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DEVELOPMENT OF REAL-TIME PCR ASSAY FOR THE EARLY DIAGNOSIS, TREATMENT RESPONSE PREDICTION AND MONITORING OF

NASOPHARYNGEAL CARCINOMA (NPC) DISEASE

MAI ABDEL HALEEM A. ABUSALAH

UNIVERSITI SAINS MALAYSIA

2021

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DEVELOPMENT OF REAL-TIME PCR ASSAY FOR THE EARLY DIAGNOSIS, TREATMENT RESPONSE PREDICTION AND MONITORING OF

NASOPHARYNGEAL CARCINOMA (NPC) DISEASE

by

MAI ABDEL HALEEM A. ABUSALAH

Thesis submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

July 2021

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ACKNOWLEDGEMENT

My PhD path is the gift of God the Almighty, Allah's mercy and blessings. This PhD thesis is the product of the commitment and help of Allah and of many people to whom i am most thankful. First and foremost, I would like to thank my family. I have the privilege of having a wonderful and supportive family. I would like to inscribe my thesis to my lovely father, Dr. Abdul Haleem Abusalah, my wonderful mother, and my brothers and sisters, Manal, Suzana, Dr. Mohamad, Eng. Ahmed, Dr. Abdul Razaq for their support, encouragement and patients during my study. My warm and sincere thanks to my supervisor, Assoc. Prof. Dr. Chan Yean Yean, and my coaches, Assoc.

Prof. Dr. Siti Asma Binti Hassan, Assoc. Prof. Dr. Norhafiza Mat Lazim and Prof. Dr.

Baharudin. Abdullah. It was a privilege to work with all of them. I hope to be able to work with them again soon. I would also like to thank my great professor Dr. Asem Ata Al-Shehabi (The University of Jordan, Jordan), Dr. Kueh Yee Cheng (USM, Malaysia), AP. Dr. Mu'taman Jarrar (IAU, Saudi Arabia) and Mohammed A. M.

Alhoot (MSU, Malaysia) for their efforts and times in my study. My sincere gratitude and appreciation to my colleagues who makes this journey more joyful, less lonely and provided me with a friendly and inspiring environment to work, including Dr. Saleem, Dr. Foo, Lee, Ridhuan, Mohamad Hatamlih, Ahmed, Afifah, Amira, Nik Hafiza, Nik Zuraina, Yasmin, Shafiqah, Jana Khalil, Ira and many more. I wish you all the best and hope that our friendship lasts forever. I would also like to acknowledge all lecturers, lab technologists from the Department of Medical Microbiology and Parasitology and staff for their helping and support during in different aspect during my PhD journey. My acknowledgement also to Bridging Grant from USM, grant number [304/PPSP/6316129] for the research funding support. Thank you

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TABLE OF CONTENTS

ACKNOWLEDGEMENT ... ii

TABLE OF CONTENTS ... iiii

LIST OF TABLES ... xi

LIST OF FIGURES ... xvi

LIST OF SYMBOLS ... xx

LIST OF ABBREVIATIONS ... xxi

ABSTRAK………..………… xxiv

ABSTRACT……… xxvi

CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW ... 1

1.1 Epstein–Barr virus (EBV) ... 1

1.2 EBV structure and genome ... 2

1.3 EBV transmission and life cycle ... 9

1.4 EBV infection stages ………...13

1.4.1 EBV lytic infection……….13

1.4.2 EBV latent infection………...16

1.4.2(a) EBV latency patterns………...17

1.4.3 EBV-associated diseases………...20

1.5 Nasopharyngeal carcinoma (NPC) ... 24

1.5.1 Epidemiology of NPC………24

1.5.2 Anatomy of nasopharynx………...32

1.5.3 Etiological agents and risk factors of NPC………34

1.5.4 Clinical features, staging and diagnosis of NPC………38

1.5.4(a) Clinical features………...38

1.5.4(b) Staging and classification of NPC…...………....41

1.5.4(c) Diagnosis and screening of NPC ………....49

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1.5.5 Prognosis of NPC………...51

1.5.6 Treatment of NPC………..57

1.6 Epstein-Barr virus and nasopharyngeal carcinoma …...……….64

1.6.1 EBV entry and establishment of latent infection in NPC…………..64

1.6.2 EBV expression and pathogenesis in NPC………67

1.6.3 Role of Latent Membrane Protein 1 (LMP1) in development of NPC…….………...75

1.6.4 LMP1 30 bp deletion and NPC………..87

1.7 Laboratory diagnosis of EBV in NPC ... 95

1.7.1 Clinical utility of circulating EBV DNA in NPC screening and management………..102

1.7.2 Polymerase chain reaction (PCR) molecular methods……….109

1.7.3 Hydrolysis probe-based real-timePCR (qPCR)….………...121

1.8 Rationale of the study ... 128

1.9 The objective of the study ... 131

1.10 Overview of the study ... 132

CHAPTER 2 MATERIAL AND METHOD ... 133

2.1 Materials ... 133

2.1.1 General equipment and material………133

2.1.1(a) Reagents and chemical………..133

2.1.1(b) Kits and consumable ………133

2.1.1(c) Equipment……….133

2.1.2 Preparation of reagent and materials……….133

2.1.2(a) Preparation of 0.5 M ethylenediaminetetraacetic acid disodium salt (EDTA) solution (pH8.0)………...133

2.1.2(b) Preparation of 0.5X Tris Borate EDTA(TBE) buffer…...134

2.1.1(c) Electrophoresis agarose gel preparation ………..134

2.1.1(d) Preparation of 100 bp plus DNA ladder working solution…….………134

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2.1.1(e) Preparation of 1X Phosphate Buffered Saline (PBS)

stock solution………....135

2.1.1(f) Preparation of 25 mg/mL Proteinase K…………....…...135

2.2 Study design ………..135

2.2.1 Ethical approval………....136

2.2.2 Sample size calculation………....136

2.2.3 Collection of clinical samples………..138

2.2.4 Inclusion criteria………...138

2.2.5 Exclusion criteria………..139

2.2.6 Genomic DNA extraction from WB samples………...139

2.2.7 Genomic DNA extraction from tissue samples………....140

2.3 Method ………..………....141

2.3.1 i-qPCR assay development………..141

2.3.1(a) Sequencing of archive samples……….142

2.3.1(b) Synthetic DNA designing………..143

2.3.1(c) Designing of oligonucleotide……….144

2.3.1(d) Designing of the gap-filling mutant primer………...144

2.3.1(e) Designing of non-extendable blocking oligonucleotide...147

2.3.1(f) Bioinformatic analysis of oligonucleotide……….148

2.3.1(g) Oligonucleotide stock solutions’ reconstitution………...148

2.3.1(h) Oligonucleotide working solutions’ preparation...……...149

2.3.1(i) Reconstitution of synthetic dsDNA stock solutions……...149

2.3.1(j) Optimization of conventional PCR parameters……..……149

2.3.1.1(j)(i) Optimization of multi-points degenerative blocker………...………..………149

2.3.1(k) Optimization of i-qPCR assay parameters………..150

2.3.1.1(k)(i) Optimization of annealing temperature....150

2.3.1.1(k)(ii) Optimization of oligonucleotides’ concentration ………..….………....151

2.3.1(l) The functionality of the optimized i-qPCR assay………..152

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2.3.2 Analytical evaluation of the developed i-qPCR assay………....152

2.3.2(a) Analytical sensitivity……….153

2.3.1.2(a)(i) Limit of detection (LOD)…………..…....153

2.3.2(b) PCR Efficiency and Linearity………....155

2.3.2(c) Analytical specificity……….156

2.3.3 Diagnostic evaluation of the developed i-qPCR assay………...158

2.3.3(a) Diagnostic sensitivity……….158

2.3.3(b) Diagnostic specificity……….159

2.3.3(c) Positive predictive value (PPV)………...159

2.3.3(d) Negative predictive value (NPV)………...159

2.3.4 Clinical epidemiology of NPC patients………...160

2.3.4(a) Demographic data of NPC patients………...160

2.3.4(b) Clinical data and outcome of NPC patients.………..160

2.3.4(c) Treatment of NPC patients………....161

2.3.5 Statistical analysis………..162

2.3.5(a) Descriptive analysis………...162

2.3.5(b) Association statistical analysis………..162

2.3.5(c) Correlation statistical analysis………...163

CHAPTER 3 RESULTS AND DISCUSSIONS ………164

3.1 i-qPCR assay development ... 164

3.1.1 The gene of interest selection and sequence alignment…………...165

3.1.2 Oligonucleotide design………167

3.1.2(a) The design and characteristics of primers and multi- points degenerative blocker………...167

