissue that migrate to the liver and suppress viral replication, and T-cells from the liver environment where high HCV RNA loads promote T-cell exhaustion and viral escape. The CD8+ T-cell response to HCV during chronic infection is directed against a broad range of epitopes with no immunodominant epitope being consistently recognised. This response appears to be inefficient, allowing high HCV RNA loads that promote T-cell exhaustion and viral escape (Lauer et al, 2002a;Ward et al, 2002). CD8+ T-cell responses could be detected in the majority of patients with chronic HCV infection when a panel of 301 20mer peptides, overlapping each other by lOaa and spanning all HCV proteins, were used as the antigen (Lauer et al, 2002b). This study confirmed the fact that epitopes restricted to a single HLA allele, such as HLA A2 gave incomplete information about the HCV specific cellular immune response in an individual.

Chronic HCV infection is also characterised by inflammatory infiltrates in the liver (Gonzalez-Peralta & Lau, 1995). Liver lesions arise during infection, probably due to a continuous active T-cell response triggered by persistent HCV infection. Wound healing in response to this ongoing injury (liver fibrosis) leads to structural changes in the liver that may culminate in cirrhosis, liver failure or HCC. Within the liver, Thl cytokines have been associated with progressive liver injury possibly by recruiting non-antigen specific CD8+ T-cells (Ballardini et al, 1995;Napoli et al, 1996). The phenotype of peripheral CD8+ T-cells detected during chronic infection is of low CD62L and high CD45RO (‘memory’ phenotype markers), these cells are also low CD69, CD38 and MHC class II (‘resting’ phenotype markers), high in CD27 and low in CD28 (possibly ‘immature’ phentoype) (Lechner et al, 2000b;Appay et al, 2000b). In contrast, intrahepatic CD8+ T-cells are predominantly CD69+, which is indicative of activation (He et al, 1999). Peripheral CD8+ T-cells from patients recently progressed into CHC are defective in their ability to secrete antiviral Thl cytokines (Gruener et al, 2001). Dendritic cells (DC) in chronic HCV infection are impaired in their ability to present antigen (Hiasa et al, 1998;Kanto et al, 1999), but CD8+ T-cell responses to other viruses, such as EBV, appear to be normal (Lechner et al, 2000b;Gruener et al, 2001). Transduction of DC with HCV core and El leads to

36 Chapter 1: General Introduction incomplete activation characterised by enhanced CD25 expression but reduced IL-2 production, although the mechanism for this remains unknown (Sarobe et al, 2002). More work is needed to clarify both the role of DC in HCV infection and reason why HCV specific CD8+ T lymphocytes are dysfunctional. Figure 1.5 summarises some of the immunopathogenic mechanisms involved in CHC and is adapted from Gonzalez-Peralta et al, (1994).

1.10.4 Innate immunity and additional factors

NK cells can quickly produce large amounts of IFN-y, skewing the adaptive immune response in a Thl direction; in fact, clearance of HBV in chimpanzees by IFN-y (possibly due to NK cell activation) has been demonstrated prior to accumulation of T-cells (Guidotti et al, 1999;Tseng & Klimpel, 2002). Cross-linking of CD81 receptors by monoclonal antibody (mAh) or HCV E2 inhibits both NK cell cytotoxicity and IFN-y production (Tseng & Klimpel, 2002;Crotta et al, 2002). There is an unusual subset of NK cells called NKT-cells that have a restricted alpha-beta TCR in combination with surface markers common to NK cells. These cells are known to produce pro-inflammatory and regulatory cytokines and have been detected in the liver using CDld-lipid tetramers (the NKT ap T-cell receptor recognises lipid- CDld complexes) (Matsuda et al, 2000;Karadimitris et al, 2001). In contrast to NK cells, CD81 ligation on NKT-cells by mAh or HCV E2 delivers a co-stimulatory signal (Crotta et al, 2002). HCV specific gammadelta T-cells compartmentalise to the liver, and the intrahepatic frequency of these cells is greater in HIV co-infected patients (Agrati et al, 2001). The role of these and other cells in chronic HCV infection remains to be clarified.

HCV negative strand RNA has been detected in B-cells (Karavattathayyil et al, 2000), which also express CD81. This may be why HCV is associated with some B-cell mediated disorders, such as type II cryoglobulinaemia and B-cell non-Hodgkins lymphomas (Dammacco et al, 2000;Imai et al, 2002). However, these studies are controversial and further work is needed, as experiments to detect negative strand HCV RNA have proven difficult to reproduce. Additionally, recent experiments have not detected any effect of HCV core on B-cell regulation of proliferation or

37 ■ complement Impaired antigen ^ CD4/8 Tcell J ^ / ^ o r ADCC presentation antibody X Defective T-cell activation

UNINFECTED HEPATOCYTE Interference with Autoimmune pathogenesis dendritic cell due to shared epitopes function

direct cytopathic ( h ^ damage HCV INFECTED w Replication 00 In B-cells? HEPATOCYTE T-cell mediated damage to virally infected cells IL-2, IFN-y, TNF-a [Thl cytokines] Bystander Recruitment of non-antigen effects specific T-cells

antibody O : HCV antigen | f : autoantigen/neoantigen U:BCR | : CD40L/CD40 I : HLA class I \Z7: HLA class II \J : HLA class I or II : CD4 • CD8 \7 \7 | f : TCR (Tc,Th or either)

Figure 1.5: Immunopathogenic mechanisms potentially involved in hepatocellular damage in chronic HCV infection. Adapted from Gonzalez-Peralta et al, 1994. Chapter 1: General Introduction programmed cell death signal transduction pathways (Giannini et al, 2002). The mechanism for this association therefore remains unclear. Binding of HCV to CD81 on B-cells could also lower the cells activation threshold, facilitating the production of autoimmune antibodies (Fearon & Carter, 1995). EBV binding to CD21 is an analogous situation (Cooper et al, 1988) (see Figure 1.5). Additionally, chronic HCV infection is often associated with psychological distress and HCV negative strand has also been recently detected in the CNS (Barrett et al, 2001;Radkowski et al, 2002).

Transgenic mice intrahepatically expressing the HCV core protein develop progressive steatosis (Odeberg et al, 1997). Bile duct damage (common in HCV infection), is uncommon in other forms of hepatitis (Bach et al, 1992;Lefkowitch et al, 1993) and Mallory-like bodies (eosinophilic material in the cytoplasm of periportal hepatocytes) are found in ~20% of CHC cases (Lefkowitch et al, 1993). Histologically, the above triad of steatosis (large droplets of fat vacuoles in hepatocytes), bile-duct damage and lymphoid follicles are indicative of chronic HCV infection (Bach et al, 1992;Scheuer et al, 1992).

1.11 HIV epidemiology

Since its discovery in 1983 (Barre-Sinoussi et al, 1983), over 60 million people have been infected with HIV worldwide. In this section, HIV refers to HIV-1 rather than HIV-2 due to its greater prevalence and pathogenicity. HIV is now the fourth biggest cause of death and at the end of 2001, it was estimated that 40 million people were HIV positive. At present, sub-Saharan Africa is the worst affected area, with 2.3 million African HIV related deaths in 2001 and 28.1 million HIV positive people. In some places such as Botswana, the prevalence rate among pregnant women exceeds 30%. The Caribbean is the region with the second highest prevalence, whilst the fastest growing rate of HIV infection is being observed in Eastern Europe, particularly in the Russian Federation fuelled by the increasing availability of illicit drugs and a burgeoning sex trade. There have been over 25 million HIV related deaths since the epidemic started (UNAIDS/WHO, 2001).

39 Chapter 1: General Introduction

Epidemiological evidence indicates that the most common means of HIV transmission are homosexual or heterosexual intercourse, receipt of infected blood or blood products and transmission from mother to infant (30% probability of transmission unless mother is treated with antiviral agents). Similarly to HCV (see Section 1.2), many haemophiliacs were infected with HIV from large donor pool derived blood products prior to the introduction of heat sterilisation in 1985 (Sabin et al, 2000h;Goldsby et al, 2000). The prevalence of HIV infection amongst UK haemophiliacs that were given these products is 19.5% and virtually all are HCV co- infected (Darby et al, 1995;Lee, 1998).

Although this thesis focuses primarily on aspects of chronic HCV infection, it does so in the context of concurrent HIV infection. The presence of HIV increases HCV RNA load and greatly accelerates liver disease progression (Eyster et al, 1994;Telfer et al, 1994) whilst the presence of HCV increases the risk of death or an AIDS defining illness and impairs CD4 T-cell count recovery on HAART (Greub et al, 2000).

1.12 HIV natural history

Over half (and possibly up to 90%) of primary HIV infections are symptomatic, but most are not recognised in the acute phase (Schacker et al, 1996). Symptoms are extremely varied and include fever, rash, pharyngitis, and lymphadenopathies (Niu et al, 1993). Other symptoms may occur such as myalgias, arthralgias, diarrhoea, nausea, vomiting, headache, hepatosplenomegaly, weight loss, thrush and neurological symptoms with a mean duration of three weeks (Kinloch-de Loes et al, 1993). See Figure 1.6, adapted from Fauci et al, 1996 and Goldsby et al, 2000 for an overview of the natural history of HIV-1.

Untreated chronic HIV infection results in an average of 10 years of clinical latency (although this is very variable between individuals) and it may be associated with some fatigue and generalised lymphadenopathy. As the CD4+ T-cell count falls below 500 cells/pl, syndromes associated with depressed cellular immunity begin to appear such as candidiasis, recurrent or multidermatomal herpes zoster etc, as well as

40 Chapter 1: General Introduction

Seroconversion Death

Acute phase Chronic Phase AIDS Anti-HIV antibody

1200

Symptom Symptom category C category A a. Symptom category B c 3 oO O(D t—' TT+ Q U HIV RNA load CD4+ T cell coi

0 Weeks Years

Figure 1.6: Natural history of HIV infection in an untreated patient, from initial HIV infection to death, at 10 to 11 years post infection. Redrawn from Fauci et al, 1996 and Goldsby et al, 2000. The interval between disease stages averages out to the years shown, but is very variable between individuals. See Table 1.2 for outlines of symptom categories A to C.

41 Chapter 1: General Introduction constitutional symptoms such as unexplained fever or diarrhoea lasting for more than one month (1992). As the CD4+ T-cell count decreases to below 200 cells/pl, the loss of integrity of the cell mediated immune response allows pathogens with limited virulence to become life threatening (see Table 1.2) (Cohen & Fauci, 2002). The steep increase in the risk of development of AIDS defining illnesses below CD4+ T- cell counts of 200 cells/pl have led to this threshold being considered as AIDS defining in the USA (1992).

1.13 HIV genome organisation and replication

The genome organisation of HIV-1 (and HIV-2) is shown in Figure 1.7 along with encoded gene functions. The first step in productive HIV infection is the binding of SU (env gpl20 or surface envelope glycoprotein) to CD4 on its target cell. This induces conformational changes that allow it to bind to one of a range of G-coupled, 7-transmembrane chemokine co-receptors. The two chemokine receptors most frequently used by HIV in the human host are CCR5 that binds macrophage tropic, non-syncytium inducing HIV strains (R5 viruses) and CXCR4 that binds late disease stage T-cell tropic, syncytium inducing HIV strains (X4 viruses) (Scarlatti et al, 1997). Co-receptor binding induces the coiled protein TM (env gp41 or transmembrane envelope protein) to open and expose three peptide fusion domains that associate with the lipid bilayer, creating hairpin structures that promote fusion of viral and cell membranes. This allows HIV cores to be released into the cell (Chan & Kim, 1998).

Viral uncoating and liberation fi*om the plasma membrane is a poorly understood process that probably involves the phosphorylation of MA (gag p i7 or matrix) via MAP kinase, cyclophilin A, HIV Nef (negative effector, p24) and HIV Vif (viral infectivity factor, p23) proteins, as well as possible modification of local pH by the association of Nef with the V-ATPase universal proton pump in a manner similar to the function of influenza M2 (Franke et al, 1994;Lu et al, 1998;Cartier et al, 1999;Ohagen & Gabuzda, 2000;Schaeffer et al, 2001;Takeda et al, 2002). This process generates the plasma membrane liberated viral reverse transcription complex that consists of the HIV diploid RNA genome, tRNA^^® primer, RT, IN (pol p32 or

42 Chapter 1: General Introduction

Table 1.2: USA AIDS case definitions for adults and adolescents. Redrawn from Cohen et aL 2002.

Clinical categories CD4 count ABC categories Asymptomatic, Symptomatic®, Clinical lymphadenopathy not category AIDS** or acute infection A or C >500/pL A1 B1 Cl (>29%) 200-499/pL A2 B2 C2 (14-28%) <200/pL A3 B3 C3 (<14%)

Categories A3, B3 and Cl-3 are defined as AIDS. ^ Examples of these symptoms include bacillary angiomatosis: thrush; vulvovaginal candidiasis that is persistent or poorly responsive to therapy; cervical dysplasia or carcinoma in situ; constitutional symptoms such as fever or diarrhoea of >1 month duration; oral hairy leukoplakia; multidermatomal or recurrent herpes zoster; immune thrombocytopaenic purpura; listeriosis; pelvic inflammatory disease and peripheral neuropathy.

^ Candidiasis of the oesophagus or respiratory tract; invasive cervical cancer; extrapulmonary coccidomycosis; extra-pulmonary cryptococcosis; extralymphatic cytomegalovirus infection; herpes simplex with mucocutaneous ulcer >1 month duration, or bronchitis, pneumonitis, or oesophagitis; extrapulmonary histoplasmosis; HIV-associated dementia; wasting syndrome; isoporiasis; Kaposi’s sarcoma; CNS lymphoma; non-Hodgkins lymphoma; pulmonary tuberculosis; disseminated M tuberculosis, M avium or M kansasii infection; norcarsiosis; Pneumocystis carinii pneumonia; recurrent bacterial pneumonia; progressive multifocal leukencephalopathy; recurrent Salmonella septicaemia; extraintestinal strongyloidiasis and toxoplasmosis.

43 Chapter 1: General Introduction

gag

pol env 3’LTR

5’LTR 5’LTR: Initiation of transcription, contains TAR element, binds host transcription factors

Gene Protein product Function of encoded proteins gag 53 kDa precursor Nucleocapsid proteins

pl7 Matrix (MA): forms outer core-protein layer p24 Capsid (CA): forms inner core-protein layer p7 Nucleocapsid (NC): binds directly to genomic RNA p6 Interacts with Vpr, contains PTAP, has role in virion budding env 160 kDa precursor Envelope glycoproteins {env contains Rev binding RRE) I gp41 Transmembrane protein (TM): associated with gpl20, mediates fusion gpl20 Surface envelope protein (SU): binds CD4 + chemokine receptors pol Precursor Enzymes I p66 Reverse transcriptase (RT): and RnaseH activity p51 Reverse transcriptase (RT) plO Protease (PR): cleaves gag and pol precursors p32 Integrase (IN): mediates insertion of provirus

vif p23 Viral infectivity factor: yields more stable RT complexes

vpr pl5 Viral protein R: promotes 02 cell cycle arrest

tat pl4 Transcriptional activator: binds TAR, enhances RNA transcription

Regulator of viral gene expression: promotes export of incompletely rev pl9 spliced mRNAs from nucleus, inhibits splicing, binds RRE

nef p27 Negative effector: Upregulates viral transcription, downregulates host cell CD4 and MHC-1, blocks apoptosis, enhances infectivity vpu pl6 Viral protein U: Promotes CD4 degradation, influences virion release Figure 1.7: Genetic organisation of HIV-1 and functions of encoded proteins. HIV-2 organisation is very similar, except that vpu is replaced by vpx. Adapted from Goldsby et al,

2000 and Greene et al, 2002.

44 Chapter 1: General Introduction integrase), MA, NC (gag p7 or nucleocapsid), Vpr (viral protein R, p i5) and various host proteins. Initially, this process utilises the proteins packaged in the HIV virion. This complex docks with actin microfilaments via phosphorylated MA and the HIV genome is reverse transcribed (Karageorgos et al, 1993;Bukrinskaya et al, 1998).

Completion of reverse transcription gives rise to the preintegration complex (PIC) composed of the viral cDNA, IN, MA, Vpr, RT and the DNA binding protein HMGI(Y), which moves towards the nucleus by possibly using microtubules. How the switch from actin micro filaments to microtubules is achieved is unknown (Miller et al, 1997). The PIC is roughly double the size of the diameter of the central aqueous channel of the nuclear pore, which it needs to cross. IN, MA and Vpr have been implicated in this nuclear import, although its mechanism is also unknown at present. IN, MA and Vpr also contain nuclear localisation signals (NLS) and a triple helical domain or ‘DNA flap’ that is generated during reverse transcription may also possibly bind a host nuclear targeting signal (Bukrinsky et al, 1993;Heinzinger et al, 1994;Gallay et al, 1997;Zennou et al, 2000;Sherman et al, 2001). Once in the nucleus, integration of the dsDNA into the host genome is mediated by IN which binds to the ends of the dsDNA. HMGI(Y) and BAF proteins are also needed for integration, but their role in this process is unknown. IN produces a two base recess in the ends of the viral dsDNA, correcting the ragged ends produced by the RT and catalysing the joining reaction that inserts the dsDNA into the chromosome to form the provirus. The viral dsDNA can form three other structures, two LTR circles, single LTR circles or auto-integrated rearranged circular structures, all of which do not produce infectious virus, although they may be transcriptionally active (Miller et al, 1997;Chen & Engelman, 1998;Wu & Marsh, 2001).

Most cells contain more than one provirus and the chromosomal milieu probably affects proviral transcriptional activity (Greene & Peterlin, 2002). The 5’LTR contains upstream and downstream promoter elements that allow the positioning of RNA polymerase II at the site of transcriptional initiation (Taube et al, 1999). Inefficient elongation produces small transcripts stabilised by the presence of an RNA stem-loop called the transcriptional response (TAR) element (Kao et al, 1987). How transcriptionally silent proviruses are roused is unknown, but NFkB is a possible

45 Chapter 1: General Introduction mediator (Greene & Peterlin, 2002). When the pro virus is activated, HIV Tat in association with cyclin T1 binds TAR and recruits Cdk9, which phosphorylates the C- terminal domain of RNA pol II as part of the positive transcription elongation factor b (P-TEFb) complex, marking the transition from initiation to elongation of transcription (Wei et al, 1998;Price, 2000). See Figure 1.8a for a summary of these stages of HIV replication.

Over a dozen HIV-specific transcripts are generated after transcription of the HIV genome; Nef, Tat and Rev are processed cotranscriptionally and rapidly exported to the cytoplasm. Other singly spliced or unspliced viral transcripts remain stably in the nucleus. These encode the viral RNA genome and structural enzymatic accessory proteins, and the nuclear export of these depends on a threshold amount of Rev. Rev binds multimerically to an RNA stem loop called the Rev response element (RRE) located in the env gene, and it contains both an NLS and a nuclear export signal (NES). Export also depends on Ran, a host protein found in an RCCl (Ran nucleotide exchange factor) GTP charged form in the nucleus (Ran-GTP) and RanGAP (RanGTPase protein) catalysed form (Ran-GDP) in the cytoplasm. In nuclear export, outbound protein is loaded onto CRMl/exportin-1 (which forms a complex with NES) in the presence of Ran-GTP and is released in the cytoplasm when Ran-GDP replaces Ran-GTP (Cullen, 1998). See Figure 1.8b for a summary of these stages of HIV replication.

All components of the HIV virion are assembled at the plasma membrane. The immature capsid requires about 1500 gag polypeptides for proper assembly, probably using the human ATP binding protein HP68 as a molecular chaperone (Wilk et al, 2001 ;Zimmerman et al, 2002). Env, Vpr and the recruitment of two copies of viral RNA are also important in this process (Freed, 1998). Myristylation and palmitoylation of the gag polyprotein associate it preferentially with cholesterol and glycolipid rich membrane microdomains (lipid rafts). Virion budding occurs through these domains resulting in cholesterol-rich virion membranes that favour release, stability and fusion of HIV virions with target membranes (Ono & Freed, 2001;Campbell et al, 2001). Virion budding depends on a Tate domain’ PTAP tetrapeptide sequence in the p6 portion of gag, and ubiquitination. TSGlOl (tumour suppressor gene product 101) binds PTAP and recognises ubiquitin through its UEV

46 Chapter 1: General Introduction

Cytoplasm Mucteus H/V-1 Mauijt (MA) CapMd (CA) Inlcgrsfro (IN) EnvMops N u c l e Protein V* "•“'W'* Integration «««Siïïïf y . **îî*éî^ (RT) , Proteese HIV provirus

EriMclope Nuclear P rotein import IN BAF C04 Receptor HMG!(Y) Chemokine coreceptor ^ ^ , Micfolubules n Nuclear Pre-integrafion _Qjg , complex complex V Lipid raft 'A Fusion 0 I f * Reverse transcription on microfilaments Net (7) . Pre-integration complex . . Uncoating 1 ^ »

Vpf

Figure 1.8a: Schematic representation of early events occurring after HIV infection of a susceptible target cell including interactions between gpl20, CD4 and chemokine receptors (CCR5 or CXCR4). These lead to gp41-mediated fusion followed by virion uncoating, reverse transcription of the RNA genome, nuclear import of the viral preintegration complex, and integration of the double­ stranded viral cDNA into the host chromosome, thus establishing the HIV provirus, Greene et al,

2002.

47 Chapter I: General Introduction

R e v # #T at Adaptors CD4 receptor Importing

Lysosome

CRM-1 Inhibition RanGTP of apoptosis CD4 down- regulation /4A SK .l\ TPI34( I \ ip53 / Coated Full-length genomic RNA pit TRan GDP enymRNA Gag-Pol #R ev Virion CRM-1# Env assembly

Vpr-induced n uclear herniation o MHC I • • Cori/fjhufes fo •* * G2 cell-cycte arrest

Figure 1.8b: A summary of late events in the HIV-infected cell culminating in the assembly of new infectious virions. Highlighted are the roles of various viral proteins in optimising the intracellular environment for viral replication including downregulation of CD4 and MHC I, inhibition of apoptosis by Nef, and the induction of G2 cell-cycle arrest by Vpr. A key action of the HIV Rev protein is the nuclear export of incompletely spliced viral transcripts that encode the structural and enzymatic proteins , Greene et al, 2002.

48 Chapter 1: General Introduction

(ubiquitin E2 variant) domain. TSGlOl normally associates with other cellular proteins in the vacuolar-sorting pathway, forming the ESCRT-1 complex that selects cargo for incorporation into the MVB (multi-vesicular body). The MVB is produced, when surface patches of late endosomes bud away from the cytoplasm into the lumen of the endosome. MVB subsequently fuses with lysosomes releasing its contents for degradation. HIV may be able to use this pathway as a means of budding into the extracellular environment (Gamier et al, 1999;Strack et al, 2000;Garms et al, 2001;VerPlank et al, 2001;Katzmann et al, 2001). The Vif protein of HIV is also required in late stages of vims production to suppress the action of CEM15, an antiviral cellular gene that renders progeny vims non-infectious (Sheehy et al, 2002). See Figure 1.8c for a summary of the final stages in the HIV life cycle.

HIV encoded proteins also alter the cell environment; Nef enhances HIV vimlence indirectly by affecting the signalling cascades of T-cell receptor activation, decreasing CD4 expression on the cell surface to promote virion release, activating FasL expression that induces bystander Fas expressing cells (such as CTLs) to apoptose and decreasing surface expression of MHC class I (Greene & Peterlin, 2002). It also blocks apoptosis in the infected cell, prolonging its life and allowing enough time for vims replication (Greenway et al, 2002). Rev dependent expression of Vpr arrests the cell in the G2/M phase of the cell cycle in order to increase transcription and probably enhances viral gene expression. Additionally, this activity may promote nuclear herniations that intermittently cause mixing of soluble nuclear and cytoplasmic material (Gob et al, 1998;De Noronha et al, 2001). See Figure 1.8b for a summary of the effects of Nef and Vpr.

49 Chapter 1 : General Introduction

Endoplasmic ! reticulum \ \ 0 Virion 0 budding Assembly intermediate? V p s 4 0 NIyristyhitlon \ E n v / HP6Î Gag-Pol

Secretory lata domain vesicle -TrCP TSG101

Viral Lipid raft 0 Ubiquitination\ RNA 0 Proteasom e degradation Plasma membrane

Figure 1.8c: Late steps in the assembly of new HIV virions. Components of vesicular protein sorting machinery, TSGlOl and Vps4, have critical roles in the terminal phases of virion budding. Although virion assembly occurs principally at the plasma membrane, the involvement of these vesicular sorting proteins raises the possibility that virion assembly may be initiated on secretory vesicles that are destined for the plasma membrane. The final phase of virion release likely involves viral 'hijacking' and retargeting the process of budding away from the cytoplasm, that normally occurs in the multivesicular body, Greene et al, 2002.

50 Chapter 1: General Introduction

1.14 HIV and HCV co-infection

The greatest prevalence of HIV and HCV co-infection is found in people with haemophilia and IVDUs (Ockenga et al, 1997). In the USA, some 15% to 30% of HIV positive individuals are also HCV co-infected (Sherman et al, 2000). The presence of HIV accelerates HCV disease and this effect can be so marked that liver disease becomes the major cause of death in some co-infected cohorts (Sabin et al, 2000b;Bica et al, 2001).

1.14.1 Effect of HIV co-infection on liver disease

The presence of HIV increases the severity of liver disease in patients co-infected with HCV. A study of 236 co-infected individuals found that palpable livers and spleens were 2.3 and 2.5 times more prevalent respectively in co-infected individuals, as were raised transaminase levels. In this group, after 10 years, the cumulative incidence of AIDS was 31% and liver failure 17% (Eyster et al, 1993). A further study of 255 patients revealed a 10.8% likelihood of liver decompensation after 20 years in HIV co-infected individuals, i.e. they are 21 times more likely to develop this complication (Teller et al, 1994). After HIV seroconversion, HCV RNA load increases, remaining at a higher level than in mono-infection throughout the course of chronic infection. A 58-fold increase in HCV RNA load from 1978 to 1993 was found in a cohort of 223 co-infected haemophiliacs, when the corresponding HCV mono-infected group experienced only a three-fold increase (Eyster et al, 1994). In a Dutch study of 19 HCV seroconverters with 9-year follow-up, HCV RNA loads were on average 1.1 log higher in HIV co-infected patients, a difference that appeared immediately after HIV seroconversion (Beld et al, 1998). As the correlation between HCV RNA load and liver histology is poor, median fibrosis progression rate has been examined and shown to be significantly faster in those HIV and HCV co-infected (Puoti et al, 2001). HIV co-infected patients also have a greater level of lobular inflammation (centrilobular fibrosis, cholestasis and granulocytic cholangiolitis), portal and periportal inflammation and extrahepatic manifestations such as a syndrome of red fingers, cryoglobulinaemia and glomerulonephritis (Pechere et al, 1996;Cohen er a/, 1997).

51 Chapter 1: General Introduction

In a cohort of 310 haemophiliacs, with 25 years of follow-up, 6 out of 183 non-HIV infected HCV positive patients died a liver-related death compared to 20 out of 122 HIV co-infected individuals (p=0.0002) (Sabin et al, 2000b;Yee et al, 2000). Cox proportional hazard models have ascribed an adjusted relative hazard of death for HIV and HCV co-infected individuals of 19.5 (95% Cl 9.2-41.1). Other hazards such as age at HIV infection, HCV genotype 1 and increased alcohol consumption are also significantly associated with elevated relative hazards of death (Yee et al, 2000). A curious related point involves CCR5, the chemokine co-receptor primarily used (in conjunction with CD4) for cell entry by HIV. Patients homozygous for a 32bp deletion in this gene (the CCR5A32 allele) have truncated non-functional CCR5 receptors and are protected against HIV infection. Heterozygosity is associated with slower HIV disease progression (Barroga et al, 2000). In HCV infected patients however, CCR5A32 homozygosity is three times higher than predicted by the Hardy- Weinberg equation and is associated with elevated HCV RNA loads (Woitas et al, 2001;Woitas et al, 2002). This higher frequency may however reflect resistance to HIV in haemophilic patients who are HIV and HCV co-infected (Zhang et al, 2003).

1.14.2 Mechanisms by which HIV may influence HCV disease progression

The presence of HIV alters the cellular immune response to HCV antigens. The production of both Thl and Th2 cyokines is enhanced in CD4/CD45RO phenotype T- cells and may accelerate liver disease as liver injury in CHC correlates with elevated Thl cytokines (Napoli et al, 1996). As shown in Figure 1.5, CTL cytotoxicity probably plays a role in the pathogenesis of HIV and HCV co-infection (Nelson et al, 1997;John et al, 1998). Lymphocytes isolated from individuals with CHC proliferate weakly on exposure to HCV antigens and the presence of HIV further impairs these responses (Valdez et al, 2000). CD4+ T-cell depletion is associated with liver fibrosis in HIV co-infected patients, possibly because the depletion skews the intrahepatic cytokine profile in a Th2 direction, activating hepatic stellate cells, and promoting collagen deposition, which may eventually culminate in cirrhosis (Puoti et al, 2001). HIV co-infection influences the diversity of HCV in co-infected individuals, but the results obtained so far appear contradictory. Heterogeneity in the HVR-1 region of

52 Chapter 1: General Introduction

E2 is greater in HIV co-infected patients, which the authors say may reflect poor immunological control of HCV (Dove et al, 1999), Conversely, HIV co-infection is also associated with lesser HCV quasispecies complexity, which is indicative of reduced immune pressure, if one assumes that HIV-induced immunosuppression lessens the pressure for selecting HCV substitutions (Mao et al, 2001).

The presence of HIV is significantly and independently associated with elevated HCV RNA load irrespective of CD4 count (Beld et al, 1998). A possible explanation for this is that Kupffer cells in the liver can harbour HIV, which allows HIV and HCV to come into close contact with each other (Cao et al, 1992). HIV tat is a potent transcriptional activator (Vogel et al, 1988), and the HCV NS4 gene contains a putative tat-binding site (Ferbeyre et al, 1997), so direct upregulation of HCV replication by HIV is a possibility that requires further investigation.

1.14.3 Effect of HCV co-infection on HIV disease

Pre HAART, no relationship was found between HCV seropositivity and evolution of HIV disease, as progression to AIDS was too rapid. Antiretroviral therapy has now greatly increased the life expectancy of HIV infected people and as the effects of chronic HCV infection increase with time, so the impact of HCV co-infection on these patients is likely to become increasingly significant. In a Swiss study of 3111 HIV infected patients, HCV co-infection was associated with a 1.70 (1.26-2.30) increase in the hazard ratio for AIDS or death. In the same group, CD4 counts in patients on HAART increased at a slower rate when co-infected with HCV, particularly if they had HCV subtype 3a (Greub et al, 2000). Whether HCV has any influence on HIV disease progression however remains controversial. A recent study found that the presence of HCV did not alter the risk of dying, AIDS progression or response to HAART (Sulkowski et al, 2002a).

53 Chapter 1: General Introduction

1.15 HIV therapy

Therapy for HIV is a complex and rapidly evolving field with three simple aims:

• Maximal and durable suppression of HIV RNA load • Restoration and/or preservation of immune function • Reduction of HIV-related morbidity and mortality

Combination therapy or HAART currently consists of three different drug classes: Pis, NNRTIs and NRTIs (see Table 1.3). NNRTIs inhibit the HIV RT by binding to an allosteric site, NRTIs are doubly or triply phosphorylated before being incorporated into the nascent DNA chain, and act as chain terminators. Pis peptidomimetically inhibit the HIV protease (De Clercq, 2000). Regimens currently involve a minimum of three drugs of at least two drug classes and if possible, regimen changes do not involve switching to the unused drug class in order to preserve it for possible future use. HAART failure, usually as a result of poor adherence or viral resistance is a serious problem and there is a constant need for new drugs. There are new NRTIs (amdoxovir and emtricitabine), NNRTIs (DPC-083 and TMC-125) and Pis (atazanavir and tipranavir) in development (Yeni et al, 2002). Drugs to novel HIV targets now include HIV entry or fusion inhibitors such as T-20 and co-receptor entry blockers such as AMD-3100 (De Clercq, 2000). Other novel targets include, integrase inhibitors and viral assembly inhibitors, (De Clercq, 2001;Condra et al, 2002). Drugs to novel targets such as T-20 are already allowing currently multiply drug resistant patients to control their HIV RNA load (Vass, 2002), but resistance mutations to T-20 have already appeared and the need for more drugs or more efficient treatment strategies remains a high priority (Wei et al, 2002).

As the currently available therapeutic strategies do not eliminate HIV, the aim of treatment is to inhibit viral replication so that the patient can once again develop an efficient immune response to most microbial pathogens (Yeni et al, 2002). Treatment is usually initiated when a patient develops symptomatic HIV disease or when their CD4 count falls below 200 cells/pl. Therapy may also be initiated in different settings such as when the HIV RNA level is above 50,000 to 100,000 copies/ml or when CD4 counts are rapidly declining. After initiation of therapy, the CD4 count

54 Chapter 1: General Introduction

Table 1.3: Established antivirals for HIV therapy and their liver related adverse effects. DHHS guidelines 2000.

