Delineation of the Genome-Wide Recruitment of Hepatitis B Virus Trans-Activator Protein Hbx, in Primary Hepatocytes and Liver Cancer Cells

Delineation of the Genome-wide Recruitment of Hepatitis B Virus Trans-activator Protein HBx, in Primary Hepatocytes and Liver Cancer Cells

By Amanda Jayne Lyon

B.S. in Biomedical Technology, May 2006, Norwich University M.S. in Public Health Microbiology, Emerging Infectious Diseases, May 2009 The George Washington University

A Dissertation submitted to

The Faculty of The Columbian College of Arts and Sciences of The George Washington University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

August 31, 2012

Dissertation directed by:

Rakesh Kumar Professor of Biochemistry and Molecular Biology

The Columbian College of Arts and Sciences of The George Washington University certifies that Amanda Jayne Lyon has passed the Final Examination for the degree of

Doctor of Philosophy as of August 7, 2012. This is the final and approved form of the dissertation.

Delineation of the Genome-wide Recruitment of Hepatitis B Virus Trans-activator Protein HBx, in Primary Hepatocytes and Liver Cancer Cells.

Amanda Jayne Lyon

Dissertation Research Committee:

Rakesh Kumar, Chairman and Professor of Biochemistry and Molecular Biology

Paul J. Brindley, Professor of Microbiology, Immunology and Tropical Medicine

Ajit Kumar, Professor of Biochemistry and Molecular Biology

iii Dedication

I would like to dedicate this dissertation to my family members; Cherie Lyon, David Lyon,

Laurie Lyon, and Shaina Lyon, as well as to my Fiancée, Dirk Vandeveer. You are all instrumental in my life and have always been encouraging and supportive, thank you.

iv Acknowledgements

I would like to express my gratitude towards everyone who played a role in this experience, to include all of the professors and members of IBS as well as those who contributed to my dissertation research. I would like to thank Dr. Rakesh Kumar and my committee members Dr. Paul Brindley, Dr. Ajit Kumar, Dr. Jeyanthy Eswaran and Dr.

Anton Sidawy, for their guidance and support throughout this experience. I am grateful for the opportunity to work on this interesting research project, which has taught me numerous skills that I will take with me. Thank you to all members of Dr. Kumar’s laboratory for your suggestions and guidance. Thank you, Dr. Ali Ramezani, for your help with the lentiviral vectors and Dr. Krishna Banudha for your help with the PHHs. Thank you to everyone who supported me in the completion of this dissertation research project, your assistance is greatly appreciated.

I would like to thank Dr. Linda Werling for her support and guidance. Dr. Werling, you are a wonderful person who truly cares for her students and whose leadership in IBS makes the program so successful. Thank you to my Academic Advisor, Dr. David

Leitenberg who has always been helpful and supportive. I must thank Dr. Dante Verme who was one of my very first professors at GWU, in the Fall of 2007. You are an outstanding professor and I enjoyed my time as your Graduate Administrative Assistant and Instructional Assistant for GIS. I will miss it.

v Thank you to my friends in the IBS, especially the entering class of the Fall of

2009. Thank you to Claire Hoptay, Lindsay Garvin, and Amanda Woerman, who have

become close friends of mine. Thank you Ngoc-Han Ha, for your friendship and support throughout this experience, and beyond. Thank you for listening, and for your advice. I will always remember the good times.

At the beginning of the Ph.D., I was told that a strong support system is vital to a

student’s success. Luckily, I never had to worry about that, and it is due to my amazing

family and Fiancée. Mom, you always told me that I could be whatever I wanted to be, and that advice has kept me striving for more. Thank you for lending an open ear when ever I needed to talk. Your support is a vital part of my success. Dad, your support has also been vital to my success. Your words of encouragement and advice often come to my mind. I have always looked up to you and have strived to work as hard, as I know you do. Laurie,

“the human dictionary,” you have always been an inspirational sister, who I’ve looked up to and have strived to be like, even though, as someone who is very independent, I would never admit it. Today, I still look up to you and am proud to have you as a role model.

Shaina, you are the source of laughter in our family. You make life more fun and enjoyable and I admire that. Thank you for your support and for always being there for me. To the

Vandeveers, you have been like family to me, for many years now. Thank you for being so supportive and caring. You are wonderful people who I admire and look up to. Dirk, I could not have completed the M.S., or the Ph.D. without you. Your daily support and encouragement has kept me going, through it all. Our time together has made me a much happier and stronger person. Without you, my academic success would not have been possible, thank you.

vi Abstract

Delineation of the Genome-wide Recruitment of Hepatitis B Virus Trans-activator Protein HBx, in Primary Hepatocytes and Liver Cancer Cells

Hepatocellular carcinoma (HCC) is among the top five cancers worldwide, with

Hepatitis B virus (HBV)-associated HCC accounting for the majority of all cases. The

cancer promoting activity of HBV is derived from one of its gene products, HBx, the

primary trans-activator of cellular genes with roles in carcinogenesis. Although the

contribution of HBx to HCC is firmly established, the nature of comparative genome-wide targets of HBx in primary human hepatocytes (PHH) and liver cancer cells, remains unknown, and is being investigated in the present work. Using a genome-wide chromatin immunoprecipitation (ChIP) approach, we characterized the patterns of global recruitment

(and consequently, affected genes) of HBx or its mutant, deficient in binding to p65/RelA,

of the NF-κB complex, in the presence or experimental depletion of a master coregulator

MTA1. We found that the overall recruitment of HBx increases following an interruption

in the involvement of MTA1 and/or p65/RelA, suggesting that the levels or activities of