3.1.2(b) The design and characteristics of probe sequences.…….172

3.1.2(c) The potential formation of self-dimerisation and hetero- dimerisation between oligonucleotides………...174

3.1.2(d) Characteristics and size of the amplicon………...176

3.2 Genomic DNA template’s preparation ... 177

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3.3 Synthetic DNA fragments’ preparation (30 bp deletion and IAC

templates)………..180 3.4 Optimization of conventional PCR parameters ... ………183

3.4.1 Optimization of multi-points degenerative blocker concentration..183 3.5 The monoplex i-qPCR’s development for 30 bp deletion tumour marker

detection ... 185 3.5.1 The functionality of the monoplex i-qPCR for the detection of 30 bp deletion tumour marker………...186 3.5.2 Preliminary specificity testing of the monoplex i-qPCR for the 30 bp deletion tumour marker detection………..188 3.5.3 Optimization of the developed monplex i-qPCR……….190 3.5.3(a) Optimization of annealing temperature.……….…...190 3.5.3(b) Optimization of primer concentration for 30 bp deletion

tumour marker………...191 3.5.3(c) Optimization of probe concentration for 30 bp deletion tumour marker………...192 3.5.3(d) Optimization of MT gBLOCK and WT gBLOCK for 30 bp deletion tumour marker………..……….193 3.6 The monoplex i-qPCR’s development for IAC detection ……….196

3.6.1 The monoplex IAC assay’s functionality………196 3.6.2 Testing of preliminary specificity of monoplex IAC assay……….198 3.6.3 Optimization of IAC template concentration………..200 3.6.4 Efficiency, linearity and limit of detection (LOD)………..202 3.7 The duplex i-qPCR’ development for 30 bp deletion tumour marker

detection.………...204 3.7.1 The functionality of the developed duplex i-qPCR……….204 3.7.2 Limit of detection and Cq cut-off value of developed i-qPCR

assay…….………207

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3.7.3 The comparison of linearity and efficiency between duplex and

monoplex i-qPCR ssay.……….………...212

3.7.4 Amplification of 30 bp deletion tumour marker in the presence of IAC….………..214

3.7.5 The analytical specificity of the developed i-qPCR……….214

3.7.6 Diagnostic evaluation of the developed i-qPCR………..216

3.7.7 Treatment response prediction of the developed i-qPCR………….219

3.8 Clinical epidemiology of NPC patients ……….224

3.8.1 Descriptive statistics……….224

3.8.1(a) Demographic data of NPC patients………....224

3.8.1.1(a)(i) Age, race and gender……….………..224

3.8.1(b) Clinical data of NPC patients………...228

3.8.1.1(b)(i) Primary symptoms and previous family history of NPC.……….228

3.8.1.1(b)(ii) WHO types of NPC………...……...228

3.8.1.1(b)(iii) Anatomic and TNM staging of NPC patients………....231

3.8.1.1(b)(iv) Treatment and prediction of treatment response in NPC……….…………...234

3.8.1.1(b)(v) Detection of 30 bp deletion tumour marker by the developed i-qPCR and conventional PCR methods………...236

3.8.2 Association statistics………...239

3.8.2(a) The association between the NPC correlated prognostic factors and clinician treatment response prediction……..239

3.8.2(b) The association between the NPC correlated prognostic factors and Cq value of 30 bp deletion tumour marker…...241

3.8.2(c) The association between the NPC correlated prognostic factors and 30 bp deletion tumour marker (detected by conventional PCR)...246

3.8.2(d) Correlation statistics………...……251

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3.8.1.2(d)(i) Correlation between WB and tissue

samples from same NPC patient………..251

CHAPTER 4 GENERAL DISCUSSION……….253

4.1 The i-qPCR’s analytical sensitivity ………...258

4.2 The i-qPCR’s analytical specificity ... .268

4.3 Impact of PCR cycle ... 271

4.4 The application of internal amplification control (IAC) ... 273

4.5 The i-q PCR assay’s clinical evaluation ... 278

4.6 Clinical epidemiology ... 284

4.7 Association and correlation statistics ... 291

CHAPTER 5 CONCLUSION,LIMITATION AND FUTURE DIRECTION……….………...312

REFERENCES………...317 APPENDIX A: REAGENTS AND CHEMICALS USED IN THIS STUDY APPENDIX B: KITS USED IN THIS STUDY

APPENDIX C: EQUIPMENT USED INTHIS STUDY APPENDIX D: CONSUMABLES USED IN THIS STUDY APPENDIX E: DATA COLLECTION SHEET

APPENDIX F: THE DETECTION OF 30 BP DELETION IN WB SAMPLES FROM NON-NPC PATIENTS BY CONVENTIONAL PCR AND

DEVELOPED I-QPCR ASSAY

APPENDIX G: THE DETECTION OF 30 BP DELETION IN WB SAMPLES FROM NON-NPC PATIENTS BY CONVENTIONAL PCR AND

DEVELOPED I-QPCR ASSAY

APPENDIX H: THE DETECTION OF 30 BP DELETION IN WB SAMPLES FROM HEALTHY INDIVIDUALS BY CONVENTIONAL PCR AND

DEVELOPED I-QPCR ASSAY

APPENDIX I: THE DETECTION OF 30 BP DELETION IN WB SAMPLES FROM NPC PATIENTS BY CONVENTIONAL PCR AND DEVELOPED I- QPCR ASSAY AND ITS RESPONSE TREATMENT PREDICTION

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APPENDIX J: THE DETECTION OF 30 BP DELETION IN TISSUE SAMPLES FROM NPC PATIENTS BY CONVENTIONAL PCR AND DEVELOPED I-QPCR ASSAY AND ITS RESPONSE TREATMENT PREDICTION

LIST OF PUBLICATIONS CONFERENCE

VIVA VOCE EXAMINATION COMMENTS

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LIST OF TABLES

Page Table 1.1 The EBV proteins’ function, EBV latency pattern and

associated malignancy.. ... 19

Table 1.2 Diseases associated with EBV infection ... 22

Table 1.3 Possible risk factors of NPC ... 35

Table 1.4 Histopathological Classification of Nasopharyngeal Carcinoma ... 43

Table 1.5 The frequency of LMP1 30 bp deletion in different studies ... 91

Table 1.6 Disadvantages and advantages of several EBV diagnostic methods ... 96

Table 2.1 The summary of sample size calculation for sensitivity and specificity testing. ... 138

Table 2.2 List of primers for sequencing ... 142

Table 2.3 Conventional PCR mixture for sequencing used in this study ... 143

Table 2.4 Conventional PCR cycling condition ... 143

Table 2.5 Conventional PCR cycling condition ... 150

Table 2.6 The i-qPCR cycling condition ... 151

Table 2.7 Optimized i-qPCR cycling condition. ... 152

Table 2.8 The i-qPCR mixture used in this study. ... 154

Table 2.9 DNA copies number for synthetic DNA. ... 155

Table 2.10 The list of ATCC strains and clinical isolates used in this study. .... 157

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Table 3.1 The list of primers and multi-points degenerative blocker

criteria, characteristics and sequences in this study ... 169

Table 3.2 The description of the presence of a hairpin structure in primers and multi-points degenerative blocker at ≥ 60 C and ≤ 60 C. ... 171

Table 3.3 List of probes criteria, characteristics and sequences in this study .. 173

Table 3.4 The presence of hairpin loop structure among probes at ≤ 60 C and ≥ 60 C ... 174

Table 3.5 Homo- and Hetero-dimerization between primer pairs and primer pairs versus blocker ... 175

Table 3.6 Homo- and Hetero-dimerization between primers, blocker and probes ... 176