NRTI drug class Liver related adverse effects Didanosine (ddl) Lactic acidosis with hepatic steatosis Zalcitabine (ddC) (rare but potentially life threatening) Stavudine (d4T) Lamivudine (3TC) Abacavir (ABC) NNRTI drug class Liver related adverse effects Nevirapine Elevated transaminase levels and hepatitis Delavirdine Elevated transaminase levels Efavirenz PI drug class Liver related adverse effects Indinavir Possible increased bleeding episodes in haemophiliacs and nephrolithiasis but no direct liver related adverse effects Ritonavir Inhibits cytochrome P450 system, Hepatitis and possible increased bleeding may be used to increase half life in haemophiliacs. of co-administered Pis. Nelfinavir Possible increased bleeding episodes in haemophiliacs but no direct liver related adverse effects Saquinavir Elevated transaminase levels and possible Amprenavir increased bleeding episodes in haemophiliacs

55 Chapter I: General Introduction usually rises by over 50 cells/|rl at four to eight weeks, followed by a subsequent yearly increase of 50 to 100 cells/fil. A CD4 count of over 200 cells/|il is protective against many opportunistic infections. Effective HAART usually reduces HIV RNA load by over 90% (a 1 log or 10-fold reduction), failure to attain this reduction after four weeks of therapy suggests viral resistance or poor adherence to therapy. A comprehensive review of current treatment recommendations is available in Yeni et al 2002.

1.15.1 Novel approaches to HIV therapy

Structured treatment interruptions (STIs) are a novel treatment strategy currently being evaluated. The approach is being assessed in three different clinical settings:

• Shortly after acute infection, when the patient has strong T-cell mediated responses, in order to achieve immune control of viral replication and prolong the period prior to commencement of HAART. • During chronic infection, to decrease the toxicity associated with HAART and improve quality of life whilst maintaining treatment efficacy. • During chronic infection, when a patient has resistant virus. The interruption allows build-up of non-resistant virus so that the next round of treatment will be more effective.

These approaches are reviewed in more detail in Lisziewicz & Lori, 2002. Other possible therapies being evaluated include immune activation with IL-2 which accelerates CD4 count normalisation on HAART and has been shown to be clinically useful (Davey, Jr. et a l 2000;Stellbrink et al, 2002), or immune suppression with agents such as cyclosporin A, corticosteroids or mycophenolic acid (Kilby et al, 1997).

1.15.2 HIV therapy in HCV co-infected patients

In general, HIV and HCV co-infected patients respond well to HAART and therapy rarely has to be modified (den Brinker et al, 2000). Despite this, HAART related hepatotoxicity is greater in these patients and liver function tests should be closely

56 Chapter 1: General Introduction monitored (den Brinker et al, 2000;Sulkowski et al, 2000). Elevated transaminases on HAART have recently been significantly associated with shorter survival (Rancinan et al, 2002). HCV co-infection and therapy complicates HAART and impairs its effectiveness (Greub et al, 2000;Pol et al, 2002) whilst immune restoration post-HAART may worsen liver lesions in patients with CHC (Vento, 2000). For these reasons, and the improved effectiveness of pegylated interferons (see Section 1.9.3), clinicians are increasingly keen to treat HCV before HIV in co-infected patients. NRTIs are toxic to mitochondria and HCV infected hepatocytes are predisposed to toxicity (Barbaro et al, 1999). In fact, the whole NRTI drug class and particularly zidovudine (AZT) are associated with steatohepatitis (Morris & Carr, 1999;Pessayre et al, 1999). Additionally, RBV does not modify HIV RNA load in patients on HAART (Zylberberg et al, 2000) and inhibits AZT phosphorylation, causing cytopenia and anaemia in this setting (see Section 1.8.2). This combination should therefore be avoided (Vogt et al, 1987). Both NNRTIs and RBV can also inhibit mitochondrial DNA synthesis, and interfere with cellular metabolism which occasionally leads to potentially fatal lactic acidosis and liver dysfunction (Carr et al, 2000;Lafeuillade et al, 2001). Some groups have also associated NNRTs with hepatotoxicity in co-infected patients (Sulkowski et al, 2002b), although some have not (Palmon et al, 2002). Of the Pis, indinavir has been associated with increased incidence of nephrolithiasis in HBV and HCV co-infected patients (Malavaud et al, 2000) and ritonavir has been associated with elevated ALTs (Sulkowski et al, 2000). Hepatotoxicity associated with the NNRTI nevirapine and PI ritonavir has recently been shown not to be due to immune reconstitution, so the mechanism behind hepatotoxicity in HCV co-infected patients remains to be elucidated (Martin- Carbonero et al, 2002). The vast majority of HIV infected haemophiliacs are HCV co- infected and clinicians are cautious with PI use in this patient group because of the risk of spontaneous bleeding episodes (Sabin et al, 2000b). The introduction of pegylated interferons (Section 1.9.3), which only have to be administered once a week, may simplify the treatment of HIV and HCV co-infected individuals (Glue et al, 1999). Interferon-a may decrease HIV load and recent trials have found that pegylated interferons also decrease HIV load in treatment naïve patients, suggesting that a combined therapy for both viruses may be possible (Emilie et al, 2001;Tossing, 2002).

57 Chapter I: General Introduction

1.15.3 Effect of HIV therapy on HCV

It is often reported that HCV RNA load remains unchanged post HAART (Hammer et al, 1997;Rutschmann et al, 1998;Greub et al, 2000), but some studies have reported 1 to 1.5 log decreases in HCV RNA load (Perez-Olmeda et al, 2000) and even occasional clearance of HCV viraemia (Fialaire et al, 1999;Yokozaki et al, 2000). In contrast, another study detected HCV RNA, load elevation (Ragni & Bontempo, 1999) and two others found no effect on HCV RNA but elevated aminotransferase levels in patients with undetectable HIV RNA load (Gavazzi et al, 2000;Filippini et al, 2000). Anti-HCV proliferative responses are unchanged by HAART, suggesting that immune reconstitution may not qualitatively alter the anti-HCV cellular immune response (Valdez et al, 2000). It has also been observed that patients who respond well to HAART, achieving undetectable HIV RNA loads, develop higher HCV RNA loads, raising the possibility that immune reconstitution could promote HCV disease, as has been seen with CMV and vitritis (Deayton et al, 2000). The anti-HCV antibody response may also be modified by HAART as HCV RNA levels correlate inversely with B-cell counts pre-HAART and this correlation disappears post- HAART (Yokozaki et al, 2000).

1.16 Immune response to HIV

HIV persists in the human host despite eliciting a strong immune response. This is primarily due to infection and subsequent depletion of CD4+ T-cells by HIV and its very high mutation rate that allows the virus to evade host immune responses directed against it.

1.16.1 Humoral immunity

Antibodies to HIV appear between one and three months after initial infection. Early antibodies recognise epitopes from HIV-1 structural proteins and later ones also recognise epitopes on non-structural proteins, which may derive from virion debris and are possibly non-neutralising (Parren et al, 1997). Neutralising antibodies are primarily directed against the hypervariable V3 loop of envelope glycoprotein gpl20

58 Chapter 1: General Introduction or a ‘neutralising face’ on the same protein that overlaps the CD4 and chemokine receptor-binding site of the virus (Parren et al, 1999).

As in HCV infection (see Section 1.10.1), the role of antibodies in clearing HIV-1 infection remains unclear. Viraemia has usually significantly declined before the appearance of HIV-1 antibodies and a strong neutralising antibody response is not present in all HIV-1 long-term non-progressors (LNTPs) (Koup et al, 1994;Harrer et al, 1996). Mechanisms by which HIV-1 may elude the humoral immune response include antigenic variation due to its high mutation rate, masking of important antibody epitopes by glycosylation or hindrance from the hypervariable loops VI and V2 that may obstruct antibody access to neutralising epitopes on the V3 loop (Chackerian et al, 1997;Reitter et al, 1998;Parren et al, 1999).

1.16.2 Cellular immunity (CD4+ T lymphocytes)

CD4+ T-cells, usually T-helper cells, are progressively depleted during HIV infection and in most infected individuals there is also a specific lack of HIV specific T-helper cells. A possible explanation for this is that, during acute infection, high viral loads result in widespread T-cell activation. HIV preferentially infects activated CD4+ T- cells and these cells become deleted. During the chronic phase of infection and on HAART, it may not therefore be possible to regenerate these CD4+ T-cell populations (Callebaut et al, 1993;Gandhi & Walker, 2002). Assuming this theory is correct, administration of ART during acute infection would greatly improve prognosis for a patient. Preliminary experiments have found that a greater proportion of patients are able to clear viraemia after acute phase ART, although their subsequent CTL responses are to a narrower range of epitopes than those of the untreated group (Rosenberg et al, 2000;Altfeld et al, 2001). The narrow CTL response may be due to lesser viral diversity during the acute phase as a result of ART (Gandhi & Walker, 2002). LTNPs have strong lymphoproliferative responses to HIV antigens (Schwartz et al, 1994;Rosenberg et al, 1997). In chronically infected, untreated patients, those with the greatest proliferative responses to HIV p24 had the lowest HIV RNA loads, with the converse also being the case (Rosenberg et al, 1997;Kalams et al, 1999). This is probably due to the T-helper cells maintaining CTL function.

59 Chapter 1: General Introduction

1.16.3 Cellular immunity (CD8+ T lymphocytes)

Patients with HIV-1 can develop strong CTL responses directed against both structural and non-structural proteins (Walker et al, 1987;Walker et al, 1988;Addo et al, 2001). These CTLs use two mechanisms to control HIV-1; recognition of viral peptides loaded onto class I MHC molecules, followed by lysis of the target cell, or secretion of p-chemokines such MIP-la, MIP-ip and RANTES, that block viral entry by binding to HIV co-receptors, p-chemokines and may also promote CTL cytolytic activity (Wagner et al, 1998;Hadida et al, 1998).

CTLs are very important in controlling HIV replication. Clearance of HIV viraemia correlates with appearance of CTLs (Koup et al, 1994). CTLs from HIV infected individuals can inhibit viral replication in autologous CD4+ T-cells in vitro (Yang et al, 1996) and in adoptive transfer experiments in HIV infected patients, antigen specific CTLs home to areas of HIV infection (Brodie et al, 2000). Additionally, in SrV infected macaques, CTL depletion by antibody results in an increase in SIV load that is reduced on CTL restoration (Schmitz et al, 1999). MHC class I tetramer staining of HIV specific CD8+ T-cells has revealed an inverse correlation between the number of tetramer positive cells and HIV RNA load, although this was not seen in patients with low CD4 counts, probably due to impaired CTL fimction in advanced HIV disease (Ogg et al, 1998;Kostense et al, 2001). It is possible that tetramer positive CD8+ T-cells may lack fimction without CD4+ T-cell help. This theory is supported by the fact that CD4 knockout mice infected with LCMV produce non­ functional CTLs, unable to lyse infected cells or secrete IFN-y (Zajac et al, 1998). CD8+ T-cells from patients chronically infected with HIV also have other defects such as diminished cytolytic activity, lack of perforin and display a skewed maturation profile that may affect their fimction in vivo (Appay et al, 2000a;Champagne et al, 2001).

60 Chapter 1: General Introduction

1.17 Aims of thesis

The overall aim of this thesis was to investigate HCV RNA load and immune parameters during chronic HIV and HCV co-infection in the context of haemophilia. The completion of this project involved the attainment of four objectives:

1. The development of both a fully quantitative competitive reverse transcriptase PCR (QC RT-PCR) assay for the detection of HCV RNA in serum samples, and a PCR and RFLP based genotyping assay for HCV.

2. The use of the above assays in a retrospective cohort study to clarify whether HCV RNA load is associated with clinical outcomes by investigating the prognostic value of a single HCV RNA load measured early after HIV seroconversion, for long-term progression to either AIDS or all-cause mortality.

3. The development of immunofluorescence assays to measure HCV specific antibody titre and the use of these in conjunction with the QC RT-PCR assay to investigate the relationship between HCV RNA load and anti-HCV titre, and whether this is affected by immune reconstitution post-HAART.

4. An investigation into whether co-infection with two chronic viruses (HIV and HCV) affects the expression of CD8+ T-cell memory markers. Antibody staining and FACS analysis were used to investigate memory marker expression.

61 Chapter 2: Materials and Methods

Chapter Two

Materials and Methods

62 Chapter 2: Materials and Methods

2.1 Construction of an internal standard for a quantitative competitive reverse transcriptase PCR (QC-RTPCR) assay for hepatitis C virus

Section 2.1.1 describes the methods used for amplification from patient serum of a 249bp fragment of the HCV 5’UTR. Section 2.1.2 describes the PCR based mutagenesis method used to engineer a unique restriction site in the fragment, which was then used as the internal standard (IS) in the QC-RTPCR assay. Figure 2.1 shows a diagrammatic overview of this procedure. Sections 2.1.3 to 2.1.19 describe the generation wild-type (wt) and IS RNA transcripts which were used to optimise the QC RT-PCR assay. For HCV RNA quantification, known copy numbers of the IS RNA fi-agment were co-amplified with viral RNA extracted from patient serum samples. The IS amplicon was then Hindlll digested and the viral load in the sample calculated by comparing the relative intensity the single band wt amplicons with the two bands resulting from IS amplicon digestion. These bands were scanned from polyacrylamide gels. Agarose gels were not used for scanning as they are too thick and the relative intensity of scanned bands did not accurately reflect DNA content.

2.1.1 Cloning of HCV 5’ UTR into pCR2.1 TA cloning vector

A 249bp fragment of the HCV 5’UTR was cloned from patient serum using a nested PCR reaction. The patient had genotype 1 HCV and the primer sequences are shown below, with the nucleotide position of the HCV genome they are complementary to:

5’ ATGGGGGCGACACTCCACCATGAATCACTCCCC 3’(0uter Sense: nt 13 to 45)

5’ CCCAACACTACTCGGCTA 3’ (Outer Antisense: nt 294 to 312)

5’ GAGGAACTACTGTCTTCACGCAGAAAG 3’ (Inner Sense: nt 48 to 74)

5’ AGTCTTGCGGGGGCACGCCCAAATC 3’ (Inner Antisense: nt 272 to 292)

63 Chapter 2: Materials and Methods

The first round PCR conditions were 5 cycles at 94°C for 2 minutes, 50°C for 2 minutes and 72°C for 3 minutes followed by 30 cycles at 94°C for 1.5 minutes, 60®C for 1.5 minutes and 72°C for 2 minutes, with a final extension time of 72°C for 5 minutes. The second round PCR conditions were 30 cycles at 94°C for 1 minute and 24 seconds, 40°C for 1 minute and 72°C for 1 minute with a final extension of 72°C for 5 minutes. PCR was performed on a Perkin Elmer thermal cycler and PCR products were cloned into pCR2.1 vectors using a TA cloning kit (Invitrogen).

2.1.2 Mutagenic PCR reactions

Briefly, two PCR reactions were set up, the first using the M l 3 reverse primer (Promega) and HCVMUT, the second using the M l3 forward primer (Promega) and the HCVMUTB primer (the pCR2.1 plasmid contains sequences complementary to M l3). The HCVMUT and HCV MUTB primers are complementary and the two PCR reactions produce amplicons that overlap and can thus hybridise with each other when single stranded, see Figure 2.1. The highlighted nucleotides in the HCVMUT and HCVMUTB primers indicate mismatched mutagenic bases that generate a Hind III restriction site in the PCR product. The details of the primers used are as follows:

5’ GACGACCGGGTCCAAGCTTGGATCAACCC 3’ (HCVMUT nt 164 to 193)

5’ GGGTTGATCCAAGCTTGGACCCGGTCGTC 3’ (HCVMUTB nt 193 to 164)

5’ CGCCAGGGTTTTCCCAGTCACGAC3’ (M13F)

5 TCACACAGGAAACAGCTATGAC 3 (M13 R)

Amplifications were carried out in the following 50pl reaction: IX Amplitaq Gold Buffer, 2mM MgCb, 25pM of each dNTP, 200ng of each primer, 5 units of Amplitaq Gold polymerase (PE) and 2pl of lOOng/ pi pCR2.1 plasmid containing the cloned

64 Chapter 2: Materials and Methods

HCVMUT

M 13F ;Z / HCVMUTB \M13R

pCR2.1

PCR with HCVMUT PCR with HCVMUTB and M13F primer and M13F primer

PCR products mixed and annealed

Single stranded regions ^ Klenow filled ^

PCR amplification using HCVTOl HCVTOl and 5’UTR 01

5’UTROl

Ligate directly into pGEM pGEM T-Easy vector

Figure 2.1: Schematic diagram of site-directed mutagenesis methodology used for introducing a restriction site into the HCV wt 5’UTR sequence (in red). M is the target mutation site AAGAAA which is mutated to the //zW//7 restriction site AAGCTT (M*). See also Section 2.1.5 for HCVTOl and 5’UTROl primer sequences.

65 Chapter 2: Materials and Methods

5’UTR fragment. The PCR conditions were a hot start at 95°C for 10 minutes followed by 25 cycles of 95°C for 30 seconds, 45°C for 30 seconds and 72°C for 45 seconds. Amplicons were visualised on 1% agarose gels run in Ix TBE buffer.

2.1.3 Agarose gel electrophoresis

For a 1% agarose gel, Ig of multi-purpose agarose (Bioline) was weighed in a sterile glass bottle and 100ml of IxTBE (90mM Tris-borate, 2mM EDTA) was added. The mix was heated in an 850W microwave oven until the agarose had dissolved. On cooling to around 50°C, 2pl of ethidium bromide (lOmg/ml Sigma) was added and the mix poured into a gel frame containing a comb for loading. 5 pi of PCR product or PCR marker (Promega) was mixed with 5 pi of loading dye (0.25% bromophenol blue (Sigma), 0.25% xylene cyanol (Sigma), 15% Ficoll type 400 (Sigma) in sterile distilled water, SOW) and loaded into the wells. Gels were electrophoresed at around 120V, 100mA for 30min, visualised under UV light on a transilluminator with a Baby Imager (Appligene-Oncor) and photographed using a video copy processor (Mitsubishi).

2.1.4 Annealing and ‘Klenow’ fill of PCR products

Equimolar amounts of either 2.5 pmol or 0.5 pmol of each product from Section 2.1.2 were mixed together and denatured at 95°C. Concentrations were estimated by comparing the intensity on an agarose gel of PCR product bands against PCR marker bands (Promega) of known DNA quantity. The products were annealed by allowing them to cool down to room temperature for 30min and single stranded regions of the resultant product were ‘Klenow’ fragment filled. Briefly, a 30pl reaction mixture containing 20U of DNA polymerase 1 Large (Klenow) fragment (Promega), 200pM of each dNTP, in IX Reaction buffer [50mM Tris-HCl (pH 7.2), lOmM MgS 04, O.IM DTT] and either the 0.5 or 2.5pmol PCR product mix were incubated at room temperature for 40min. The reaction was stopped during the hot start of the PCR reaction by denaturing the DNA polymerase I enzyme fragment at 95°C for 5min.

66 Chapter 2: Materials and Methods

2.1.5 PCR reactions

Amplifications of the Klenow filled products were carried out in the following 50pl reaction, IX Amplitaq Gold Buffer, 2mM MgCh, 25pM of each dNTP, 100 or 200ng of HCVTOl and 5’UTROl primers (see below), 5 units of Amplitaq Gold polymerase (PE) and lOOng of the 2,5pmol or 41.5ng of 0.5pmol PCR products respectively. Cycling conditions were, hot start at 95°C 15min, followed by 40 cycles at 94°C 30sec, 60°C 30sec, 72°C 30sec and a final extension at 72°C lOmin.

The primers for the PCR reaction amplify a 204hp fragment of HCV 5’UTR and their sequences are shown below:

5’ CACGCAGAAAGCGTCTAGCCAT 3’ (HCVTOl nt: 49 to 71)

5’ CCCAACACTACTCGGCTA 3’ (5’UTROl nt: 253 to 235)

All oligonucleotide primers were synthesised commercially (Oswel, Southampton UK).

2.1.6 Purification of the 5’UTR wild type and control inserts

Amplicons were purified from a 1% w/v low melting point molecular biology grade low melting point agarose gel (Sigma) run in Ix TAB buffer (40mM Tris-acetate, ImM EDTA) using a Wizard PCR DNA purification kit (Promega) according to the manufacturers instructions. Briefly, gel fragments of approximately 300mg were excised from the gel using a sterile scalpel under long or medium wave U.V light to minimise exposure of DNA to the light. The slice was transferred to a 1.5ml centrifuge tube and incubated at 70°C until it had completely melted. 1ml of resin was added to the melted slice and mixed by inversion for 20 seconds. A Wizard minicolumn was attatched to the barrel of a 3ml syringe. The resin/DNA mix was pippetted into the barrel and the slurry was pushed into the column using the plunger. The minicolumn was then removed from the barrel and the plunger removed from the syringe. The minicolumn was reattached and 2ml of 80% isopropanol was pushed

67 Chapter 2: Materials and Methods through it to wash the DNA. The syringe was removed, the minicolumn transferred to a 1.5ml centrifuge tube and centrifuged for 2min at lOOOOg to dry the resin. Finally, the minicolumn was transferred to a fresh 1.5ml centrifuge tube, 50^1 water was added and after 1 minute it was spun at lOOOOg for 20 seconds to elute the DNA fragment. The DNA was stored at -20°C and the amount of DNA obtained from the gel was estimated at 3.5ng/|al by comparison on an agarose gel with PCR markers (Promega) of known DNA quantity following electrophoretic separation.

2.1.7 Ligation into pGEM T-Easy vector

4ng and 12ng of each of the two purified Klenow filled and amplified products (233bp each) were ligated into 50ng of pGEM-T Easy vector (Promega) at an insert to vector molar ratio of 1:1 and 3:1 respectively, in the presence of 3 units of T4 DNA ligase, 5pi of 2x Rapid Ligation Buffer [60mM Tris-HCl pH 7.8, 20mM MgCb, 20mM DTT, 2mM ATP and 10% polyethylene glycol (MW8000, ACS Grade)] made up to a total volume of lOpl with SDW. Control ligations of a 542bp fragment of pGEM-luc^^ DNA (Promega) and linearised vector alone were also set up. Ligation reactions were incubated overnight at 4°C and 2pl of each ligation was used to transform 50pl of competent Eschericia colt (E.coli) JM109 cells.

2.1.8 Preparation of transformation competent E'.co/i JM109 cells

JM 109 cells (Promega) carrying the F’ episome were used for transformation reactions. The JM 109 phenotype is shown below: endAX, recAX, gyrA96, thi hsdR ll (rk',mk^), re/Al, supEAA A(Zac-^mAB), [F’ traD2>6,proAB /ac%AM15].

A single colony from an agar plate (0.5% w/v yeast extract (Sigma), 2% w/v tryptone (Oxoid), 20mM MgS 04, 1.4% agar (Sigma) adjusted to pH 7.6 with KOH prior to autoclaving) was picked and used to inoculate a 7ml culture of Luria Bertani (LB) broth (0.5% w/v yeast extract (Sigma), 2% w/v tryptone (Oxoid), 20mM MgS 04,

68 Chapter 2: Materials and Methods adjusted to pH 7.6 with KOH prior to autoclaving). The culture was incubated for 2- 3 hours in a shaking incubator (250rpm) until the OD 550 reached 0.48. This was then chilled on ice for 20min and centrifuged in 30ml Falcon tubes at 6000g for 5min at 4°C. The cells were resuspended in 40ml (2/5 volume) of ice-cold transformation buffer I (Tfbl) (30mM potassium acetate, lOOmMRbCb, lOmM CaCl 2, 50mM MnClz, 15% (v/v) glycerol at pH 5.8 adjusted with 0.2M acetic acid prior to filter sterilising) and left on ice for 20min. Cells were centrifuged at 5000g for 5min at 4°C and resuspended in 4ml of ice-cold transformation buffer II (Tfbll) (lOmM MOPS, lOmM RbCl], 75mM CaClz, 15% v/v glycerol at pH 5.8 adjusted with 0.2M acetic acid prior to filter sterilising) and left on ice for another 20min. 200pl of the resultant suspension of competent JM109 E.coli cells were snap frozen into 1.5ml centrifrige tubes pre cooled in a methanol/dry ice bath and stored at -70°C until needed.

2.1.9 Transformation into competent JM109 cells

Competent cells were thawed at room temperature until just liquid then placed on ice for lOmin. 2pl of the ligation (from Section 2.1.8) were added to 50pl of thawed competent JM109 cells in a sterile 1.5ml centrifuge tube. One tube per ligation was used and incubated on ice for 30min, followed by heat shock at 42°C for 90sec. The tubes were placed on ice for Imin to cool and 400pl of sterile LB broth (Sigma) pre­ warmed to 37°C was added to each. The tubes were incubated at 37°C for 1 hour and then lOOpl or 400pl aliquots of transformed cells were plated out onto LB agar plates, [0.5% w/v NaCl (Sigma), 0.5% w/v yeast extract (Sigma), 1.0% w/v tryptone (Oxoid), 1.5% w/v agar (Oxoid) adjusted to pH 7.5 with NaOH prior to autoclaving]. The agar was supplemented with 50pg/ml ampicillin (Sigma), 40pg/ml 5-bromo 4- chloro 3-indolyl-P-D-galactoside (X-gal) (Sigma) and 50pg/ml isopropyl-P- thiogalactopyranoside (IPTG) (Sigma) when hand hot, just before pouring the plates. After overnight incubation at 37°C, colonies containing the desired insert appeared as white, whilst non-recombinant colonies appeared blue.

69 Chapter 2: Materials and Methods

2.1.10 Mini-preparation of plasmid DNA from bacterial cultures

A number of white colonies were picked, inoculated into 5ml of LB broth (Sigma) containing 50pg/ml ampicillin and incubated overnight at 37°C in a shaking incubator. The selected colonies were also streaked onto LB agar plates (see Section 2.1.8) and stored at 4°C to act as stocks. The following day, SOOpl of the bacterial suspension was added to 200pl of sterile glycerol (Sigma) in 1.5ml sterile centrifuge tubes, vortexed, snap frozen in a methanol/dry ice bath and stored at -70°C. The remainder of the culture was used for DNA purification using the Wizard Plus Miniprep DNA purification system (Promega) according to the kit instructions. Briefly, the remaining culture was spun down at lOOOOg for lOmin at room temperature and the supernatant was poured off. The pellet was completely resuspended in 300pl of cell resuspension solution (50mM Tris-HCl pH7.5, lOmM EDTA, lOOpg/ml RNase A) and transferred to a 1.5ml centrifuge tube. 300pl of cell lysis solution was then added (0.2M NaOH, 1% SDS) and the tube inverted 4 times to mix, 300pl of neutralization solution (1.32M potassium acetate pH4.8) was added and the cell lysate was centrifuged at lOOOOg for 5min. The cleared lysate was added to 1ml of Wizard miniprep DNA purification resin and mixed by inversion. A Wizard minicolumn was attatched to the barrel of a 3ml syringe; the slurry was pippetted in and gently pushed through the column. The flow-through was discarded; the syringe was detatched from the minicolumn and the plunger removed from the syringe barrel. 2ml of column wash (80mM potassium acetate, 8.3mM Tris-HCl pH7.5, 40pM EDTA, 55% ethanol) was pippetted into the barrel and gently pushed through the minicolumn. The minicolumn was placed into a fresh 1.5ml centrifuge tube, 50pl of SDW was added and the DNA eluted by centrifugation at lOOOOg for 20sec. The plasmid DNA was stored at -20°C.

2.1.11 Screening of plasmid colonies by restriction enzyme digestion

The plasmid clones were analysed by restriction enzyme digestion. 5pi of isolated plasmid DNA was digested at 37°C for 1.5 hours with 0.5pl of Eco R1 (lOu/pl) in 2pl of lOx Buffer H (500mM Tris-HCl, lOOmM MgCb, IM NaCl, lOmM dithioerythritol at pH 7.5) made up to a final volume of 20pl with 12.5 pi of SDW. This was to

70 Chapter 2: Materials and Methods verify the presence of the cloned insert. In order to verify the presence of the novel restriction site, 5 pi of plasmid DNA was also digested at 37°C for 1.5 hours with 0.5pl of EcoRl (lOu/pl) and 0.5pl of Hind III (lOu/pl) in 2pl of lOx Buffer B (lOOmM Tris-HCl, lOM NaCl, 50mM MgCli, lOmM 2-mercaptoethanol at pH 8.0) made up to a final volume of 20pl with 12pl of SDW. The digests were analysed on 1.5% agarose gels run in Ix TBE buffer (see Section 2.1.4).

2.1.12 Plasmid sequencing reactions

Plasmid DNA containing the 233bp wt and control inserts was sequenced using Sequenase Version 2.0 T7 DNA polymerase (United States Biochemical, USB) with universal M l3 forward and reverse primers (see Section 2.1.3). Sequencing reactions were set up for two wt and two IS clones as determined by restriction digests. 20pl of miniprepped DNA (approximately 5pg) was denatured with 5pl of IM NaOH, ImM EDTA (pH 8.0) at room temperature for 15min. CL- 6B sepharose in TE (Sigma) columns were then prepared. A hole was punched with a needle in the bottom of a 0.5ml tube and 425-600 micron glass beads (Sigma) were placed in it to about 20pl in height. This was overlaid with 700pl of CL- 6B sepharose, placed into a 1.5ml tube with a hole punched in the bottom, and then both placed in a 15ml tube before spinning at 1400rpm for 5min in a Beckman TJ -6 bench top centrifuge (Figure 2.2). The column was placed into a fresh intact 1.5ml centrifuge tube and the denatured DNA pippetted onto the column and spun at 1400rpm for 5min. The denatured DNA was divided into two 8 pl aliquots (for the forward and reverse primers). Ipl of either primer was added to 8 pl of DNA and Ipl of lOx TM buffer (lOOmMTris-HCl, lOOmM MgClz), left to anneal at 37°C, allowed to cool to room temperature and chilled on ice. 2.5pi of each dideoxy base (ddGTP, ddATP, ddTTP and ddCTP) was added to four 0.5ml tubes per primer i.e. 8 tubes per sample (forward and reverse primers). 2pl of nucleotide labelling mix (1.5pM each of dGTP, dTTP, dCTP) (Amersham), diluted 1:5 in SDW, Ipl DTT (O.IM solution) (Sigma), 0.5 pi of [a- ^^S]dATP (5pCi Amersham UK) and 2pl of sequenase enzyme (12u/pl) diluted 1:8 in enzyme dilution buffer (lOmM Tris-HCl pH 7.5, 5mM DTT, 0.5mg/ml BSA) were added to the annealed DNA and incubated at room temperature for 5min. 3.5pi of annealed reaction mix was then added to each of the tubes containing

71 Chapter 2: Materials and Methods

Add sample

CL-6B sepharose

0.5ml centrifuge tube

425-600 micron glass beads - Hole punched in base

1.5ml centrifuge tube

15ml tube

Eluate

Figure 2.2: Set-up of CL- 6B sepharose column for purifying annealed DNA.

72 Chapter 2: Materials and Methods ddNTP’s, prewarmed to 37°C and incubated at 37°C for 5min. 4pl of stop solution (95% w/v formamide, 20mM EDTA pH8.0, 0.05% w/v bromophenol blue, 0.05% w/v xylene cyanol) was then added and the samples stored at -20°C until needed.

2.1.13 Analysis of sequencing reactions by 7M polyacrylamide urea gel electrophoresis

Sequencing reactions from Section 2.1.12 were analysed on a 7M urea polyacrylamide wedged sequencing gel. 75g of molecular biology grade urea (Sigma) was dissolved in 30ml of 40% bis-acrylamide (Scotlab), 15ml of filtered TBE (see Section 2.1.3) and 45ml of SDW in a plastic jug covered with cling film on a heated stirrer at 50°C for 1 hour or until the urea had completely dissolved. During this time, the gel plate assembly was set up. Briefly, two 33 x 43cm and 5mm thick glass plates (Gibco) were thoroughly cleaned with 70% ethanol and the shorter plate then siliconised in a fume hood with dichlorodimethylsilane (Sigma). Two spacers

(430 X 0.4mm) were positioned at the outer edges of the larger plate to separate the plates and two additional 20 x 0.4mm spacers placed at the bottom. The shorter plate was then placed on top and the plates and spacers tightly taped together. When the gel had cooled to 40°C, 900pl of 10% w/v ammonium persulphate (APS) (Sigma) and 80pl of N,N,N’,N’ tetramethylethylenediamine (TEMED) (Sigma) were added and mixed well. This was poured into the assembled gel plates. Two 24 well shark-tooth combs (Sigma) were then placed between the gel plates with their flat side against the poured gel before it set, this ensured the exposed edge of the gel was flat. The gel was allowed to set at room temperature for 30 minutes, and then placed in a gel tank. The combs were carefully removed and turned around to form sample wells and any unpolymersised acrylamide or residual urea was removed with Ix TBE and a fine tipped pippette. The gel was pre-warmed by running in Ix TBE at 40V for 30min.