MTA1 and p65/RelA represent two major modifiers of HBx recruitment to the human

genome. Special attention was placed on targets with recruitment to transcription start sites

(TSS), suggesting a probable contribution of the trans-regulatory processes, in influencing the expression of the putative HBx target genes. Representative target genes with TSS recruitment were validated by PCR and DNA gel electrophoresis and with quantitative

PCR for analysis of resulting altered expression in ChIP samples. This is the first high- throughput analysis of the genome-wide recruitment of HBx to characterize the involvement of a master chromatin modifier as well as a transcription factor, which act to alter the ability of HBx to trans-regulate genes that may be involved in the development of

vii HBV-associated HCC. This analysis provides novel insight into the identity of targeted genes that are trans-regulated by this viral protein and elucidates how these factors may contribute to the functions of HBx, a major risk factor for the development of HCC.

viii Table of Contents

Dedication………………………………………………………………………………....iv

Acknowledgements………………………………………………………………………...v

Abstract……………………………………………………………………………..…….vii

Table of Contents……………………………………………………………………...…..ix

List of Figures…………………………………………………………………………….xii

List of Tables ……………………………………………………………………….……xiv

List of Abbreviations………………………………………………………………….…..xv

Chapter 1: Introduction……………………………………………………………………..1

1.1 Hepatitis B virus and Hepatocellular Carcinoma………...….....……………….1

1.1.1 Viral Oncology and HBV…………………..……………..………………1

1.1.2 HBV and HBx…………….……………...……………………………….2

1.1.3 HBx and HCC…………………...….…………………………………….3

1.2 Host-viral Interactions Associated with HBx……...……………………….…..9

1.2.1 MTA1 and HBx…………………………..………………..……………..9

1.2.2 NF-κB, MTA1 and HBx………………..…….…………………………12

1.3 Specific Aims………………..……...…………………………………………18

Chapter 2: Materials and Methods………………………………………………………...19

2.1 Cell Lines…………….………..…………………………..…………………..19

2.2 Cloning………………………...………………………………….…………...19

2.3 Lentiviral Vectors…………………………...………………………………...20

2.4 siRNA Experiments………..…………………….……………………………20

ix 2.5 Western Blotting Analysis………………………………………………..……21

2.6 FACS Analysis and Fluorescent Microscopy…….…………………………….21

2.7 Chromatin Immunoprecipitation and Sequencing…………….……….………..22

2.8 Computational Analyses…………………..………………………………...….22

2.8.1 Avadis NGS………………………………………………………….22

2.8.2 UCSC Genome Browser…………...………………………………..23

2.8.3 Ingenuity Pathway Analysis (IPA)………..………………………...24

2.9 PCR, DNA Gel Electrophoresis, and qPCR…..………...…….………………...24

Chapter 3: Results…………………………………………………………………………26

3.1 Introduction and Experimental Model…………………….……………………26

3.1.1 Introduction…………………………..……………………………..26

3.1.2 Experimental Strategy…………………………………………….....27

3.2 Global Genome-wide Targeting of HBx and the Role of MTA1…………….....40

3.2.1 Characteristics of Binding………….……………………………….40

3.2.2 MTA1 and p65 are Central to Genome-wide Targeting by IPA

Network Analysis…………………….……….……………………………46

3.2.3 Genome-wide Targeting of HBx to Chromosomes…………..……..56

3.2.4 Unfiltered Heaviest HBx Recruitment……………………………….61

3.3 MTA1 Status Alters the Ability of HBx to Target Categories of Genes……..……61

3.3.1 Molecular and Cellular Functions and Canonical Pathways of

Targeted Genes……….…………...……………………………….……...61

3.3.2 HBx Recruitment to Top Nodal Points of Networks…………….....71

x 3.4 HBx Recruitment to Gene Expression and Cancer Related Genes is Dependent on

MTA1 Status…………………………………..…...………………………………….79

3.4.1 HBx Targeting of Cancer Genes………………………….………....79

3.4.2 HBx Targeting of Tumor Suppressor Genes and Oncogenes……....80

3.4.3 HBx Targeting of Gene Expression Related Genes……….….…....83

3.5 MTA1 Status Alters HBx Recruitment to Target the TSS of Host Genes…...…..90

3.5.1 Shared and Specific Genes Targeted by Venn Diagram Analysis…...90

3.5.2 All Genes Targeted at the TSS ……………………………………..93

3.5.3 Binding Motifs of TSS Targeted Genes…………………………....102

3.6 Validation of HBx Binding and Resulting Altered Gene Expression of

Representative Genes……………………………………………………………..….107

3.6.1 Validation of HBx Binding to Representative Genes…………...….107

Chapter 4: Discussion……………………………………………………………………118

Chapter 5: Future Directions…………………………………………………………….133

Chapter 6: Bibliography…………………………………………………………………139

xi List of Figures

Figure 1. Rates and viral causes of liver cancer…………………………………………….4

Figure 2. Known Functions of HBx………………………………………………………...7

Figure 3. Host-viral Interactions Connecting HBx, MTA1 and p65………………………10

Figure 4. Schematic of Proposed Host-viral Interactions…………………………………15

Figure 5. Cloning and the Lentiviral Vector System……………………………………..28

Figure 6. Experimental Strategy – Workflow……………………………………………..31

Figure 7. Detection of HBx Transduction and Reduction of MTA1 Expression………….34

Figure 8. The Use of ChIP-Seq to Identify Targeted Genes………………………………36

Figure 9. Experimental Strategy – Targets………………………………………………..38

Figure 10. Chromatin Mark Proximity by Bioinformatics…….………………………….41

Figure 11. Genome-wide Recruitment Patterns of HBx by Total Binding Sites, Total Genes and Annotated Regions…………………………………………………………….44