Table 3.7 Homo- and Hetero-dimerization between probes ... 176

Table 3.8 Size and respective characteristics of the amplicons ... 177

Table 3.9 The i-qPCR mixture was used in this study ... 185

Table 3.10 Annealing temperature optimization ... 191

Table 3.11 LMP1 30 bp deletion tumour marker primers’ optimization ... 192

Table 3.12 LMP1 30 bp deletion tumour marker probe’s optimization ... 193

Table 3.13 Performance of IAC monoplex assay ... 203

Table 3.14 Sensitivity of IAC monoplex assay ... 203

Table 3.15 The i-qPCR mixture used in this study ... 205

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Table 3.16 Mean threshold value (Cq), coefficient of variation (CV) and standard deviation (SD) for duplex developed i-qPCR to

determine the LOD of 30 bp deletion tumour marker ... 209 Table 3.17 The Cq cut-off values of 30 bp deletion tumour marker in WB

NPC samples to detect the suspected and newly diagnosed

NPC patients ... 210 Table 3.18 The Cq cut-off values of 30 bp deletion tumour marker in

tissue NPC samples to detect the suspected and newly

diagnosed NPC patients ... 210 Table 3.19 The Cq cut-off values of 30 bp deletion tumour marker in WB

samples of NPC patients for treatment response prediction ... 210 Table 3.20 The Cq cut-off values of 30 bp deletion tumour marker in

tissue samples of NPC patients for treatment response

prediction... 210 Table 3.21 The cut-off values of EBV DNA in various types of samples

among NPC patients in different studies ... 211 Table 3.22 The comparison between the performance of developed

duplex and performance of monoplex i-qPCR for 30 bp

deletion tumour marke. ... 213 Table 3.23 Amplification of 30 bp deletion tumour marker in the with and

without IAC target... 214 Table 3.24 The analytical specificity of the developed duplex i-qPCR

assay among the extended spectrum of microorganisms ... 215

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Table 3.25 The analytical specificity of the developed duplex i-qPCR assay among biopsy tissue and FNA samples from NPC

patients ... 216 Table 3.26 The diagnostic evaluation of the i-qPCR to detect NPC patients .... 218 Table 3.27 Distribution of treatment response prediction of the i-qPCR

result of 30 bp deletion tumour marker against clinician

treatment response prediction ... 220 Table 3.28 Pattern of 30 bp deletion variant was detected by conventional

PCR among NPC patients, non-NPC patients and healthy

individuals ... 237 Table 3.29 Association between NPC correlated prognostic factors with

clinician treatment response prediction of NPC patients

(n=34). ... 240 Table 3.30 Association between NPC correlated prognostic factors with

categorical Cq of 30 bp deletion tumour marker in NPC WB

samples (n=34) ... 243 Table 3.31 Association between NPC correlated prognostic factors with

Categorical Cq of 30 bp deletion tumour marker in NPC tissue

samples (n=7) ... 244 Table 3.32 Association between treatment response prediction based on

Cq values of 30 bp deletion tumour marker and clinician

treatment response prediction in NPC WB samples (n=34) ... 245

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Table 3.33 Association between treatment response prediction based on Cq values of 30 bp deletion tumour marker and clinician

treatment response prediction in NPC tissue samples (n=7). ... 245 Table 3.34 Association between NPC correlated prognostic factors with

30 bp deletion tumour marker variant detected in NPC WB

samples by conventional PCR (n=34) ... 248 Table 3.35 Association between NPC correlated prognostic factors with

30 bp deletion tumour marker variant detected in NPC tissue

samples by conventional PCR (n=7) ... 250 Table 3.36 Correlation between WB and tissue samples from the same

NPC patient (n=7). ... 252

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LIST OF FIGURES

Page

Figure 1.1 Structure of EBV. ... 4

Figure 1.2 The Epstein–Barr virus genome. ... 5

Figure 1.3 BamHI restriction-endonuclease map of prototype B95.8 genome with open reading frames location for the EBV latent proteins. ... 8

Figure 1.4 EBV life cycle ... 11

Figure 1.5 Latent and lytic phases of EBV life cycle ... 15

Figure 1.6 Global distribution of the incidence of NPC in 2018 ... 26

Figure 1.7 Standardized incidence and mortality rates for NPC in Asia in 2012. ... 28

Figure 1.8 The incidence and mortality rate of NPC among males and females in world regions, 2018. ... 30

Figure 1.9 TNM staging of NPC ... 48

Figure 1.10 Theory of functions of EBV infection and genomic changes in NPC development ... 74

Figure 1.11 Molecular interactions and signalling pathways associated with LMP1 in NPC carcinogenesis ... 81

Figure 1.12 The functional domains and schematic presentation of the del- LMP1 and wild type LMP1 ... 89

Figure 1.13 qPCR assay’s types based on fluorescent molecules ... 113

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Figure 1.14 TaqMan hydrolysis probes’ mechanism of action and structure ... 116 Figure 1.15 Structure and action mechanism of snake assay. ... 118 Figure 1.16 Standard TaqMan hydrolysis probe structure ... 122 Figure 1.17 Schematic of DNA target amplification in TaqMan hydrolysis

assay ... 124 Figure 1.18 Reporter and quencher dyes used in qPCR ... 127 Figure 2.1 Alignment of reference strain (V01555.2) (first line) with 25

sequences of archive tissue and FNA samples from NPC

patients... ... 146 Figure 3.1 Schematic diagram of the i-qPCR (innovative special features

of the gap-filling mutant primer with multi-points degenerative reverse primer blocker) EBV LMP1 30 bp

deletion assay ... 168 Figure 3.2 Gel electrophoresis of extracted genomic DNA (Lane1, 2, 3).

Lane L is GeneRuler™ 100 bp Plus DNA Ladder. ... 179 Figure 3.3 Gel electrophoresis of IAC gBLOCK (Lane1), WT gBLOCK

(Lane 2), MT gBLOCK (Lane 3). Lane L is GeneRuler™ 100

bp Plus DNA Ladder ... 179 Figure 3.4 The IAC gBLOCK sequence used in the current study ... 181 Figure 3.5 Gel electrophoresis of synthetic IC gBLOCK (Lane 1). Lane

N is NTC and Lane L is GeneRuler™ 100 bp Plus DNA

Ladder ... …181 Figure 3.6 The sequences of WT gBLOCK, and MT gBLOCK used in

this study ... 182

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Figure 3.7 Gel electrophoresis of synthetic WT gBLOCK (Lane 2) and MT gBLOCK (Lane 3). Lane 2 is NTC and Lane L is

GeneRuler™ 100 bp Plus DNA Ladder ... 182

Figure 3.8 Gel electrophoresis of 40:1 ratio of multi-points degenerative blocker: gap-filling mutant primer. Lane1, WT gBLOCK; Lane 2, MT gBLOCK; Lane 3, MT NPC archive sample; Lane 4, WT NPC archive sample; Lane L, GeneRuler™ 100 bp Plus DNA Ladder ... 184

Figure 3.9 Amplification of synthetic MT gBLOCK in monoplex assay. ... 187

Figure 3.10 Preliminary specificity testing of the developed monolplex i- qPCR for detecting of 30 bp deletion tumour marker. A) Detecting of 30 bp deletion tumour marker in healthy and NPC WB samples. B) Detecting of 30 bp deletion tumour marker in WT and MT NPC WB samples ... 189

Figure 3.11 Optimization of MT gBLOCK and WT gBLOCK concentrations. A) MT gBLOCK concentrations (20 pg - 2 fg per reaction). B) WT gBLOCK concentrations (20 fg - 20 ag per reaction) .... ... 195

Figure 3.12 Amplification of synthetic IAC gBLOCK in monoplex assay ... 197

Figure 3.13 Preliminary specificity testing of monoplex IAC assay. ... 199

Figure 3.14 Optimization of IAC gBLOCK concentrations... 201

Figure 3.15 Overall performance of IAC monoplex assay ... 203

Figure 3.16 Preliminary functionality of developed duplex i-qPCR ... 206

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Figure 3.17 Standard curve of the developed duplex and monoplex i-qPCR for 30 bp deletion tumour marker. A) Standard curve of the developed duplex i-qPCR, B) Standard curve of monoplex i-

qPCR. ... 213

Figure 3.18 Age distribution of NPC patients ... 226

Figure 3.19 The frequency of NPC patients based on age categories ... 226

Figure 3.20 Race distribution of NPC patients ... 227

Figure 3.21 Gender distribution of NPC patients ... 227

Figure 3.22 WHO types distribution of NPC patients ... 230

Figure 3.23 WHO types distribution of NPC patients based on age categories .. 230