Samples were heated at 94°C for 2min and 5pi of each sample (Section 2.1.12) was loaded in the order ‘G’, ‘A’, ‘T’, ‘C’. Samples were electrophoresed at 75W until the bromophenol blue dye was about 3cm from the bottom of the gel (a long run). At this point the same samples were loaded again into new wells and the gel run again until the bromophenol blue dye was 3cm from the bottom of the well (a short run). The gel

73 Chapter 2: Materials and Methods plates were separated leaving the gel attached to the non-siliconised plate. The gel was fixed in 10% glacial acetic acid (BDH) for 30min. The gel was blotted with IsT3 cartridge paper (Whatman) and subsequently transferred onto it before being vacuum dried at 80°C for 2.5 hours using a Bio-rad dryer and Aquavac pump. The dried gel was exposed to Hyperfilm MP X-ray film (Amersham) for between 24h and 1 week depending on the activity date of the [a-^^S]dATP used in the labelling reaction. The DNA sequence was read from the autoradiograph on a light box.

2.1.14 Large scale preparation of plasmid DNA

An endo-free Maxi prep kit (Qiagen) was used to extract DNA on a larger scale from two recombinant pGEM clones; one containing the 233bp wild type 5’UTR insert the other the mutagenised internal standard insert. Briefly, -70°C frozen stocks of the desired clones were streaked out onto agar plates supplemented with ampicillin and X-gal (see Section 2.1.10) and incubated overnight at 37°C. Single colonies were then picked, 5ml starter cultures set up from each in LB broth supplemented with 50pg/ml ampicillin and incubated overnight at 37°C in a shaking incubator (~250rpm). This culture was diluted 1/500 (200pl) into 100ml of LB containing 50|ig/ml ampicillin and grown at 37°C for 16 hours in a shaking incubator (~250rpm). The cells were harvested at 6000ipm for 15min at 4°C in an IECPR-7000 centrifuge and the bacterial pellets completely resuspended in 10ml of PI cell resuspension buffer (50mM Tris-HCl pH 8.0, lOmM EDTA, lOOpg/ml Rnase A). 10ml of P2 cell lysis buffer (200mM NaOH, 1% SDS) was then added, and the lysate mixed by inverting 4-6 times, before incubation at room temperature for 5min. 10ml of chilled P3 neutralisation buffer (3.0M potassium acetate pH 5.5) was added, the lysate inverted 4-6 times to mix, immediately poured into the barrel of a stoppered Qiafilter cartridge and incubated at room temperature for lOmin. The cap was removed from the outlet nozzle and the cell lysate filtered into a 50ml tube using a plunger. 2.5ml of buffer ER (composition withheld by supplier) was added to the filtered lysate mix by inverting ~10 times and incubated on ice for 30min. Meanwhile, a Qiagen-tip 500 was equilibrated by adding 10ml of QBT equilibration buffer (750mM NaCl, 50mM MOPS pH7.0, 15% isopropanol, 0.15% Triton X-100) and allowing the column to empty by gravity flow. The filtered lysate was placed on

74 Chapter 2: Materials and Methods the column and allowed to enter the resin by gravity flow. The flowthrough was discarded and the column washed twice with two 30ml aliquots of QC wash buffer (l.OM NaCl, 50mM MOPS pH 7.0, 15% isopropanol). The DNA was eluted with 15ml of QN elution buffer (1.6M NaCl, 50mM MOPS pH 7.0, 15% isopropanol), precipitated with 10.5ml (0.7vol) of room temperature isopropanol and centrifuged immediately at 24000rpm for 30min at 4°C in a Beckman L-80 ultracentrifuge. The supernatant was decanted off and the pellet washed with two 2.5ml aliquots of endotoxin free room temperature 70% ethanol and air dried for 20min. The pellet was resuspended in lOOpl of endotoxin free SDW. The concentration of the DNA was determined by optical density at 260nm in a Genequant II RNA/DNA calculator (Pharmacia Biotech) where an OD 260 of 1.0 is equivalent to 50pg of double stranded DNA. The stock DNA was stored at -20°C until needed.

2.1.15 Linearisation of plasmid prior to transcription

Recombinant pGEM wt and control vectors were initially linearised with Spe I prior to the transcription reaction to produce positive sense RNA of a discrete length (287nt). 4pg of each of the plasmids was digested with 1 pi Spe I (lOu/pl Promega) in 2pl of lOx Buffer B (60mM Tris-HCl, 60mM MgCb, 500mM NaCl, lOmM DTT pH 7.5) for 3h. 0.5 pi of the uncut and linearised plasmid was added to 5 pi of loading dye and run on a 0.8% agarose gel with 1 pi of high molecular weight Eco R l/ Hind III X- DNA markers (Promega) at lOOV and 130mA for 55min to verify complete linearisation of the two vectors.

2.1.16 In-vitro transcription using T7 RNA polymerase

The linearised vectors were used for in vitro transcription using the RiboMAX™ large scale RNA production system (Promega) to make positive sense RNA transcripts. 750ng of linearised pGEM vector DNA was transcribed in the following reaction mixture: 20pl 5x transcription buffer (400mM HEPES-KOH pH7.5, 120mM MgCl], lOmM spermidine, 200mM DTT), 30pl rNTPs (25mM each of GTP, ATP, UTP and CTP), lOpl of T7 enzyme mix (300u/pl T7 RNA polymerase, 15u/plRNasin

75 Chapter 2: Materials and Methods ribonuclease inhibitor, 190u/ml yeast inorganic pyrophosphate) made up to lOOpl with nuclease free water. The reaction was incubated in a water bath at 37°C for 3h and frozen at -70°C until needed.

2.1.17 Removal of DNA template with RNase free DNase 1

The pGEM DNA template was removed from the transcription reaction by digestion with RNase free DNase 1 (Ambion). 50pl of transcription reaction was treated with 2pl of DNase 1 (2u/pl) made up to lOOpl with nuclease free water and incubated for 15min at 37°C.

2.1.18 Clean up of RNA

The resultant RNA preparation was cleaned up using an RNeasy kit (Qiagen). The composition of certain buffers in this procedure cannot be given here, as they are not revealed by the manufacturer. Briefly, 350pl of RLT lysis buffer (lOpl of p- mercaptoethanol added to 1ml of RLT buffer before use) was added to lOOpl of DNase treated RNA (Section 2.1.18) followed by 250pl of 100% ethanol, mixed by pippeting and loaded onto an RNeasy spin column inserted into a 2ml centrifuge tube. The column was then spun at lOOOOrpm for 15sec in a Jouan M14.il bench top centrifuge. The flow through was discarded, the column washed with SOOpl of RPE column wash buffer (4vol of ethanol added before use) and centrifuged at lOOOOrpm for 15sec. The wash step was repeated with the spin increased to 2min to dry the membrane. The RNA was finally eluted from the colunm with 50pl of nuclease free water.

2.1.19 MOPS/ formaldehyde gel electrophoresis of RNA transcripts

5|xl of purified DNase treated RNA was analysed on a 1% MOPS formaldehyde agarose gel along with RNA markers (Promega). Ig of agarose (Bioline) was added to 85.2ml DEPC (diethylpyrocarbonate) treated water (Sigma) and 10ml of lOx

76 Chapter 2: Materials and Methods

MOPS buffer (Sigma) in a sterile glass bottle. The agarose was dissolved in an 850W microwave and the mix left to cool to 65°C. 4.8ml of formaldehyde (Sigma) and 1^1 of ethidium bromide (Sigma) were added, poured into a gel frame containing a comb for loading that had been previously treated with RNase Zap (Ambion) to remove RNases and allowed to set for 2h at 4°C. 5 pi of sample or 2pl of marker were mixed with 5pi of sample buffer [for 1ml 0.72ml formamide (Sigma), 0.16ml lOx MOPS (Sigma), 0.26ml formamide (Sigma), 0.18ml DEPC water, 0.1ml 80% glycerol (Sigma) and 0.08ml of a saturated solution of bromophenol blue (Sigma)] and denatured at 65°C in a heat block for 5min. The gel was run in IX MOPS buffer (Sigma) at lOOV, 150mA for 90min, visualised on a transilluminator with a Baby Imager (Appligene-Oncor) and photographed using a video copy processor (Mitsubishi). Ethidium bromide is a polycyclic fluorescent dye that binds to dsDNA molecules by intercalating a planar group between the stacked base pairs of the nucleic acid. It can also be used for the visualisation of ssRNA, but it is less efficient as it can only bind to regions of secondary structure. Greater quantities of ethidium bromide must therefore be added to the gel, making high background fluorescence an occasional problem with this method (Ausubel et al, 1998).

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2.2 Optimisation of QC-RTPCR using internal standard RNA transcripts

Sections 2.2.1 to 2.2.5 describe the generation of a standard curve for the QC-RTPCR assay to determine its dynamic range i.e. what are the minimum and maximum copy numbers of both wt (a substitute for patient RNA during optimisation) and IS RNA that the assay can amplify linearly. Section 2.2.6 describes the method used for extracting patient RNA.

2.2.1 Reverse transcription and PCR amplification of cloned HCV 5’UTR transcripts

The RT reactions were performed on a Hybaid OmniGene thermal cycler. 2pl of diluted transcript or extracted viral RNA was reverse transcribed in 20pl volumes consisting of IX HotStar Taq buffer [Tris-HCl, KCl, (NH 4)2S04, 1.5mM MgClz; pH 8.7, some concentrations withheld by supplier], 3.5pM MgCb (Perkin Elmer), ImM of each dNTP (PE), 50ng of HCVT02 primer (Spmol), SOunits of MuLV RT (PE) and 20units of RNase Inhibitor (PE). Reagents were set up on ice. Conditions were 42®C for 20min followed by 99°C for 5min. The HCVT02 primer allowed specific amplification of HCV RNA from extracted patient viral RNA, see Figure 3.13 for location.

5’ ATCAGGCAGTACCACAAGGC 3’ (HCVT02 nt: 282 to 262)

5 pi of cDNA from the previous reaction was amplified using Ix HotStar Taq buffer [Tris-HCl, KCl, (NH4)2S04, 1.5mM MgCb; pH 8.7 some concentrations withheld by supplier), l.Spl of dNTP mix(10mM each dNTP)], lOOng of HCVTOl and 5‘UTROl primers and 0.25pl of HotStar Taq (5u/pl) in SOpl volumes. The PCR reactions were performed on a Hybaid Onmigene thermal cycler. PCR reaction conditions were the same as those described in Section 2.1.5.

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2.2.2 Generation of standard curve for the QC-RTPCR assay

IS and wt RNA transcripts were titrated against each other to determine whether they amplified with the same efficiency and to determine the dynamic range of the assay. A fixed copy number of IS transcript i.e. 10"^ was co-amplified with three different wt copy numbers i.e. 5x10^, 10"^ and 5x10^ and this procedure was repeated with IS RNA input copy numbers from 10^ to 10^. After RT-PCR, the products were digested with Hind III, run on a 10% DNA polyacrylamide gel, photographed, scanned and quantified. The dynamic range for the assay was between 1x10^ and 5x10^ copies of RNA.

2.2.3 Hind III digests of amplified DNA

After amplification, 5 pi of each PCR product was run on a 1% agarose gel (see Section 2.1.2) to confirm that they had amplified. 1 Opl was then digested with 1 pi of Hind III (lOu/pl) in a mix containing 2pl of lOx Buffer B (lOOmM Tris-HCl, lOM NaCl, 50mM MgCb, lOmM 2-mercaptoethanol at pH 8.0) and made up to a final volume of 20pl with 12pi of SDW for 90min at 37°C.

2.2.4 Polyacrylamide Gel Electrophoresis (PAGE) of RT-PCR products

After digestion, lOplof digest and loading dye were mixed together and loaded onto a 10% DNA polyacrylamide gel [2.5ml 40% bis-acrylamide (Scotlab), 1ml lOxTBE, 7.5ml SDW, 70pl 10% w/v APS (Sigma), 7pl of TEMED (Sigma)], before running in Ix TBE buffer at 200V and 45mA for 45min. Gels were stained in 50ml of TBE containing 5 pi (lOmg/ml) of ethidium bromide (Sigma) for 5min, visualised under UV light on a transilluminator with a Baby Imager (Appligene-Oncor) and photographed using a video copy processor (Mitsubishi). The gel was not directly scanned as the laboratory only owned a standard computer scanner.

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2.2.5 Gel scanning and quantification

A non-radioisotopic method of quantification was used (Kidd IM et al., 2000). Gel photographs were scanned electronically at 240 pixels per inch on an Astra 600S scanner using VistaScan software. The image was imported into the NIH Image program version 1.61 on a Power Macintosh 6100/66 and the program produced a negative image of the photograph. The gel lanes were marked using gel-reading macros and electronic densitometric plots generated. The ratio of wt signal (upper single band) to total signal (wt band plus doublet of Hindlll digested IS bands) multiplied by the copy number of the input internal standard RNA gave the estimated copy number for standard curve generation or viral load in routine use (Figure 2.3).

2.2.6 Viral RNA extractions

When quantifying clinical samples, HCV RNA was extracted using a High Pure Viral RNA kit (Roche) following the manufacturers instructions. Briefly, 400pl of working solution consisting of binding buffer (4.5M guanidinium hydrochloride, 50mM Tris- HCl, 30% Triton X-100 (w/v) pH 6.6) supplemented with poly (A) RNA was added to 200pl of serum and mixed. The filter and collection tube were combined and the mixture pipetted into the upper reservoir. The assembly was spun for 15 sec at 8000g (10,000rpm) in a benchtop centrifuge. The flowthrough was discarded and 500pl of inhibitor removal buffer (40% ethanol, 5M guanidine-HCl, 20mM Tris-HCl pH 6.6) pippetted into the upper reservoir and spun at SOOOrpm for Imin. The flowthrough was then discarded, 450pl of wash buffer (75% ethanol, 20mM NaCl, 2mM Tris-HCl pH7.5) pipetted into the upper reservoir and spun for 15 seconds at 10,000rpm. The flowthrough was again discarded and this step repeated, before finally increasing the centrifuge speed to 13,000rpm for 10 seconds to remove residual wash buffer. The filter tube was placed into a nuclease free 1.5ml tube, 50pl of elution buffer (nuclease free water) added and centrifuged at 10,000 for Imin to elute the RNA. Samples were stored at -80°C until needed.

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2.3 Routine use of the QC RT-PCR assay for HCV

Viral RNA was extracted from patient serum samples and stored at -80°C until needed (Section 2.2.6), or amplified on the same day in a qualitative RT-PCR following the conditions detailed in Sections 2.2.1 and 2.1.5 for reverse transcription and PCR amplification respectively. The qualitative RT-PCR was carried out in order to estimate how much IS RNA to add to each sample, (Figure 2.4a). In the quantitative RT-PCR reaction, samples with greater levels of HCV RNA needed a greater copy number of IS RNA to be added. This is because IS RNA would be out- competed in the PCR amplification by the sample HCV RNA if there was two logs more of it than IS RNA and vice-versa. As the estimation of how much IS RNA to add was done by eye, one must take into account inaccuracies in patient RNA level estimation from the gel of the qualitative RT-PCR. For this reason, two separate PCR reactions were set up for each patient sample; each containing a different IS RNA copy number, 1 log apart. Extracted RNA samples for quantification were thawed on ice; 2pi was then added to the RT reaction mix along with the appropriate IS RNA copy number in 2pl. These were then reverse transcribed and amplified as described in Sections 2.2.1 and 2.1.5. Resultant products were digested with Hindlll and run on 10% DNA polyacrylamide gels (see Sections 2.2.3 and 2.2.4). The gels were then photographed (Figure 2.4b) and the viral loads quantified using the non-radioisotopic methodology described in Section 2.2.5.

81 Chapter 2: Materials and Methods

Optians Proce«« Special Statics iDindouis Tools ______Temp ______Plots 10 sncsllhnltd B

J \

Results

lie * oo ISM 00 C 1074 oo c w i « A#»*: 2168 t«Mr* ptar»h M 5 2 .C O H » « i 0 00 2 8 0 6 0 0 Hm:S t4 D000 * v . O jOQ 00 H a h 0 00 1603 00 2IM 00 I

. 1

Figure 2.3: Macintosh screen display of stages involved in analysis of the QC RT-PCR

assay PAGE photographic image. Screen section A (window 'Temp') shows the

delineation of regions of analysis for each lane of the image. Section B (window Plots')

displays densitometric graphs for all bands in each lane, together with the manually applied

short vertical demarcation lines separating the relevant wt and IS sequence areas. Hindlll

digested IS is the lower molecular weight doublet. Section C (window ‘Results’) displays

the pixel area under each demarcated peak. Image taken from Kidd et al, 2000.

82 Chapter 2: Materials and Methods

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1920

lOOObp 204bp 500bp undigested 50bp PCR product

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

lOOObp 500bp 204bp 50bp undigested PCR product

Figure2.4a: 1.5% agarose gel of qualitative RT-PCR (sample number 599 to 624).

Every seventh sample is an SDW RT-PCR control.

Sample 599 600 601 603 604 IS JO^ lO; JO^ 10^ JO^ 10%10"^ 10^ J03 10% 1 2 3 4 5 6 7 8 9 10 11

300bp -204bp wt 150bp \32hp Hindlll digested IS

_72bp Hindlll digested IS

50bp

Figure 2.4b: 10% DNA polyacrylamide gel for the quantification of five HCV positive samples

extracted from patient serum.

83 Chapter 2: Materials and Methods

2.4 HCV genotyping assay

This section describes the development of a PCR and RFLP based genotyping assay for HCV. The methods were adapted from Harris et al, 1999. Sections 2.4.1 to 2.4.5 describe the nested amplification of a section of the HCV 5’UTR, its digestion with four restriction enzymes and the running of combinations of these on a polyacrylamide gel to determine HCV genotype and subtype by RFLP. The section of 5’UTR amplified in the QC-RTPCR assay would ideally have been used, avoiding the need for re-amplification, but it would have been too time consuming to work out the restriction digests for this fragment.

2.4.1 Reverse transcription of HCV RNA

On ice, reaction mixtures were set up consisting of, IX HotStar Taq buffer, 3.5mM MgCl], ImM of each dNTP (Perkin Elmer), 3.3pM random hexamers (Operon), 5OU of MuLV reverse transcriptase (Perkin Elmer), 20U of RNase inhibitor (Perkin Elmer), made up to 18pi with nuclease free water (Promega), and overlayed with mineral oil (Sigma). 2pl of extracted RNA (Section 2.2.6) was amplified with water controls (2pi nuclease free water) every six samples and a reaction containing HCV positive RNA without reverse transcriptase was set up for each round of samples to check for DNA contamination. Reactions were carried out on a Hybaid Omnigene Thermal Cycler and conditions were 42°C for 20min and 99°C for 5min to terminate the reaction.

2.4.2 First round PCR

Reaction mixtures were set up containing, IX PCR buffer (20mM Tris-HCl, 50mM KCl pH8.4) (Gibco), 2mM MgCb (Gibco), 0.3mM of each dNTP (Qiagen), 0.625U of Taq polymerase (Gibco), 5pmol of HCVGEN 1 sense primer, 5pmol of HCVGEN 2 antisense primer (synthesised by Oswel), the volume made up to 40pl with SDW and overlaid with mineral oil (Sigma).

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5’ AGCGTCTAGCCATGGCGT 3’ (HCVGENl nt: 57 to 75)

5’ GCACGGTCTACGAGACCT 3’ (HCVGEN2 nt: 321 to 303)

10(il of cDNA (from Section 2.4.1) was added to the appropriate tubes, with each set of reactions containing a water control every sixth tube and a positive PCR control. Reactions were carried out on an Omnigene Thermal Cycler (Hybaid), cycling conditions were; one cycle of 94°C for 30 sec followed by 35 cycles of 94®C for 30sec, 62°C for 40sec and 72°C for 50sec. The first round PCR amplifies a 265bp product located in the HCV 5’UTR between nucleotides 57 and 321; the presence of the product was verified on a 1% agarose gel (see Section 2.1.3).

2.4.3 Second round PCR

Reaction mixtures were set up containing IX PCR buffer (20mM Tris-HCl, 50mM KCl pH8.4) (Gibco), 2mM MgCb (Gibco), 0.3mM of each dNTP (Qiagen), 0.625U of Taq polymerase (Gibco), 25pmol of HCVGEN 3 sense primer, 25pmol of HCVGEN 4 antisense primer (synthesised by Oswel), the volume made up to 48pi with SDW and overlaid with mineral oil (Sigma).

5’ GTGGTCTGCGGAACCGG 3’ (HCVGEN 3 nt: 126 to 143)

5’ GGGCACTCGCAAGCACCC 3’ (HCVGEN 4 nt: 299 to 281)

2pl of first round product (see Section 2.3.2) was added to the appropriate tubes and cycled on an Omnigene Thermal Cycler (Hybaid), the conditions were 25 cycles of 94“C for 30sec, 68 °C for 40sec and ITC for 30sec. The second round PCR amplifies a 174bp fragment located between nucleotides 126 and 299 of the HCV 5’UTR and this was verified on a 1% agarose gel (see Section 2.1.3).

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2.4.4 Restriction digests of second round PCR products

4.5|il of the second round PCR product was added to four labelled 0.5ml reaction tubes. Each tube contained 4pl of SDW, 0.5 pi of the appropriate enzyme and Ipl of the appropriate lOX buffer. The enzymes and buffers were; Scrjl and Hinfl, both with buffer 2 (50mM NaCl, lOmM Tris-HCl, lOmM MgCb, ImM DTT, pH7.9) (New England BioLabs), BstUI with buffer 4 (50mM Potassium acetate, 20mM Tris- acetate, lOmM Magnesium acetate, ImM DTT, pH 7.9) (New England BioLabs) and Mval with buffer H (50mM Tris-HCl, lOOmM NaCl, lOmM MgClz, ImM DTT, pH7.5) (Rocbe). Tubes were flicked to mix and pulse spun in a microcentrifuge. ScrfI, Mval and Hinfl tubes were incubated in a water batb for 2bours at 37°C and the BstUI tubes for 2bours at 60®C. After incubation, all tubes were heated to 80”C in a beating block (Tecbne) for 30min to inactivate the enzymes, pulse-spun and stored at -20°C until needed.

2.4.5 15% polyacrylamide gel electrophoresis of digested DNA

Scrfl and Mval digests for each sample were pooled into a single tube and Hinfl and BstUI digests pooled into another. In a microtitre plate, Ipl of PbiX174 jy^AJHinfl markers (Promega) or Ipl of pooled digests were mixed with lOpl of loading dye (0.25% bromophenol blue (Sigma), 0.25% xylene cyanol (Sigma), 15% Ficoll type 400 (Sigma) in SDW). PAGE was carried out as in Section 2.2.3, but each 15% gel consisted of 3.75ml 40% bis-acrylamide (Scotlab), 1ml lOxTBE, 70pl 10% w/v ammonium persulphate (APS) (Sigma) and 7pl N,N,N’,N’ tetrametbyletbylenediamine (TEMED) (Sigma). They were run in Ix TBE buffer at 200V and 30mA for 105min. Gels were stained for 5min in 70ml of IX TBE containing 7pl of SYBR Green 1 (Flowgen), photographed using a Fluor-s- Multilmager (Bio-rad) and analysed using Multi-Analyst/PC version 1.1 (Bio-rad). A restriction map of the fragments generated and gels of the different subtypes are shown in Figures 3.14 and 3.15 respectively.

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2.5 Immunofluorescence assays for determining HIV and HCV specific antibody titres

Sections 2.5.1 to 2.5.3 describe basic cell culture techniques used when dealing with baculoviruses. Sections 2.5.4 to 2.5.6 describe the methods used to determine the optimal time of protein expression for the two baculovirus constructs employed where this was not known [full-length (FL) and E1E2]. Antibody titres were determined using three different immunofluorescence assays set up with three baculovirus constructs donated by Professor Ian Jones of Reading University (Livingstone and Jones, 1989;Moore et al, 1990;Chan-Fook et al, 2000;Deayton et a/,2003).

• Full length (FL)-HCV : expressing all HCV proteins • E1E2: expressing GST fusions of the immunodominant envelope glycoproteins of HCV • Env: expressing the envelope glycoprotein of HIV

Section 2.5.7 describes the method used to determine antibody titre by immunofluorescence using the above three baculovirus constructs.

2.5.1 Sf-21 cell culture

Baculovirus strains were maintained in spodoptera frugiperda (Sf-21) insect cells (Invitrogen) in accordance with standard protocols. The cells were grown at 28°C in complete TC-lOO media (GibcoBRL), supplemented with lOOU and lOOOU respectively of penicillin and streptomycin (GibcoBRL) and 10% heat inactivated foetal calf serum (Labtech). Media were stored at 4°C.

87 Chapter 2: Materials and Methods

2.5.2 Generation of high titre baculovirus stocks

For each baculovirus construct, two 75cm^ tissue culture flasks were seeded with 5x10^ Sf-21 cells, which were left to adhere for one hour, and infected with 0.1 moi of the original baculovirus stocks in 1ml volume of complete TC-lOO media for 1 hour, rocking every 15min to ensure even coverage with virus inoculum. After 1 hour, the inoculum was removed, replaced with 10ml of complete TC-lOO media and the cells incubated at 28°C in a humidified atmosphere for 120h. The supernatant was removed and virus titre assayed by plaque assay.

2.5.3 Sf-21 cell plaque assay

Two six well plates (Costar) were seeded with 1.5x10^ Sf-21 cells in a total volume of 2ml of complete TC-lOO media per well and left for 1 hour to adhere. 10'^, 10'^, 10'^, 10"^ and 10'^ dilutions of new virus stock virus in complete TC-lOO media were prepared in 1ml volumes in sterile 1.5ml tubes vortexing between each dilution to ensure even mixing of the virus. lOOpl of the appropriate dilution was added in duplicate to each well, lOOpl of complete TC-lOO media was added to the remaining two wells as an uninfected cell control. Plates were gently rocked every 15min for one hour to ensure even coverage of cells with virus inoculum and the inoculum was then removed. 3% low-gelling type VII agarose (Sigma) in SDW was melted in a microwave and equilibrated to 55°C in a water bath. This was diluted 1:2 with complete TC-lOO media and 2ml was gently added to each well. The agarose was allowed to set for 30 minutes then overlaid with 1ml of complete TC-lOO media. The dishes were incubated at 28°C in a humidified atmosphere for 72 hours. The media overlay was then removed from the wells and replaced with 2ml of a 1:12 dilution in sterile PBS of neutral red solution (Sigma), the stain was left on for 2 hours at 28°C, removed and the plates left overnight, upside down at 28°C in an incubator for clear plaques to develop. Plaques were then counted to determine virus titre in plaque forming units (pfu), (Figure 2.5).

88 Chapter 2: Materials and Methods

Uninfected 1Q2 1Q3

Figure 2.5: Neutral red stained plaque assay of high titre stock of full-length HCV baculovirus construct. All dilutions in duplicate (above and below each other). Final stock titre: mean no of plaques % dilution factor % 10 (to express per ml) = pfu/ml

20 clear plaques jc 10^ dilution % 10 = 2x10^ pfii/ml FL baculovirus stock titre

89 Chapter 2: Materials and Methods

2.5.4 Baculovirus protein expression time course in Sf-21 cells

A time course was performed to determine the optimal time of protein expression for the FL-HCV and HCV E1E2 baculoviruses; optimal expression for the HIV env baculovirus had already been determined and was 48h (Deayton et al, 2003). 24, 48, 72 and 96h time points were set up for each virus at 1, 5 and 10 moi. 10 moi of a control virus (PMB UL97 P4 a kind gift from Ms C.D. Shannon-Lowe) and negative uninfected control was also set up and time points taken at 24, 48, 72 and 96h. For each desired time point, 35cm^ tissue culture flasks (Costar) were seeded with 2x10^ Sf-21 cells in 5ml of complete TC-lOO media and left to settle for one hour. The media was removed and replaced with one ml of the required virus dilution, diluted in complete TC-lOO media (Gibco). Cells were infected for one hour, rocking every 15min. After a further hour, the inoculum was removed, replaced with 5ml of complete TC-lOO media and incubated at 28°C in an incubator for the required period of time.

The cell monolayer was removed from inside the flask at the required time point using a fine tipped pipette and the TC-lOO media from inside the flask. Cells were clearly infected but detached easily and were intact. The media and cells were removed, placed in a 15ml Falcon tube and spun at 1500 rpm for lOmin. The supernatant was removed and the pellet washed 3 times with 5ml of autoclaved, sterile PBS (Sigma).

Finally, the PBS was removed and the pellet resuspended in 200pl of sonication buffer [50mM Tris-HCl pH7.6 (Sigma), lOOmM NaCl (Sigma), 5mM MgClz (Sigma), 0.1% nonidet (Sigma), 10% glycerol (Sigma)]. Cells from the resuspended pellet were disrupted by sonication three times for 10 sec using an MSE Soniprep 150 probe sonicator at 5 microns with 30 sec cooling periods on ice in between. After sonication, the lysate was spun at 4°C in a bench top centrifuge for lOmin. The supernatant was removed and stored until needed at 4®C.

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2.5.5 SDS polyacrylamide gel electrophoresis

Protein expression was analysed by western blot and coomassie blue stained SDS PAGE gels. The resolving gel was poured into gel plates and overlayed with water- saturated butanol (Sigma) to ensure an even interface. The water-saturated butanol was decanted, the gel was rinsed with tap water once polymerised and left to dry upside down whilst preparing the stacking gel. The stacking gel was poured in and the gel left to polymerise, (see Table 2.1). 15pl of sample buffer [lOOmM Tris-HCl (Sigma), 200mM DTT if buffer stored frozen (Sigma), 4% SDS (Sigma), 0.2% bromophenol blue (Sigma), 20% glycerol (Sigma)] and 15 pi of sample were mixed and boiled on a heat block for 3min at 100°C before loading onto gel. 3 pi of Rainbow™ markers were loaded directly onto each gel without boiling. Gels were run in Ix Tris-Glycine buffer (25mM Tris, 250mM glycine (pH 8.3) at 160V for 120 minutes. The SDS-PAGE gels were stained with Coomassie brilliant blue stain (40% methanol (BDH), 10% acetic acid (BDH), 50% SDW, 0.25% Coomassie brilliant blue R250 (Sigma) v/v/v/w) by soaking for 1 hour or overnight and then destained in 40% methanol, 10% acetic acid, and 50% SDW (v/v/v) until protein bands were visible (approx 2 hours).

2.5.6 Western blot analysis

After electrophoresis (see Section 2.5.5), an SDS-PAGE gel was sandwiched between layers of thin and thick filter paper that had been just previously soaked in transfer buffer (48%mM Tris-HCl, 0.0375% (w/v) SDS, pH 9.6) and a methanol soaked polyvinylidine difluoride membrane (PVDF, Sigma) arranged as shown in Figure 2.6. The PVDF membrane could be left in methanol until needed.

Proteins were transferred onto the PVDF membrane at 2.5mA per cm^ of gel (or 150mA) for 60 to 90 minutes using a Trans-Blot® SD Semi-Dry transfer cell (Bio- Rad). After transfer, the membrane was incubated for one hour or overnight at room temperature in blocking buffer (3% bovine serum albumin (Sigma) and 0.01% sodium azide (Sigma) in TBS buffer (lOmM Tris-HCl, pH7.5, 150mM NaCl) followed by two 5 minute washes in TBS-Tween/Triton buffer (20mM Tris-HCl, pH7.5, 500mM

91 Chapter 2: Materials and Methods

Table 2,1: Components of stacking and resolving gels for SDS-polyacrylamide gel electrophoresis (PAGE).

Resolving gel Stacking gel Component 8% gel (ml) 12% gel (ml) 5% gel (ml) SDW 6.9 4.9 6.3 30% acrylamide 4.0 6.0 1 1.5M Tris pH8.8 3.8 3.8 l.OM Tris pH6.8 2.5 10% SDS 0.15 0.15 0.1 10% APS 0.15 0.15 0.1 TEMED 0.009 0.006 0.02

92 Chapter 2: Materials and Methods

Semi-dry transfer cell Cathode

Thick filter paper

SDS-PAGE gel Protein * * ^ % PVDF membrane

Thin filter paper

1 Anode Semi-dry transfer cell

Presoaked in methanol Presoaked in transfer buffer

Figure 2.6: Set up of western blot apparatus for the transfer of proteins from a polyacrylamide gel to a PVDF membrane

93 Chapter 2: Materials and Methods

NaCl, 0.05% Tween-20, 0.2% Triton X-100) and one 5 minute rinse in TBS buffer. The membrane was then incubated at room temperature for one hour with a 1:100 dilution of four different HCV antibody positive patient sera [tested by recombinant immunoblot assay (RIBA) (Ortho Diagnostics)] diluted in 50% blocking buffer diluted in TBS (Hattori et al., 1998;Yoshioka et al., 1997). The membrane was washed as before and incubated again at room temperature for one hour with an alkaline phosphatase (AP) conjugated goat anti human IgG antibody (Sigma) diluted 1:6000 with blocking buffer. The membrane was further washed as before and immunoreactive bands visualised by incubation of the membrane with one tablet of 5- bromo-4-chloro-3-indolyl phosphate/nitro blue tétrazolium chloride (Sigma) dissolved in 10ml of SDW. Reactive protein bands appeared within ten minutes (Figure 2.7).