Figure 12. MTA1 and p65 are Central to the Genome-wide Recritment of HBx by IPA Network Analysis…………………………………………………………………………48

Figure 13. Enrichment and Reads Details of MTA1 and NF-kB Associated Genes, Targeted in HBx wild-type Conditions……………………………………………………51

Figure 14. Genome-wide Recruitment Patterns of HBx to Chromosomes………………..57

Figure 15. HBx Recruitment to Molecular and Cellular Functions, and Canonical Pathways Related Gene Groups……………………………………………………………………...67

Figure 16. HBx Recruitment to Top Nodal Points by Sample Condition…………………69

Figure 17. Recruitment Networks with the NF-κB Complex as the Central Node by Sample Condition………………………………………………………………………………….72

Figure 18. Recruitment Networks with TP53 or RB as the Central Node by Sample Condition………………………………………………………………………………….75

Figure 19. Cancer Related Genes…………………………………………………………81

Figure 20. HBx Recruitment to Oncogenes and Tumor Suppressor Genes……………….84

xii

Figure 21. HBx Recruitment to Gene Expression Related Genes by Condition…………..91

Figure 22. Venn Diagram Analysis of All Shared and Specific, HBx Targeted Genes by Sample Condition and Those Targeted at the TSS………………………………..……..100

Figure 23. Categorization of TSS Targeted Genes Based on Function by IPA……...…..100

Figure 24. Binding Motifs of All genes and TSS Targeted Genes by Sample Condition..104

Figure 25. Validation using PCR and DNA Gel Electrophoresis, of Representative Target Genes by Sample Condition……………………………………………………………..109

Figure 26. Validation using qPCR, of Representative Target Genes by Sample Condition………………………………………………………………………………...111

Figure 27. Expression of Genes Representing HBx wild-type and HBx wild-type, MTA1 knock-down Conditions in PHHs………………………………………..………………116

Figure 28. Schematic of Proposed Effects of MTA1 on the Functions of HBx with Respect to Cancer………………………………………………………...………………………130

xiii List of Tables

Table 1. Unfiltered HBx targets by Samples Condition with Corresponding Recruitment Data for All Conditions, in PHHs……………………………….………………………...62

Table 2. Unfiltered HBx targets by Samples Condition with Corresponding Recruitment Data for All Conditions, in HepG2 cells………..……………….………………………...64

Table 3. All Genes with TSS Recruitment by Sample Condition with Chromatin Mark Proximity, in PHHs……………………………………………………………………….94

Table 4. All Genes with TSS Recruitment by Sample Condition with Chromatin Mark Proximity, in HepG2 cells…………………………………………………..……...……..96

Table 5. PCR Primers for qPCR Validation of HBx Targeting of Representative Genes..114

xiv List of Abbreviations

ABL1 c-abl oncogene 1, non-receptor tyrosine kinase

ACCN1 ASIC2, acid-sensing (proton-gated) ion channel 2

AHR Aryl hydrocarbon receptor

AHRHIF Aryl hydrocarbon receptor HIF

AP-1 Activator Protein 1

AP-4 Transcription factor AP-4 (activating enhancer binding protein 4)

ATCC American Type Culture Collection b-catenin Beta-catenin is a cellular protein encoded by the gene CTNNB1

BCL2 B-cell CLL/lymphoma 2

CAMK2D Calcium/calmodulin-dependent protein kinase II delta cccDNA Covalently closed circular DNA cDNA Copy deoxyribonucleic acid

ChIP Chromatin Immunoprecipitation c-Myc Cellular gene named after the myelocytomatosis viral oncogene (v-Myc)

CP2 Transcription factor CP2

CREB c-AMP response element binding

DET1 De-etiolated homolog 1 (Arabidopsis)

DNA Deoxyribonucleic acid

DUX4 Double homeobox 4

E2F1 E2F transcription factor 1

EBV Epstein-Barr Virus

xv EGF Epidermal Growth Factor

ELK1 Member of ETS oncogene family

EMEM Eagle’s minimal essential medium

FACS Fluorescence Activated Cell Sorting

FAM90A Family with sequence similarity 90, member A

FGF2 Fibroblast Growth Factor 2

GANDEM Genetic Algorithm guided formation of spaced Dyads coupled with an EM

GFP Green Fluorescent Protein

GLTSCR2 Glioblastoma Tumor Suppressor Candidate Region 2

GNB2L1 Guanine Nucleotide binding protein beta polypeptide 2-like 1

HBV Hepatitis B virus

HBx Hepatitis B virus X protein

HCC Hepatocellular Carcinoma

HCV Hepatitis C virus

HDAC Histone deacetylase

HDM Hepatocyte-defined Medium

HEK293T Human Embryonic Kidney cells

HepG2 Hepatocellular Carcinoma cell line

HIF-1α Hypoxia Inducible Factor-1a

HIV-1 Human Immunodeficiency Virus type-1

HMGB1 High mobility group box 1

HOX Developmental genes containing a homeobox domain

xvi HOXB7 Homeobox B7

HOXC5 Homeobox C5

HOXC6 Homeobox C6

HPV Human Papillomavirus

HTLV-1 Human T Lymphotropic Virus type 1

IkB-α Nclear factor of kappa light gene enhancer in B-cells inhibitor, alpha

IL12B Interleukin 12 beta

IPA Ingenuity Pathway Analysis

IRES Internal Ribosomal Entry Site

KSHV Kaposi’s Sarcoma Herpesvirus

L1MB3 LINE DNA repeat element

LIMD1 LIM domains containing 1

LINE Long Interspersed Repeat Element

LOC Uncharacterized gene Locus

LOC728855 Uncharacterized LOC728855

LTR Long Terminal Repeat

MACS Model-based algorithm for ChIP-Seq

MAPK Mitogen-activated protein kinase

MEIS1 Homeobox 1, myeloid ecotropic viral integration site 1 homolog (mouse)