Figure 3.24 Anatomic staging distribution of NPC patients ... 232

Figure 3.25 TNM staging distribution of NPC patients. A) T staging frequency among NPC patients. B) N staging frequency among NPC patients. C) metastatic frequency among NPC patients ... 233

Figure 3.26 Treatment response distribution of NPC patients with metastasis ... 235

Figure 3.27 Treatment response distribution of NPC patients with no metastasis ... 235

Figure 3.28 The distribution of Cq of 30 bp deletion tumour marker among NPC patients. A) distribution of Cq of 30 bp deletion tumour marker in NPC WB samples. B) distribution of Cq of 30 bp deletion tumour marker in NPC tissue samples ... 238

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LIST OF SYMBOLS

+ Plus

- Minus

× Multiplication

÷ Division

± Plus-minus

⁓ Approximately

% Percentage

< Less than

> More than

≤ Less than or equal

≥ More than or equal

℃ Degree Celcius

β Beta

™ Trade mark sign

® Registered sign

µ Micro sign

λ Wavelength

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LIST OF ABBREVIATIONS

A260/A230 Absorbance at 260 nm per absorbance at 230 nm A260/A280 Absorbance at 260 nm per absorbance at 280 nm AIDS

BART BL Bp BZLF1

Acquired immunodeficiency syndrome BamHI-A rightward transcripts

Burkitt’s lymphoma Base pair

BamHI Z fragment leftward open reading frame 1 CCRT Concurrent chemoradiation therapy

Cq CT

Cycle threshold

Computed Tomography DNA

DFS DMFS EA EBER EBNA EBV

Deoxyribonucleic acid Disease-free survival

Distant metastasis-free survival Early antigen

EBV-encoded small RNAs EBV nuclear antigen Epstein–Barr virus

FDG-PET Fluorodeoxyglucose-positron emission tomography FFS Failure-free survival

fg Femtogram

FNA Fine-needle aspiration

G Gram

HL HLA IAC i-qPCR IM IMRT JNK KSCC

Hodgkin’s lymphoma Human leukocyte antigen Internal amplification control

Innovative real-time polymerase chain reaction Infectious mononucleosis

Intensity-modulated radiation therapy c-Jun N-terminal kinases

keratinizing squamous cell carcinoma

L Liter

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xxii LA locoregionally advanced LCL Lymphoblastoid cell lines LMP Latent membrane protein

LRFFS Locoregional failure–free survival

M Molar

MAPK Mitogen-activated protein kinases

Min Minute

mg Milligram

mg/mL Milligram per milliliter

MHC Major histocompatibility complex

µL Microliter

mL Milliliter

µm Micromole

mmNPC Metachronous metastasis MRI Magnetic resonance imaging

MT Mutant type

NAC Nasopharyngeal adenocarcinomas NF-κB Nuclear factor κB

Ng Nonaogram

NHL Non-Hodgkin’s lymphoma NK Natural killer

NKC Non-keratinizing carcinoma

NKDC Non-keratinizing differentiated carcinoma NKUC Non-keratinizing undifferentiated carcinoma

Nm Nanometer

NPAC Nasopharyngeal papillary adenocarcinoma NPC Nasopharyngeal carcinoma

OHL Oral hairy leukoplakia OS Overall survival

PCR Polymerase chain reaction PFS Progression-free survival

Pg Picogram

PTLD Posttransplant lymphoproliferative disorder qPCR Real-time polymerase chain reaction

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xxiii RARβ2 Retinoic acid receptor beta 2

RASSF1A Ras association domain family protein1 isoform A RFS Recurrence–free survival

RR Total treatment response rate

RT Radiotherapy

SCC Squamous cell carcinoma

Sec Second

smNPC Synchronous metastasis NPC Taq Thermus aquaticus

UC Undifferentiated carcinoma

UCNT Undifferentiated carcinoma nasopharyngeal type UV Ultraviolet

VCA Viral capsid antigen v/v Volume per volume

WB Whole blood

WT Wild type

w/v Weight per volume

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PEMBANGUNAN TINDAK BALAS BERANTAI POLIMERASE MASA- NYATA BAGI PENGESANAN AWAL, RAMALAN TINDAKBALAS RAWATAN DAN PEMANTAUAN PENYAKIT KANSER PANGKAL

HIDUNG/ NASOFARINKS (NPC)

ABSTRAK

Karsinoma Nasofarinks (NPC) adalah karsinoma sel skuamos tanpa- limfomatosa yang berlaku pada lapisan sel epitelium yang menutupi permukaan nasofarinks. NPC dianggap sebagai cabaran diagnostik bagi doktor kerana kesukaran pemeriksaan nasofarinks dan gejala yang tidak spesifik. Virus Epstein – Barr (EBV) dikait rapat dengan NPC. Selain itu, delesi 30 bp LMP1 pada EBV didapati memainkan peranan penting dalam peningkatan tingkah laku onkogenik pada sel yang dijangkiti, seterusnya menghasilkan fenotip tumour-berkaitan EBV yang lebih agresif.

Oleh itu, kajian ini bertujuan untuk membangunkan kaedah qPCR berasaskan proba hidrolisis Taqman yang inovatif untuk mengesan delesi 30 bp LMP1 pada EBV menggunakan sampel darah dari pesakit NPC. Kaedah yang dibangunkan ini akan membantu doktor dalam diagnosis awal, ramalan tindak balas rawatan, memahami sejauh mana keberkesanan rawatan dan pemantauan susulan selepas rawatan pesakit NPC. Dalam kaedah i-qPCR yang dibangunkan ini, primer, proba dan penyekat degeneratif berbilang titik yang specifik bagi mengesan mutan telah direkabentuk.

Parameter qPCR berasaskan proba hidrolisis Taqman untuk mengesan delesi 30 bp LMP1 pada EBV juga dioptimumkan. Tambahan pula, kawalan dalaman diasimilasikan bagi mengetepikan hasil keputusan negatif yang salah. Data demografi pesakit NPC dikumpulkan dan digunakan dalam analisis statistik kajian ini.

Pengesahan ujian dicapai berdasarkan garis panduan MIQE. Kespesifikan analitikal bagi kaedah yang telah dibangunkan dilakukan dengan menggunakan pencairan bersiri

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10 kali ganda MT gBLOCK (DNA sintetik). Kepekaan analitikal dinilai menggunakan 48 DNA genomik bakteria, kulat dan virus, serta 12 DNA genomik yang telah diekstrak daripada tisu biopsi arkib dan sampel aspirasi jarum halus pesakit NPC.

Penilaian diagnostik kaedah yang dibangunkan dilakukan pada 109 spesimen prospektif dari pesakit NPC, pesakit kanser bukan NPC dan individu yang sihat. LOD bagi kaedah yang telah dibangunkan ini adalah 173 salinan/ujian. Penilaian diagnostik menunjukkan 100% kespesifikan, 83.3% kepekaan, 100% PPV dan 98.7% NPV.

Hubungan yang signifikan didapati antara ramalan tindak balas rawatan doktor dan nilai Cq delesi 30 bp dalam kajian ini (nilai P = 0.033). Kesimpulannya, kajian ini berjaya mengembangkan i-qPCR untuk pengesanan awal penanda tumour delesi 30 bp dengan kepekaan dan kespesifikan yang tinggi bagi membantu doktor dalam ramalan tindak balas rawatan dan menentukan keberkesanan rawatan di kalangan pesakit NPC.