2.5.7 Immunofluorescence assay

Sf-21 cells were seeded at a density of 5x10^ cells per 75cm^ flask. The cells were allowed to settle for 1 hour and then infected with the recombinant baculoviruses FL, E1E2 or env at a moi of five for one hour in a volume of 1ml per flask with rocking at regular intervals to ensure even coverage of cells (Section 2.5.2). The inoculum was then removed, replaced with 10ml of complete TC-lOO medium and incubated at 28°C for 48 hours (optimum time for infection as determined by Western blot. Section 2.5.6).

After 48 hours, the cells were harvested. The TC-lOO medium was removed and replaced with 10ml of sterile filtered PBS, spun down at 1500rpm for 5min and washed a further 2 times. Cells from each 75cm^ flask were resuspended in 1ml of sterile PBS (Sigma), counted on a disposable haemocytometer (ISL) and the concentration adjusted to 1x10^ cells/ml. Cells were resuspended using a 2ml pipette and most remained intact after the procedure. 15 pi of the appropriate cell suspension was then added to the relevant spot on a 12 well PTFE (poly-tetra-fluoro-ethylene) coated multispot slide (Hendley-Essex), see Figure 2.8. The cells were left to air dry onto the slide and then fixed in 100% acetone at -20°C for lOminutes. Slides were either air-dried then stored at -20°C until needed or used immediately.

94 Chapter 2: Materials and Methods

mmrn*. ^ — 70Kda*

24h 48h 72h 96h

Figure 2.7a: 24, 48, 72 and 96h time course of HCV FL protein expression by recombinant baculovirus FL at an initial moi of 5. Maximal expression was observed at 48h post infection.

w > 70 Kda*

24h 48h 72h 96h

Figure 2.7b: 24, 48, 72 and 96h time course of HCV E1E2 protein expression by recombinant baculovirus E1E2 at an initial moi of 5. 48h and 72h resulted in similar protein expression, so the 48h time point was used in all further experiments.

* Only strongest reactive band is shown

95 Chapter 2: Materials and Methods

Patient serum dilution (to 1/163840 over 3 slides) also added to corresponding uninfected cells well.

1/40 1/80 1/160

1« Ab: PBS 10 Ab: PBS 20 Ab: PBS 20 Ab: F ITC conjugated anti-human IgG F(ab)2

FL baculovirus infected cells FL baculovirus infected cells (positive fluorescence) (no fluorescence)

Uninfected cells

Figure 2.8: Layout of a single baculovirus immunofluorescence assay slide. All patient sera tested for antibody titre were diluted in twofold steps from 1/20 to 1/163840 in three separate slides (occasionally to 1/81920). Each patient serum sample dilution was added to a well containing baculovirus infected Sf-21 cells and also to a control well of uninfected Sf-21 cells. Antibody titre wa s the last dilution at which positive fluorescence could be detected.

96 Chapter 2: Materials and Methods

When needed, the slides were thawed and air-dried. Doubling dilutions of patient serum in sterile PBS were prepared starting at 1/20 down to 1/163840. 15pl of the appropriate dilution was then added to the slides (Hendley Essex UK), which were incubated in a humidified chamber at 28°C for 40-60min. The slides were then washed once for 5min in 1% BSA (Sigma) in sterile PBS followed by two 5min washes with PBS. 15pl of a 1/40 dilution in PBS of rabbit anti-human IgG FITC conjugated F(ab )2 (Dako) was then added to all slide wells apart fi*om PBS controls (see Figure 2.8). The slides were again incubated in a humidified chamber for 40- 60min and then washed as before. The slides were allowed to dry completely and mounted in Vectashield™ mounting medium for fluorescence (Vector laboratories). Slides were then scored using a UV fluorescent microscope (Olympus BX60) or stored in the dark at 4°C and scored the following day. The slides were scored by eye, with the last dilution at which immunofluorescence was observed being the antibody titre. Figure 2.9 shows immunofluorescence obtained with HCV-FL, HCV- E1E2 and HlV-env baculovirus infected Sf-21 cells and a 1/160 dilution of HIV and HCV positive patient serum.

97 Chapter 2: Materials and Methods

HCV FL baculovirus infected HCV E1E2 baculovirus infected HIV env baculovirus infected Sf-21 cells. 1/160 dilution Sf-21 cells. 1/160 dilution Sf-21 cells. 1/160 dilution HCV positive serum HCV positive serum HCV positive serum

Uninfected Sf-21 cells Uninfected Sf-21 cells Uninfected Sf-21 cells 1/160 dilution 1/160 dilution 1/160 dilution HCV positive serum HCV positive serum HCV positive serum

Figure 2.9: HCV-FL, HCV-E1E2 and HIV-env baculovirus imunofluorescence assay with a 1/160 dilution of HIV and HCV positive patient serum. The digital camera attached to the Olympus BX-60 microscope did not clearly detect the faint fluorescence observed in the uninfected control wells (bottom panels).

98 Chapter 2: Materials and Methods

2.6 The expression of memory markers on CD8+ T-cells in HIV and HCV co-infected patients

In this section, the expression of memory markers on the surface of CD8+ T-cells extracted from patient blood samples was investigated. 10 or 30ml of blood were collected from patients attending the Royal Free Hospital Haemophilia and Haemostasis Centre or Ian Charleson Day Care Centre. Blood was collected into tubes containing the anticoagulant lithium heparin (Becton-Dickinson-BD). All patients provided informed consent. The Royal Free Hospital Ethics references for the project were 219-2K for patients attending the Haemophilia and Haemostasis Centre and 5523 for patients attending the Ian Charleson Centre respectively. Sections 2.6.1 to 2.6.3 describe the isolation of PBMCs (peripheral blood mononuclear cells) from patient blood, the procedure used for HLA typing of the sample and the thawing of the PBMCs prior to antibody staining and analysis by flow cytometry. Sections 2.6.4 to 2.6.6 describe the antibodies used for staining, the acquisition of data by a fluorescence activated cell sorter (FACS) and the methods used for analysis.

The FACS automates the analysis and separation of cells stained with fluorescent antibodies. A laser beam and a light detector are used to count intact cells in suspension. Laser light is deflected from the detector every time a cell passes the laser beam (an ‘event’) and this disruption is recorded. This ‘event’ gives an indication of the size and granularity of the cells. Using this information, a ‘gate’ can be drawn in the analysis program that will correspond only to the cells of interest. In this chapter, these are the ‘live lymphocytes’, (Figure 2.10). The program used for analysis is the CELLQuestTM version 3.3 software package (BD). The laser light also excites cells stained with fluorescently labelled antibodies and this is recorded by other detectors, each being specific for a different antibody fluorophore. The FACScalibur flow cytometry apparatus (BD) used in this chapter simultaneously detects live lymphocytes stained with up to three differently labelled fluorescent antibodies. For example, CD8-PerCP antibody allowed the selection of CD8+ cells within the live lymphocyte gate. CD62L-FITC and CD45RO-APC antibodies were

99 Chapter 2: Materials and Methods then used to characterise the memory phenotype of this CD8+ live lymphocyte population. During analysis, negative cut-off values of between 10^ and 10^ relative fluorescence units were arbitrarily determined for each staining. This varied for each reaction. Cells above this threshold fluorescence were considered positive for the antibody stain, (Figure 2.10) (Goldsby et al, 2000).

2.6.1 PBMC isolation

Where possible, PBMCs were isolated from patient blood on the day of collection. Whole blood was spun through Ficoll-Paque (Amersham Pharmacia Biotech) at a v/v of 1:1 at 2000rpm for 20min (ALC bench top centrifuge) with slow acceleration and gentle braking. After centrifugation, the top blood plasma layer was removed and discarded using a sterile plastic wide-bore pipette, and the plasma-frcoll interface containing the PBMCs removed and placed into a 15ml centrifuge tube using a similar pipette, taking care to carry over as little ficoll as possible. The cells were washed once at room temperature with RPMI-1640 by centrifugation at ISOOrpm for lOmin in an ALC bench top centrifuge followed by two RPMI-1640 washes at 1600rpm for 5min. After the final wash, the cells were resuspended in 1ml of filtered PCS and placed on ice to cool for 30min. A small aliquot of extracted cells was then diluted 1:10 in crystal violet, [lOng/ml of crystal violet (Sigma) dissolved in (1:12:12 glacial acetic acid:PBS:SDW (Sigma) containing 10% paraformaldehyde] and counted using a haemocytometer. Viable PBMCs stain dark violet and the paraformaldehyde was added to inactivate any pathogens contained in the cells. The counted PBMCs were then stored in 10% DMSO (Sigma) FCS in 1ml cryogenic tubes (Nalgene) at a minimum cell number of 2x10^ cells per vial. Cells were diluted to the required density using a combination of chilled filtered FCS and a chilled solution of 20% DMSO in filtered FCS. Finally, the cells were placed overnight into an isopropanol (Sigma) containing freezing chamber (Nalgene) that cooled them down to -80®C at a rate of 1°C per minute when placed in a -80°C freezer. The following day they were placed into a liquid nitrogen storage unit (Isothermal V-1500 series - CBS).

100 Chapter 2: Materials and Methods

2.6.2 HLA typing

At the time of a patient’s first sample, 10ml of blood was collected into an EDTA blood tube for HLA typing (performed by Ms Joyce Teo, Renal Department, Royal Free Hospital). The serological method used was a special monoclonal typing tray (One Lambda Inc).

2.6.3 Thawing of frozen PBMCs

PBMCs were placed in a water bath at 37°C until just thawed, added to 5ml of RPMI- 1640 media, spun at 1600 rpm for 5min (brake off) and resuspended in 5ml of RIO media (10% FCS in RPMI-1640). PBMCs were counted using a haemocytometer and approximately 5x10^ cells were added to each 4ml FACS tube (Becton, Dickinson- BD). The PBMCs were washed again in 3ml of PBS (Sigma) as described above, the supernatant poured off and the cells resuspended in 200pl of the remaining PBS.

2.6.4 Phenotyping of CD8+ T-cells using directly conjugated antibodies

A list of the memory markers assessed for and the antibodies used is given in Table 2.2. Two or 3pi (of APC or FITC conjugated antibody respectively) were added to the cells prepared in Section 2.6.3, followed by 2pl of PerCP conjugated anti-human CDS (BD). The cells were then incubated at 4°C for 20 minutes.

CD27-FITC)/CD28-APC and CDS-PerCP as well as CD62L-FITC)/CD45RO-APC and CDS-PerCP (BD) were simultaneously stained for in one tube, whilst CD95-FITC and perforin-FITC (BD) (both also with CDS-PerCP) were stained singly. Intracellular staining for perforin required a permeabilisation step before addition of antibody. 500pl of a freshly prepared working solution (1:10 dilution of permeabilising solution 2 (BD) in SDW) was added to the cells, which were then incubated at room temperature for 10 minutes. After incubation, the cells were washed in 3ml PBS (centrifuged at 1600rpm for 5min with brake off) and 3 pi of perforin-FITC and 2pl of CDS-PerCP was added followed by incubation for 20 minutes at 4®C. After incubation, the cells were washed once more and the cells

101 Chapter 2: Materials and Methods

Table 2.2a: Conjugated antibodies used for direct staining of human T-lymphocyte memory markers. Information adapted from Goldsby et al, 2000, * supplied by BD.

CD Alternate Conjugated Clone Isotype Proposed function Leukocyte number name Fluorophore expression CDS* T8, Leu-2, PerCP SKI Mouse Co-receptor for MHC MHC class I restricted Lty-2 IgG, class I restricted T-cells T cells, some thymocytes CD27* S152,T14 FITC M-T271 Mouse Mediation of a co­ Mature thymocytes, IgG, stimulatory signal for B activated B and T cells, and T cell activation most peripheral T cells, NK cells, macrophages, memory B cells CD28* T44, Tp44 APC CD28.2 Mouse Co-stimulation of T-cell Mature CD3+ IgG, proliferation, cytokine thymocytes, most production upon peripheral T-cells, binding CD80 or CD86 plasma cells CD45RO* LCA, T200, APC UCHL-1 Mouse B and T-cell antigen All haematopoietic (RO EC3.1.3.4 IgGz. receptor mediated cells, different isoforms isoform) many activation characteristic of isoforms different differentiated cell subsets CD62L* L-selectin, FITC Dreg 56 Mouse Adhesion molecule Most peripheral blood LAM-1, IgG, mediating lymphocyte B cells T cells, LECAM-1, homing to high monocytes, Leu-8, MEL- endothelial venules of granulocytes, NK cells, 14, TQ-1 peripheral lymphoid bone marrow tissue and leukocyte lymphocytes and rolling on activated myeloid cells, endothelium at thymocytes inflammatory sites CD95* APO-1, Fas APC DX-2 Mouse Mediation of apoptosis Activated B and T cells antigen (Fas) IgGz. inducing signals Perforin* FITC 5G9 Mouse Pore forming protein T cells and NK cells IgGzb involved in cell mediated cytotoxicity

Table 2.2b: Primary and secondary antibodies used for indirect staining of CCR7 on human T-lymphocytes. Information adapted from Goldsby et al, 2000, * supplied by BD, ^supplied by Dako.

CD Alternate Conjugated Clone Isotype Proposed function Leukocyte number name Fluorophore expression CCR7* BLR-2, EBI- none 2H4 Mouse Receptor for CC B and T cells and 1,CMKBR7 IgM chemokines. Regulates dendritic cells. targeting of B cells, T cells and dendritic cells to secondary lymphoid organs Goat anti N/A FITC Goat Secondary antibody to N/A mouse IgG CCR7 primary F(ab)/

102 Chapter 2: Materials and Methods resuspended and fixed in 200pl of 2% paraformaldehyde in SDW. Cells were acquired immediately at 4°C using a FACScalibur flow cytometry machine (BD) or stored overnight in the dark at 4”C and acquired the next day, see Figure 2.10 for representative stainings. Where there were sufficient cells, isotype control staining of perforin was also performed (Figure 2.11).-

2.6.5 Unconjugated antibody staining of CCR7 on PBMCs

For CCR7 staining, 3 pi of an unconjugated mouse anti-human CCR7 primary antibody was added to the PBMCs (cells prepared as previously described) see Table 2.2b for descriptions of the antibodies used. The PBMCs and primary antibody were incubated at 4°C for 20 minutes and then washed twice in PBS as described previously, to remove any unbound primary antibody. 3pi of FITC conjugated goat anti-mouse F(ab )2 secondary antibody (DAKO) was then added to the cells , which were again incubated at 4®C for 20 minutes. After incubation, the cells were washed twice more, to remove unbound secondary antibody and then 10 pi of goat serum (BD) and 2pi of CD8-PerCP (BD) were added, followed by incubation at 4°C for 20 minutes. After incubation, the cells were washed once more, the supernatant poured off and the cells resuspended and fixed in 200pl of 2% paraformaldehyde in SDW. Where there were sufficient cells, isotype control staining of CCR7 was performed, see Figure 2.11.

2.6.6 Acquisition of data and flow cytometric analysis

Data was acquired using a FACScalibur flow cytometry apparatus (BD) and the CELLQuestTM version 3.3 software package (BD) was used for analysis. The number of events acquired ranged from 100,000 to 250,000. Analysis was focused on the CD8+ T-cell population within the live lymphocyte gate. Memory marker phenotype of the CD8+ T-cells was assessed for all samples for all the markers mentioned above. The flow cytometer settings used were set-up and adjusted by Dr M. Lucas. Figure 2.10 shows representative stainings from one patient for all memory markers tested.

103 CD8+ T-cells within the Dot plots display » 33% o f acquired ■§ live lymphocyte gate Patient 12-1 memory m arker events for clarity J - expression on CD8+ T-cells CD62L: 18.94% CD45RO: 17.84% CD95: 54.33%

|ii»i^ |tiii |iiii pi |i I I I Perforin: 10.25% 200 400 600 800 1000 CD28: 45.17% FSC-Height CD27: 56.93% Live lymphocyte gate CCR7: 42.06%

12-1 CD62L/CD45R0.050 12-1 CD95.104 12-1 PERFORIN.086 12-1 CD27/CD28.068 12-1 CCR7.109

1 0 0 1 0 0 43.59 1 0.13 0.14 O U-CSI 3^

54.33 - ^ 0 ^ # ' V l 0 . 2 5 13.34 ■ ' % - P ...... I I I 1 lir ttW " I I M IIIII I 1 w,w„T "■?WHHi| '-1 1 mini ...... 'h ^ 2 10" 1 0 ' 10^10‘ 10'^10'" 10 ^ 10" 1 0 ' 10^ 10'" 10^ 10" 1 0 ' 10" 10" 10" 10" 1 0 ' 10" 10" 10" 10" 1 0 ' 10" 10" 10 C D 45R O A P C C D 95FIT C PERFORIN FITC C D 27FIT C C C R 7FITC 12-1 C062L/CD45R0.050 12-1 CD27/CD28 068

k 12 1 PfRFORINOeS u ""lo ”' C 0 6 2 L F I T C 10" 10' 10^ 10^ 10' 12-1 CD62L1CD45R0 050 C D 2 7 F I T C 8 ------K a 10" 10" id' 10^ 10^ 10' 10' 10^ Co” C D 9 5 F I T C PERFORIN FITC C C R 7 F I T C a A. 10^ 10^ 10^ 10" C 0 4 5 R O A P C CD62L and CD45RO CD95 Perforin CD27 and CD28 CCR7 Î Figure 2.10: Representative stainings for all memory markers assessed in Chapter 6. Each red arrow points to a separate staining

and all the stains are from the same HIV mono infected patient (reference number 12-1). Histograms (in purple) sometimes aid in the

determination of negative cut-off points for the dot plots (in red), numbers in dot plots indicate percentages of CD8+ cells in quadrants. Chapter 2: Materials and Methods

CCR7 isotype antibody staining

Ml

^ 'n '1...."'I?'"'..... K 10‘ 10" 10' 10^ 10^ 10 SEC AB ONLY FITC SEC AB ONLY FITC

Perforin isotype antibody staining

o Ml o3 f I U II11I...... ' . 10' 10 10"^ 10'^ 10^ Perforin ISO FITC "»n 10' 10^ 10'- Perforin ISO FITC

Figure 2.11: Isotype control staining of CCR7 and perforin. Isotype antibody staining aids in the determination of negative cut-off values for the antibody stainings (see also Figure 2.10).

105 Chapter 2: Materials and Methods

2.7 Statistical Methods

The analysis of both HCV RNA prognostic value (Chapter 4) and anti-HCV antibody titre and HCV RNA relationships (Chapter 5) has required a considerable amount of statistical analysis. Overviews of the statistical tests used and why they were chosen are given below. The data was analysed using the statistical computer package SAS (SAS Institute Inc, 2001). For a more detailed explanation of each test see Medical Statistics at a Glance (Petrie & Sabin, 2002).

2.7.1 Sign test

The Sign test is used for analysis of a single variable of interest. It was used to compare two sets of HCV RNA levels in order to determine the effect of storage at - 20°C on HCV RNA (see Section 4.4.2 and Table 4.1). The test is based on the median of the distribution and a hypothetical value X is the median of the population. Approximately half of the samples within the population are greater or less than X respectively (after excluding any values equal to X). The sign test considers the number of values in the sample that are greater or less than X (Petrie & Sabin, 2002).

2.7.2 Wilcoxon signed ranks test

This is a non-parametric test (for data that is not normally distributed) that compares paired observations i.e. responses from matched individuals or the same individual in two different circumstances. It is a more powerful test than the Sign test because it takes into account the magnitude of the differences within the sample instead of just taking into account whether something is greater or less than a median. Individual differences are calculated for each pair of results and ignoring zero results are then classified as being positive or negative. Additionally, the differences are placed in order of size, ignoring their signs and are ranked, the smallest difference being ascribed a value of one, the second smallest, two etc. up to the largest difference, ascribed a value of n’ if there are n’ non-zero differences. If two or more differences

106 Chapter 2: Materials and Methods are the same, each receives the average of the ranks these values would have received had they not been tied. Under the null hypothesis of no difference, the sums of the ranks relating to the positive and negative differences should be the same (Petrie & Sabin, 2002). See Table 4.2 data for median (range) date of HIV seroconversion.

2.7.3 Chi squared test

The Chi squared test is used on frequency data; it tests the null hypothesis that there is no relationship between the factors that define a contingency table (a usually two way table in which the entries are frequencies). If the proportions with a certain characteristic in two groups are equal, then the overall proportion of individuals with a characteristic can be estimated by p=(a+b)/n. It would be expected that njxp of them would be in Group 1 and ti2>p would be in Group 2. The expected number of individuals without the characteristic can be similarly evaluated. Therefore, each expected frequency is the product of the two relevant marginal totals (frequency in a specific row or column) divided by the overall total. A large discrepancy between the observed (O) and corresponding expected (E) frequency is an indication that the proportions in the two groups differ. The test bases its statistic on this discrepancy (Petrie & Sabin, 2002) . An example is shown in Table 4.2.

2.7.4 Analysis of variance (ANOVA)

In Section 4.4.4, HCV RNA levels in different HCV genotypes were compared using analysis of variance (ANOVA). This test is used when there are samples from a number of independent groups and it is used to compare the values in each pair of groups (i.e. HCV genotype 1 and HCV RNA level). ANOVA is a global test that determines whether there are differences between the groups. The groups are defined by the levels (i.e. HCV genotypes) of a single factor (i.e. HCV RNA load) and it is assumed that the variable (HCV RNA level) is normally distributed and that the variance within each group is the same, a reasonable sample size is needed to ensure these assumptions are met. The analysis separates the total variability of the data into differences between groups of i.e. HCV genotype and random variation within groups

107 Chapter 2: Materials and Methods i.e. HCV RNA load. These are measured using variances (hence the name of the test). The null hypothesis states that the group means are the same and that between and within group variance is similar. If there are differences between the groups, then the between group variance will be greater than the within group variance and the test is based on the ratio of these two variances (Petrie & Sabin, 2002).

2.7.5 Pearson’s product moment correlation coefficient

If there is a linear relationship between two parameters x and y, a straight line drawn through the middle of the points would provide the closest approximation to the observed relationship. This could apply for example to the relationship between HCV RNA load and HIV RNA load (see Section 4.4.4). How close observations are to that straight line is described by calculating the Pearson product moment correlation coefficient (often called the correlation coefficient). An r-value of +1 or -1 is a perfect correlation, with all points lying on the line, r = 0 is no linear correlation. There may be a non-linear relationship however. The r-value can be misleading if there is a non-linear relationship, if the data includes more than one observation per individual, outliers or if there are subgroups within the data where the mean of at least one of the two variables is different.

2.7.6 Multivariate linear regression model

Multivariate linear regression analysis was used to determine whether factors such as age at HIV seroconversion, HIV RNA level or CD4 count had an independent effect on HCV RNA level (see Section 4.4.4). The test allows the determination of the extent to which each of the explanatory variables (i.e. HIV RNA) are linearly related to the dependent variable (i.e. HCV RNA), after adjusting for the other variables. It can also predict the value of the dependent variable from the explanatory variables (Petrie & Sabin, 2002) .

108 Chapter 2: Materials and Methods

2.7.7 Kaplan-Meier analysis

Survival curves i.e. for progression to AIDS or death (see Section 4.4.4) are usually calculated by the Kaplan-Meier method. This type of analysis displays the cumulative probability of an individual reaching the endpoint (i.e. death) at any time after baseline (see Figure 4.4). As the survival probability will only change when an endpoint occurs, the ‘curve’ is drawn in a series of steps (Petrie & Sabin, 2002).

2.7.8 Cox proportional hazards regression analysis

A regression model can be set up in order to quantify the relationship between a factor of interest i.e. HIV RNA level (see Section 4.4.4) and progression to an end point (i.e. death). At any point in time, an individual has an instantaneous risk of reaching the end point, which is usually known as the hazard, given that the individual has not reached it up to that point. The Cox proportional hazards model tests the independent effects of a number of explanatory variables on the hazard. Values above one indicate increased risk and below one decreased risk, with unity being no increase or decrease in risk of achieving the end point. The relative hazard is assumed to be constant over time in this model, and this should be tested for either by graphical methods or by incorporating the interaction between the covariate and log(time) to ensure it is non­ significant (Petrie & Sabin, 2002).

2.7.9 Log rank test

The log rank test is a non-parametric test that addresses the null hypothesis that there are no differences in survival times in the groups being studied, and compares events occurring at all time points on the survival curve. The test can only assess the independence of one factor on the time to the end point (Petrie & Sabin, 2002) . In Section 4.4.5, the test is use to compare progression to either AIDS or death in three different HCV RNA load tertiles.

109 Chapter 2: Materials and Methods

2.7.10 Spearman’s rank correlation coefficient

The Spearman’s rank correlation coefficient is the non-parametric equivalent of a Pearson’s correlation coefficient (see Section 2.7.5). It is used when at least one of the variables {x or;;) is measured on an ordinal scale, is not normally distributed, there is a small sample size or the association between the two variables is not linear (Petrie & Sabin, 2002).

2.7.11 Paired t-test

If two samples are related to one numerical order or variable of interest and to each other (i.e. they are samples from the same patient but at a different time point), the data is considered paired. It is important to take advantage of the dependence between the two samples or the advantages of pairing are lost. This is done by considering the differences in the values for each pair, reducing the two samples to a single sample of differences. For this reason, the two sets of samples must be the same size. The paired t-test assumes that the data is normally distributed and that there is a reasonable sample size. If the two sets of data are the same, the mean of the differences between each pair of measurements would be zero in the population of interest. If the 95% confidence interval does not include the hypothesised value of the second mean, the null hypothesis that the two values are the same is rejected i.e. the difference between the two sets of samples is statistically significant (Petrie & Sabin, 2002) . This test was used in Chapter 5, i.e. in Figure 5.2 to determine whether HAART had a significant effect on HIV or HCV loads in a cohort of HIV and HCV co-infected patients.

110 Chapter 3: Development of HCV QC RT-PCR assay

Chapter Three

Development of a quantitative- competitive RT-PCR assay for HCV

111 Chapter 3: Development of HCV QC RT-PCR assay

3.1 Introduction

The aim of this section was to develop a quantitative-competitive RT-PCR for HCV and a PCR and RFLP based genotyping assay for HCV. The most widely used commercial tests for the quantification of HCV RNA are the Amplicor™ HCV Monitor™ test (Roche Molecular Systems, Pleasanton, CA) (Doglio et a f 1999), the Quantiplex™ HCV branched DNA (bDNA) assay (Bayer Diagnostics) (Alter et al, 1995) and the NASBA assay (van Gemen et al, 1993). As well as these, many in- house assays have also been developed using a variety of amplification and detection techniques (Whitby & Garson, 1995;Tanaka et al, 1995;Whitby & Garson, 1997;Kleiber et al, 2000). The commercial kit used for HCV RNA quantification in the Royal Free Virology department is the Chiron bDNA version 2.0 test with a limit of detection of 2x10^ genome equivalents (Eq) per ml of serum. It would be prohibitively expensive to carry out a longitudinal HCV viral load study using this commercial test and in addition, its limit of detection is high. For these reasons, a cheap and straightforward in-house quantitative competitive (QC) RT-PCR assay for HCV has been developed.

The detection of HCV RNA in serum was first described in 1990 (Garson et al, 1990;Kato et al, 1990) and in 1992, our laboratory published the method for a QC PCR assay for human cytomegalovirus (CMV) (Fox et al, 1992). The development of this QC RT-PCR assay for HCV was adapted from that paper and the non-radioactive method of quantifying viral load used in the assay was adapted from Kidd et al, 2000.

The 5’UTR of HCV is the most conserved region of the virus (Okamoto et al, 1992a) and the most common region amplified in RT-PCR assays (Whitby & Garson, 1995;Whitby & Garson, 1997;Kleiber et al, 2000), although some assays use other targets such as HCV core protein (Kobayashi et al, 1998). For this reason, the RT- PCR amplification of a fi-agment of the 5’UTR was used as the basis for this assay.

In order to further characterise the patient cohort, an RT-PCR and restriction fragment length polymorphism (RFLP) genotyping assay was also developed. The methodology was slightly modified from that given in Harris et al. (Harris et al.

112 Chapter 3: Development of HCV QC RT-PCR assay

1999). There are various non-sequencing methods used to genotype HCV, some are based on amplification using genotype-specific primers (Okamoto et al, 1992b;Ohno et al, 1997;Wu et al, 1997), on the hybridisation of biotinylated PCR products to specific probes bound onto a membrane (LIPA assay) (Stuyver et al, 1996), and others are PCR and RFLP based (Davidson et al, 1995;Pohjanpelto et al, 1996;Harris et al, 1999).

113 Chapter 3: Development of HCV QC RT-PCR assay

3.2 Materials and Methods

Detailed descriptions of the methods used to develop the HCV QC RT-PCR assay are given in Chapter 2 Section 2.1. The results obtained are described in this chapter.

3.3 Results

3.3.1 Generation of the internal standard for the HCV QC-RT PCR assay

Ligations of a 249bp fragment of the 5’UTR of HCV into the TA cloning vector pCR®2.1 were provided by Dr H.L. Devereux (Section 2.1.1). The ligations were amplified in two separate PCR reactions, using M l3 reverse or forward primers and the mutagenic primers HCVMUT and HCVMUTB respectively. These primers generate a unique Hindlll restriction site in the internal standard (IS) sequence. PCR amplification using these primer sets produced 241 and 243 bp bands respectively (see Sections 2.1.2 to 2.1.4 and Figure 3.1).

Equimolar amounts of the two products (0.5 and 2.5 pmol) were mixed, denatured at 95^C and annealed with each other at room temperature. Single stranded regions were filled in with DNA polymerase I Klenow fragment and PCR amplified using the primers HCVTOl and 5’UTROl. The resulting PCR products were purified using a Wizard PCR prep kit (Sections 2.1.5 to 2.1.7 and Figure 3.2).

The purified putative IS fragment and the unmutagenised wild type (wt) fragment were cloned into pGEM®-T Easy vectors and transformed into competent E.coli JM- 109 cells. Plasmid DNA was then extracted from bacterial colonies and analysed by restriction enzyme digestion with EcoRl to release insert from vector and Hindlll to verify the presence of the novel restriction site (Sections 2.1.8 to 2.1.12 and Figures 3.3 and 3.4).

Four IS and three wt clones were sequenced to determine their orientation within the pGEM® T-Easy vector (Sections 2.1.13 and 2.1.14 and Figure 3.5). Single positive sense IS and wt clones, cloned downstream of the pGEM® T-Easy vector T7 promoter

114 Chapter 3: Development of HCV QC RT-PCR assay

M 13 reverse M13 forward HCVMUT HCVMUTB A A \pCR.2.1 H 2O Lane 8 9 10 11

pCR2.1 (plasmid And template)

Figure 3.1: 1 % agarose gel of PCR amplification of pCR2.1 HCV 5’UTR ligations with the mutagenic primers HCVMUT and HCVMUTB coupled with M l3 reverse and forward primers respectively. Markers used in lane 1 are PCR markers (Promega)

0.5pmol 2.5pmol Lane 1 2 3

233bp Klenow fill product

Figure 3.2: 1% agarose gel separation of the 233bp mutagenised internal standard fragment containing a Hindlll restriction site.

115 Chapter 3: Development of HCV QC RT-PCR assay

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

3015bp

260bp ^140+120bp

Figure 3.3: 1 % agarose gel of restriction enzyme digests of putative internal standard (IS) cloned into pGEM T-Easy vectors (lanes 4 to 17) and control unmutagenised wt 5’UTR inserts cloned into pCR2.1 vectors (lanes 2 and 3). Even numbered lanes are E’co/?/digests and odd numbered lanes EcoRI and Hindlll double digests. The poor resolution on an agarose gel does not allow distinction between the 120bp and 140bp bands.

1234 567 89

3015bp

260bp

Figure 3.4: 1% agarose gel of restriction enzyme digests of unmutagenised wt 5’UTR cloned into pGEM T-Easy vectors. Even lanes are E'er;/?/digests and odd lanes Eco/?/and//mr////double digests.

116 Chapter 3: Development of HCV QC RT-PCR assay were selected and large scale DNA prepared from selected single bacterial colonies (Section 2.1.15 and Figure 3.6). The vector DNA was then linearised with Spel to produce discrete sense RNA transcripts of 287nt in length. In order to verify complete vector linearisation, 0.5pi of Spel digested and undigested vector templates were run on a 0.8% agarose gel (Section 2.1.16 and Figure 3.7). Positive sense RNA transcripts were produced using the T7 RiboMAX™ large-scale RNA production system, and the DNA template removed using RNase free DNase 1. Resultant RNA was cleaned up using an RNeasy kit according to its RNA clean up protocol and resuspended in sterile nuclease free water. RNA transcripts were then run on a 1% MOPS/formaldehyde gel to check transcript size and integrity (Sections 2.1.17 to 2.1.20 and Figure 3.8). Finally, PCR using the primers HCVTOl and HCVT02 (Sections 2.1.6 and 2.2.1) was used to verify complete removal of contaminant DNA (see Figure 3.9).