MEIS2 Homeobox 2, myeloid ecotropic viral integration site 1 homolog (mouse)

MMP9 Matrix metallopeptidase 9

xvii MOI Multiplicity of Infection

MTA1 Metastasis Tumor Antigen 1

MYF6 Myogenic factor 6 (herculin)

MYOD Myogenic differentiation 1

NF-AT Nuclear Factor of Activated T cells

NF-kB Nuclear Factor kappa-light chain enhancer of B cells

NGS Next-Generation Sequencing

NPAS1 Neuronal PAS domain protein 1

NR1H3 Nuclear receptor subfamily 1, group H, member 3

NuRD Nucleosome Remodeling and Deacetylase Complex p105 Nuclear factor NF-kappa-B p105 subunit p53/TP53 Tumor Protein 53 p65/TP65 Tumor Protein 65 encoded by RelA of the NF-kB complex

PAR5 Prader-Willi/Angelman syndrome-5, RNA gene

PCR Polymerase Chain Reaction

PHH Primary Human Hepatocyte cell line

PI3K/Akt Signaling Pathway involved in apoptosis and cancer

POU3F2 POU class 3 homeobox 2 qPCR Quantitative Polymerase Chain Reaction

RAB31 RAB31, member RAS oncogene family

RAS Rat Sarcoma family of oncogenes

RelA Gene which encodes for transcription factor p65 of the NF-kB Complex

REX1 REX1 transcription factor, zinc finger protein 42 homolog (mouse)

xviii REXO1L1 REX1, RNA exonuclease 1 homolog (S. cerevisiae)-like 1, GOR siRNA Small interfering RNA

SIX3 SIX3 homeobox

SMAD-4 MAD, mothers against decapentaplegic homolog 4 (Drosophila)

SP1 Specificity protein 1 transcription factor

STAT Signal Transducer and Activator of Transcription

STAT3 Signal Transducer and Activator of T cells 3

SUB1 SUB1 homolog (S. cerevisiae)

SUMO4 Small ubiquitin-like modifier 4 protein

SV40 Simian Virus 40

TAF4 TAF4 RNA polymerase II, TATA box binding protein

TBR1 T-box, brain, 1

TFAP2A Transcription factor AP-2 alpha (activating enhancer binding protein 2 alpha)

TRIM29 Tripartite motif containing 29

TSS Transcription Start Site

USP17 Ubiquitin specific peptidase 17

USP17L6P Ubiquitin specific peptidase 17 like 6 pseudogene v-gpcr viral- g-protein coupled receptor v-IL6 viral- Interleukin 6 v-ras viral encoded ras, similar to human Ras proto-oncogenes v-src viral encoded src, gene encoded by Rous sarcoma virus

Wnt Cellular gene named for wingless (Wg) and integration 1 (Int)

WTAP Wilms tumor associated protein 1

xix XRCC6 X-ray repair complementing defective repair in Chinese hamster cells 6

ZFYVE19 Zinc finger, FYVE domain containing 19

ZIC3 Zic family member 3

ZID Zinc finger and BTB domain containing 6

xx Chapter 1: Introduction

1.1 Hepatitis B virus and Hepatocellular Carcinoma

1.1.1 Viral Oncology and HBV

Viruses have been implicated as risk factors for the development of cancer since

1898 by experiments done on rabbit Myxomatosis, followed by cell-free transmission of

avian leukemia in 1908. In the early 1900’s, Rous conducted experiments on avian

sarcoma, the mouse mammary tumor virus was described, SV40 and some adenoviruses

were linked with cancer and the first human tumor virus, EBV, was discovered (Moore and

Chang 2010; Olson 1989). Viruses infecting humans, which are known to play a role in cellular transformation include Epstein-Barr virus (EBV), Human T-cell Lymphotropic virus (HTLV-1), Kaposi’s Sarcoma-associated Herpesvirus (KSHV), Human Papilloma viruses (HPV), and Hepatitis B and C viruses (HBV, HCV) (Moore and Chang 2010;

Martin and Gutkind 2009). Viruses have been shown to initiate the development of cellular immortalization, as well as interfere with cellular growth arrest and contact inhibition.

Viruses can also activate oncogene expression and hinder tumor suppressor genes (Radoja

2010). Viruses may encode protein products which can directly modulate cellular gene expression, activate signal transduction, or alter the cell cycle. Some viruses have been found to integrate into the host genome in close proximity to cellular proto-oncogenes, turning on their transcription, which may initiate cancer. DNA viruses may bring homologues of cellular proto-oncogenes into the cell, causing cancer. They may also change the functions of cellular genes. Transformation caused by viruses can also be attributed to infection occurring within non-permissive cells, as the survival of a non-

1 permissive, damaged cell may become cancerous. Examples of transducing viral

genes include viral src, viral ras, viral gpcr, viral IL-6, as well as others. Trans-activation of

c-Myc can be achieved by some retroviral activity, initiating cancer. The retinoblastoma

(RB) gene can be phosphorylated, causing increased cell cycle progression. Some viruses

can inhibit apoptosis or inactivate p53, which can stop the suppression of tumor growth. In

other cases, long latency periods lead to cancerous outcomes. Viruses such as Human T-

lymphotrophic virus type 1 (HTLV-1) are non-transducing but after infecting cells over

time, cancer can result (Radoja 2010). Hepatocellular carcinoma results from the combination of multiple events, including but not limited to, genetic mutations, the initiation of oncogene expression, the alteration of signal transduction pathways, the inhibition of tumor suppressor genes and chronic inflammation (Tsai and Chung 2010).