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DEVELOPMENT OF REAL-TIME PCR ASSAY FOR THE EARLY DIAGNOSIS, TREATMENT RESPONSE PREDICTION AND

MONITORING OF NASOPHARYNGEAL CARCINOMA (NPC) DISEASE

ABSTRACT

Nasopharyngeal carcinoma (NPC) is a non-lymphomatous squamous cell carcinoma that develops in the epithelial cells layer covering the surface of the nasopharynx. NPC is considered a diagnostic challenge to clinicians due to the difficulty in nasopharynx examination, and non-specific symptoms. The Epstein–Barr virus (EBV) is well-associated with NPC. In addition, EBV LMP1 30 bp deletion was shown to play a vital role in enhanced oncogenic behaviour of EBV infected cells and results in more aggressive EBV-related tumour phenotypes. Therefore, this study intended to develop an innovative Taqman hydrolysis probe-based qPCR to detect the EBV's LMP1 30 bp deletion using whole blood samples from NPC patients. This developed assay will help the clinicians in early diagnosis, treatment response prediction, understand the extent of treatment effectiveness, and follow-up monitoring of NPC patients after treatment. In this developed i-qPCR, the mutant-specific primers, probes and multi-points degenerative blocker were designed. The Taqman hydrolysis probe-based qPCR parameters to detect the EBV's LMP1 30 bp deletion were also optimised. Internal control (IAC) was incorporated to rule out the false negative result.

The demographic data of NPC patients were collected and used in the statistical analysis of this study. The assay validation was accomplished based on MIQE guidelines. The developed assay's analytical sensitivity was performed using 10-fold serial dilutions of MT gBLOCK (synthetic DNA). The analytical specificity was evaluated using 48 bacterial, fungal and virus genomic DNA and 12 extracted genomic

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DNA from archived biopsy tissue and fine-needle aspiration samples of NPC patients.

The diagnostic evaluation of the developed assay was performed on 109 prospective specimens from NPC patients, non-NPC cancer patients and healthy individuals. The LOD of this developed assay was 173 copies/assay. The diagnostic evaluation showed 100% specificity, 83.3% sensitivity, 100% PPV and 98.7% NPV. A significant association was found between clinician treatment response prediction and Cq values of 30 bp deletion in this study (P-value= 0.033). In conclusion, this study was effective in developing an i-qPCR assay for early detection of 30 bp deletion tumour marker with high specificity and sensitivity, to help clinicians in treatment response prediction, and determine treatment effectiveness among NPC patients.

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1 CHAPTER 1

INTRODUCTION AND LITERATURE REVIEW

1.1 Epstein Barr virus (EBV)

Epstein Barr virus (EBV) is also nominated as designated human herpesvirus 4 (HHV-4), and EBV is a member of the Lymphocryptovirus genus and classified within the gammaherpesviruses subfamily and Herpesviridae family (Ooka, 1985;

Kliszczewska et al., 2017). In 1964, EBV was first discovered in a B lymphocyte cell line from African Burkitt’s lymphoma (BL) patient by Epstein, Achong, and Barr (Epstein, 1964; Cohen, 2000; Crawford, 2001). In 1968, EBV was discovered as a causative agent of heterophile-positive infectious mononucleosis (IM) (Henle et al., 1968; Cohen, 2000). Two years later, in 1970, EBV DNA was found in tissue samples from nasopharyngeal carcinoma (NPC) patients (Zur Hausen et al., 1970; Cohen, 2000; Young et al., 2016). Moreover, after ten years later, in the 1980s, the association between EBV with oral hairy leukoplakia (OHL), in the acquired immunodeficiency syndrome (AIDS) and non-Hodgkin’s lymphoma (NHL) patients was found (Ziegler et al., 1982; Greenspan et al., 1985). From that time, EBV DNA has been found in tissue biopsy samples from different types of cancer such as Hodgkin’s lymphoma (HL) and T-cell lymphomas (Jones et al., 1988; Cohen, 2000; Young et al., 2016).

Recently, EBV is a ubiquitous pathogen that has been estimated to be occurred in more than 90% of populations worldwide based on epidemiological studies (Smatti et al., 2018).

Two main EBV genotypes were detected in human, type 1 (EBV-1) and type 2 (EBV-2) (also known as types A and B, respectively), distinguished by the differences in sequences of EBV nuclear antigens’ coding genes (EBNA-2, EBNA-3A, EBNA-

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3B, and EBNA-3C) (IARC Working Group on the Evaluation, 2012; Smatti et al., 2018). Due to the homology of EBNA-2 between EBV-1 and EBV-2 reveals only 54%, distinguished between EBV types 1 and 2 can be done based on EBNA-2 (Smatti et al., 2018).

The ability of EBV-2 to immortalize and convert B cells into lymphoblastoid cell lines (LCL) was shown to be less efficient than EBV-1 and EBV-2 infected LCL was less variability than EBV-1 infected LCL (IARC Working Group on the Evaluation, 2012; Zanella et al., 2019). A distinctive geographical distribution was discovered between EBV-1 and EBV-2. The EBV-1 is the most prevalent globally, predominantly in North and South America, Asia, and Europe. However, EBV-2 is more frequent in Papua New Guinea, Alaska, and Central Africa, with a higher frequency was reported in Kenya. In fact, in these areas, dual infections with these EBV types were also discovered (Zanella et al., 2019)

1.2 EBV structure and genome

The EBV virion is approximately 122 – 180 nm in diameter and the EBV virion structure is like other herpesviruses structures (Kliszczewska et al., 2017; Smatti et al., 2018). EBV genome is linear, double-stranded DNA with a genome size of around 172-kb DNA molecule that encodes more than 85 genes (Thompson et al., 2004;

Santpere et al., 2014). The EBV DNA is wrapped with an inner toroid-shaped protein core, a nucleocapsid with 162 capsomers with about 100 nm in diameter, a protein tegument between the nucleocapsid and the envelope, and an outer envelope with external virus-encoded glycoprotein spikes for binding of cell surface receptor (Figure 1.1) (Thompson et al., 2004; Kieff et al., 2007; IARC Working Group on the Evaluation, 2012)

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The EBV genome includes series of around 3.1 kbp internal repeat sequences and around 0.54 kbp terminal direct repeats at both ends that also assist in dividing the EBV genome into unique sequence domains (short and long; US and UL, respectively) with the highest coding capacity (Figure 1.2) (Cheung et al., 1982; Thompson et al., 2004; Arvin et al., 2007). In addition, these repetitions can assist as an indicator for the source of EBV whether the infected cells were derived from the same progenitor cell or different progenitor cell (Smatti et al., 2018).

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Figure 1.1 Structure of EBV. The main components of EBV virion are the inner EBV genome core, nucleocapsid, an amorphous tegument, and an outer envelope with external EBV-encoded glycoproteins spikes.

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Figure 1.2 The Epstein–Barr virus genome.

A. Epstein–Barr virus (EBV) virion electron micrograph.

B. Diagram represents the EBV latent genes on the double-stranded viral DNA episome, EBV latent genes' transcription, and location. The orange color represents the origin of plasmid replication (OriP). The large green solid arrows represent each latent protein-encoding exon, and the arrows indicate the direction of genes transcription into EBV latent proteins. The latent proteins consist of the six nuclear antigens (EBNAs 1, 2, 3A, 3B and 3C, and EBNA-LP) and the three latent membrane proteins (LMP1, 2A and 2B). The transcription of all the EBNAs is started by either the Cp or Wp and Qp promoter. The top arrows (blue) represent EBER1 and EBER2 (the highly transcribed non-polyadenylated RNAs); their transcription is a consistent latent EBV infection feature (Adopted from Young et al., 2004).

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The major EBV capsid that is purified from enveloped virus consists of 68 kDa portal protein, 18 kDa small capsid protein, 30 kDa minor capsid protein, 40 kDa minor capsid protein-binding protein and 155 kDa major capsid protein, all in the expected ratios, based on 12 portal molecules per virion (Kieff et al., 2007). The EBV tegument consists of the 140 kDa large tegument protein binding protein (BOLF1), 15 kDa myristylated protein (BBLF1), 58 kDa packaging protein (BGLF1), 350 kDa large tegument protein (BPLF1), 32 kDa myristylated protein binding protein (BGLF2), 27 kDa palmitylated protein (BSRF1), 47 kDa TS kinase (BGLF4) and 58 kDa capsid associated protein (BVRF1), which are prevalent elements of Herpesvirus teguments (Kieff et al., 2007). In addition, EBV has a 42 kDa BKRF4, 72 kDa BRRF2, 19 kDa BLRF2, 54 kDa BDLF2, 140 kDa major tegument protein (BNRF1), which are also specific to gammaherpesvirus (Kieff et al., 2007). Moreover, different components in EBV tegument such as Hsp90, Cofilin, actin, HSP70, enolase and β-tubulin are also significant and probably correlated to cytoplasmic re-envelopment (Kieff et al., 2007).