3.3.2 Optimisation of the QC RT-PCR assay

The Access one-tube RT-PCR system (Promega) was initially used at a range of magnesium concentrations (0.75 to 2.5mM) and primer concentrations (1 to 50pmol) but failed to amplify 1x10^ copies of wt transcripts (data not shown). The methodology used was then changed to one already in use in the department and the RT and PCR steps were separated. The reverse transcription was performed using the Gene Amp® MuLV reverse transcriptase enzyme and the subsequent PCR using the Hot Star Taq enzyme (see Section 2.2.1). The use of thin wall reaction tubes, reduction of the RT primer (HCVT02) concentration to 8pmol to reduce spurious PCR products and annealing at 60“C resulted in the detection of 1x10^ copies of wt transcripts.

117 Chapter 3: Development o f HCV QC RT-PCR assay

HCV 5’UTR WT HCV 5’UTR IS G A T C G A T C A A G Hindlll restriction lite C 5’ AAGCTT 3’ T T

Figure 3.5: 8% urea sequencing gels showing location of engineered restriction site in the IS fragment and its absence in the wt fragment.

118 Chapter 3: Development of HCV QC RT-PCR assay

Xmn I 2009 Nae I Sea I 1890 2707 1 start f1 ori Apa I Aat II Sph I BslZ Amp Nco I pGEMM Easy BstZ Vector Not I Sac II 2 (3015bp) EcoR §O cn D, Spe I X) EcoR m rs Not I BslZ I Pst\ on S a /1 Nde I Sac I BslX Nsi I 127 141 Î SP6

Figure 3.6: pGEM T-Easy vector (reprinted from schematic representation of selected cloned IS fragment. Cloned wt fragment is identical minus the Hindlll restriction site.

119 Chapter 3: Development of HCV QC RT-PCR assay

21226 5148/4973 4268 / 3530 3275bp 2027/ 1904 1584/ 1375

Figure 3.7: 0.8% agarose gel showing linearisation with Spel of pGEM^ T-Easy plasmid containing the IS fragment. Lane 1, Ipl of ÀDNA EcoRI/Hindlll high molecular weight markers (size in bp on left of lane 1, Promega). Lane 2, Circular undigested pGEM^ T-Easy plasmid containing IS insert. Lane 3, Spel linearised pGEM^ T-Easy plasmid containing IS insert.

ISOOnt

287nt

Figure 3.8: 1% MOPS/formaldehyde agarose gel of the purified IS RNA, 287nt long transcript. Lane 1, 2pl of RNA markers (size in bp on left of lane 1, Promega). Lane 2, 5pl of purified IS transcripts and Lane 3, 5pl of the 1800nt kit control luciferase gene transcript.

120 Chapter 3: Development of HCV QC RT-PCR assay

1234 5678 9

233bp cloned wt or IS band

Increasing amounts of degraded RNA transcripts

Figure 3.9: 1% agarose gel of PCR reactions to verily lack of DNA in wt and IS RNA transcripts. Lane 1, PCR markers. Lanes 2 to 4, 1, 3 and 5pl of wt RNA transcripts. Lane 5, wt cloned in pGEM*^-T Easy vector. Lanes 6 to 8, 1, 3 and 5pl of IS RNA transcripts. Lane 9, IS cloned in pGEM*^-T Easy vector.

121 Chapter 3: Development of HCV QC RT-PCR assay

3.3.3 Generation of the standard curve and calibration of the quantitative competitive RT-PCR assay

In order to determine the dynamic range of the QC RT-PCR assay, known copy numbers of both wt and IS sequence ranging from 1x10^ to 5x10^ copies were mixed together and co-amplified using the conditions determined in Section 3.3.2. After amplification, the PCR products were digested with Hindlll to digest the IS sequence and separated by electrophoresis on 10% polyacrylamide gels run in TBE. Gels were photographed, scanned and quantified using NIH Imager software. The ratio of wt signal to total signal multiplied by the copy number of the input IS RNA allowed copy number to be calculated. A gel illustrating one of these experiments is shown in Figure 3.10. The mean of three experiments for each point is plotted as a standard curve in Figure 3.11 see also Sections 2.2.2 to 2.2.5. The calculated and actual input wt copy numbers were highly correlated by linear regression analysis (R=0.99 p=<0.0001) indicating that the method was highly reproducible, accurate and had a broad dynamic range of 1x10^ to 5x10^ RNA copies. This range does not take into account dilution effects from the serum sample RNA extraction during routine use.

3.3.4 Quantification of stored serum samples

Serum samples were stored at -40®C, and viral RNA was extracted from 200pl using the High Pure Viral RNA kit. Extracted viral RNA was then eluted using 50|il of nuclease free water and stored at -80®C until needed. 2pi of extracted RNA was then reverse transcribed and 5 pi of this reaction was added to the PCR mix for amplification (Sections 2.2.1 and 2.2.6). These dilution effects decrease the sensitivity of the assay to 1 x 1 copies/ml, which is still more sensitive than the Chiron bDNA version 2.0 assay at 2x10^ Eq/ml.

122 Chapter 3: Development of HCV QC RT-PCR assay

123456789 10

300bp

-204bp wt 150bp

132bp Hindlll digested IS

72bp Hindlll digested IS

50bp

Figure 3.10: 10% polyacrylamide gel analysis of 10"^ copies of IS transcript mixed in triplicate wit! 5x10^, (lanes 2 to 4) 10"^ (lanes 5 to 6) or 5 x 10"^ (lanes 7 to 9) copies of wt transcripts, RT-PCR amplified and Hind III digested. PCR markers in lane 1.

123 Chapter 3: Development of HCV QC RT-PCR assay

r =0.99 P= <0.001

Di-H I n c

oCIh o <

VO

03 3 O <

1 2 ,3 ,4 ,5 6 7 Calculated wt6 RNA copy number

Figure 3.11: Calibration of the HCV quantitative-competitive RT-PCR assay. Standard curve generated by triplicate repeats of IS and wt co-amplification experiments (Section 3.3.3). The standard error of the mean is plotted for each point as the error bar. The line of best fit is plotted through the points and there is a highly significant linear relationship between the actual input wt copy number and the calculated wt copy number over a range of 1x10^ to 5x10^ copies (R^=0.99 p=<0.0001).

124 Chapter 3: Development of HCV QC RT-PCR assay

3.3.5 Evaluation of concordance between the HCV QC RT-PCR assay and the Chiron branched DNA (bDNA) version 2.0 assay

45 HCV positive samples that had been previously quantified using the Chiron bDNA version 2.0 assay, were thawed and retested on the QC RT-PCR assay, see Figure 3.12. Values obtained using the QC RT-PCR assay ranged between 2x10^ and 9.5x10^ copies/ml (median 5.42x10^). Values obtained using the bDNA version 2.0 assay ranged between 2.8x10^ and 6.7x10^ copies/ml (median 7.03x10^). All values for samples negative in either assay were not included in the analysis. A linear regression was performed and the values obtained from both assays correlated well R=0.57 p=<0.001 (Figure 3.12) although at higher levels, QC RT-PCR values were significantly lower than those measured on the bDNA version 2.0 assay. This is similar to the correlation seen between the Roche AMPLICOR Monitor assay and the Chiron bDNA version 2.0 assay (Cordoba et al, 2000), see also Section 1.7.

3.3.6 Evaluation of quantification in different HCV genotypes

39 samples from HCV mono infected patients previously quantified on the bDNA assay and of known genotype were quantified on the QC RT-PCR assay. 16 were genotype 1,12 were genotype 2 and 11 genotype 3. Overall, there was no significant difference between viral loads calculated on the Chiron and the QC RT-PCR assay (p=0.52 Sign-rank test). There was no significant difference between the two assays for genotype 1 (p=0.91 Sign-rank test) but bDNA values were higher for genotype 2 (p=0.004 Kruskal-Wallis test) and lower for genotype 3 (p=0.004). However, differences between the two assays are not significant for genotypes 1 (median difference -1.2 [-280.2, 16.5], p=0.91. Sign-rank test) and 2 (median difference 18.49 [-8.0, 43.0], p=0.16. Sign-rank test) respectively. However, there was a suggestion of a real difference in the quantification of genotype 3 between the two assays, with the QC RT-PCR assay giving higher loads (median difference -34.34 [-37.8, -25.9], p=0.06. Sign-rank test). The primer sets match well with 5’UTR sequences from all HCV genotypes and subtypes detected in the Royal Free Haemophilia centre cohort, see Figure 3.13.

125 Chapter 3: Development of HCV QC RT-PCR assay

R= 0.57 p= <0.001

Cu

HCV QC RT-PCR RNA copies/ ml

Figure 3.12: Linear regression performed on HCV RNA loads from 45 HCV positive serum samples quantified for HCV RNA using the Chiron bDNA version 2.0 assay and the QC-RT PCR assay.

126 Chapter 3: Development of HCV QC RT-PCR assay

Figure 3.13: Alignments of 5’UTR nte sequences of different HCV genotype with QC RT-PCR primer sequences. 5’UTR nucleotides in black (n), mismatched bases in red (n) and primers in blue (n). Genbank accession numbers: la-D31603, Ib- AF217301, 2a-D31605, 2b-AF217307, 2c-D31972, 3a-AF046866 and 4-AF217314.

Primers (HCVTOl) — ► cacgcag la cttcacgcag lb cacgcag 2a cttcacgcag 2b cacgcag 2 c 3a cttcacgcgg 4 cacgcag

Primers aaagcgtcta la aaagcgtcta gccatggcgt tagtatgagt gtcgtgcagc ctccaggacc lb aaagcgtcta gccatggcgt tagtatgagt gtcgtgcagc ctccaggacc 2a aaagcgtcta gccatggcgt tagtatgagt gttgcacagc ctccaggccc 2b aaagcgccta gccatggcgt tagtatgagt gtcgtgcagc ctccaggccc 2c ccatggcgt tagtatgagt gtcgtacagc ctccaggccc 3a aaagcgccta gccatggcgt tagtatgagt gtcgtgcagc ctccaggacc 4 aaagcgtcta gccatggcgt tagtatgagt gttgtgcagc ctccaggacc

Primers la ccccctcccg cgagagccat agtggtctgc ggaaccggtg agtacaccgc lb ccccctcccg ggagagccat agtggtctgc ggaaccggtg agtacaccgg 2a ccccctcccg ggagagccat agtggtctgc ggaaccggtg agtacaccgg 2b ccccctcccg ggagagccat agtggtctgc ggaaccggtg agtacaccgg 2c ccccctcccg ggagagccat agtggtctgc ggaaccggtg agtacaccgg 3a ccccctcccg cgagagccat agtggtctgc ggaacgggtg agtacaccgg 4 ccccctcccg ggagagccat agtggtctgc ggaaccggtg agtacaccga

Primers la aattggcagg acgaccgggt cctttcttgg atcaacccgc tcaatgcctg lb aattgccagg acgaccgggt cctttcttgg attaacccgc tcaatgcctg 2a aattgccggg aagactgggt cctttcttgg ataaacccac tctatgcccg 2b aattaccgga aagactgggt cctttcttgg acaaacccac tctatgtccg 2c aattgccggg aagactgggt cctttcttgg ataaacccac tctatgcccg 3a aatcgctggg atgaccgggt cctttcttgg agcaacccgc tcaatgactc 4 atcgccggg atgaccgggt cctttcttgg ataaaacccgc tcaatgcccg

Primers (5'UTROl) a tcggctcatc acaaccc la gagatttggg cgtgcccccg caagactgct agccgagtag tgttgggtcg lb gagatttggg cgtgcccccg caagactgct agccgagtag tgttgggtcg 2a gccatttggg cgcgcccccg caagactgct agccgagtag cgttgggttg 2b gtcatttggg cgtgcccccg caagactgct agccgagtag cgttgggttg 2c gccatttggg cgtgcccccg caagaccgct agccgagtag cgttgggttg 3a cagaattggg cgtccccccg caggatcact agccgagtag tgttgggtcg 4 gaaaatttggg cgtgcccccg caagactgct agccgagtag tgttgggtcg

Primers cgga acaccatgac ggacta (HCVT02 ) la cgaaaggcct tgtggtactg cctgataggg tgcttgcg lb cgaaaggcct tgtggtactg cctgataggg tgcttgcgag tgccccggg 2a cgaaaggcct tgtggtactg cctgataggg tgcttgcgag tgccccggg 2b cgaaaggcct tgtggtactg cctgataggg tgcttgcgag tgccccggg 2c cgaaaggcct tgtggtactg cctgataggg tgcttgcgag tgccccggg 3a cgaaaggcct tgtggtactg cctgataggg tgcttgcg 4 cgaaaggcct tgtggtactg cctgataggg tgcttgcgag tgccccggg

127 Chapter 3: Development of HCV QC RT-PCR assay

3.3.7 Evaluation of QC RT-PCR reproducibility

17 serum samples were quantified on the QC RT-PCR assay. After quantification, viral RNA was re-extracted from the sample and this was quantified again. The viral loads obtained from both experiments were then compared, see Table 3.1. There was no significant difference between the two sets of data (mean difference = -0.02, SD = 0.20, p= 0.76, paired t-test) indicating that the viral loads obtained with this assay are reproducible.

3.3.8 Development of a genotyping assay for HCV

The genotyping assay was slightly modified from (Harris et al, 1999). It was found that a concentration of 0.3mM of each dNTP, resulted in more efficient amplification for both the first and second rounds of PCR (Sections 2.4.2 and 2.4.3) than the published concentration of ImM. Genotype was determined by RFLP on 15% DNA polyacrylamide gels stained with SYBR Green I. Samples were digested for 2 hours at either 37”C or 60°C and heat denatured at 80”C for 30 minutes rather than the published 1.5 hours and 15 minute dénaturation, as this gave clearer restriction fragments. The gels used were polyacrylamide gels as opposed to MDE (Flowgen) gels; this reduced the cost of the assay and cut the run time of the gels to 105 minutes from an original time of 240 minutes. See Sections 2.4.1 to 2.4.5 for methodology and Figures 3.14 and 3.15 for restriction digest patterns. The distribution of genotypes for the patient cohort used in Chapter Four is shown in Table 4.3.

128 Chapter 3: Development of HCV QC RT-PCR assay

Sample Initial HCV RNA load Second HCV RNA load measurement (copies/ml) measurement (copies/ml) 1 e.ixio" 5.5x10* 2 2.2x10*’ 7.3x10** 3 2.4x10*’ 2.6x10* 4 5.1x10“ 2.5x10“ 5 7.6x10*’ 8.6x10* 6 1.0x10* 1.1x10* 7 2.7x10' 2.0x10’ 8 3.1x10*' 2.2x10* 9 1.1x10* 5.2x10“ 10 3.1x10* 2.2x10* 11 5.0x10' 8.3x10' 12 2.5x10' 2.3x10’ 13 3.2xlO' 3.9x10’ 14 4.3x10' 5.1x10’ 15 4.9x10’ 5.5x10’ 16 4.2x10' 5.0x10’ 17 4.9x10** 2.8x10* Mean - SD 6.75-1.03 6.74-1.15

Table 3.1: Assay reproducibility data. 17 HCV positive serum samples were quantified on the QC RT-PCR assay, then viral RNA fi*om the same sample was re-extracted and the viral load determined again. There was no significant difference between the viral loads obtained in each of the two experiments (p= 0.76, paired t-test).

129 Chapter 3: Development of HCV QC RT-PCR assay Figure 3.14: Restriction fragment length polymorphisms of the 174bp fragment amplified from the 5’UTR region used to identify genotypes and subtypes of HCV. Restriction site (I), all fragment sizes in bp.

50 100 150 174 H 13’ Genotype L_ 36 1 9 1 32 1 97 Scrfl r 1 36 « 1 97 Mval la ^ 1 1 174 1 r “ Hinfl | _ 129 1 45 1BstUI r 1

L_ 36 1 9 1 32 1 97 1Scrfl r t l _ 36 « 1 97 Mval lb 1 1 174 Hinfl r" | _ 99 1 30 1 45 1BstUI 1 1

36 1 41 97 Scrfl 1 ' !Mval 2a ^ 174 1 1 1 Hinfl 1 174 1BstUI

1 174 1Scrfl 1 174 1Mval 2b 174 1 1 Hinfl 1 174 1BstUI

L_ 45 129 1 1 Scrfl 1 174 1 Mval 3 a ( a ) ^ 29 , 145 1 1 Hinfl L_ 99 1 30 1 45 1BstUI r 1 1

45 129 Scrfl 1 ' 174 1Mval 3 a ( P ) [ “ 29 1 145 Hinfl r~ 1 1_ 129 J 45 1BstUI T 36 L_ 1 9 1 32 97 Scrfl 1 ' ' '.74 ! Mval 3b 29 1 145 h" 1 Hinfl L_ 99 1 30 1 45 1BstUI n 1 1

L_ 36 1 9i 32 97 Scrfl 1 ' ' 'l74 1Mval 4 29 1 145 Hinfl r" 1 L_ 129 1 45 1BstUI n 1

l_ 36 1 9 1 32 97 Scrfl 1 ' ' ' 174 1Mval 5 174 h" Hinfl i_ 99 1 30 1 45 1BstUI 1 1

L_ 36 1 9 1 32 1 97 Scrfl r 1 1_ 36 « 1 97 Mval 6 [ 1 1 174 Hinfl 174 BstUI

130 Chapter 3: Development of HCV QC RT-PCR assay

Serf! H infl Scrfl Hinfl Scrfl Hinfl Scrfl Hinfl Mval BstUI Mva I BstU I Mva I BstU I Mva / BstU /

• — 1 7 4 b p 1 7 4 b p I— 174bp 174bp — ■174bp 174bp- I29bp 9 7 b p 9 7 b p . » — 9 9 b p 9 7 b p —

■ 45bp — 4 5 b p 41 b p — 41 b p — ------4 1 b p ■ 3 6 b p ■ 3 6 b p — 3 6 b p — % 3 2 b p . 3 2 b p - — 3 0 b p

la lb 2a/2c 2b

Scrfl Hinfl Scrfl Hinfl Mval BstUI Scrfl Hinfl Mval BstUI Mva / BstU /

1 7 4 b p 17 4 b p — — 1 4 5 b p 1 2 9 b p — 145bp 174bp— 1 2 9 b p — a # — _ 1 4 5 b p !2 9 b p . — 9 9 b p — 1 2 9 b p \ 9 7 b p .

4 5 b p — 4 5 b p 4 5 b p . — 4 5 b p 4 5 b p

. 3 0 b p 3 6 b p . — 2 9 b p 3 2 b p . — 2 9 b p 2 9 b p 't a ; ^

3a(a) 3a(P)

Figure 3.15: 15% polyacrylamide gels of different digestion patterns diagnostic of various HCV genotypes. The methodology was adapted from Harris et al, 1999.

131 Chapter 3: Development o f HCV QC RT-PCR assay

3.4 Discussion

3.4.1 Development of the QC RT-PCR assay for HCV

The aim of this section was to develop a fully quantitative competitive RT-PCR assay for HCV. The 5’UTR was chosen as the target region for amplification as it is the most conserved region of the virus and the one usually targeted for amplification (Bukh et al, 1992;Whitby & Garson, 1995;Colucci & Gutekunst, 1997). The fragment of the 5 ’UTR was amplified from a patient with genotype 1 HCV infection. Genotype 1 was chosen, as it is the most prevalent genotype in the examined patient group (Harris et al, 1999). Additionally, there are very few differences in the nucleotide sequence of this amplified region between different HCV genotypes, see Figure 3.13.

There were four important aims when evaluating the assay: that it correlated well with an established commercial assay, equally quantified all HCV genotypes found in the Royal Free Haemophilia cohort, was cheaper to run than the Chiron version 2.0 bDNA assay and more sensitive. The assay correlated well with the bDNA assay, as evaluated by the QC RT-PCR quantification of 45 samples previously quantified on the bDNA assay (R=0.57, p=<0.001. Figure 3.12). The primer sets matched well with all the HCV genotypes encountered (Figure 3.13) and the quantification of different HCV genotypes was similar between the two assays (Section 3.3.6). The cost of a single HCV RNA load run on the Chiron version 2.0 bDNA assay is £40, the cost on the QC RT-PCR assay averaged £10. Finally, taking into account dilution effects due to sample viral RNA extraction, the QC RT-PCR assay had a limit of detection of 1x10^ Eq/ml, the limit of detection for the Chiron version 2.0 bDNA assay is 2x10^ Eq/ml. All four aims were achieved.

There are now PCR techniques more modem than the ones used in this Chapter that are routinely in use such as the Taq-Man® (Applied Biosystems) methodology (Kuimelis et al, 1997). This system can analyse emerging PCR products in real-time, dispensing with need for running gels. A one-step RT-PCR method using dual labelled fluorogenic probes to the 5’UTR of HCV (Roche) coupled with the ABI

132 Chapter 3: Development of HCV QC RT-PCR assay

Prism 7700 real time sequence detection system (Perkin-Elmer) has been published (Martell et at, 1999). However, the limit of detection for the assay (as seen in its standard curve) was 10^ copies of HCV RNA, which is 1 log higher than this assay (see Figure 3.11). In preliminary experiments, I had found that although the Access™ one-step RT-PCR system was quicker, it was also significantly less sensitive than the separate RT and PCR methodology, see Section 3.3.2.

3.4.2 HCV genotyping assay

The most accurate method of genotyping involves the sequencing of the whole HCV genome and the production of dendrograms to describe how sequences are related to each other. In this method, similar genotypes and subtypes would cluster together (Clewley, 1998a;Clewley, 1998b). Clearly, this is a very time consuming and expensive technique that also requires powerful computer analysis using various mathematical algorithms to assess nucleotide similarity. Instead, fragments of the genome are used for phylogenetic analysis, particularly a 222bp fragment of the NS5B gene (Simmonds et al, 1993). The preferred HCV genotyping assay is the line probe assay, based on the hybridisation of biotinylated PCR products to membrane bound type specific probes (Davidson et al, 1995). It is based on the highly conserved HCV 5’UTR which makes false genotype alignments or negative genotyping results unlikely. However, the low sequence diversity limits the assays ability to detect different subtypes and unfortunately the assay is prohibitively expensive for routine use. Genotyping assays that use PCR with genotype-specific primers are usually based on the core region (Okamoto et al, I992b;Ohno et al, 1997;Wu et al, 1997). This region is more variable than the 5’UTR, allowing for the identification of a greater number of subtypes. Unfortunately, this also means that incorrect genotype alignments and the false identification of mixed infections are common. Another method for the identification of HCV genotype is based on RFLP analysis of amplicons generated from the 5’UTR (Davidson et al, 1995;Pohjanpelto et al, 1996;Harris et al, 1999). This was the method chosen as the conservation of the 5’UTR results in a more reliable assay. The assay used distinguishes between the following genotypes and subtypes, la, lb, 2a/2c, 2b, 3a, 3b, 4, 5 and 6. Other genotypes and subtypes may be untypable or incorrectly assigned to one of the

133 Chapter 3: Development of HCV QC RT-PCR assay aforementioned genotypes and subtypes; in addition, subtypes 7, 8 and 9 are classified as genotype 1, but these are extremely rare in the British population (Tokita et al, 1998).

134 Chapter 4: Prognostic value o f a single HCV RNA load

Chapter Four

The prognostic value of a single hepatitis C (HCV) RNA load measured

early after HIV seroconversion

135 Chapter 4: Prognostic value of a single HCV RNA load

4.1 Introduction

This Chapter used the HCV QC RT-PCR and HCV genotyping assays developed in Chapter 3 to determine whether a single HCV RNA load measured early after HIV seroconversion in HIV and HCV co-infected individuals was associated with subsequent progression to ADDS or death.

Virtually all patients with inherited bleeding disorders in the United Kingdom were infected with HCV if they were treated with large pool clotting factor concentrates (CFC) prior to the introduction of heat sterilisation in 1985. Of these, 19.5% also became infected with HIV (Darby et al, 1995). These men were infected very early on in the HIV epidemic and many died before the introduction of highly active antiretroviral therapy (HAART) in 1996. Progression to ADDS dropped dramatically after this point, but the death rate remains high in these HIV and HCV co-infected individuals. The Royal Free Hospital Haemophilia Cohort is one of the most intensively studied cohorts of haemophiliac men in the world ( Lee et al, 1989;Lee et al, 1990;Sabin et al, 2000b;Yee et al, 2000). Liver disease is now the primary cause of death amongst HIV and HCV co-infected individuals from within this as well as other HIV and HCV co-infected cohorts (Sabin et al, 2000b;Bica et al, 2001).

The presence of HIV elevates HCV RNA load and accelerates HCV liver disease progression (Eyster et al, 1994;Telfer et al, 1994). Conversely, the presence of HCV increases the risk of death or an AIDS defining illness as well as impairing CD4+ T cell recovery on HAART (Greub et al, 2000). Unfortunately, the underlying mechanism by which this occurs remains unknown.

HIV-1 RNA load has been shown to be a useful marker of HIV disease progression and its prognostic value is well-documented (Mellors et al, 1995;Mellors et al, 1996). In contrast, the prognostic value of HCV RNA load for progression to all cause mortality, ADDS or death from liver disease remains unclear (Berger et al, 1996; Sabin et al, 1997;Puoti et al, 1999;Daar et al, 2001b;Goedert et al, 2001). Elevated HCV RNA levels have been detected in HIV co-infected individuals compared to those infected with HCV alone (Eyster et al, 1994;Chambost et al, 1995;Berger et al.

136 Chapter 4: Prognostic value o f a single HCV RNA load

1996;Beld et al, 1998;Bonacini et al, 1999). Other longitudinal studies of HCV RNA load have found associations with HIV-1 disease progression, response to antiretroviral therapy and histological liver damage (Greub et al, 2000;Adinolfi et al, 2001;Daar et al, 2001b). There may also be an inverse correlation between HCV RNA load and CD4 count as well as genotype related effects (Eyster et al, 1994;Booth et al, 1997;Sabin et al, 1997;Beld et al, 1998;Daar et al, 2001a). However, there have been no studies to date that have evaluated the prognostic value of the isolated HCV RNA loads that are measured in HCV positive individuals.

This study assessed the prognostic value of a single HCV RNA load measured early post HIV seroconversion in a cohort of 96 HIV and HCV co-infected individuals attending the Royal Free Hospital Haemophilia and Haemostasis Centre.

137 Chapter 4: Prognostic value of a single HCV RNA load

4.2 Materials and Methods

Detailed descriptions of the methodology used in this chapter are given in Chapter 2. Sections 2.1 to 2.3 for the QC RT-PCR assay, Section 2,4 for the HCV genotyping assay and Section 2.7 for the methods used in the statistical analysis of this data.

4.3 Patients studied

4.3.1 Study population (and samples)

The cohort consisted of 111 HIV and HCV co-infected male patients with inherited bleeding disorders registered at the Royal Free Hospital Haemophilia Centre. Patients from this cohort have been described previously (Lee et al, 1989;Sabin et al, 2000b;Yee et al, 2000). Dates of HIV seroconversion had been retrospectively estimated for each patient using stored serum samples (Lee et al, 1989). Age at HIV seroconversion ranged from 1.9 to 77.8 years (median 22.6) and all patients had been infected with HCV either prior to or at the same time as HIV.

4.3.2 HIV and HCV therapy

Patients were treated according to the guidelines in place at the time. Since the end of 1995, patients with low CD4 counts have been offered HAART regimens including at least one non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor (PI). PFs are used with caution in this group because of the possibility of liver complications in HCV positive patients and spontaneous bleeding episodes in haemophilic men (Ginsburg et al, 1997;Yee et al, 1997). Patients with CD4 counts of <200x10^ cells/L have been offered prophylaxis against Mycobacterium avium since 1988. However, because of immune reconstitution as a result of HAART therapy, there is currently less need for prophylaxis and this is now stopped once a patient’s CD4 count increases to levels above 200cells/mm^ whilst on HAART. Antiviral therapy for HCV was administered to 16 (14.4%) of the 111 patients in the cohort, 13 were treated with interferon monotherapy and three with interferon plus ribavirin. The use of interferon has not been controlled for in this study because the doses used

138 Chapter 4: Prognostic value of a single HCV RNA load have been shown not to have an effect on HIV progression (Yee et al, 2000). HAART was offered according to the guidelines in place at the time (2001), currently when CD4 counts fall below 300cells/mm^.

139 Chapter 4: Prognostic value o f a single HCV RNA load

4.4 Results

4.4.1 Quantitative RT-PCR and HCV genotyping

HCV RNA levels were measured in all 111 patients in the cohort using the QC RT- PCR assay developed in Chapter 3 (range 1x10^ to 2.5x10^ copies/ml), see Section 2.3 for routine use methodology. HIV RNA levels had been measured prospectively in these patients since 1996 using the Roche Amplicor HIV-1 Monitor v.1.0 assay plus add-in non-B primers (range 4x10^ to 7.5x1 O^copies/ml) along with the ultrasensitive version of the assay (range 50 to 7.5x10"^ copies/ml Roche Diagnostic Systems, Branchburg, New Jersey, USA). Inclusion of add-in non-B primers improves the detection of non-B HIV subtypes. Additionally, HIV-1 RNA loads had also been retrospectively measured as part of a previous study (Sabin et al, 2000a). All HCV and HIV RNA loads are reported as log values. Where possible, patients from the cohort were genotyped using an RT-PCR and RFLP based assay as described in Section 2.4. Since 1982, lymphocyte subset analysis has been routinely performed on all fresh samples at the Royal Free Hospital, as described previously (Sabin et al, 2000a).

Where possible, four HCV RNA loads were measured post the estimated date of HIV seroconversion per patient in the cohort. The stored serum samples used for each patient were as close to a year apart from each other as possible, (Figure 4.1). An initial exploratory analysis of the data suggested that HCV RNA levels increased over the first three to four years after HIV infection, but stabilised after this point (Figure 4.1). Four reasons were considered to account for the increase; 1) inaccuracies in the date of estimated HIV seroconversion, 2) the presence of HIV results in increased HCV RNA replication during this period of time 3) a possible inverse correlation between progressive immunodeficiency and HCV RNA level post HIV seroconversion or 4) HCV RNA degradation in the serum samples.

140 Chapter 4: Prognostic value o f a single HCV RNA load

All loads Median

-S

>

2 3 Measurement

Figure 4.1: Median HCV RNA load for each measurement post HIV seroconversion. Median years post HIV seroconversion; Measurement 1: 2.17, Measurement 2: 3.12, Measurement 3: 4.12 and Measurement 4: 5.24.

141 Chapter 4: Prognostic value o f a single HCV RNA load

4.4.2 Sample storage assessment

All serum samples used in the study had been stored at -40°C. To exclude the latter of the above four reasons, 10 HCV positive serum samples, previously quantified in 1994 using the branched DNA (bDNA) version 2.0 assay (Bayer) were retested using the same assay. These samples had been stored at -20°C at the Royal Free Hospital Department of Medicine and ffeeze-thawed an unknown number of times and the viral loads are given in Table 4.1. The difference between the two sets of data was analysed using the Sign rank test (Section 2.7.1), and there was no significant difference between them (p=0.82).

4.4.3 Relationship between CD4 count and HCV RNA level in the four initial HCV RNA levels measured

The relationship between CD4 counts and increasing HCV RNA level during the four initial HCV RNA levels measured (Figure 4.1) was investigated to exclude the penultimate of the reasons outlined in section 4.4.1. Of the cohort, 78 patients had at least two post HIV seroconversion HCV RNA levels measured four years apart so that change could be measured over the four years. Only HCV RNA levels from patients known to be HIV positive at the time were included. The median increase over the first four years was 1.30 (range -1.88 to 4.48) logio HCV RNA copies/ml. Of the 66 patients with at least two CD4 counts measured during this period, the median change in CD4 count was -55 (range: -890 to 440) cells/mm^. The change in HCV RNA over the four year period was not correlated with either baseline CD4 count (r= -0.02, p= 0.85), CD4 count at four years post HIV seroconversion (r= 0.05, p= 0.69) or change in CD4 count (r= 0.10, p= 0.42). All tests were performed using Spearman’s rank correlation (Section 2.7.10). As there was no relationship between CD4 count and HCV RNA level, the initial increase in HCV RNA load was due to either inaccuracies in the estimated date of HIV seroconversion or the presence of HIV facilitating HCV replication by a mechanism other than immunodeficiency.

142 Chapter 4: Prognostic value of a single HCV RNA load

Sample 1994 2001 A003 3.22X10" 1.50x10" A052 1.08X10' 3.10x10" B631 2.70X10" 1.40x10" B632 7.30X10" 1.30x10' B633 2.10X10' 3.00x10' B674 9.00X10" 7.00x10" B705 5.40x10" 5.40x10" B776 6.60x10" 1.20x10" B812 2.60x10' 3.40x10' B842 4.70x10" 8.70x10"

Table 4.1: Sample storage assessment data. 10 HCV positive serum samples that had been previously quantified in 1994 on the branched DNA (bDNA) version 2.0 assay (Bayer) were requantified in 2001 using the same assay. Samples had been stored at -20°C and ffeeze-thawed an unknown number of times. There was no significant difference between the two sets of data (p=0.82 Sign rank test).