Clearly, some viruses have been shown to aid in the initiation and progression of cancer.

Research focused on mechanisms employed by viruses to transform the cell, could reveal new insights into how this occurs and these details could be utilized in the development of more specific and more successful therapies against pathogens that cause cancer.

1.1.2 HBV and HBx

The Hepatitis B virus is a small hepatotropic DNA virus which causes acute and chronic infections and may result in HCC (Beasley 1988). Infection with HBV most commonly occurs following exposure to infected blood or other bodily fluids. The majority of symptoms are non-specific but may also include more specific symptoms such as jaundice and liver failure (Thomas et al., 2005). HBV has an incubation period of two to three months and a 90% recovery rate, although over 400 million people worldwide live with a chronic infection, putting them at risk for developing HCC (Hepatitis B Foundation).

2 Chronic infections cause persistent inflammation, cirrhosis, reduced liver function, HCC,

and may be fatal (Ganem 1982; Gerber and Thug 1985; Hoofnagle et al., 1987). In 1981 a

recombinant vaccine was developed, which is widely used today in regions with access to it

(Emini et al., 1986; Zajac et al., 1986; Thomas et al., 2005). Post-infection therapy includes

alpha-interferon and nucleotide/nucleoside analogs which result in a range of outcomes

based on individual response (Thomas et al., 2005).

The Hepatitis B virion is comprised of an envelope surrounding the icosahedral

core which houses the viral DNA. HBV has partially double stranded circular DNA which

encodes for the core, X, polymerase, and surface antigen genes (Tiollais et al., 1985;

Ganem and Varmus, 1987). HBV is transmitted though exposure to infected bodily fluids

and enters hepatocytes by interacting with the cell surface through uncharacterized

receptors. Endocytosis also plays a role in cellular entry and the viral capsid is released.

Covalently closed circular DNA (cccDNA) forms and is replicated within the nucleus of

the host cell. Newly assembled virions traffic towards the plasma membrane and exit by

budding, to target neighboring cells (Ruiz-Opazo et al., 1982). The life cycle of HBV and

functions of the viral protein products have been widely studied, although the functions of

the protein product HBx, of the X gene, are still being explored. This product has been

implicated in the direct development of HCC (Castelmann, 1995; Henkler and Koshy,

1996), and is an interesting topic for viral oncology research.

1.1.3 HBx and HCC

HCC is the third leading cause of cancer death worldwide (Parkin 2001) with the

highest prevalence rates in Asia and Africa (Lupberger and Hildt 2007). A large set of epidemiological studies have established that infection with HBV or HCV precedes the

Figure 1

4 Figure 1. Rates and viral causes of liver cancer. Liver cancer is among the top five

cancers worldwide with 78% of cases occurring following infection with Hepatitis B or C viruses and 53% from Hepatitis B virus alone. Both HBV and HCV have been implicated in cellular transformation in both direct and indirect manners. HBV encodes a viral protein

HBx, which has been implicated in direct transformation leading to the development of

HCC. Diagram modified from Block et al., Oncogene, 22, 5093–5107, 2003.

5 development of approximately 80% of all HCC cases, worldwide, with over half of these

cases being linked to HBV (Arsura and Cavin 2005) (Figure 1). It is generally accepted

that one of the viral-derived products, the Hepatitis B virus X protein (HBx) contributes to

the development of HCC through its ability to trans-activate host genes (Castelmann 1995;

Colgrove et al., 1989; Nakatake et al., 1993), in a direct manner which in turn, promotes

cellular transformation (Block et al., 2003) (Figure 1). HBx trans-activated host genes participate in cellular processes including cell cycle regulation, survival, proliferation,

DNA repair, apoptosis, and transcriptional regulation (Kremsdorf et al., 2006). HBx also targets signaling cascades in the cytoplasm (i.e., Wnt/b-catenin, MAPK, STAT, PI3K/Akt, p53) (Tsai and Chung 2010; Branda and Wands 2006; Aravalli et al., 2008) (Figure 2). An

interaction with p53, has been shown, suggesting a role in transformation and a role in the

hindrance of DNA repair mechanisms (Tannock et al., 2005). Following inactivation of

p53, apoptosis, DNA repair, tumor suppression and other anti-cancer cascades are

inhibited. Furthermore, HBx interacts with transcription factors including NF-AT, CREB,

AP-1 etc (Nicholas et al., 2008) as well as transcriptional components in the nucleus, which

could influence gene expression (Andrisani and Barnabas 1999). It is known that HBx

cannot directly interact with the DNA and thus, must interact with cellular factors to target

the chromatin and complete its genomic effects (Rossner 1992).

Although HBx has been shown to trans-activate genes and target chromatin in the

proximity of these genes, a genome-wide perspective of HBx on the host genome, remains

unknown. Gene expression profiles of HBx target genes, within both primary human

hepatocytes (PHH) and HCC cells have begun to be explored, revealing targeted oncogenes

(i.e., c-myc) and tumor suppressor genes (Wu et al., 2001). Another study revealed targeted

Figure 2

7 Figure 2. Known Functions of HBx. The HBV trans-activator protein HBx has been shown to alter many signaling pathways and cellular components which causes an increase in genomic instability, epigenetic modifications, and proliferation as well as a decrease in apoptosis and differentiation. These functions have been attributed to the ability of this viral protein to aid in the development of liver cancer. Diagram modified from Tsai and

Chung, Oncogene, 29, 2309–2324, 2010.