EBV has several major envelope glycoproteins components which are gp78 (BILF2), gH (BXLF2), gp350 (BLLF1), gB-N, gB-C, gp42 (BZLF2), gp150 (BDLF3), gM (BBRF3), full-length gB (BALF4), gN (BLRF1), and gL (BKRF2) (Kieff et al., 2007).

However, the gp350/220 is considered a major envelope protein that played an important role in B lymphocyte infection by binding gp350/220 with complement receptor type 2 (CR 2 or CD21) molecule (Chandran et al., 2007).

In 1982, the partial sequence (some small fragments) of B95-8 EBV was published (Cheung et al., 1982; Tzellos et al., 2012), but in 1984, the first complete EBV sequence of the B95-8 strain (accession number V01555) was published based on BamHI, also called BART (BamHI-A rightward transcripts) transcripts, fragment

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library (Baer et al., 1984; Tzellos et al., 2012). The BamHI-restriction fragments map was used to establish the nomenclature of the EBV open reading frames, where based on the sizes of the found fragments, these fragments were ordered in descending order from A to Z, which were also classified into latent or lyric genes (Figure 1.3) (Smatti et al., 2018).

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Figure 1.3 BamHI restriction-endonuclease map of prototype B95.8 genome with open reading frames location for the EBV latent proteins. The BamHI fragments are designated based on their size, from A (the largest) to Z (the smallest) in alphabetical order. The purple colour represents the TRs of the EBV genome at both termini (Adopted from Young et al., 2004).

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During the EBV infection of the cell, the EBV DNA becomes a circular episome by joining its terminal repeats (TRs), based on the number of TRs in the parental genome. Generally, the EBV progeny episomes have a comparable number of TRs to the parent genome. Although, during EBV DNA replication, difference in the numbers of TRs can be added to the termini of the EBV genome. During the latent infection, future EBV episomes’ generations will have the same number of TRs.

Therefore, the numbers of latently infected cells’ TRs can help determine the common progenitor, either the cancer cells derived from a single cancer-infected progenitor or multiple progenitors (Thompson et al., 2004 ; Kieff et al., 2007). However, in the lytic phase, EBV DNA is in the linear form during the integration with chromosomes (Kliszczewska et al., 2017).

1.3 EBV transmission and life cycle

The oral route is the main route of transmission of the EBV (Smatti et al., 2018). However, the EBV transmission through blood transfusion and organ transplantation was also reported (Cen et al., 1991; Alfieri et al., 1996; Hanto et al., 1981; White et al., 2019).

The transmission of EBV usually occurs through the saliva. Afterward, EBV enters the epithelium layer of the Waldeyer tonsillar ring situated in the oropharynx.

The virus replication will start during the lytic phase of infection (Smatti et al., 2018).

Subsequently, while B lymphocytes move close to the tonsil epithelial cell, the infection of naive B lymphocytes in the underlying lymphoid tissues occurs. The naive B lymphocytes transform to activated lymphoblasts. Then these cells migrate to the lymph node follicle where the reaction in the follicle germinal center will initiate through “latency III” program, where all latent growth proteins (Figure 1.2) such as

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latent membrane proteins (LMP1, LMP2A, and LMP2B) and the EBV nuclear antigens (EBNA1, EBNA 2, EBNA3A, EBNA3B, EBNA3C, and EBNA-LP) are expressed, and adversely autoregulate the growth of EBV (Young et al., 2004; Smatti et al., 2018).

Then type II latency program is started (only EBNA1, the EBERs (EBV- encoded RNA), the BARTs, LMP1, and LMP2A are expressed) and subsequently, the infected B cell leaves as memory B lymphocytes from the germinal center. Afterward, the “Latency 0” phase begins where the expression of all the viral proteins in the memory B lymphocytes will be suppressed. However, latency type I program will be initiated if only the EBNA-1 gene is expressed during the division of these memory B lymphocytes (Thorley-Lawson et al., 2008; IARC Working Group on the Evaluation, 2012).

Moreover, the infected memory B lymphocytes can also eventually return to the tonsils, where they sometimes go through plasma-cell differentiation, which induce more viral replication and thus cause the infection of other B lymphocytes as well as may be released into saliva and thus transmitting the EBV virus to other individuals (Thorley-Lawson et al., 2008; IARC Working Group on the Evaluation, 2012) (Figure 1.4).

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Figure 1.4 EBV life cycle (Adapted from Thorley-Lawson et al., 2008).

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Usually, the primary infection arising during childhood is asymptomatic, while in certain developing countries, IM occasionally appears in adolescents who get delay EBV infection. In addition, acute IM patients were found to have high titers of infectious EBV, where new EBV virion shed in the throat from the lytic infection phase at oropharyngeal sites and can easily be transmitted to the new susceptible individuals during persistent lytic infection (Young et al.,, 2004).

EBV virus infects the B lymphocytes by the binding of the viral envelope glycoprotein gp350/220 to CD21 and by the binding of gp42 (second glycoprotein) to human leukocyte antigen (HLA) (class II molecules) as a co-receptor. While, the EBV Infection of other cells such as epithelial cells are much less effective and occurs by separate, as yet poorly defined pathways (Borza et al., 2002; Prabhu et al., 2016). In addition, a mechanism involving two other viral glycoproteins, such as gp85 and gp25, can be used to bind the EBV virion envelope to the host cell membrane. (Li et al., 1995; Prabhu et al., 2016). However, the exact route of EBV entry into memory cells is still a matter of much debate.

Current proof suggests that in healthy chronic virus carriers, the EBV infection is mostly limited to B cells. However, the EBV virus also can be detected in epithelial cells in certain cases. The epithelial cells' role in EBV infection is mostly considered a site for EBV replication and amplification instead of considering these cells as a site of stable latent EBV infection, but until now still questionable (IARC Working Group on the Evaluation, 2012; Prabhu et al., 2016). In addition, recent studies have shown that the EBV can also infect monocytes/macrophages, smooth muscle cells, T lymphocytes, natural killer (NK) cells, and endothelial cells rather than epithelial cells and B cells (Okano, 2000; Prabhu et al., 2016). This was demonstrated by detecting

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EBV in some T-cell lymphomas and other diseases, such as OHL in immunocompromised, gastric carcinomas and nasopharyngeal patients (Kieff et al., 2007; Prabhu et al., 2016).

T lymphocytes are responsible for removing newly EBV infected cells and for managing the infection throughout the primary infection. However, during latency, the EBV is protected from the immune system as it stays silenced in the resting memory B lymphocytes without expressing any EBV protein. (Smatti et al., 2018).

1.4 EBV infection stages

There are two alternative phases of EBV in cells: latent or lytic (Murata et al., 2014). After B cell infection, the linear EBV genome transforms to circular (episome).

Episomes are existing as circular genetic elements inside the host cell’s nucleus that are closely associated with, but not integrated into, the host DNA. During latent infection, episomes are replicated during S phase, but new viral particles are not produced and the infected cell survives (Serquina et al., 2017). It usually remains in the latent phase inside the infected B cells. However, only a small percentage will be spontaneously activated among the latently infected B lymphocytes, and the lytic phase will start (Cohen, 2000).

1.4.1 EBV lytic infection

EBV lytic replication is required for virus spreading from host to host and from cell to cell and can be occurred in both B cells and epithelial cells (Drouet, 2019). Lytic replication is initiated by oriLyt replication origin, which encodes DNA polymerase and results in the release of EBV infectious particles (Tsurumi et al., 2005; Drouet, 2019).

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EBV is occasionally activated and replicated in latently infected B cells of most asymptomatic EBV infected carriers, followed by EBV virion can be detected in oral secretions. The replication process produces new EBV virions called EBV lytic replication (Faulkner et al., 2000; Tsurumi et al., 2005). In addition, the reactivation process means a switchover from the latent to lytic cycle (Figure 1.5) (Miller et al., 2007; Murata et al., 2014). However, the mechanism of triggering EBV reactivation by physiological stimuli in vivo is not clearly understood. However, in vitro, the EBV reactivation process can be elicited by treating with some biological or chemical reagents, such as TPA (12-O-tetradecanoylphorbol-13-acetate), calcium ionophore, TGF-β (Transforming growth factor-beta), anti-Ig (anti-immunoglobulin) and sodium butyrate. This stimulation leads to the expression of two viral (immediate-early) IE genes that are known as BZLF1 (BamHI Z fragment leftward open reading frame 1) (which encodes transactivators proteins such as Zta, Z, ZEBRA, and EB1) and BRLF1 (which encodes transactivators proteins such as Rta, R, and EB2) (Miller et al., 2007;

Murata et al., 2014).