143 Chapter 4: Prognostic value of a single HCV RNA load

4.4.4 Patient samples excluded from analysis

Viral load increases stabilised four years after HIV seroconversion. Therefore, the relationship between the first HCV RNA level measured at least four years post HIV seroconversion and progression to AIDS and all cause mortality was investigated. There were insufficient clinical end points within the cohort for statistical analysis of deaths from liver disease. Of the total cohort of 111 haemophilic men, 15 (13.5%) could not be included in the analysis as they only had HCV RNA measurements within the first four years post HIV seroconversion. Therefore, the total sample analysed consisted of 96 patients (86.5%) who had an HCV RNA level measured at least four years post HIV seroconversion. The 15 excluded men were older (p=0.0006), seroconverted to HIV in later calendar periods (p=0.02), and consequently had shorter follow-up (p=0.03) than those included in the analysis (see Table 4.2). There were however, no differences in progression rates to AIDS or death and haemophilia diagnosis between the two groups.

4.4.5 Data analysis

HCV RNA levels were approximately normally distributed after log transformation. Therefore, HCV RNA levels were compared with those of different HCV genotypes using analysis of variance (ANOVA), and relationships between HCV RNA level and patient age at the time of HIV seroconversion, CD4 count and HIV RNA level (after log transformation) at the time of HCV RNA measurement were tested for significance using Pearson’s correlation coefficient, (Sections 2.7.4 and 2.7.5). CD4 counts and HIV RNA levels at the time of HCV RNA measurement were defined as those values that had been measured closest in time to the HCV RNA level and were always within a year of the HCV RNA measurement. A multivariate linear regression model was used to identify which of these factors was independently associated with the HCV RNA level, (Section 2.7.6).

In order to consider the relationship between HCV RNA level and HIV disease progression, patients were stratified into three groups according to their HCV RNA measurement (groups were identified according to the tertiles of the observed

144 Table 4.2: Comparison of the 15 haemophilic men who were excluded from the analysis because they did not have an HCV RNA level at 4 years after HIV seroconversion, and the 96 men who were included in the analysis.

Included Excluded p-value*

Number of patients 96 15

Median (range) age at the time of HIV seroconversion 20.8(1.9-62.3) 37.3 (8.9-77.8) 0.0006 (years): f Haemophilia diagnosis Severe A 86 (90.5) 13 (92.9)

Other/not known 10(9.5) 2(7.1) 0.67 Known to have developed AIDS: n (%) 52 (54.2) 6 (40.0) 0.46 I Known to have died: n (%) 57 (59.4) 12 (80.0) 0.21 I Median (range) date of HIV seroconversion: Mar 82 (Oct 79 - May 85) Feb 83 (Jan 80 - Mar 85) 0.02

Median (range) follow-up since HIV seroconversion (years): 18.3 (7.3-20.9) 16.7(12.4-20.7) 0.03 I

Obtained from Wilcoxon test (quantitative variables) or Chi-squared test (qualitative variables)

I Chapter 4: Prognostic value of a single HCV RNA load distribution). Kaplan-Meier methods (Section 2.7.7), were used to illustrate progression to AIDS and death in the three groups. Patient follow-up was defined from the time of HIV seroconversion and was right-censored on the August 2000 if the patient remained alive and AIDS free on this date. For progression to AIDS, patient follow-up was defined from the time of HIV seroconversion and was right- censored on the date of last follow-up, where a patient was known to have transferred to another clinic.

Cox proportional hazards regression models, see Section 2.7.8, were used to quantify the relationships between the HCV RNA level and progression to AIDS and death after adjusting for other important cofactors, (Tables 4.4 and 4.5). For this analysis, whilst follow-up was defined from date of seroconversion, follow-up was left truncated to take into account late entry as HIV RNA levels had been measured only four or more years post HIV seroconversion. As the Kaplan Meier curves suggested that the relationship between HCV RNA level and HIV disease progression was not linear, it was felt unreasonable to include the HCV RNA level as a continuous covariate in the Cox models, the categorical grouping was retained in this analysis for the same reason. Other variables included in the model were age of the patient at the time of HIV seroconversion, HCV genotype (la, lb, 3 or other), CD4 count and HIV RNA level at the time of HCV RNA level measurement. The latter two variables were included in the Cox proportional hazards regression model as continuous variables after taking square root (CD4 count) and logio (HCV and HIV RNA) transformations. These analyses were also adjusted for calendar year as a time updated covariate (<1992 [no/monotherapy], 1992-1995 [dual NRTIs],>1996 [HAART]) to allow for the gradual introduction of antiretroviral therapy over time. All analyses were performed using the statistical software package SAS (SAS Institute Inc, 2001).

146 Chapter 4: Prognostic value of a single HCV RNA load

Table 4.3: Laboratory values of patients at time of first sample - all values shown are median (range), unless otherwise stated

Number of patients 96

Date of sample used for HCV RNA measurement Nov 86 Feb 84 - July 90

Time since HIV seroconversion (years) 4.7 4.1 -6.7

HCV RNA level (logio(copies/ml)) 6.5 4.0 - 8.5

Age at HIV seroconversion 20.8 1.9-62.3

CD4 count (cells/mm^)* 480 10-1770

HIV RNA level (logio copies/ml)** :L88 2.60 - 5.82

HCV genotype: n (%) la 32 (33.3) lb, lab 22 (22.9) 2 15 (15.6) 3 20 (20.8) 4 4 04 2) Unclassified 3 (3.1)***

* Based on 93 patients with a CD4 count measured within one year before or after the HCV RNA measurement

** Based on 89 patients with an HIV RNA level measured within one year before or after the HCV RNA measurement.

*** The HCV genotype of these patients was not determined by sequencing as all serum samples tested from them were negative for HCV RNA.

147 Table 4.4: Results from univariate and multivariate analyses of progression to AIDS.

Univariate Multivariate

RH 95% Cl p-value RH 95% Cl p-value

HCV RNA: <5.90 logio(copies/ml) 1 - - 1 - - >5 .90, <6.86 logio(copies/ml) 1.91 0.94-3.89 0.07 2.39 1.07-5.33 0.03 >6.86 logio(copies/ml) 1.49 0.70-3.18 0.31 1.33 0.58-3.05 0.50

Calendar year: <1992 1 - - 1 -- 1992-1996 0.70 0.23-2.14 0.54 0.58 0.19-1.75 0.33 -1^ 00 >1997 0.38 0.06-2.56 0.32 0.30 0.04-1.99 0.21 I Age (per 10 years): 1.39 1.12-1.72 0.003 1.06 0.81-1.40 0.66 I HCV Genotype: la 1 - - --- lb 0.64 0.29-1.40 0.27 --- n g 3 0.66 0.30-1.44 0.29 --- r Other/don’t know 0.67 0.30-1.49 0.32 - - -

CD4 count (per Vigo cells higher): 0.89 0.85-0.94 0,0001 0.91 0.86-0.96 0.0005 I

HIV RNA (per logio higher): 2.79 1.89-4.11 0.0001 2.28 1.42-3.67 0.0007

I Table 4.5: Results from univariate and multivariate analyses of progression to death.

Univariate Multivariate

RH 95% Cl p-value RH 95% Cl p-value

HCV RNA <5.90 logio(copies/ml) 1 - - 1 -- >5.90, <6.86 logio(copies/ml) 1.56 0.79-3.11 0.20 2.16 0.96-4.82 0.06 >6.86 logio(copies/ml) 2.07 1.06-4.04 0.03 2.03 0.96-4.27 0.06

Calendar year <1992 1 - - 1 - - 1992-1996 0.39 0.14-1.10 0.07 0.23 0.08-0.67 0.007 0.09 0.02-0.51 0.006 -F^ >1997 0.47 0.09-2.31 0.35 VO I Age (per 10 years) 1.69 1.40-2.05 0.0001 1.61 1.26-2.07 0.0002 HCV Genotype: la 1 - - --- Î lb 0.52 0.25-1.06 0.07 - - - 3 0.59 0.30-1.19 0.14 - - - I Other/don’t know 0.42 0.19-0.94 0.04 - - - $ CD4 (per V100 cells higher): 0.90 0.86-0.94 0.0001 0.91 0.87-0.96 0.0005 I HIV RNA (per logio higher): 2.97 2.04-4.34 0.0001 2.20 1.38-3.50 0.0009

I Chapter 4: Prognostic value o f a single HCV RNA load

4.4.6 Relationship of HCV RNA level with HCV genotype and stratification of HCV RNA loads

The laboratory values of the 96 patients included in the study are shown in Table 4.3. There was a positive correlation between HCV RNA level and patient age at HIV seroconverison (r=0.25, p=0.01). Additionally, there was also a significant difference between HCV RNA levels in patients with different HCV genotypes (p=0.01, ANOVA), (Figure 4.2), with those with genotype la having the highest HCV RNA levels and those with genotypes 2 or 4 (the ‘other’ group) the lowest values. However, there was no significant correlation between the HCV RNA level and either the CD4 count (r=0.17, p=0.11) or the HIV RNA level (r=0.15, p-0.16) measured at the same time. Multivariate linear regression analysis suggested that the effects of HCV genotype and age at HIV seroconversion were independent. Thus, the HCV RNA level was O.OBlogio copies/ml higher for each additional year of age (p=0.004) and compared to those with genotype la, was 0.341ogio copies/ml lower (p=0.32) in those with genotype lb/lab, 0.861ogio copies/ml lower in those with genotype 3 (p=0.01) and 1.01 logio copies/ml lower in those with other genotypes (p=0.005). Figure 4.2.

The cut off date for analysis was the end of August 2000 and by this point, 52 (54.2%) of the 96 patients had developed ADDS and 57 (59.4%) had died. The patients were stratified into three groups according to the tertiles of the observed distribution of HCV RNA levels. Therefore, 32 patients (33.3%) had HCV RNA levels < 5.90 logic copies/ml (low HCV RNA), 33 patients (34.4%) had HCV RNA levels from > 5.90 to 6.86 logic copies/ml (moderate HCV RNA) and 31 patients (32.2%) had HCV RNA levels of >6.86 logic copies/ml (high HCV RNA). Kaplan- Meier analyses (Figures 4.3 and 4.4) suggested that there was a relationship between initial HCV RNA level and both progression to AIDS and all cause mortality. In particular, 15 years after HIV seroconversion, 40.2%, 61.9% and 55.3% of those with low, moderate and high HCV RNA levels had progressed to AIDS (p=0.13, log rank test. Figure 4.3) whereas 37.5%, 47.0% and 61.3% had died by the same time timepoint, respectively (p=0.08, log rank test), (Figure 4.4 and Section 2.7.9).

150 Chapter 4: Prognostic value of a single HCV RNA load

10

6X) 8 - O <

> u X

la lb, lalb Other

Figure 4.2: Relationship between first HCV RNA level at least four years post HIV seroconversion and HCV genotype- bars indicate median value

151 Chapter 4: Prognostic value of a single HCV RNA load

Figure 4.3: Kaplan-Meier plot showing relationship between HCV RNA level measured approximately 4 years post HIV seroconversion and progression to AIDS

o 100 1

80 - CQ .O & 60 c/) ^ 40 - <

3 20 - E 5 u 0 5 10 15 Years after HIV seroconversion

— Low HCV RNA — Moderate HCV RNA — High HCV RNA

152 Chapter 4: Prognostic value of a single HCV RNA load

Figure 4.4: Kaplan-Meier plot showing relationship between HCV RNA level measured approximately four years post HIV seroconversion and progression to all-cause mortality.

100 1

80 - o 6 60 a. Æ > I 40 -

E 20 -

0 5 10 15 Years after HIV seroconversion

— Low HCV RNA — Moderate HCV RNA — High HCV RNA

153 Chapter 4: Prognostic value o f a single HCV RNA load

4.4.7 The prognostic value of HCV RNA level for AIDS and death

Results from Cox proportional hazards regression models (Tables 4.4 and 4.5) confirmed that there was an increased hazard of AIDS and death in those with HCV RNA levels greater than 5.90 logio Eq/ml. Additionally and as expected, those with higher HIV RNA levels and lower CD4 counts at baseline also experienced faster progression to AIDS as well as shorter survival. There was no significant relationship between the HCV genotype and progression to either end point in this cohort of patients, although those with genotype la did progress more rapidly to each end point than those with other genotypes. After adjusting for the patient age, CD4 count, HIV RNA level (all as fixed covariates) and calendar year (as a time updated covariate), the effect of the initial HCV RNA level remained associated with both end points. Those with HCV RNA levels above 6.86 logio gEq/ml had a 139% increase in the hazard of AIDS (p=0.03) and 116% increase in the hazard of death (p=0.06). The CD4 count and HIV RNA level remained significantly associated with both end points in the multivariate analysis.

154 Chapter 4: Prognostic value o f a single HCV RNA load

4.5 Discussion

In this study, the prognostic value of a single HCV RNA level measured retrospectively early after HIV seroconversion has been investigated using a cohort of 96 patients with previously estimated dates of HIV seroconversion (Lee et al, 1989). The point at which year-on-year elevation of HCV RNA becomes non-significant in this cohort was four years after HIV seroconversion. The results show that a single HCV RNA load measured at this point is predictive of clinical progression to AIDS and all cause mortality over a period of at least 15 years. There was a correlation between age at HIV seroconversion and HCV RNA load (r=0.25, p=0.01) that had been previously reported (Goedert et al, 2001;Thomas et al, 2000) and therefore, all analyses have controlled for age. In multivariate analysis, patients with moderate level HCV RNA loads (5.90-6.861ogio copies/ml) progressed significantly faster to AIDS than those in the low tertile (RH=2.39, 95%CI 1.07-533 p=0.03). A surprising result was that there was no significant relationship between the upper HCV RNA load tertile and progression to AIDS and this requires further investigation. However, the greatest reduction in relative hazard for the high viral load category occurred when adjusting for changing CD4 counts rather than HIV RNA levels, whereas there were comparable reductions in relative hazard for progression to AIDS in patients with moderate HCV RNA levels, (Table 4.4). This data implies that there may be substantial differences in the level of immunodeficiency between these two groups; an issue that requires further investigation.

The predictive value of a single HCV RNA level for progression to death was also investigated. In this analysis, similar relative hazards for the moderate and high HCV RNA load tertiles were observed. These were of borderline significance (p=0.06 for both tertiles). As these analyses were performed after controlling for HIV RNA load, the results are not just due to a correlation between HIV and HCV RNA loads. The data implies that sustained HCV replication early after HIV infection is a risk factor for death. When patients were stratified according to HCV genotype, it was found that patients infected with genotype 1 a also progressed more rapidly to death (Table 4.5). This probably reflects the poor response of genotype la to interferon therapy

155 Chapter 4: Prognostic value of a single HCV RNA load

(Bell et al, 1997) but also confirms previous findings that associated genotype la with accelerated disease progression in HIV co-infected patients (Sabin et al, 1997).

It has been shown in many studies that the presence of HIV increases the severity of HCV related disease, elevates HCV RNA load and accelerates liver fibrosis (Eyster et al, 1993;Eyster et al, 1994;Puoti et al, 2001). Additionally, co-infection with HCV in HIV infected individuals has been associated with increased morbidity, mortality and impairment of CD4+ T cell recovery on HAART (Greub et al, 2000;Torres et al, 2000) although other studies have observed no such effects ( Quan et al, 1993; Wright et al, 1994;Staples et al, 1999). Recent prospective longitudinal studies have also shown an association between HCV RNA load and progression to AIDS as well as response to HAART (Greub et al, 2000;Daar et al, 2001b). The results of this chapter confirm and extend these studies since the mean follow-up in this study was 15 years and the former studies had substantially lower mean follow-up periods (28 months and 7 years respectively). Additionally, associations between HCV RNA load and progression to AIDS and death did not appear until the ninth or twelfth year respectively post HIV seroconversion, (Figures 4.3 and 4.4). They would therefore have been missed in a study with shorter follow-up.

To conclude, the analysis in this chapter shows that elevated HCV RNA levels measured four years after HIV seroconversion (the point at which year-on-year elevation of HCV RNA becomes non-significant in this cohort) are associated with an increased risk of AIDS and death, independent of other factors. However, further long-term follow up of intensively studied cohorts is needed in order to determine whether there is also an association between high levels of HCV RNA early in infection and liver related death. Despite the well known fact that both CD4 counts and HIV RNA level are closely associated with progression to AIDS and death, (Tables 4.4 and 4.5), this is the first study to show that HCV RNA level is also associated with those clinical end-points. Although the association is not as strong as for CD4 counts and HIV RNA, these results nevertheless suggest that treatment of HCV early in infection may be of benefit to HIV and HCV co-infected individuals.

156 Chapter 5: Effect of HAART on anti-HCV humoral immunity

Chapter Five

The effect of HAART on HCV specific

humoral immunity

157 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.1 Introduction

The results obtained in Chapter Four suggested that there might be a link between immunodeficiency in an HIV and HCV co-infected patient, and HCV RNA load. Previous studies have suggested that antigenic stimulation by HCV is a determinant of HCV specific antibody titres (Simon et al, 1994; Osella et al, 1997;Kondili et al, 2002). Therefore a positive correlation is expected to be seen between antigen (or HCV RNA) and antibody titre. Antibody aids in the clearance of virus so it is also possible that an inverse correlation could exist between itself and HCV RNA although this has not been observed so far in HCV. However, the aformentioned studies were performed in immune competent populations, and did not examine this relationship specifically in immunodeficient patients, where inadequate T-cell function may affect the function of different arms of the immune response. In this Chapter, immunofluorescence assays to determine HCV specific antibody titres were developed and used alongside the QC RT-PCR assay developed in Chapter Three to determine whether the immune state of an individual affects the relationship between HCV specific antibody titre and HCV RNA level.

HAART has been shown to greatly improve prognosis in HIV infection (Lipsky, 1996Hammer et al, 1997;), but the effect of HAART, if any on HCV disease remains controversial. Most studies have found that HAART has no effect on HCV RNA load (Hammer et al, 1997; Garcia-Samaniego et al, 1998; Rutschmann et al, 1998; Zylberberg & Pol, 1998;Matsiota-Bemard et al, 2001), although there have been reports of elevations (Ragni & Bontempo, 1999), reductions (Perez-Olmeda et al, 2000;Yokozaki et al, 2000) and even clearances of detectable HCV RNA post HAART (Fialaire et al, 1999;Yokozaki et al, 2000). Additionally, the question of whether HAART affects HCV specific immune responses in general remains controversial (Valdez et al, 2000;Yokozaki et al, 2000).

Cellular immune responses are important in the control of HCV infection. A strong, multispecific and long lasting CD4+ T helper cell response is associated with resolution of acute infection (Diepolder et al, 1995;Gerlach et al, 1999; Rosen et al, 1999;Harcourt et al, 2001) and CD4+ T helper cells play a role in both controlling

158 Chapter 5: Effect of HAART on anti-HCV humoral immunity disease and pathogenesis during chronic infection (Gerlach et a f 1999;Eckels et al, 2000;Takaki et al, 2000; Chang et al, 2001; Klenerman et al, 2002). A strong multispecific CD8+ cytotoxic T lymphocyte (CTL) response is also associated with resolution of acute infection (Lechner et al, 2000a;Lechner et al, 2000b; Takaki et al, 2000;Chang et al, 2001) and CTL are probably responsible for both clearance of virus and liver damage during chronic infection ( Ballardini et al, 1995;Napoli et al, 1996). The interaction of both cellular and humoral responses to HCV is likely to be important in disease outcome (Klenerman et al, 2000), although less is known about the role of humoral immunity in HCV and different studies have given apparently conflicting results. During acute infection with HCV, high titres of antibodies that inhibit the binding of HCV envelope glycoprotein-2 (E2) to human cells have been correlated with resolution of infection (Ishii et al, 1998). In contrast, patients who cleared HCV during acute infection had transient and weak antibody responses directed against HCV-like particles although patients with high titres of these antibodies were significantly more likely to respond to interferon monotherapy (Baumert et al, 2000). During acute infection, variation in the hypervariable region-1 (HVR-1) of E2 is associated with viral escape and progression to chronicity (Farci et al, 2000). Additionally, reduced HVR-1 variability is associated with more severe disease during chronic infection (Curran et al, 2002). Chronic infection is characterised by elevated antibody titre (Baumert et al, 2000) and over time, antibody becomes undetectable in between 2% and 20% of patients (depending on the study), usually correlating with the disappearance of HCV viraemia. This suggests that the anti-HCV humoral response requires antigenic stimulation in order to be maintained (Simon et al, 1994; Osella et al, 1997;Seeff et al, 2001;Kondili et al, 2002). Other components of the immune system such as natural-killer cells and gammadelta T cells also play a role in disease progression and outcome (Guidotti et al, 1999;Agrati et al, 2001;Tseng & Klimpel, 2002) as do other factors such as age at HIV seroconversion, HCV genotype, alcohol intake and racial background (Eyster et al, 1993; Reddy et al, 1999;Sabin et al, 2000b; Yee et al, 2000).

In this study, I have investigated HCV specific antibody responses in an immunodeficient and immune competent setting, by determining the effect of HAART on HCV specific antibody titre, HCV RNA level and the relationship between the two parameters in a cohort of 24 patients with haemophilia. The

159 Chapter 5: Effect of HAART on anti-HCV humoral immunity relationship between HIV RNA load and anti-HIV env antibody titre was also examined in the above cohort. The effect of successful pegylated interferon and ribavirin combination therapy for HCV on both HCV specific antibody titre and on the relationship between antibody titre and HCV RNA level was also investigated in a cohort of 11 HCV positive without HIV.

160 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.2 Materials and Methods

Detailed descriptions of the methodology used in this chapter are given in Chapter 2, Section 2.5 for the immunofluorescence assays to determine antibody titre and Section 2.7 for the methods used in the statistical analysis.

5.3 Immunofluorescence assays for determining antibody titres to baculovirus expressed virus derived proteins

An immunofluorescence assay to determine levels of anti-HIV env antibodies was already in use in our department (Deayton et al, 2003) and this methodology was used for these assays, see Section 2.5.7. Accordingly, the remainder of this section will describe the production of a high titre stock of the HCV FL and HCV E1E2 baculoviruses and determination of their optimum time for protein expression in Sf-21 insect cells. The FL baculovirus produced all 10 HCV proteins and the E1E2 baculovirus produced GST fusions of the immunodominant envelope glycoproteins of HCV, El and E2. Titres to FL proteins were considered indicative of total anti-HCV antibody titre and titres to E1E2, a measure of immunodominant HCV envelope glycoprotein antibody titre.

5.3.1 Introduction to baculovirus protein expression

Baculovirus expression vectors are often used as expression systems because of their ability to produce large quantities of protein. Baculoviruses are multiple nuclear polyhedrosis viruses (MNPV) of which the prototype virus is autographa califomica MNPV (AcMNPV). AcMNPV naturally infects the alfalfa looper, and this infection is characterised by the formation of large intranuclear occlusions in infected cells called polyhedra derived virus (PDV) consisting largely of a single polyhedrin protein of 29 kDa. When an infected insect dies, decomposition releases thousands of PDVs that protect virions from external factors such as desiccation. Insect larvae then feed on infected vegetation, the PDVs dissolve in the midgut and extracellular AcMNPV infection becomes disseminated throughout the larva.

161 Chapter 5: Effect of HAART on anti-HCV humoral immunity

Polyhedrin protein accounts for 30 to 50% of total cell protein, but is not needed in insect cell culture, allowing for the development of an expression system that replaces the polyhedrin ORF with a foreign ORF (i.e. HCV E1E2). The polyhedrin promoter should theoretically express foreign proteins at the same level as polyhedrin and expression levels are often very high, although they vary depending on the nature of the inserted protein and translatability of its mRNA. AcMNPV plO protein, gp64, 39 kDa and basic protein promoters have also all been exploited for foreign gene expression (Ansari & Emery, 1998). In this chapter, all baculovirus constructs used contained HIV or HCV derived proteins cloned downstream of the polyhedrin promoter.

5.3.2 Generation of high titre stocks of FL and E1E2 baculovirus constructs and determination of optimal time point for protein expression in Sf-21 cells

High titre stocks of the FL and E1E2 baculoviruses were generated from the original virus stocks (a gift from Professor I.M. Jones) and virus titre (in pfu/ml) determined by plaque assay, (see Sections 2.5.1 to 2.5.3 and Figure 2.5) (Moore et a f 1990;Chan- Fook et a f 2000). The final stocks, which were sufficient for completion of this project, consisted of 22ml of FL baculovirus at 2x10^ pfu/ml and 22ml of E1E2 baculovirus at 2.25x10^ pfu/ml. The HIV env baculovirus stock was used directly from a pre-existing stock at 7x10^ pfu/ml.

In order to determine the time point for optimal protein expression, a time course was set up for both FL and E1E2 at a moi (multiplicity of infection) of 1, 5 and 10 for 24, 48, 72 and 96 hours (see Section 2.5.4). Western blotting revealed the optimal moi and time of expression for each baculovirus construct to be a moi of 5 for 48h for both FL and E1E2 constructs (see Sections 2.5.5, 2.5.6 and Figure 2.7). This agrees both with previously published data for proteins expressed under the control of the AcMNPV polyhedrin promoter and with the HIV env baculovirus construct (Moore et al, 1990;Whitefieet-Smith et al, 1989;Ansari & Emery, 1998).

162 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.3.3 Assessment of protein expression by western blot

The primary antibody used in the western blot (see Figure 2.7) was a 1:100 dilution of serum from four patients with known high titres of anti-HCV antibody (a gift from the Virology Department Diagnostic Virology section), which only revealed one distinct band for each construct. The experiment was repeated using 48h infections at an moi of 5 for each construct and a 1:10 dilution of the combined patient serum as the primary antibody in the western blot to improve expressed protein detection. These blots revealed three distinct bands for both the FL and E1E2 baculovirus constructs despite the high background, showing that both constructs were successfully expressing all required proteins, see Figure 5.1 and Table 5.1.

Table 5.1: Western blot band sizes and HCV proteins expressed from the FL and E1E2 baculovirus constructs.

FL band size (KDa) HCV protein 70 NS5B (68-70 KDa) NS3 (70-72 KDa) E2 (61-72 KDa) 50 NS5a (56-58 KDa) 22 C (21-22 KDa) NS4B (27 KDa) NS2 (21-23 KDa) 10 NS4A (4-10 KDa ) NS2 fragment (7 KDa) E1E2 band size (KDa) 110 GST fusion of E2 (61-72 KDa) 90 GST fusion of El (31-37 KDa) 70 E2 (61-72 KDa)

163 Chapter 5: Effect of HAART on anti-HCV humoral immunity

FL construct E1E2 construct / \ / \ 24 48 72 96 24 48 72 96 Rainbow markers 1 2 3 4 5 6 7 8 9. (kDa) Blue: 220 Brown: 97 ■ ^ 7"' 110kDa(ElE2)

90 kDa (E1E2) ■f # Red: 66 ■f 1 70 kDa (FL-E1E2)

Yellow: 45 50 kDa (FL) Orange: 30

Blue: 20.1 22 kDa (FL) Magenta: 14.3 10 kDa (FL)

Figure 5.1: 10% bis-tris NuPAGe gel and western blot of 24, 48, 72 and 96 hour time points of protein expression for the FL and E1E2 baculovirus constructs. A 1:10 dilution of anti-HCV antibody positive serum from four separate patients was used as the primary antibody.

164 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.4 Patients studied

5.4.1 Study population

The subjects were 24 men with inherited bleeding disorders registered at the Royal Free Hospital Haemophilia Centre, and patients from this cohort have been described previously (Lee et a f 1989;Sabin et al, 2000b; Yee et al, 2000) and in Chapter 4. This cohort consisted of all the patients from the Royal Free Haemophilia Centre that had been treated with HAART and had one serum sample pre and post therapy stored in the Haemophilia Centre serum sample store. The 24 men that comprised the cohort were infected with both HIV and HCV following treatment with unsterilised clotting factor concentrates prior to the introduction of heat sterilisation of blood products in 1985. They were seen at the Centre at least every three months at which time they underwent a clinical and laboratory review; serum samples from these patients were regularly taken and stored for future use. All patients had been infected with HCV either prior to or at the same time as HIV.

The 10 control serum samples of patients that achieved a sustained viral response after pegylated interferon and ribavirin therapy for HCV were taken from the Royal Free Hospital Virology Department temporary serum sample store. These patients were registered at both the Royal Free Hospital Haemophilia and Haemostasis Centre and Centre for Hepatology. Five of the patients had inherited bleeding disorders, five did not and all were HIV negative. One sample pre and post-successful therapy as close to a year apart as possible was obtained for each of the patients in this group.

5.4.2 HIV and HCV therapy

Patients were treated according to guidelines in place at the time (1992). Since the end of 1995, patients with low CD4 counts have been offered HAART regimens including at least one NNRTI or PI. Pis are used with caution in these patients because of the possibility of liver complications in patients with HCV and spontaneous bleeding episodes in people with haemophilia (Ginsburg et al, 1997;Yee et al, 1997). Patients with CD4 counts of <200x10^ cells/L have been offered prophylaxis against Pneumocystis carinii pneumonia (PCP) and Candida spp since

165 Chapter 5: Effect of HAART on anti-HCV humoral immunity

1988 and patients whose CD4 counts fell to <50x10^ cells/L have been offered prophylaxis against Mycobacterium avium since 1991. Immune reconstitution as a result of HAART therapy has now resulted in less need for prophylaxis and this is now stopped when a patient reaches a CD4 count of over 200 cells/mm^ whilst on HAART. HAART was offered according to the guidelines in place at the time (2001), currently when the CD4 count falls below 300 cells/mm^. Antiviral therapy for HCV was administered to none of the 24 patients in the cohort.

166 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.5 Results

5.5.1 Measurement of HIV and HCV RNA loads

HCV RNA levels in this cohort were measured retrospectively on serum samples that had been stored at -40°C. The effect of serum sample storage had been previously assessed and storage at -20°C for up to eight years does not significantly affect resultant HCV RNA load (see Section 4.4.2). HCV RNA levels in the cohort of 24 HAART treated men with haemophilia were measured using the in-house quantitative-competitive RT-PCR assay (range IxlO"^ to 2.5x10^ copies/ml) developed in Chapter 3. HCV RNA levels in the control group of 11 responders to HCV therapy were measured using the branched DNA (bDNA) version 2.0 assay (Bayer) (range 2x10^ to 1.2x10^ genome Eq/ml). HIV RNA levels were measured using the Roche Amplicor HIV-1 Monitor vl.O assay plus add-in non-B primers (range 4x10^ to 7.5x10^ copies/ml; Roche Diagnostic Systems, Branchburg, New Jersey, USA) or the ultrasensitive version of the assay (range 50 to 75000 copies/ml). HIV RNA loads have been measured prospectively since 1996 using the standard assay or the ultrasensitive assay post HAART when this was available. Dr D.Pillay at the University of Birmingham Medical School quantified all cohort serum samples that had not already been routinely quantified for HIV RNA. All HCV and HIV RNA loads are reported as log values.

5.5.2 Measurement of anti-HCV FL/E1E2 and anti HIV env antibodies

Antibody titres were measured using the immunofluorescence assay described in Section 2.5.7. Antibody titres to HCV FL, HCV E1E2 and HIV env proteins were measured for all available serum samples from the 24 patients in the principal cohort and only titres to HCV FL and HCV E1E2 were measured in the control group, as only one patient in the group was HIV positive.

167 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.5.3 Data analysis

As HCV specific antibody titres decline after clearance of HCV RNA (Simon et al, 1994;Osella et al, 1997;Seeff et al, 2001;Kondili et al, 2002), it was decided to exclude two patients from the HIV positive HAART treated cohort on the basis of persistent HCV RNA negativity. These two patients were excluded only from analysis of HCV specific parameters.

After log transformation, antibody titres and viral loads were approximately normally distributed; therefore a paired t-test was used to compare antibody titres and viral loads pre and post therapy in both the HIV positive and HIV negative groups. Where data had not been log transformed, the Wilcoxon signed ranks test was used to compare values pre and post therapy, (see Section 2.7.2). Relationships between antibody titres, viral loads, liver function tests and CD4 counts (after log transformation) were tested for significance using Pearson’s correlation coefficient, (see Section 2.7.5). CD4 counts, ALT and AST levels where available, were measured on samples obtained at the same date as those used for determination of antibody titres and viral loads.

5.5.4 Effect of HAART on HCV and HIV RNA level and antibody titre

Table 5.2 shows a summary of the data before and after HAART. There was no effect of HAART on HCV RNA level (p= 0.92) in this cohort of patients, see Figure 5.2a. However, HAART was successful in reducing HIV RNA load in this cohort to undetectable levels in most cases (p= 0.003) see Figure 5.2b. The cut-off value for HIV RNA loads was adjusted to 400 copies/ml for all samples regardless of the sensitivity of the assay used (400 or 50 copies/ml).

Anti-HCV FL and E1E2 titres were highly correlated (R= 0.89 p= <0.0001) see Figure 5.3. HAART did not significantly affect anti-HCV E1E2 antibody titres (p= 0.23), but did result in a small but significant increase in anti-HCV FL antibody titres (p= 0.02) see Figure 5.4. Anti-HIV env antibody titres decreased significantly post HAART (p= 0.003) see Figure 5.5.