8 transcription factors including SMAD4, CP2, ZID, AHR, AHRHIF, MYOD, ELK1, and

GL1, by chromatin immunoprecipitation and microarray technologies (Sung et al., 2009).

Although informative, these studies offer a limited view of the trans-activation functions of

HBx as the recruitment of HBx throughout the genome remains to be revealed. By understanding which genes this protein binds to, studies on the specific interactions of these genes can be explored further, to aid in the development of better therapies against this oncogenic virus.

1.2 Host-viral Interactions Associated with HBx

1.2.1 MTA1 and HBx

While searching for the cellular factors used by HBx to engage the host chromatin, our lab discovered that HBx stimulates the expression of metastasis tumor antigen 1

(MTA1), a master chromatin modifier and a component of the nucleosome remodeling histone deacetylation complex (NuRD). MTA1 is one of the widely up-regulated genes in human cancer (Manavanthi and Kumar 2007; Mazumdar et al., 2001) and it promotes tumor aggressiveness (Yoo et al., 2008) and has been linked with a reduced survival rate of cancer patients (Ryu et al., 2008). A connection between MTA1, HDAC1 and HBx within

HCC cells was also demonstrated by Yoo et al, where these factors together, secure HIF-1α expression, which may contribute to hypoxia-associated angiogenesis and metastasis (Yoo et al., 2008). In another study, by Moon et al, it was shown that 69% (n = 45) of HCC specimens over-expressed MTA1, 20 of these displaying invasion into the vasculature

(Moon et al., 2004). Furthermore, HCC patients were followed after removal of their liver tumors, with many showing increased MTA1 expression levels within their tumor cells but not within the surrounding normal tissue. This up-regulation of MTA1 expression was seen

Figure 3

10 Figure 3. Host-viral Interactions Connecting HBx, MTA1 and p65. HBx has been

shown to increase the expression of MTA1 by Western blotting and luciferase activity, and

this induction occurs at the transcriptional level as shown with Actinomycin D (A).

Induction of MTA1 by HBx occurs though the NF-κB complex (p50/p65) as shown with

the use of parthenolide. The region of HBx which interacts with the NF-κB complex

(p50/p65), was mutated and the induction of MTA1 by this mutated HBx protein was reduced (B), indicating that HBx induces the expression of MTA1 through the NF-κB complex (p50/p65). Relevant panels were adopted from Bui-Nguyen et al., Oncogene, 1–

11, 2009a.

11 in larger tumors and within those patients exhibiting increased invasion. These studies

highlight the significant role that MTA1 plays on invasion and growth of HCC. Patients

who have HCC and HBV, and whose cancer cells over-express MTA1, have a shorter

survival period than those whose cancer cells are MTA1 negative (Ryu et al., 2008). Our

lab has shown that HBx can induce the expression of MTA1 at the transcriptional level

(Figure 3). An increase in the expression of MTA1 protein would allow for a change in the

structure of the chromatin. MTA1 plays a role in how condensed or relaxed the chromatin

is. When the chromatin is relaxed, more factors can interact with unhindered genes,

resulting in altered gene expression. Because MTA1 is a dual co-regulator, it can play a

role in the activation or repression of various gene targets. This is significant because

MTA1 protein has been shown to be increased in many types of cancers and has been

linked with the ability of these cancer cells to metastasize. The MTA1 co-regulator protein

may alter the ability of HBx to interact with various cellular genes by regulating the

chromatin structure at various regions within the host genome. With an increase in MTA1

expression, the chromatin will become relaxed in some regions of the genome while

condensed in others, based on MTA1’s functions and target regions within the chromatin.

Because HBx increases the expression of MTA1, we believe that this virus is inducing a master co-regulator to allow it to complete its trans-activation functions by modulating its ability to interact with cancer-associated genes, leading to cellular transformation.

1.2.2 NF-κB, MTA1 and HBx

One cellular transcription factor that has previously been implicated in the trans- activation functions of HBx is nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) (Meyer et al., 1992). In normal hepatocytes, NF-κB activation is tightly

12 controlled by inhibitory molecules which are subject to regulation and can be activated

through stimulation by many factors including viral pathogens, such as HBV (Hiscott et al.,

2001). Increased activation of NF-κB has been described in the early stages of liver cancer

development, presumably due to persistent inflammation and the altered regulation of

targeted genes (Bui-Nguyen et al., 2009a). NF-κB also plays a critical role in liver

regeneration, the stress response, and cell fate (Arsura and Cavin 2005). HBx has been

found to degrade NF-κB inhibitors IkB-α and p105, relieving inhibitory effects on the

stimulation of NF-κB (Arsura and Cavin 2005).