It is well known that EBV expresses approximately 90 proteins during lytic replication. They are classified as IE, early (E) and late (L) proteins (Figure 1.5). After EBV infection, the expression of IE and E proteins will occur in the presence of protein synthesis inhibitors and viral DNA synthesis inhibitors, respectively. However, in the presence of these inhibitors, the L proteins will not express. IE proteins are transactivator proteins which play a role in triggering the early proteins expression in the virus, including enzymes that are important in virus DNA replication. During the late phase of the lytic cycle, the expression of L proteins that are structural proteins will occur. The EBV viral particles that are packing EBV DNA will assemble before

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the release of EBV infectious virions (Cohen, 2000; Young et al., 2007). However, the control of both BRLF1 and BZLF1 gene transcription is required to have a balance between EBV lytic and latent infection inside the EBV infected cells (Li et al., 2016).

Figure 1.5 Latent and lytic phases of EBV life cycle.

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16 1.4.2 EBV latent infection

The persistence of EBV without active EBV production occurs mostly within resting memory B cells in the human body and also it is possible to occur in epithelial cells (Cohen, 2000; Odumade et al., 2011). In addition, it was reported that 1 to 50 B cells per million are carrying the EBV genome in the blood circulation of normal adults, and the number of latently infected B cells stays constant throughout the years (Babcock et al., 1998; Cohen, 2000). It is generally believed that EBV genomes can persist as episomes or/and as integrated DNA in latently infected B cells (Kieff et al., 1982; Kieff et al., 1985; Odumade et al., 2011).

During latent EBV infection in B cells, only a limited set (⁓10) of nearly 100 viral genes (expresses during replication) are expressed in vitro (Sixbey et al., 1983;

Cohen, 2000). The replication of EBV episomal genome occurs once per cell cycle via the host DNA polymerase and the oriP replication origin, and also there is no production of progeny EBV virus in this phase (Tsurumi et al., 2005; Drouet, 2019).

In these latently infected B cells in vitro, two types of non-translated type of EBERs, six EBV nuclear antigens (EBNA1, EBNA2, EBNA3A, EBNA3B, EBNA3C, EBNA leader protein (EBNA-LP)), BARTs from the BamHI A region (Bam A) of EBV genome, microRNAs (miRNAs) and three latent membrane proteins (LMP1, LMP2A and LMP2B) are expressed (Cohen, 2000; Young et al., 2007; Odumade et al., 2011;

Yin et al., 2019).

Therefore, EBV can persist over the life inside the infected B cells and avoid immune system detection during the latent phase (Knipe et al., 2013; Drouet, 2019).

In immune-competent individuals, a cell-mediated response such as EBV-specific T cells (CD4+ and CD8+) and NK cells are responsible for controlling latently infected

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B cells by targeting both lytic and latent antigens, prevent the outgrowth and containing the reactivation of EBV infected latent B cells (Rickinson et al., 2014).

Thus, in congenital or acquired immunosuppressed individuals who get EBV infection are highly vulnerable to EBV reactivation and malignant transformation (Cesarman, 2011; Dierickx et al., 2018). Furthermore, EBV infected patients who have organ/stem cell transplantation and was treated with immunosuppressive drugs are at high risk of developing the posttransplant lymphoproliferative disorder (PTLD), which is a serious, often fatal B-cell lymphoproliferative disease (LPD) complication after transplantation, and also may sometimes promote the development of NHL (Dierickx et al., 2018; Drouet, 2019).

EBV latency patterns

In vitro, such as in Burkitt’s tumour cell lines and EBV-immortalized LCLs and also in vivo, at least three different latency programs were found to be expressed (Thorley-Lawson et al., 2004; Yin et al., 2019). During these different latency programs, in dividing memory cells, the EBV genome will be multiplied (type I), B- cell differentiation will be induced (type II), naïve B cells will be activated (type III), or the expression of all gene will be entirely restricted in a specific manner (Table 1.1) (Thorley-Lawson et al., 2004; Kimura et al., 2008; Odumade et al., 2011).

Latency 0 characterizes by a very limited spectrum of latent EBV gene expression in memory B cells, namely EBERs and BARTs transcripts and founds in healthy carriers (Kimura et al., 2008; Kimura et al., 2013). However, In EBV- associated diseases, different EBV latency programs can detect, which are classified into latency I, II and III as shown in Table 1.1 (Gulley, 2001; Young et al., 2007;

Kimura et al., 2008). Latency type I associates with BL and gastric carcinoma and

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only a restricted spectrum of EBV latent genes expresses, such as EBV EBNA1, LMP2A, BARTs and EBERs. However, latency type II associates with HL, T cell lymphoma and NPC. The expression of EBNA1, LMP1, LMP2, BARTs, and EBERs is detected. In contrast, all latency genes are expressed in latency type III, include EBNAs (1, 2, 3A, 3B, 3C, -LP), the LMPs (1, 2A, 2B), BARTs and EBER (Gulley, 2001; Young et al., 2007; Kimura et al., 2008;).

The latency III program is usually seen in LCLs and associates with acute IM, lymphoproliferative disorders, and immunosuppressed states, such as in PTLD or AIDS patients (Gulley, 2001; Kimura et al., 2008). However, the expression pattern of EBV latent genes can be different in the same EBV infected patient among different B cell subsets or even in the same tissue. Hence, the classification of EBV latency patterns into four latency programs are not restricted and in different EBV-associated disease, heterogeneous patterns were detected. Moreover, within the same EBV infected individual or even in the same tissue, both lytic and latent infections were reported (Kimura et al., 2008; Kimura et al., 2013). For example, in IM, both latent infection of latency III program in EBV infected B cells and lytic infection of plasma cells or epithelial cells were reported (Yoshioka et al., 2001; Kimura et al., 2008;). In addition, in NPC, the majority of the cells are detected with latent infection of latency II program and few cells may progress to lytic infection (Brooks et al., 1992; Kimura et al., 2008).

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Table 1.1 The EBV proteins’ function, EBV latency pattern and associated malignancy.

Footnote: EBV, Epstein–Barr virus; EBNA, Epstein-Barr virus nuclear antigen; BARTs, BamHI A rightward fragments; LMP, latent membrane protein; EBERs, EBV-encoded small RNAs; NK cells, natural killer cells; NK/T cell, nasal natural killer (NK)/T-cell;

MNCs, mononuclear cells; WBC, white blood; IM, infectious mononucleosis; NPC, nasopharyngeal carcinoma; CAEBV, chronic active EBV disease; PTLD, post-transplant lymphoproliferative disorder.

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20 1.4.3 EBV-associated diseases

The current estimation has shown that EBV causes 200,000 new cancer cases yearly (∼2% of cancers worldwide) (Cancer Research UK) (Al Moustafa et al., 2018).

In 2009, the International Agency for Research on Cancer review (IARC Working Group on the Evaluation, 2012) classified EBV as group 1 carcinogenic that has an important role in carcinogenesis of several EBV- associated carcinomas (Bouvard et al.,, 2009; Prabhu et al., 2016). It has been shown that in culture, EBV immortalizes normal B cells; the expression of different EBV latent gene products in all EBV- associated carcinomas; and, at the molecular level, the expression of encoded latent gene products during latent viral infection will induce block apoptosis, cell prolifertion, modulate cell migration, tumour maintenance, cell progression and growth. Moreover, these events can be happened before or during cancer beginning (Prabhu et al., 2016).