168 Table 5.2: Summary of data values, before and after HAART, and changes during treatment

Pre-HAART Post-HAART Difference p-value for (pre-post) difference^ HIV RNA (logio) n 24 23 23 Mean (SD) 4.34(1.29) 2.94(1.28) 1.40(1.59) 0.0003'" HCV RNA (logic) n 22 22 22 Mean (SD) 7.39(1.21) 7.41 (1.16) -0.02 (0.83) 0.92+ AST n 13 8 5 Median (range) 45 (16, 80) 40.5 (18, 137) 2 (-30, 19) 1.00* ALT n 13 8 5 Median (range) 44(33, 126) 31.5 (16, 236) 14 (-52, 17) 0.63* o\ Anti-HIV env (In) n 24 24 24 I Mean (SD) 8.91 (0.84) 8.40 (0.89) 0.52 (0.42) o.ooor Anti-HCV FL (In) n 21 21 21 I Mean (SD) 8.41 (1.29) 8.84(1.17) -0.43 (0.74) 0.02+ Anti-HCV E1E2 (In) n 21 21 21 I>3 Mean (SD) 6.79(1.33) 6.99(1.05) -0.20 (0.73) 0.23+ § CD4 (square root) n 24 20 20 Mean (SD) 0.14 (0.12) 0.17(0.12) -0.05 (0.11) 0.09+ '^Obtained from Wilcoxon signed ranks test (*non-parametric) or paired t-test Cparametric), as appropriate. I I Chapter 5: Effect of HAART on anti-HCV humoral immunity

ion

S Paired t-test cx o p= 0.92 o n= 22 -o O 8- < - Z 7.39 7.41 : - u z o o0Û 6 -

pre HAART post HAART

Figure 5.2a: Antiretroviral therapy for HIV has no effect on HCV RNA load. Green diamonds indicate mean HCV RNA loads pre- and post-therapy. 7-1 Paired t-test p= 0.0003 .1 &J n=23 '5. O g s- < z 4- > X 3- 3.48

pre HAART post HAART

Figure 5.2b: Significant decrease in HIV RNA load observed as a result of successful

antiretroviral therapy. Green diamonds indicate mean HIV RNA loads pre- and post­

therapy.

170 Chapter 5: Effect of HAART on anti-HCV humoral immunity

9 - c

ë f Î Pearson correlation R= 0.89 p=<0.0001 n= 42

5 6 7 8 9 10 11 12 anti-HCV FL antibody titre (1/ln)

Figure 5.3: Correlation between anti-HCV FL and anti-HCV E1E2 antibody titres.

171 Chapter 5: Effect of HAART on anti-HCV humoral immunity

9-1 Paired t-test c p= 0.23 21

I 6.99 6.79

6 - W

5-

pre HAART post HAART

11 -1

1 0 -

9- T3O 8.84 03C 8.41 8- Paired t-test p= 0.02 n= 21 7-

TT pre HAART post HAART

Figure 5.4: Antiretroviral therapy has no effect on anti-ElE2 (top panel) but results in a significant increase in anti-FL antibody titres (lower panel).

Green diamonds represent mean antibody titres pre- and post-therapy.

172 Chapter 5: Effect o f HAART on anti-HCV humoral immunity

11 n Paired t-test I,.. p= 0.0001 s n= 23 % 94 "E 8.40 I 8- > § I

6 -

pre HAART post HAART

Figure 5.5: Antiretroviral therapy for HIV significantly decreases anti-HIV env antibody titres. Green diamonds represent mean antibody titres pre- and post­ therapy.

173 Chapter 5: Ejfect of HAART on anti-HCV humoral immunity

5.5.5 Relationships between anti-HCV antibody titres and HCV RNA loads in the cohort of HAART treated patients

Overall, taking into account all samples both pre and post HAART, no significant relationship between HCV RNA load and either anti-HCV FL or anti-HCV E1E2 antibody titres was observed (R= -0.12, p= 0,45 and R= -0.24, p= 0.12 respectively) (Table 5.3).

It was then decided to investigate the correlation between anti-HCV antibody titre and HCV RNA separately pre and post HAART. A significant inverse correlation between anti-HCV FL and HCV RNA level pre HAART was observed, which disappeared or was obscured post therapy (R= -0.42, p= 0.05 and R= 0.24, p= 0.30 respectively) (Figure 5.6). In addition, a significant inverse correlation was observed between anti-HCV E1E2 antibody titre and HCV RNA level that also disappeared or was obscured post therapy (R= -0.54, p= 0.01 and R= 0.16, p= 0.50 respectively) (Figure 5.7 and Table 5.3).

5.5.6 Relationships between anti-HIV env antibody titres and HIV RNA loads in the cohort of 23 HAART treated patients

As a control, the correlation between anti-HIV env and HIV RNA level was also investigated in this group. A trend towards a positive correlation was observed overall between anti-HIV env antibody titre and HIV RNA load (R= 0.26, p= 0.07). This is probably due to the decrease in HIV RNA load post HAART and resultant decrease in anti-HIV env titre as a result of reduced antigenic stimulation; (Figures 5.5 and 5.8). There was however, no correlation between anti-HIV env and HIV RNA pre HAART (R= 0.27, p= 0.20), (Figure 5.8). The relationship post HAART was not investigated as the majority of patients in the cohort had undetectable HIV RNA levels.

174 Chapter 5: Effect of HAART on anti-HCV humoral immunity

A: Pre HAART

Pearson correlation 1 0 - R= -0.42 c p= 0.05 n= 22 ë I § -J > UX I

5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0

B: Post HAART HCV RNA (gEq/ml)

10 - c

ë 1 Pearson correlation R= 0.24 p= 0.30 u- m > n= 22 UX

5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 HCV RNA (gEq/ml)

Figure 5.6: Relationship between anti-HCV FL antibody titre and HCV RNA load

pre- and post- HAART. An inverse correlation of borderline significance disappears

post-therapy.

175 Chapter 5: Effect of HAARTon anti-HCVhumoral immunity

A: Pre HAART

9

8

(D 7

? "c CD 6 CN Pearson correlation LU R= -0.54 LU p= 0.01 c 5 CD n= 22

4 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 HCV RNA (gEq/ml) B: Post HAART 9.0-,

8.5 —

c i . O -

I 7.5-

.c 7.0- I ■ a 65- w Pearson correlation > 6.0 - U R=0.16 3: p= 0.50 6 5.5- n= 22 i . 5.0-

5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 HCV RNA (gEq/ml)

Figure 5.7: Relationship between anti-HCV E1E2 antibody titre and HCV RNA load

pre- and post- HAART. A significant inverse correlation pre-HAART disappears post

therapy.

176 Chapter 5: Effect o f HAART on anti-HCV humoral immunity

A: Overall

Pearson correlation R= 0.26 p=0.07 10 - n—23 c

I c > g > E

1 2 3 4 5 6 7 B: Pre HAART HIV RNA load (gEq/ml) Pearson correlation R= 0.27 10.5- p=0.20 n= 23 c

10.0 -

% 9 .5 - I ■ g 9.0 - > g > 8 .5 - 3:

8 .0 -

7.5 2 3 4 5 6 71 HIV RNA load (gEq/ml)

Figure 5.8: Trend towards a positive correlation in the top panel due to decrease in HIV RNA level and anti-HIV env antibody titres post HAART. There is no significant

relationship between the two parameters pre-HAART (bottom panel).

177 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.5.7 Effect of successful pegylated interferon and ribavirin combination therapy for HCV on anti-HCV antibody titres and RNA load

In this cohort of patients, treatment with pegylated interferon and ribavirin resulted in undetectable HCV RNA post therapy as well as consequent significant decreases in anti-HCV FL and anti-HCV E1E2 antibody titres (p= 0.008 and p= <0.0001 respectively) (Figure 5.9 and Table 5.4).

5.5.8 Relationship between anti-HCV antibodies and HCV RNA load in a cohort of patients treated with pegylated interferon and ribavirin combination therapy

In this setting, there was a positive correlation of borderline significance between anti-HCV E1E2 antibody titre and HCV RNA load pre therapy (R=0.60, p=0.06) (Table 5.5). However, there was no relationship between anti-FL antibody titre and HCV RNA load in this cohort (R=0.21, p=0.56). All these patients became HCV negative by RT-PCR post therapy, so the relationship between anti-HCV antibody titre and HCV RNA post therapy was not examined.

178 Chapter 5: Effect of HAART on anti-HCV humoral immunity

12-1

Paired t-test p= 0.008 1 N= 10 10.34 10- 9.65 c 03 9- -J

8 -

T pre IFN therapy post IFN therapy

10 n

Paired t-test p= <0.0001 N = 10 8.47 8- % 7.58 cQC CN 7- w 5

03

pre IFN therapy post IFN therapy

Figure 5.9: Significant decreases in both anti-HCV FL (upper panel) and anti-HCV E1E2 antibody titres (lower panel) after successful interferon and ribavirin combination therapy for HCV. Green diamonds represent mean antibody titres pre- and post-therapy.

179 Chapter 5: Effect of HAART on anti-HCV humoral immunity

Table 5.3: Correlations between all measured parameters in the HAART treated cohort. Correlations (r, p-value) between variables measured using Pearson correlation on transformed data.

Correlation between: Overall Before HAART After HAART Anti-HCV FL (In) Anti-HCV E1E2 (In) 0.89 (0.0001) 0.88 (0.0001) 0.90 (0.0001) Anti-HIV env (In) 0.02 (0.89) 0.09 (0.71) 0.06 (0.80 HIV RNA (logic) -0.26 (0.10) -0.25 (0.28) -0.16(0.50) HCV RNA (logic) -0.12 (0.45) -0.42 (0.05) 0.24 (0.30) CD4 (square root) 0.06 (0.71) -0.007 (0.98) 0.09 (0.71) AST (logic) -0.18(0.44) 0.13(0.68) -0.50 (0.21) ALT (logic) -0.07 (0.76) 0.31 (0.33) -0.48 (0.23) Anti-HCV E1E2 (In) Anti-HIV env (In) 0.14(0.37) 0.26 (0.26) 0.07 (0.76) HIV RNA (logic) -0.30 (0.05) -0.35 (0.12) -0.24 (0.31) HCV RNA (logic) -0.24 (0.12) -0.54 (0.01) 0.16(0.50) CD4 (square root) 0.02 (0.90) 0.01 (0.95) 0.004 (0.99) AST (logic) -0.11 (0.63) 0.16(0.63) -0.41 (0.31) ALT (logic) -0.02 (0.93) 0.29 (0.36) -0.40 (0.32) Anti-HIV env (In) HIV RNA (logic) 0.26 (0.07) 0.27 (0.20) 0.04 (0.87) HCV RNA (logic) -0.15 (0.32) -0.15(0.49) -0.16(0.47) CD4 (square root) -0.004 (0.98) 0.003 (0.99) 0.06 (0.79) AST (logic) -0.12(0.58) -0.21 (0.45) 0.19(0.60) ALT Oogic) 0.05 (0.82) -0.15(0.61) 0.25 (0.49) HIV RNA (logio) HCV RNA (logic) -0.06 (0.70) 0.009 (0.97) -0.14(0.54) CD4 (square root) -0.30 (0.05) -0.15(0.48) -0.41 (0.08) AST (logic) -0.40 (0.05) -0.39 (0.15) -0.48 (0.20) ALT Gogio) -0.37 (0.09) -0.51 (0.06) -0.52 (0.15) HCV RNA (logio) CD4 (square root) 0.03 (0.85) -0.15(0.50) 0.24 (0.33) AST (logic) 0.13 (0.57) 0.31 (0.31) -0.26 (0.54) ALT (logic) -0.17(0.46) -0.06 (0.84) -0.31 (0.46) CD4 (square root) AST (logic) 0.06 (0.80) -0.19(0.51) 0.25 (0.52) ALT (logic) 0.14(0.53) 0.06 (0.84) 0.26 (0.50) AST (logio) ALT (logic) 0.86 (0.0001) 0.82 (0.0003) 0.95 (0.0001)

180 Table 5.4: Summary of data values, before and after interferon and ribavirin combination therapy for HCV and changes during treatment.

Pre-IFN Post IFN Difference p-value for (pre-post) difference^ HCV RNA n 10 10 10 Median (range) 2.18x10^(110, 4.4x10^) 110(110,110) 2.18x10^ (-7.5x10^ 0.002* 4.4x10^) Mean (SD) (log scale) 7.29 (7.17) 2.04 (0) 5.25 (4.0) 0.0001+ Anti-HCV FL n 10 10 10 Median (range) 40560 (2560, 162240) 20480(1280,81920) 10240 (-20080, 80320) 0.04* Mean (SD) (log scale) 10.38(1.15) 9.65 (1.09) 0.73 (0.71) 0.015+ I I Anti-HCV E1E2 n 10 10 10 o, CO Median (range) 5120(1280, 20480) 2560 (320, 10240) 2560 (640, 10240) 0.001* Î Mean (SD) (log scale) 8.47 (0.83) 7.57 (0.99) 0.90 (0.33) 0.0001+

^Obtained from the Wilcoxon signed ranks test (*non-parametric) or paired t-test (+parametric), as appropriate I>3 031 I 3 Chapter 5: Effect of HAART on anti-HCV humoral immunity

Table 5.5: Correlations (r, p-value) between variables in the cohort successfully treated with interferon and ribavirin combination therapy for HCV.

Pearsons correlation on transformed data Correlation between: Before IFN HCV RNA (logio) Anti-HCV FL (In) 0.21 (0.56) Anti-HCV E1E2 (In) 0.60 (0.06) Anti-HCV FL (In) Anti-HCV E1E2 (In) 0.56 (0.09)

182 Chapter 5: Effect of HAART on anti-HCV humoral immunity

5.6 Discussion

In this study we found no effect of HAART on HCV RNA level (p=0.92) or anti- HCV E1E2 antibody titre (p=0.23). This agrees with many other studies that found no effect of HAART on HCV RNA level (Hammer et al, 1997; Garcia-Samaniego et al, 1998 ;Rutschmann et al, 1998;Zylberberg & Pol, 1998;Matsiota-Bemard et al, 2001). There was however a small but significant increase in the titre of anti-HCV FL antibodies (p=0.02), suggesting that immune reconstitution does enable the production of a higher titre of total anti-HCV specific antibodies; (Table 5.1). HCV RNA load as well as both anti-HCV FL and anti-HCV E1E2 antibody titres post therapy were significantly lower than pre therapy in our cohort of 10 responders to pegylated interferon and ribavirin combination therapy for HCV (p=0.0001, p=0.015 and p=0.0001 respectively). The decrease in HCV RNA was paralleled by the decreases in HCV specific antibody titres and this positive correlation between HCV RNA and antibody titre suggests that antigenic stimulation is required to maintain the HCV specific humoral response, which agrees with other studies (Simon et al, 1994; Osella et al, 1997;Seeff et al, 2001;Patel & Germer, 2002), (Table 5.3). HIV RNA level and anti-HlV env antibody titre post therapy were also significantly lower in the cohort treated with HAART (p=0.0003 and p=0.0001 respectively) (Table 5.1). This suggests that continuous antigenic stimulation is also responsible for the maintenance of HIV specific antibody titres.

In the cohort of HAART treated patients, there were inverse correlations overall between HIV RNA load and AST and ALT, which were statistically significant for the former (R=-0.40, p=0.05 and R=-0.37, p=0.09 respectively), (Table 5.2). This may reflect the greater hepatotoxicity (and consequent ALT and AST elevation) associated with HAART in HCV co-infected patients (den Brinker et al, 2000;Sulkowski et al, 2000), the inverse correlation would then be generated as HIV RNA level decreased on HAART, (see also Section 1.14.2).

A significant inverse correlation between both anti-HCV FL and anti-HCV E1E2 antibody titres and HCV RNA level pre HAART (R=-0.42, p=0.05 and R=-0.54, p=0.01 respectively) was observed and this disappeared or was obscured post

183 Chapter 5: Effect of HAART on anti-HCV humoral immunity

HAART (R=0,24, p=0.30 and R=0.16, p=0.50 respectively) (Table 5.2). Higher titres of HCV specific antibodies are associated with lower HCV RNA loads in an immunosuppressed setting. This situation contrasts with the positive correlation observed between HCV RNA load and HCV specific antibody titres pre and post successful pegylated interferon and ribavirin combination therapy for HCV, (Table 5.3). This effect of HAART on HCV specific humoral immunity is corroborated by a previous study that reported an inverse correlation between B-cell counts and HCV RNA pre HAART that disappeared post therapy (Yokozaki et al, 2000). It is an effect specific to HCV as there was no relationship between anti-HIV env antibody titre and HIV RNA level pre or post HAART (R=0.27, p=0.20 and R=0.04, p=0.87 respectively). It is also an effect that is not observed in immunocompetent patients prior to receiving pegylated interferon and ribavirin combination therapy for HCV (R=0.21, p=0.56 and R=0.60 p=0.06 respectively for anti-HCV FL and anti-HCV E1E2 antibody titres) (Table 5.5). Low sample numbers may have masked an association however, because there was a positive correlation of borderline significance between anti-ElE2 antibodies and HCV RNA level. This is the opposite effect to the inverse correlations between these parameters observed in patients pre HAART (see top panels of Figures 5.7 and 5.8) and agrees with the findings of Sections 5.5.3 and 5.5.6 where antigenic stimulation is an important determinant of anti-HCV and anti-HIV antibody titres.

In this study I have shown an alteration in the relationship between anti-HCV antibody titres and HCV RNA in an immunocompromised setting. An inverse correlation between anti-HCV antibody titre and HCV RNA level was observed only pre HAART and it disappeared or was obscured post therapy. This is a significant effect of HAART on anti-HCV immunity. The disappearance of this correlation coincided with an increase in CD4+ T cell counts of borderline significance (p=0.09) (Table 5.2); suggesting that improved T-cell help may possibly shift the HCV specific immune response in a Thl direction, towards T-cell mediated immunity. This switch in the type of predominant immune response to HCV could be a possible mechanism by which HAART causes fulminant hepatitis (personal communication. Professor C.A. Lee), reduces HCV viraemia (Perez-Olmeda et al, 2000;Yokozaki et al, 2000) or eradicates HCV in some patients (Fialaire et al, 1999;Yokozaki et al, 2000).

184 Chapter 6: Expression of memory markers on CD8+ T-cells

Chapter Six

The expression of memory markers on

CD8+ T-cells in HIV and HCV co­

infected patients

185 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

6.1 Introduction

The aim of this chapter was to investigate the expression of memory markers on CD8+ T-cells in HIV and HCV co-infected individuals. In order to do this, the expression of a range of memory markers was examined using antibody staining of PBMCs and flow-cytometry.

Naïve T-cells that have not encountered antigen, continually recirculate between the blood and the lymph systems. If a naive T-cell becomes activated through encountering antigen (a process dependent on TCR engagement and a CD28-B7 interaction), it will enlarge into a blast cell, undergo multiple rounds of cell division and generate a large clone of progeny cells that differentiate into a variety of ‘antigen- experienced’ cells. (Greenfield et a f 1998). These ‘antigen-experienced’ cells can be divided into roughly two states; resting memory cells and effector cells. Effector T- cells are short lived, mediate functions such as cytotoxic killing and express different surface markers to memory T-cells, which contributes to their different recirculation pattern (peripheral not lymphoid). Memory T-cells are longer-lived than effector T- cells and they react with heightened reactivity to subsequent challenge with the same antigen in order to generate a secondary immune response (Goldsby et al, 2000). The differentiation pathway from memory to effector T-cells however, remains unclear and recent papers have also postulated the existence of a continuous range of populations of ‘antigen-experienced’ T-cells from memory to full effector with different phenotypes and functional characteristics (Sallusto et al, 1999;Champagne et al, 2001;Tomiyama et al, 2002).

The T-cell co-stimulatory molecules CD27 and CD28 can be used to differentiate between memory and effector CD8+ T-cells. CD28 interacts with CD80 (B7-1) and CD86 (B7-2), which are expressed on antigen presenting cells (APC). CD28 is both an adhesion and signalling molecule and its coengagement with the TCR is required for T-cell activation, after which CD28 is downregulated in some populations of effector cells (Greenfield et al, 1998). The expression of CD27 is upregulated after TCR stimulation and its ligand (CD70), is transiently upregulated when the T-cell antigen receptor is stimulated. Ligation of CD27 then induces expansion of CD8+ T-

186 Chapter 6: HCV and expression of memory markers on CD8+ T-cells cells (Hintzen et al, 1995;Oshima et al, 1998). Recent studies have led to a putative model of T-cell differentiation based on the expression of CD27 and CD28 where CD28+CD27+ cells are precursor or early differentiated T-cells and CD27-CD28- cells are fully differentiated T-cells, with an intermediate CD28-CD27+ population also having been identified (Appay et al, 2002).

When naïve or memory CD8+ T-cells home to lymph nodes, they roll on high endothelial venules using CD62L (or L-selectin) allowing CCR7 (a lymph node homing receptor) to bind SLC (secondary lymphoid tissue chemokine), which is expressed on endothelial cells. This interaction activates integrins that promote firm adhesion and transmigration of the cells into the lymph node (Gunn et al, 1998;Campbell et al, 1998a;Campbell et al, 1998b). CCR7 and CD62L are therefore both essential for the migration of lymphocytes to the lymph nodes (Butcher & Picker, 1996;Gunn et al, 1998). The expression of CCR7 has been used to divide CD8+ memory T-cells into two separate subsets. CCR7- memory T-cells express receptors for migration to inflamed tissues and display immediate effector function whilst CCR7+ ‘central’ memory T-cells express lymph node homing receptors and lack immediate effector function, although they efficiently interact with dendritic cells and can differentiate into CCR7- effector cells (Sallusto et al, 1999;Tomiyama et al,

2002).

Human naïve and memory T-cells have been distinguished by the reciprocal expression of the RA and RO isoforms of CD45 (Michie et al, 1992). However, recent experiments have revealed the existence of CD45RA+ T-cells in the CD8+ memory pool (Callan et al, 1998;Gillespie et al, 2000). The full meaning of this reversion to CD45RA from RO is not understood as both splice forms act as phosphatases and lead to downregulation of T-cell activation. Some CD45RA+ CD8+ T-cells are thought to be terminally differentiated effector cells, although they will revert to CD45RO upon activation in vitro (Wills et al, 1999). As the expression of these two markers is usually reciprocal, only CD45RO was examined in this study.

Perforin monomers of 65 kDa are found in storage granules within CTLs. Perforin is a pore forming protein that can directly mediate target cell lysis and also allow entry of granzyme proteases into the target cell (Goldsby et al, 2000). Levels of

187 Chapter 6: HCV and expression of memory markers on CD8+ T-cells intracellular perforin were assessed in this study as an indicator of the effector function of these cells (i.e. their ability to lyse virally infected cells). Additionally, perforin (and IFNy) expression are associated with differentiated (CCR7-) CD8+ T- cells, which further characterises their memory phenotype (Champagne et al, 2001).

The expression of CD95 (APO-1, Fas antigen) was also assessed. Expression of CD95 is elevated in activated T-cells, which makes them more predisposed towards apoptosis (Mueller et al, 2001). It is possible however, that activated CD8+ T-cells that have been engaged by specific antigen on their class I MHC are protected from activation induced cell death (AICD) pre amplification as has been shown for CD4+ T-cells (Di Somma et al, 1999).

In summary, on the basis of recent papers (Sallusto et al, 1999;Tussey et al, 2000), naïve, memory and effector CD8+ T-cells have been described on the basis of memory markers as shown in Figure 6.1.

During primary infection, virus specific CD8+ T-cells (identified by epitope specific HLA class I tetramers) have similar phenotypes. HIV-1, EBV and HCV specific CD8+ T-cells are at an early stage of differentiation (CD27+CD28+) with low but significant levels of perforin expression. They express high levels of CD38, indicating that they are highly activated and express high levels of the proliferation marker Ki67 as well as low levels of the anti-apoptotic factor Bcl-2 which would make the cells prone to apoptosis (Appay et al, 2002).

Different chronic viral infections however, are characterised by enrichment of CD8+ T-cells with different phenotypes. For example, if one divides CD8+ cells into three categories on the basis of CD27 and CD28 expression, EBV and HCV specific CD8+ T-cells are early phenotype enriched, CMV specific cells are predominantly differentiated and HIV specific cells are of intermediate phenotype. As expected, HIV, CMV and EBV specific cells (that have been antigen primed) express granzyme and GMP-17 (a marker of cytotoxic granules). However, high perforin expression is restricted to CMV specific cells (Appay et al, 2002). Additionally, some recent experiments (Lucas et al, unpublished data), have suggested that the presence of HCV

188 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

Memory markers on different subsets Naïve CD8+ T-cells of memory CD8+ T-cells

CD45RA, CCR7 CD62L, CD27, CD28

Do not express; IFN-g, TNF-a, perforin

‘Central’ memory (T^.^) CD8+ T-cells

CCR7, CD62L, CD27, CD28, CD45RO

Do not express; perforin

‘Effector’ memory T-cells

Perforin, IFN-y

Do not express; CD27, CD28, CD62L, CCR7

Figure 6.1: The expression of memory markers on different subsets of memory CD8+ T-cells.

89 Chapter 6: HCV and expression of memory markers on CD8+ T-cells may affect the expression of these memory markers on CMV specific CD8+ T-cells. HCV specific CTL are predominantly high in CD28, CD27 and low in perforin and CD95 (Fas). This phenotype is not apparently restricted to HCV specific cells in these patients, but ‘spreads’ to CD8+ T-cells of other phenotypes such as the CMV specific and total CD8+ populations.

In order to further investigate the possibility that HCV may alter the memory phenotype of non-HCV specific CD8+ T-cells, I investigated whether HCV co- infection had an effect on the memory phenotype of the global CD8+ T-cell population in patients co-infected with HIV, by assessing the expression of the following memory markers; CD27, CD28, CD62L, CCR7, CD95, CD45RO and perforin.

190 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

6.2 Materials and Methods

Detailed deseriptions of the methodology used in this chapter are given in Chapter 2, Section 2.6 for antibody staining of memory markers on human T-lymphocytes and Section 2.7 for the methods used in the statistical analysis of the data.

6.2 Patients studied

6.2.1 Study population and samples

Three patient cohorts were investigated, these consisted of HIV and HCV co-infected patients, HIV mono infected patients and HCV mono infected patients. All patients were registered either at the Royal Free Hospital Haemophilia Centre or Ian Charleson Day Care Centre; and all provided informed consent (Royal Free Hospital Ethics references for the project were 219-2K and 5523 for patients from each centre respectively). The HIV and HCV co-infected and HCV mono-infected cohorts consisted predominantly of patients with inherited bleeding disorders, whilst the HIV mono-infected cohort did not, see Table 6.2. Any statistically significant differences between the three groups are also shown in Table 6.2. All co-infeeted patients had been infected with HCV prior to or at the same time as HIV (Herrero-Martinez et al, 2002).

There were two significant differences between the cohorts; firstly, the HIV/HCV co- infected cohort had lower CD4 counts than the HIV mono-infected (p= 0.0004), and secondly, the HIV/HCV and HCV cohorts consisted predominantly of patients with inherited bleeding disorders and the HIV mono infected did not. These two different patient groups have significantly different clinical characteristics (Greub et al, 2000; Sabin et al, 2000b;Yee et al, 2000). The differences in CD4 eounts are due to a smaller proportion of the co-infeeted group being on HAART and the co-infeeted (predominantly haemophiliac) groups longer average duration of HIV infeetion (Darby et al, 1995). The control cohort consisted of 12 laboratory eo-workers, who were approximately age matched to the patient cohorts and assumed to be HIV and HCV negative.

191 Chapter 6: HCV and expression of memory markers CD5+ on T-cells

HIV and HCV co-infected cohort (n= 28) Median Range Age at time of sample (years) 39 24-53 Patients on HAART (% and n) 67.85 (19) HIV RNA load (logio copies/ml)* 4.38 2.07-5.86 CD4 count (cells/mm 3)+ 258 18-1461 HCV RNA load (lU/ml)** 6.23 4.28-6.88 ALT (U/L) 48 21-327 Haemophilia diagnosis (% and n) 96.4 (27) Successful IFN, IFN + RBV or Peg-IFN 10.7% therapy for HCV at time of sample (% and (3 of 28) n of total) Self-resolved HCV (% and n of total) 7.1% (2 of 28) HIV mono-infected cohort (n= 24) Age at time of sample (years) 40 27-54 Patients on HAART (%) 83.3 (20) HIV RNA load (logic copies/ml)* 4.09 1.73-5.50 CD4 count (cells/mm 3)+ 561.50 139-1390 Haemophilia diagnosis (% and n) 0(0) HCV mono infected cohort (n= 30) Age at time of sample (years) 39 19-73 HCV RNA load (lU/ml)*» 6.48 5.75-8.25 ALT (U/L) 53 17-145 Haemophilia diagnosis (% and n) 100(100) Successful IFN, IFN + RBV or Peg-IFN 10% therapy for HCV at time of sample (% and (3 of 30) n of total) Self-resolved HCV (% and n) 6.7% (2 of 30)

* Samples negative for HIV RNA excluded ** Samples negative for HCV RNA excluded + HIV mono infected cohort has significantly higher CD4 counts than HIV/HCV co- infected cohort (p= 0.0004 Mann-Whitney U-test).

Table 6.1: Demographic data of patient cohorts studied, all values shown are median (range), unless stated.

192 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

6.3.2 HIV and HCV therapy

Section 4.3.2 outlines the treatment protocols for HIV and HCV treatment at the Royal Free Hospital London. It should be noted that the total numbers detailed in this section for different measured parameters from within each cohort is occasionally less than the total mentioned in Table 6.1 as I was not able to acquire the same amount of clinical data for each patient. Antiretroviral therapy for HIV was administered to 19 of 28 patients (67.85%) in the HIV and HCV co-infected and 20 of 24 patients (83.3%) in the HIV mono-infected group. Antiviral therapy for HCV was successfully administered to three of 28 patients (10.7%) in the HIV and HCV co-infected and three of 30 patients (10%) in the HCV mono infected cohort. Of the six patients that responded to therapy, three had been treated with interferon monotherapy, two with interferon and ribavirin combination therapy and one with pegylated interferon and ribavirin combination therapy. Two patients from each of the HCV infected cohorts cleared HCV naturally (i.e. were negative for HCV RNA by assay sensitive to <10 lU/ml).

193 Chapter 6: HCV and expression of memory markers CD5+ on T-cells

6.4 Results

6.4.1 Expression of perforin, CD95 and CD45RO

Perforin and CD95 are upregulated in activated CD8+ T-cells and so can be considered markers of T-cell activation. Levels of perforin expression give an indication of the cytotoxic capacity of CD8+ T-cells, whilst elevation in CD95 expression increases the susceptibility of these cells to apoptosis. The association of CD45 isoforms with activation status is less clear-cut.

A dominant effect of HCV was seen in analysis of perforin, in that both the HCV mono-infected and HIV/HCV co-infected cohorts express significantly lower levels of perforin than the HIV mono-infected group (10.78% and 3.43% vs 21.45%, p=< 0.0001 for both relationships). In fact, levels of perforin expression were even lower in the HIV/HCV co-infected than in the HCV mono-infected group (3.43% vs 10.78%, p= <0.0001). Perforin expression was similar between the HIV and control groups (21.45% vs 22.98%, p=0.73) (Figure 6.2).

Expression of CD95 was significantly lower in the HCV mono-infected cohort compared to the HIV mono-infected, HIV/HCV co-infected and control groups (41.21% vs 68.35%, 65.72% and 58.12%, p= <0.0001, <0.0001 and 0.001 respectively). CD95 expression was elevated slightly but significantly in the HIV positive cohort compared to controls (68.35% vs 58.12%, p= 0.035), although there was no significant difference between the HIV/HCV co-infected cohort and either the control or HIV mono infected cohort however (p= 0.26 and p= 0.63 respectively). The clearest difference however, is observed in the HCV mono-infected cohort, which express significantly lower levels of CD95 than all of the other cohorts, (Figure 6.3).