The most abundant form of NF-κB is a heterodimer consisting of NF-κB1 (p50)

and RelA (p65), a known target of HBx (Bui-Nguyen et al., 2009a). The ability of HBx to

bind to p65 of this NF-κB complex allows it to target genes in the nucleus through the

specific –κB motif. This laboratory has previously shown that HBx utilizes the NF-κB

pathway to stimulate the expression of an oncogenic gene product with an established role

in human cancer, MTA1, as previously mentioned (Bui-Nguyen et al., 2009a). Our lab has

shown that p65 can interact with HBx, and that the resulting complex is recruited to the

MTA1 gene chromatin, increasing the expression of MTA1 protein (Bui-Nguyen et al.,

2009a) (Figure 3). HBx has been shown to activate MTA1 through NF-κB by quantitative

polymerase chain reaction (qPCR) where MTA1 relative expression increases in the

presence of HBx but is reduced by the addition of an NF-κB inhibitor, Parthenolide

(Figure 3). Our lab has also identified the site within HBx which interacts with NF-κB, and

mutated it, resulting in a reduction in the interaction between HBx and NF-κB(p65). A successful reduction in this interaction was also shown by luciferase activity, where, in the presence of the HBx Mutant, the relative promoter activity of MTA1 is less than when in

13 the presence of wild-type HBx protein. Together these results show that NF-κB is an important player in the ability of HBx to increase the expression of MTA1. In summary,

HBx has been shown to interact with p65 of the NF-κB complex and this interaction allows

HBx to be recruited to the host genome as NF-κB is a transcription factor that can translocate into the nucleus. Once inside the nucleus, HBx interacts with many genes on the chromatin, one of which is MTA1. Following the interaction of NF-κB(p65)/HBx, with the

MTA1 gene chromatin, MTA1 expression is increased. The HBx Mutant, devoid of the ability to use NF-κB to gain entry into the nucleus and target MTA1, will not cause an increase in MTA1 expression. The resulting increase in MTA1 protein allows for a change in chromatin structure. MTA1 protein can condense or relax the chromatin at various regions of the genome, altering whether HBx can bind to specific genes. When MTA1 protein is increased we expect that the genome-wide recruitment of HBx will be altered

(Figure 4).

Among various signaling pathways in HCC, the NF-κB pathway plays an important role in MTA1 function and also in supporting the survival and proliferation of hepatocytes.

In this context, our lab has shown that MTA1 is required for the optimal stimulatory effect of HBx on the expression of a number of cellular genes with roles in cancer progression

(Bui-Nguyen et al., 2009a). It was also shown that HBV-associated HCC caused a greater increase in MTA1 expression levels than Hepatitis C virus (HCV)-associated HCC, supporting the idea that the interaction between HBx and MTA1 is significant in the development of HBV-associated HCC, specifically (Ryu et al., 2008). Although a link between MTA1 and the NF-κB(p65)/HBx complex has been identified, the significance of

Figure 4

15 Figure 4. Schematic of Proposed Host-viral Interactions. HBx interacts with p65 of the

NF-κB complex (p50/p65) and is translocated to the nucleus where it targets and increases

the expression of MTA1 as well as other NF-κB target genes. As a co-regulator, MTA1 can

both increase, as well as decrease transcription by binding to the promoter region of genes and condensing the chromatin structure by associating in the Mi-2/NuRD complex,

respectively. Diagram modified from Luedde and Schwabe, Nat. Rev. Gastroenterol.

Hepatol, 2011, and Denslow and Wade, Oncogene, 2007.

16 these two cellular components in the ability of HBx to influence genome-wide transcription remains to be determined, particularly in the context of primary human hepatocytes (PHHs) as compared to transformed hepatocytes (HepG2). Based on the above observations, I have formulated the testable hypothesis that MTA1 could be central to the genome-wide recruitment of HBx and that the interaction between MTA1 and NF-κB may further influence the nature of putative cellular genes that are destined to be trans-regulated by

HBx. In this context, by high-throughput analyses, we have shown that NF-κB/p65 and

MTA1 play significant roles in the optimal stimulatory effect of HBx on the expression of a number of cellular genes with roles in gene expression and cancer, and have provided clues about the progression switches involved in the transformation of normal cells into cancer cells.

17 1.3 Specific Aims

Aim 1: To develop the experimental strategy and isolate the genome-wide chromatin

that HBx targets, in conditions with altered MTA1 and p65 involvement. HBx

interacts with, and trans-regulates host genes which may play a role in cellular

transformation. By isolating the genes targeted by HBx in conditions with wild-type and

altered MTA1 and p65 involvement, we can elucidate the functions of HBx with respect to

two host proteins.

Aim 2: To define the overall genome-wide recruitment patterns of HBx and the roles of MTA1 and p65. By characterizing genome-wide recruitment patterns, the roles of

MTA1 and p65 in the ability of a viral protein to target genes globally, may be defined.

Aim 3: To reveal the most significant genes for resulting trans-regulation, (targeted at

the TSS) and how this targeting is altered by MTA1 and p65. HBx recruitment to the

TSS of host genes may result in altered gene expression, aiding cancer development. By

analyzing these genes, the trans-regulation functions of HBx can be further characterized,

identifying top targets for future study.

Aim 4: To validate these findings, confirming bioinformatic methods. Validation to

confirm these findings through PCR and DNA gel electrophoresis of binding and qPCR of

binding and expression of representative genes, including one gene per sample condition,

supports the identification of these genes as being targeted by HBx, and the roles of p65

and MTA1.

18 Chapter 2: Materials and Methods

2.1 Cell Lines. Primary human hepatocytes (PHH) were a gift from Dr. Krishna Banudha

of The George Washington University and were cultured in HDM as described in

Banaudha, et al., 2010. Sustained primary hepatocyte cell culture is due to initial co-culture

of PHH cells with hepatic stellate cells and also the use of formulated media for optimal growth, as described. HepG2 cells are an adherent, hepatocellular carcinoma cell line, isolated from a 15 year old Caucasian male with no signs of HBV DNA present. These cells were purchased from American Type Culture Collection (ATCC) (HB-8065) and were cultured in EMEM from ATCC (30-2003) supplemented with 10% fetal bovine serum from Atlanta Biologicals (S11150) and 1% Antibiotic-Antimycotic from GIBCO

(15240).