Approximately, 95% of the world’s population are asymptomatic life-long EBV carriers and most of them after getting EBV infection, they will obtain adaptive immunity (Jain et al., 2011; Chijioke et al., 2013). However, infants gain the immunity from maternal antibody, hence after this protection disappears, the infants will become highly suscepatible to EBV infection (Ebell, 2004; Jain et al., 2011). In normal healthy carriers, EBV persist for long term inside in the memory B-cells and the reactivation for latent EBV will contribute to EBV-associated disease and carcinomas. The primary infection in majority of children usually is asymptomatic or similar to the other mild disease of childhood (Hjalgrim et al., 2007; Jain et al., 2011). However, when the adolescence or teenagers get the primary infection, IM will be resulted in 35% to 69%

of infected adolescence or teenagers (Ebell, 2004; Jain et al., 2011). For this reason,

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EBV is best known as causative agent for IM (commonly known as kissing disease synonyms, Pfeiffer's disease, Filatov's disease, glandular fever or “mono” in North America) (Jain et al., 2011; Ali et al., 2015; Shannon-Lowe et al., 2019).

In addition, Previous reports have detected that particular EBV-latency programs are shown in numerous benign and neoplastic diseases (Table 1.2), including those of a lymphoid form such as IM, PTLD, HL (Salehiniya et al., 2018), BL, and T- cell lymphomas and those of an epithelial form such as OHL, NPC, lymphoepithelioma-like carcinomas, and gastric carcinoma (Gulley, 2001; Ali et al., 2015; Elgui de Oliveira et al., 2016).

Moreover, EBV association with leiomyosarcomas such as smooth muscle cells-derived sarcoma in immunocompromised patients, central nervous system lymphomas associated with HIV and with autoimmune diseases such as dermatomyositis, rheumatoid arthritis, Sjogren’s syndrome, systemic lupus erythematosus, and multiple sclerosis have been reported (Table 1.2) (Niedobitek et al., 2001; Jain et al., 2011; Fujiwara et al., 2015; Draborg et al., 2016; Prabhu et al., 2016). The association between EBV and breast, prostate, cervical, oral squamous cell (OSC) and salivary gland carcinomas was reported, while limited or no association between EBV and lung, testis, leukaemia and multiple myeloma was detected (IARC Working Group on the Evaluation, 2012; Shi et al., 2016; Teow et al., 2017a). The investigation of patients with EBV-infected carcinomas has provided a sensible degree of evidence that EBV was present before neoplastic transformation, which highlights the requirement of further studies to better understand the extent of EBV involvement in tumourigenesis of different EBV-associated carcinomas (Gulley, 2001).

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Table 1.2 Diseases associated with EBV infection.

Tumour Subtypes Association

with EBV (% cases)

References

Autoimmune disease Multiple sclerosis 99 (Pender, 2004) Systemic lupus

erythematous

99 (Pender, 2004) Rheumatoid arthritis 88 (Pender, 2004)

Sjogren’s syndrome 57 (Fujiwara et al., 2015)

XLP XLP1 and XLP2 65 (Zhang et al., 2016a)

Benign reactive infection

Infectious mononucleosis

>99 (Gulley et al., 2008) Oral hairy leukoplakia >95 (Gulley et al., 2008)

Chronic active EBV infection

100 (Gulley et al., 2008) Nasopharyngeal

carcinoma

Non-keratinizing 100 (Chang et al., 2005b) Keratinizing 30-100 (Chang et al., 2005b)

Gastric carcinoma UCNT 100 (Chang et al., 2005b)

Adenocarcinoma 5-15 (Chang et al., 2005b) Non-Hodgkin lymphoma and related neoplasms

BL Endemic 100 (Shannon-Lowe et al.,

2017)

Sporadic 10-80 (Shannon-Lowe et al., 2017)

AIDS-associated 30-40 (Shannon-Lowe et al., 2017)

B-

lymphoproliferative disease

Post-transplant >90 (Shannon-Lowe et al., 2017)

HIV-related >90 (Shannon-Lowe et al., 2017)

DLBCL NOS 10 (Shannon-Lowe et al.,

2017)

PAL 100 Shannon-Lowe et al.,

2017)

HIV-related 20-60 Shannon-Lowe et al., 2017)

Rare immunocompromise

d B lymphomas

Plasmablastic lymphoma

75-90 Shannon-Lowe et al., 2017)

Primary effusion lymphoma

75-90 Shannon-Lowe et al., 2017)

/NK

lymphoproliferative disease

CAEBV 100 Shannon-Lowe et al.,

2017) Extra-nodal T/NK

lymphoma

100 Shannon-Lowe et al., 2017)

Aggressive NK lymphoma

100 Shannon-Lowe et al., 2017)

(51)

23 Table 1.2 Continued.

Hodgkin lymphoma

NLPHL - <4 (usually

absent)

(Huppmann et al., 2014) Classical Hodgkin

lymphoma

All subtypes 40 (Marshall-Andon et

al., 2017) Nodular sclerosis 10-40 (variably

present)

(Shannon-Lowe et al., 2017; Carbone et al.,

2018) Mixed cellularity 70-80 (usually

present)

(Shannon-Lowe et al., 2017; Carbone et al.,

2018) Lymphocyte depleted 10-50 (variably

present)

(Shannon-Lowe et al., 2017; Carbone et al.,

2018) Lymphocyte rich 30-60 (variably

present)

(Shannon-Lowe et al., 2017; Carbone et al.,

2018)

HIV-related >90 (Shannon-Lowe et al., 2017; Carbone et al.,

2018) Other types of cancers

Salivary gland carcinoma

- 44 (Mozaffari et al.,

2017)

Cervical carcinoma - 43.63 (Vranic et al., 2018)

Breast cancer - 35 (Richardson et al.,

2015)

Prostate cancer - 8-37

(Grinstein et al., 2002;

Whitaker et al., 2013;

Shi et al., 2016)

ESCC - 6.5 (Yanai et al., 2003)

OSCC - 5.03 (She et al., 2017)

Footnote: XLP, X-linked lymphoproliferative disease; PAL, pyothorax-associated lymphoma; CAEBV, chronic active EBV infection; NOS, not otherwise specified;

NK/T-cell, nasal natural killer /T-cell; HIV, Human immunodeficiency virus; AIDS, acquired immune deficiency syndrome; BL, Burkitt lymphoma; DLBCL, Diffuse large B cell lymphoma; UCNT, undifferentiated carcinomas of nasopharyngeal type;

NLPHL, nodular lymphocyte-predominant Hodgkin’s lymphoma; ESCC, Esophageal squamous cell carcinoma; OSCC, Oral squamous cell carcinoma.

1.5 Nasopharyngeal carcinoma (NPC)

Nasopharyngeal carcinoma (NPC) is a non-lymphomatous squamous cell carcinoma that develops in the epithelial cells layer that line the surface of the

(52)

24

nasopharynx (Brennan, 2006; Tabuchi et al., 2011). In 1921, the first description of NPC was defined by Regaud and Schmincke (Regaud et al., 1921; Schmincke, 1921;

Brennan, 2006).

This cancer commonly seen in Fossa of Rosenmüller (FOR) (pharyngeal recess) and demonstrates different degrees of differentiation (Shamet et al., 1990;

Tabuchi et al., 2011). NPC is a distinct form of head and neck cancer that differs from other types of upper aerodigestive tract in terms of its etiology, clinical presentation, pathology, geographical and racial distribution and response to treatment (Tabuchi et al., 2011; Lao et al., 2020).

1.5.1 Epidemiology of NPC

Globally, NPC is an uncommon malignancy with an occurrence rate of usually

< 1 per 100,000 person-years, but regions with high incidence are in southern China (e.g., Cantonese), Southeast Asia (e.g., Sarawak Bidayuh), North Africa and the Arctic (e.g., Inuit, Alaska native) (Figure 1.6 A). At the age-standardized incidence rate (ASR) for males, the prevalence in these populations are 100 times higher than in other ethnic groups. Approximately 129,000 new cases/year are reported in the world (Figure 1.6 B), with > 70% reported in Eastern and South-Eastern Asia (Chen et al., 2019; Rickinson et al., 2019). According to the International Organization for Cancer Research study in 2008, more than 80 % of NPC patients are in Asia and just 5 % of NPC patients are registered in Europe. Specifically, 71 % of new NPC cases are registered in East and South East Asia and 29 % are diagnosed in South and Central Asia and North and East Africa (Chang et al., 2006a). In 2012, ⁓ 86,000 NPC cases were diagnosed worldwide and the reported number of deaths exceeded 50,000,

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