Levels of CD45RO were similar in the HIV positive and control groups (40.31% vs 36.67%, p= 0.42), and significantly lower in the HCV mono-infected cohort than in the HIV mono-infected cohort (29.14% vs 40.31%, p= 0.02). There was no

194 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

100-1

0 t/3 80 2

1 60

40

TT 204 V ▼ 0 HIV/HCV HCV HIV Cont

Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 22 vs 30 21.45 ± 2.79 vs 10.78 ± 1.02 0.0002

HIV vs HIV/HCV 22 vs 20 21.45 ± 2.79 vs 3.43 ± 0.48 <0.0001

HIV vs Controls 22 vs 12 21.45 ±2.79 vs 22.98 ±2.80 0.73 HIV/HCV vs HCV 20 vs 30 3.43 ± 0.48 vs 10.78 ± 1.02 <0.0001 HIV/HCV vs Controls 20 vs 12 3.43 ± 0.48 vs 22.98 ± 2.80 <0.0001 HCV vs Controls 30 vs 12 10.78 ± 1.02 vs 22.98 ± 2.80 <0.0001

Figure 6.2: Expression of intracellular perforin in human CD8+ T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

195 Chapter 6: HCV and expression of memory markers CD5+ on T-cells

lO O n

a 0 80 3 h . ▼t Jtv 03 T 03 TT 1 60 in IT o\ ijîîî e 40 A ^A A — ^A A

2 0 ^ aaa A

0 HIV/HCVHCV HIV Cont

Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 23 vs 30 68.35 ± 2.96 vs 41.21 ± 2.77 <0.0001

HIV vs HIV/HCV 23 vs 22 68.35 ±2.96 vs 65.72 ±4.52 0.63

HIV vs Controls 23 vs 12 68.35 ± 2.96 vs 58.12 ± 3.03 0.035 HIV/HCV vs HCV 22 vs 30 65.72 ± 4.52 vs 41.21 ± 2.77 <0.0001 HIV/HCV vs Controls 22 vs 12 65.72 ±4.52 vs 58.12 ±3.03 0.26 HCV vs Controls 30 vs 12 41.21 ±2.77 vs 58.12 ±3.03 0.0011

Figure 6.3: Expression of CD95 on the surface of human CD8+ T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

196 Chapter 6: HCV and expression of memory markers on CD8+ T-cells significant difference between the HCV mono-infected and control cohorts (29.14% vs 36.67%, p= 0.18) although the control cohort expressed slightly higher levels of CD45RO. As observed for CD95 expression, CD45RO expression in the HIV/HCV co-infected was similar to the HIV mono-infected group (42.48% vs 40.31%, p= 0.59), (Figure 6.4).

6.4.2 Expression of CD27 and CD28

Expression of these markers can be used to differentiate between memory and effector T-cells, with ‘early’ or ‘central’ memory T-cells being CD27+CD28+ and effector T- cells CD27-CD28-. An intermediate CD27+CD28- population has also been identified, (see Section 6.1).

Expression of CD27 was significantly lower in the HIV mono-infected cohort than in the HCV mono-infected, HIV/HCV co-infected and control cohorts, (34.21% vs 61.61%, 60.69% and 57.10%; p= <0.0001, <0.0001 and 0.0001 respectively). There was no statistically significant difference in the expression of this marker between the HIV/HCV co-infected, HCV mono-infected and control cohorts, so the HIV/HCV co- infected cohort appeared similar to the HCV mono-infected group, (Figure 6.5).

Expression of CD28 was again significantly lower in the HIV mono-infected cohort than in the HCV mono-infected and control groups (32.92% vs 51.46% and 44.44%; p= 0.001 and p= 0.026 respectively). In contrast to CD27 however, the HIV/HCV co- infected group appeared similar to the HIV mono infected, expressing lower levels of CD28 than the HCV mono-infected and control groups respectively (33.72% vs 51.46% and 44.44%, p= <0.0001 and 0.018 respectively) (Figure 6.6).

6.4.3 Expression of CD62L and CCR7

As both of these memory markers are involved in the migration of memory T- lymphocytes to the secondary lymph nodes (see Section 6.1), they have been grouped together for analysis. Expression of CD62L and CCR7 on the surface of

197 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

lO O n oC c/3 t/i 80 £ ? 60 S I-: À À §40 ••

2 0 4 T T

0 HIV/HCV HCV HIV Cont Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 24 vs 16 40.31 ± 2.67 vs 29.14 ± 4.01 0.02

HIV vs HIV/HCV 24 vs 22 40.31 ±2.67 vs 42.48 ±2.96 0.59

HIV vs Controls 24 vs 12 40.31 ±2.67 vs 36.67 ±3.20 0.42 HIV/HCV vs HCV 22 vs 16 42.48 ± 2.96 vs 29.14 ± 4.01 0.01 HIV/HCV vs Controls 22 vs 12 42.48 ±2.96vs 36.67 ±3.20 0.22 HCV vs Controls 16 vs 12 29.14 ±4.01vs 36.67 ±3.20 0.18

Figure 6.4: Expression of CD45RO on the surface of human CD8+ T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

198 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

100 a • 1-H0 C/3 80 03 1 60 ee (N Q U 40

20 ▼ t v

0 HIV/HCV HCV HIV Cont

Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 24 vs 30 34.21 ±3.17 vs 61.61 ±3.74 <0.0001

HIV vs HIV/HCV 24 vs 24 34.21 ±3.17 vs 60.69 ±4.36 <0.0001

HIV vs Controls 24 vs 10 34.21 ±3.17 vs 57.10 ±2.87 0.0001 HIV/HCV vs HCV 24 vs 30 60.69 ±4.36 vs 61.61 ±3.74 0.87 HIV/HCV vs Controls 24 vs 10 60.69 ±4.36 vs 57.10 ±2.87 0.61 HCV vs Controls 30 vs 10 61.61 ±3.74 vs 57.10 ±2.87 0.51

Figure 6.5: Expression of CD27 on the surface of human CD8+ T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

199 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

lOOn a A O t/) 80 A CA AA a A g T & 60 00 ▼ t t (N 8 40 : — gJLV—

▼ ▼ tvv 2 0 ▼ ▼▼▼

0 HIV/HCV HCV HIV Cont Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 24 vs 30 32.92 ± 3.21 vs 51.46 ± 3.05 0.0001

HIV vs HIV/HCV 24 vs 24 32.92 ±3.21 vs 33.72 ±2.68 0.85

HIV vs Controls 24 vs 13 32.92 ± 3.21 vs 44.44 ± 3.12 0.026 HIV/HCV vs HCV 30 vs 24 33.72 ± 2.68 vs 51.46 ± 3.05 <0.0001 HIV/HCV vs Controls 24 vs 13 33.72 ± 2.68 vs 44.44 ± 3.12 0.018 HCV vs Controls 30 vs 13 51.46 ±3.05 vs 44.44 ±3.12 0.17

Figure 6.6: Expression of CD28 on the surface of human CD8+ T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

200 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

T-lymphocytes from the three cohorts studied is shown in Figures 6.7 and 6.8 respectively, along with statistical analysis of the data.

Expression of CD62L was significantly lower in both the HCV and HIV/HCV infected cohorts compared to the HIV mono infected cohort (12.07% and 13.91% compared to 19.40%, p= 0.004 and p= 0.04 respectively) (Figure 6.7). The control cohort was not significantly different from any other however, although the small size of the control group may have affected this result as the two outlying patients in this group mask the fact that the controls are more similar to the HCV infected cohorts. If this is the case, it would suggest that CD62L expression is slightly elevated in HIV mono infected patients, whilst HIV/HCV co-infected patients have a phenotype more similar to that in the HCV mono-infected or control groups. In contrast to CD62L, there was no significant difference in the expression of CCR7 between any of the four cohorts studied, (Figure 6.8).

6.4.4 Effect of CD4 count on expression of memory markers

As the only significant difference between the studied cohorts (other than haemophilia diagnosis), was in the CD4 count, it was therefore decided to investigate whether there was a relationship between CD4 count and expression of any of the activation markers investigated. Table 6.2 shows the analysis of the relationship between CD4 counts and the levels of expression of the measured memory markers.

The expression of three memory markers (CD45RO, CD27 and CD28) was found to be significantly inversely related to the CD4 count but only in the HIV/HCV co­ infected group. The expression of CD45RO in the HIV/HCV co-infected cohort was no different to the HIV mono-infected group, so the CD4 count was probably not responsible for the results observed in Figure 6.4 despite the inverse correlation in the co-infected cohort. The expression of CD27 in the HIV/HCV co-infected cohort was similar to that in the control and HCV mono-infected cohorts, these cohorts presumably have significantly higher CD4 counts, so the CD4 count is unlikely to be related to the lower CD27 expression observed in Figure 6.5 for the HIV mono­ infected group. Finally, expression of CD28 was significantly lower in the two HIV

201 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

lOOn

I c« 80 c/3 g e- 60 tN Q 40 U ▼ T ▲ ▲ 2 0

t i s 0 — e-e- HIV/HCV HCV HIV Cont Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 24 vs 30 19.40 ± 2.00 vs 12.07 ± 1.46 0.004

HIV vs HIV/HCV 24 vs 22 19.40 ± 2.00 vs 13.91 ± 1.63 0.04

HIV vs Controls 24 vs 9 19.40 ±2.00 vs 16.43 ±6.07 0.55 HIV/HCV vs HCV 22 vs 30 13.91 ±1.63 vs 12.07 ±1.46 0.41 HIV/HCV vs Controls 22 vs 9 13.91 ±1.63 vs 16.43 ±6.07 0.59 HCV vs Controls 30 vs 9 12.07 ± 1.63 16.43 ±6.07 0.31

Figure 6.7: Expression of CD62L on the surface of human CD8+T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

202 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

lOOn a 0 t/5 80 2

1 60 A 8 A u 40-

A A ^ -#— #- T 20 - ^ A ^ e# A TT

0 HIV/HCV HCV HIV Cont

Cohort

Comparison n Mean % (SEM) p-value HIV vs HCV 11 vs 14 24.53 ±6.88 vs 31.06 ±4.54 0.42

HIV vs HIV/HCV 11 vs 19 24.53 ± 6.88 vs 24.79 ± 3.20 0.97

HIV vs Controls 11 vs 12 24.53 ± 6.88 vs 24.73 ± 3.22 0.98 HIV/HCV vs HCV 19 vs 14 24.79 ±3.20 vs 31.06 ±4.54 0.25 HIV/HCV vs Controls 19 vs 12 24.79 ±3.20 vs 24.73 ±3.22 0.99 HCV vs Controls 14 vs 12 31.06 ±4.54 vs 24.73 ±3.22 0.28

Figure 6.8: Expression of CCR7 on the surface of human CD8+T-lymphocytes from four different patient cohorts. Differences between groups were assessed by a two- tailed unpaired t-test and significant differences are indicated in bold. The mean of the expression levels obtained is indicated by a bar in the top panel.

203 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

Comparison Spearman’s correlation R (p-value) HIV/HCV CD4 vs CD62L -0.11 (0.64) HIV CD4 vs CD62L -0.11 (0.61) HIV/HCV CD4 vs CCR7 -0.06 (0.75) HIV CD4 vs CCR7 0.12(0.60) HIV/HCV CD4 vs CD95 -0.21 (0.35) HIV CD4 vs CD95 0.03 (0.90) HIV/HCV CD4 vs perforin 0.03 (0.32) HIV CD4 vs perforin -0.13 (0.58) HIV/HCV CD4 vs CD45RO -0.58 (0.01) HIV CD4 vs CD45RO 0.26 (0.23) HIV/HCV CD4 vs CD27 -0.47 (0.04) HIV CD4 vs CD27 0.33 (0.13) HIV/HCV CD4 vs CD28 -0.47 (0.03) HIV CD4 vs CD28 0.32 (0.15)

Table 6.2: Relationship between CD4 counts and memory marker expression. Significant correlations are highlighted in bold.

204 Chapter 6: HCV and expression of memory markers on CD8+ T-cells positive cohorts, which argues in favour of a role for CD4 count. The situation is more complex for this marker however, because there is a trend towards a positive correlation between CD4 count and CD28 in the HIV mono-infected group (see Table 6.2); the opposite to that observed for the HIV/HCV, which suggests that the CD4 count might not play a part in the result observed in Figure 6.6.

205 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

6.5 Discussion

In this study, I have shown for the first time that the presence of HCV can significantly affect the expression of memory markers on the surface of the total CD8+ T-cell population; a summary of these effects is given in Table 6.3. The effects observed are complex however, and further investigation is needed to determine whether these differences impact on immune function and disease progression.

The presence of HCV was associated with significant decreases in the level of expression of perforin and it has recently been published that patients with chronic HCV infection express lower levels of perforin (Par et al, 2002) which would presumably result in impaired CD8+ T-cell cytolytic activity. HCV infection was also associated with reduced expression of CD95, a marker that is associated with activation of CD8+ T-cells as well as apoptosis (Krammer, 2000). The low expression of both these markers in patients with chronic HCV infection, may alternatively suggest that CD8+ T-cells may not be normally activated, a situation that could be explained by defective antigen presentation. It is known that HCV impairs the function of dendritic cells (DC). Transfection of HCV core into DCs results in abnormal priming of CD4+ T-cells. DCs recovered from the PBMCs of patients with chronic HCV infection are impaired in their alio stimulatory capacity, and DCs from these patients do not respond to maturation stimuli (Kanto et al, 1999;Auffermann- Gretzinger et al, 200I;Sarobe et al, 2002). Alternatively, as most patients in this study had active HCV infection, it is possible that the large turnover of activated CD8+ T-cells observed within the liver during chronic HCV may skew the CD8+ T- cell memory marker profile in the direction of CD95-, perforin- and CD45RO- (Ward et al, 2002). The inclusion of a control group of patients with non-HCV hepatitis would be needed in the study in order to clarify this point. If the effect were still observed this would suggest that the liver is the responsible site, if not, then the effect is HCV specific and the site of action (i.e. liver or DC) would need to be determined. It is also possible that HCV mediates these effects by directly infecting T-cells {Monso et al, 1999).

206 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

Virus effect CD62L CCR7 CD95 Perforin CD45RO CD27 CD28 HCV - - - - - HIV +? + - - - “ - HIV + HCV + - - - - -

Table 6.3: Summary of the effect of individual virus infections on the expression of memory markers on CD8+ T-cells.

Key + + + Strong increase + + Moderate increase + Weak increase Strong decrease

Moderate decrease

Weak decrease

207 Chapter 6: HCV and expression of memory markers on CD8+ T-cells

The presence of HIV was associated with a small elevation in the expression of CD62L, an increase in the expression of CD95 and a decrease in the expression of CD27 and CD28. The increase in CD95 would mean that CD8+ T-cells in HIV positive individuals were more predisposed to apoptosis, an effect that has already been demonstrated for HlV-specific CD8+ T-cells (Mueller et al, 2001). The decrease in CD27 and CD28 expression suggests that there may be a disproportionate number of precursor or early-differentiated T-cells in HIV positive patients. The effect that HIV replication in lymphoid tissue would have on T-cell activation could be used as a possible explanation for these effects (Pantaleo et al, 1993;Hosmalin et al, 2001).

HIV and HCV co-infection was associated with variations in memory marker expression that are difficult to explain because the ‘HCV effect’ appeared to dominate with some markers (perforin and CD27) and the ‘HIV effect’ with others (CD95, CD45RO and CD28). In fact, HIV and HCV co-infection was associated with significantly lower perforin expression than even the HCV mono-infected cohort. Possible explanations for the observed effects have already been given for the HIV and HCV mono-infected cohorts, but a theoretical dissection of the causes of these effects in the HIV and HCV co-infected group would be unrealistic at this point. Nevertheless, given the crucial role of CTL in the control of HIV (Walker et al, 1991;McMichael et al, 2000), it is possible that impairment of CD8+ T-cell effector function through the influence of HCV on perforin content could have an important effect on control of viral replication. Practically, this also means that studies of CTL in HIV need to take into account the influence of HCV on these cells.

208 Chapter 7: General Discussion

Chapter Seven

General Discussion

209 Chapter 7: General discussion

7. General Discussion

The aim of this thesis was to investigate HIV and HCV co-infection in patients with inherited bleeding disorders. The serum samples used in Chapters 3, 4 and 5, were taken from the Hepstore at the Haemophilia and Haemostasis Centre of the Royal Free Hospital London, which contains samples that date back to 1979. The PBMC samples used in Chapter 6 were isolated freshly from whole blood donated by patients attending clinics at the Haemophilia and Haemostasis Centre and Ian Charleson Day Care Centre both at the Royal Free Hospital London. All patients also gave informed consent prior to blood sample donation. Two Royal Free Hospital Ethics Committee Applications were submitted and approved for this study the application reference numbers were 219-2K and 5523 for each centre application respectively.

7.1 Development of a QC RT-PCR assay for HCV

The initial aim of this thesis was to develop a QC RT-PCR assay for HCV and the assay had to achieve four objectives; it had to be cheaper to run and more sensitive than the Quantiplex™ HCV branched DNA (bDNA) version 2.0 assay (Bayer Diagnostics) (Alter et al, 1995) routinely in use at the time in the Royal Free Hospital Virology Department, it had to correlate well with the established assay and to quantify reasonably equally all HCV genotypes found in the UK haemophilic population. These four aims were achieved (see Chapter 3). Over the course of this thesis, the QC RT-PCR assay was used to quantify over 1000 HCV RNA loads. The estimated cost of running the assay was £10 per load compared to £40 per load for the commercial assay. Assuming that £30 was saved per HCV RNA load, over £30,000 was saved over the course of this thesis solely by the routine use of the QC-RT PCR assay.

There were however, various ways in which the assay could have been improved. The final sensitivity of the assay was 1x10"^ copies/ml and the RT-PCR was capable of detecting 1x10^ copies of RNA, see Figure 3.11. If lOpl of reverse transcribed product was taken into the PCR reaction instead of 5 pi, the sensitivity could be increased to 5x10^ copies/ml, see Section 2.3. Additionally, as is done in the

210 Chapter 7; General discussion

Ultrasensitive version of the Amplicor™ HCV Monitor™ test (Roche Molecular Systems, Pleasanton, CA) (Doglio et al, 1999), a greater volume of serum could have been extracted (400pi instead of 200pi for example) and the final amount eluted into a smaller volume (lOpl instead of 50pl) or concentrated, see also Section 2.2.6. This would have increased the sensitivity of the assay 10-fold to 5x10^ copies/ml. The main reason why this was not done however was that the Hepstore is a unique resource and to extract 400pl from each sample would be wasteful.

There are now also, more modem real-time PCR techniques such as the Light Cycler® (Roche) and Taq-Man® (Applied Biosystems) methodologies (Kuimelis et al, 1997) that can analyse emerging PCR products in real-time, dispensing with need for mnning gels. Adaptation of the QC RT-PCR assay to the Taq-Man® or Light Cycler® methodologies would significantly reduce the mn-time of the assay as well as reducing the production dangerous waste such as ethidium bromide stained gels and released amplicon.

It would also have been desirable to develop a PCR and RFLP based genotyping assay that could use RFLP of the PCR product from the QC RT-PCR assay instead of requiring de novo RT-PCR of previously extracted viral RNA, see Sections 2.2.6 and 2.4. Unfortunately, this was not done as only 111 samples had to be genotyped and the elucidation of novel restriction sites that were diagnostic of HCV genotype in the original amplicon would have been very time consuming.

7.2 The prognostic value of a single HCV RNA load measured early after HIV seroconversion

In Chapter 4, I undertook a retrospective cohort study that utilised stored semm samples from 111 men with inherited bleeding disorders infected with HIV and HCV prior to the heat sterilisation of clotting factor concentrates in 1985. The semm samples were from the Haemophilia Centre Hepstore and the chapter relied on the QC RT-PCR and genotyping assays developed in Chapter 3. HCV RNA loads were measured using the QC RT-PCR assay for HCV and 104 of the 111 participants were genotyped for HCV using the RT-PCR and RFLP method (see Chapter 3). The

211 Chapter 7: General discussion participants not genotyped for HCV were HCV RNA negative in the QC RT-PCR assay. Multivariable analysis of the HCV RNA loads of patients in this cohort, controlling for age at HIV seroconversion, HIV RNA load and CD4 count demonstrated for the first time that HCV RNA levels measured early (in this case, four years) post HIV seroconversion were predictive of progression to both AIDS and all-cause mortality over a period of at least 15 years (Herrero-Martinez et al, 2002).

Analysis of death from liver disease was not possible in this study however, because the number of patients that died a liver related death was too small for statistical analysis (n= 16). A larger cohort would have allowed this clinical end point to be taken into account as well as allowing the all-cause mortality end point to be more thoroughly investigated. As is mentioned in Section 4.5, associations between HCV RNA and all cause mortality only became apparent at 12 years post HIV seroconversion, which coincides with the first deaths from liver disease in the cohort. A larger cohort would have allowed a more detailed analysis of this data and revealed whether high HCV RNA loads are a risk factor for non-liver related mortality, liver related mortality or both clinical end-points. Additionally, a larger cohort would have strengthened the significances of the associations of HCV RNA load with the all­ cause mortality and AIDS endpoints. As far as I am aware however, there are no other collections of long-term stored serum samples large enough to repeat this study in order to strengthen the associations observed between HCV RNA load and clinical outcome.

This work was done as a retrospective cohort study using stored serum samples from the Haemophilia Centre Hepstore. It would have been optimal to perform this work as a prospective study, as degradation of viral RNA due to long-term sample storage may confound the data. However, this was clearly not possible in this study due to the length of follow-up required. It is likely however, that had the study been prospective, associations between HCV RNA level and clinical outcomes would have been strengthened due to the removal of the sample storage variable. Other studies have looked at the prognostic value of HCV RNA prospectively, but with much shorter follow-up than this study, see Section 4.5 (Greub et al, 2000;Daar et al, 2001b).

212 Chapter 7; General discussion

It would have been informative to know whether HCV RNA levels measured before HIV seroconversion were also associated with the studied clinical end points (AIDS and all-cause mortality). Unfortunately, there were not enough samples in the Haemophilia Centre Hepstore to investigate this.

The fact that high levels of HCV RNA are predictive of progression to AIDS may initially appear surprising but there is however a plausible explanation for this observation. Patients with high HCV RNA loads are likely to have greater numbers of activated CD4+ T-cells. HIV infects these cells more readily and these individuals will consequently develop relatively higher HIV RNA loads and progress to AIDS and/or death more rapidly. CD26 could play a role in the enhanced infection of activated CD4+ T-cells by HIV. CD26 is a T-cell activation marker expressed on activated T-cells, the expression of which has been shown to facilitate entry of HIV into CD4+ T cells in conjunction with CD4 (Callebaut et al, 1993). There is also an increased rate of HIV entry into CD4+/CXCR4+ T-cells expressing relatively high levels of CD26 (Callebaut et al, 1998). Therefore, higher HCV RNA loads and greater numbers of activated CD4+ T-cells at the time of HIV infection will be associated with an elevated initial HIV RNA load and the HIV RNA load set point early after HIV seroconversion is strongly associated with progression to both AIDS and death (Mellors et al, 1995;Mellors et al, 1996).

7.3 The effect of HAART on anti-HCV specific humoral immunity

This study aimed to clarify the effect of HAART on HCV specific antibody mediated immunity and its relationship with HCV RNA load. As control groups, the effect of HAART on the relationship between anti-HCV env antibodies and HIV RNA loads as well as the effect of successful pegylated interferon and ribavirin combination therapy for HCV on the relationship between anti-HCV antibodies and HCV RNA load were also investigated.

This study found that antigenic stimulation is an important determinant of both HIV and HCV specific antibody level in serum. Additionally, a significant inverse correlation between anti-HCV E1E2 antibody titre and HCV RNA load was observed

213 Chapter 7: General discussion pre-HAART and this disappeared or was obscured post therapy. An inverse correlation of borderline significance between anti-HCV FL antibody titre and HCV RNA was observed as well and this also disappeared or was obscured post-HAART. In contrast, no significant relationship was observed between anti-HIV env antibody titre and HIV RNA pre-HAART or between anti-HCV antibody titre and HCV RNA load pre-successful pegylated interferon and ribavirin combination therapy for HCV.

Suitable serum samples (i.e. pre and post HAART) were available for 24 of the 28 individuals with inherited bleeding disorders treated with HAART attending the Royal Free Haemophilia and Haemostasis Centre. Although the inverse correlations between anti-HCV E1E2 and anti-HCV FL antibody titre and HCV RNA level were significant pre-HAART, a larger cohort would have strengthened the power of the study. A larger number of patients would also have allowed further investigation of some of the interesting associations revealed in Table 5.3, such as the inverse correlations between ALT/AST and HIV RNA.

Initially, this project was to be performed using western blotting instead of immunofluorescence. In particular, the protein products of baculovirus FL (expressing all 10 HCV proteins, see Section 2.5) were to be run on polyacrylamide gels, transferred onto a PVDF membrane and blotted with the relevant patient serum. Scans of the western blots would have allowed the methodology to be semi- quantitative and any changes in the relative response to all the 10 different HCV proteins would have been analysed. Unfortunately, this was not possible, as I could not achieve a satisfactory separation of the 10 proteins expressed by the FL baculovirus. As well as PAGE, a selection of NuPAGE gels (Invitrogen) were used, along with various running buffers, but resolution of the protein bands remained poor. This was probably due to the fact that many of the proteins expressed were of a similar size (see Figures 1.1 and 5.1) and that the patient serum used as the primary antibody may not have had antibodies specific for all the expressed proteins. It is also possible that some of the proteins were expressed at lower levels by the baculovirus construct. Immunofluorescence had the advantage of more reliable quantitation, but unlike western blotting, the technique cannot distinguish between the different proteins expressed by FL. For this reason, the FL baculovirus was used as a measure

214 Chapter 7: General discussion of total anti-HCV antibody and E1E2 as a measure of anti-HCV envelope specific antibody titre in the immunofluorescence assays.

It would be interesting to investigate whether immune reconstitution post-HAART could alter the avidity of both HCV and HIV specific antibodies in this cohort. Antibody avidity can be assessed by a combination of immunofluorescence and urea solution washes of different molarities. Low and high avidity antibodies can be distinguished by comparing the immunofluorescence after PBS or 8M urea washes. The urea wash would wash off low but not high avidity antibody (Ward et al, 1993). In this study, it would also have been informative to have investigated true titres of antibodies capable of neutralising HCV (Bichr et al, 2002). In the Bichr paper, the ability of patient serum to inhibit HCV infection of primary human biliary cells was used to give an indication of neutralising antibody titre. Unfortunately, time constraints did not allow this methodology to be tested. Additionally, future studies should also investigate HCV specific CD4+ and CD8+ T-cell responses pre and post HAART by ELISpot, intracellular cytokine staining or tetramer staining methodologies. This would reveal whether HAART affects cellular as well as humoral responses to HCV.

7.4 The expression of memory markers on CD8+ T-cells in HIV and HCV co- infected patients

This chapter is part of an ongoing project, the aim of which is to determine whether the presence of HCV affects the expression of memory markers on HIV-specific T- cells as well as total CD8+ T-cells. Some recent experiments (Lucas et al, unpublished data), have suggested that the presence of HCV affects the expression of these memory markers on CMV specific CD8+ T-cells. HCV specific CTL are predominantly high in CD28, CD27 and low in perforin and CD95 (Fas). This phenotype is not apparently restricted to HCV specific cells in these patients, but ‘spreads’ to CMV specific as well as total CD8+ T-cell populations.

Patient samples are still being collected for this study in order to achieve three objectives. Firstly, to assemble a non-HCV hepatitis control group to determine

215 Chapter 7; General discussion whether any observed effeets are due specifieally to HCV infection or just to liver inflammation. Secondly, to assemble a control group of HIV positive patients with non-HCV hepatitis to determine whether non-HCV hepatitis or liver inflammation affects the expression of CD8+ T-cell memory markers in HIV positive patients. Finally to obtain about 10 patient samples from each of the three final HIV positive cohorts (HIV mono-infeeted, HIV/HCV co-infected and HIV/non-HCV hepatitis), with strong MHC elass-I tetramer staining for HIV A2-gag peptides - strong staining is needed to accurately phenotype the tetramer positive cells. This would allow the effect of HCV co-infection and liver inflammation on the memory phenotype of these HIV-specific CD8+ T-eells to be investigated.

Additionally, novel techniques such as the flow cytometric analysis of telomere lengths from antigen specific cells could start to give an idea of what mechanism is responsible for the observed differences in the various patient groups (Plunkett et al, 2001). If rapid turnover of CD8+ T-cells in the liver was responsible for the observed phenotypes, one might expect telomere lengths of total CD8+ T-cells to be shorter than those in cells that have been defectively activated, as they would have undergone more rounds of cell division. It would also be important to assess dendritic cell function in all the different cohorts studied, as there may be differences in the allostimulatory capacity, or in secretion of cytokines from DCs derived or isolated from the different cohorts (Kanto et al, 1999;Sarobe et al, 2002). As there is recruitment of lymphocytes to the liver during chronic HCV infection, analysis of lymphocytes from the periphery may be misleading (Gonzelez-Peralta & Lau 1995). In the future, it would be informative to compare the expression of memory markers both in liver and peripheral CD8+ T-eells.

Significant variations in the expression of memory markers on CD8+ T-eells from HIV positive, HCV positive and HIV and HCV co-infected patients were observed in this study. It is now important to determine the role of CD8+ memory T-cells subsets with different phenotypes in different virus infections (Champagne et al, 2001;Appay et al, 2002). Although the results I have observed are interesting, they do not give an indieation of whether the observed variations affect CD8+ T-cell funetion. Further functional analysis of T-eell function in these patients is needed, using ELISpot assays or intraeellular cytokine staining to determine whether there are any functional

216 Chapter 7; General discussion differences between the different groups. In the future, it will also be important to address whether the memory phenotype of CD8+ T-cells has an effect on the disease progression of HIV as well as other viral infections.

217 Chapter 8: References

Chapter Eight

References

218 References

8. References

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Anastassopoulou,C.G., Touloumi,G., Katsoulidou,A., Hatzitheodorou,H., Pappa,M., Paraskevis,D., Lazanas,M., Gargalianos,?., & Hatzakis,A. (2001) Comparative evaluation of the QUANTIPLEX HIV-1 RNA 2.0 and 3.0 (bDNA) assays and the AMPLICOR HIV-1 MONITOR vl.5 test for the quantitation of human immunodeficiency virus type 1 RNA in plasma. J. Virol.Methods, 91, 67-74.

Ansari,A. & Emery,V.C. (1998) Baculovirus Vectors. Molecular Biomethods Handbook (ed. by R. Rapley & J. M. Walker) Humana Press Inc, Totowa NJ.

Appay,V., Dunbar,P.R., Callan,M., Klenerman,?., Gillespie,G.M., Papagno,L., Ogg,G.S., King,A., Lechner,?., Spina,C.A., Little,S., Havlir,D.V., Richman,D.D., Gruener,N., Pape,G., Waters, A., Easterbrook,?., Salio,M., Cerundolo,V., McMichael,A.J., & Rowland-Jones,S.L. (2002) Memory CD8+ T cells vary in differentiation phenotype in different persistent virus infections. Nat.Med., 8, 379- 385.

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258 Publications

Publications

Herrero-Martinez E. Hepatitis B and hepatitis C co-infection in patients with HIV. Reviews in Medical Virology 2001 11, Issue 4 253-270.

Herrero-Martinez E, Sabin CA, Evans JG, Griffioen A, Lee CA and Emery VC. The prognostic value of a single hepatitis C (HCV) viral load measured early post HIV seroconversion. Journal of Infectious Diseases 2002.186 470-6.

Sabin CA, Emery VC, Devereux HE, Griffioen A, Bishop J, Yee T-T, Herrero-Martinez E and Lee CA. Longitudinal analysis of hepatitis C virus (HCV) RNA levels in a cohort of HIV seronegative men with haemophilia infected with HCV. Journal of Medical Virology 2002. 68 68-75.

Sabin CA, Griffioen A, Yee T-T, Emery VC, Herrero-Martinez E, Phillips AN and Lee CA. Markers of HIV disease progression in haemophilic men co-infected with hepatitis C virus: strong relationship between albumin levels and progression to AIDS and survival. Lancet 2002. laMceZ 2002, 360 1546-1551.

Herrero-Martinez E, Sabin CA, Lee CA, Jones IM, Pillay D and Emery VC. The effect of highly active antiretroviral therapy for HIV on the anti-HCV specific humoral immune response. Submitted to the Journal of Medical Virology.

Published abstracts

Herrero-Martinez E, Devereux HL, Sabin CA, Bishop JA, Lee CA, Emery VC. Abstract COOl: Development of a quantitative competitive RT-PCR assay for hepatitis C virus. Antiviral Therapy 2000; 5 (Suppl 1):PAGE C.3

Herrero-Martinez E, Sabin CA, Emery VC, Griffioen A, Devereux HL, Bishop JA, Yee T- T, Lee CA, Abstract C l05: Longitudinal study of hepatitis C virus (HCV) RNA levels in a cohort of HIV seronegative men with haemophilia infected with HCV. Antiviral Therapy 2000; 5 (Suppl 1):PAGE C.56

Herrero-Martinez E, Sabin CA, Emery VC, Lee CA, Abstract B-96: The prognostic value of a single Hepatitis C Virus (HCV) RNA load measured early post HIV seroconversion. Haemophilia 2002; 8 (No 4) p.529.

Conference presentations

Herrero-Martinez E, Devereux HL, Sabin CA, Bishop JA, Lee CA, Emery VC. Abstract COOl: Development of a quantitative competitive RT-PCR assay for hepatitis C virus. The 10*'’ International Symposium on Viral Hepatitis and Liver Disease, Atlanta Apr. 9- 13, 2000

Herrero-Martinez E, Sabin CA, Emery VC, Griffioen A, Devereux HL, Bishop JA, Yee T- T, Lee CA, Abstract Cl 05: Longitudinal study of hepatitis C virus (HCV) RNA levels in a cohort of HIV seronegative men with haemophilia infected with HCV. The 10* International Symposium on Viral Hepatitis and Liver Disease, Atlanta Apr. 9- 13, 2000

Herrero-Martinez E, Sabin CA, Emery VC and Lee CA, The prognostic value of a single HCV RNA load measured early post HIV seroconversion. XXV International Congress of the World federation of Haemophilia, Seville May 19-24 2002

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