2.2 Cloning. The HBx and HBx Mutant plasmids were obtained from Dr. V. Kumar,

International Centre for Genetic Engineering and Biotechnology, India. The HBx Mutant

plasmid has a mutation within amino acids 111 to 114 (YKFD to FAEN), as described in

(Bui-Nguyen et al., 2009a). Both plasmids were cloned into similar pcDNA 3.1c vector

backbones using restriction enzyme digestion with EcoR1 and T4 DNA ligase.

Transformation of plasmids into Ecoli cells was completed by a 45 second heat shock, and cells were plated onto ampicillin containing LB Agar plates and allowed to grow overnight.

Colonies were selected and grown in 4 mL of LB Broth with 4 µL of ampicillin for one

hour, which was transferred into a conical tube with 50 mL of LB Broth and 50 µL of

ampicillin, and allowed to grow overnight. Plasmid kits from Qiagen (12945) were used to

19 isolate the plasmids and the presence of HBx or the HBx Mutant fragments were confirmed

by sequencing.

2.3 Lentiviral Vectors. Lentiviral vectors for transduction of both cell lines were

constructed with the aid of Dr. Ali Ramezani of The George Washington University as

described (Ramezani and Hawley 2002). Briefly, the gene of interest (HBx or the HBx

Mutant) was subcloned into an HIV-1 transfer vector backbone. Cotransfection of the

plasmid into HEK293T cells (recipient cell line) with packaging and envelope plasmids, or

into a stable packaging cell line was completed and vector supernatants were collected, purified and titrated as described. Lentiviral vectors were flanked with long terminal repeats, driven by the elongation factor 1 alpha promoter with an internal ribosomal entry site (IRES) following the control, HBx or HBx Mutant fragments. GFP was inserted following the IRES, for detection (Figure 5). Successful transduction of PHHs and HepG2

cells was analyzed by FACS analysis and fluorescent microscopy.

2.4 siRNA Experiments. PHH or HepG2 cells were plated 400,000 per 60mm dish, serum

starved for 30 minutes with optimem medium from Life Technologies (31985-088) and

subjected to 8 µl of 20µM MTA1 specific siRNA from Thermoscientific (L-004127-00-

0050) or a control, during two consecutive days, were allowed to grow for 24 hours and

were collected. Transfection was completed with Oligofectamine per the manufacturer’s

protocol, Invitrogen, (12250.011). Successful reduction of MTA1 expression was tested by

Western blotting analysis.

20 2.5 Western Blotting Analysis. Subsets of all samples were subjected to Western blotting

analysis to reveal protein products following transductions of HBx and the HBx Mutant as

compared to the control vector, as well as successful knock-down of MTA1 expression by

siRNA as compared to non-sense control siRNA. Cells were lysed on ice and protein

amounts were confirmed using Bio-Rad Protein Assay Reagents (500-0133, 500-0114) and

Thermoscientific GeneSys 10S UV-Vis Spectrophotometer. Equal protein amounts were

loaded onto 12% agarose gels and proteins were transferred to nitrocellulose membranes at

100v for 1 hour, were blocked in 5% milk, washed with 1x PBS with Tween-20 and probed

for MTA1 monoclonal antibody from Santa Cruz (SC-17773), for HBx with T7 monoclonal antibody from EMD (69522-3) and for Vinculin monoclonal antibody diluted

1:10,000, from Sigma (V9131-0.5). Following overnight incubation, and washing, membranes were probed for 1 hour with horseradish peroxidase-conjugated secondary antibodies, specific to each primary antibody, diluted at 1:1000 in 5% milk solution.

Membranes were washed, and developed using ECL Reagents from VWR (95038-566).

2.6 FACS and Fluorescent Microscopy. Fluorescence activated cell sorting (FACS) scan

(FACScan) was completed with aid from Dr. Ali Ramezani of The George Washington

University, in the Flow Cytometry Core Facility. This machine has a fixed-alignment

cuvette flow cell (BD Biosciences) with one laser at a wavelength of 488 nm. Briefly, cells

were trypsonized, collected, and sorted by the presence of GFP expression to quantify the

percentage of cells successfully transduced by the lentiviral vectors. Fluorescent

microscopy was completed using a fluorescence microscope (Olympus) to detect the

21 presence of GFP and take images of these cells in samples used for Chromatin

Immunoprecipitation.

2.7 Chromatin Immunoprecipitation and Sequencing. Chromatin Immunoprecipitation

was completed by following the manufacturer’s protocol for the ChIP kit from Millipore

(17-295). Briefly, samples were fixed with paraformaldehyde, snap frozen in liquid nitrogen and stored in -80 degrees Celsius. Once 25 million cells were collected for all sample conditions, the pellets were lysed, and sonicated to fragment the DNA, and pre- cleared with protein AG beads where 200 µL of pre-cleared supernatant was saved as input. Nickel beads were added to the remaining supernatant to isolate the His-tagged HBx protein, bound to the chromatin. Beads were washed with low and high salt buffers and then LiCl wash buffer, followed by TE buffer. The agarose/antibody/chromatin complex was eluted with elution buffer, cross-links were reversed and the DNA was recovered by phenol/chloroform extraction and ethanol precipitation. Reversal of cross-links and phenol/chloroform extraction with ethanol precipitation was also performed on the input samples. Samples were stored in -80 degrees Celsius and then sent to Cofactor Genomics for sequencing on an Illumina platform by 60 base-pair reads. One tenth of each sample was saved for validation. ChIP was performed again, with more cells, to isolate more material for validation.

2.8 Computational Analyses

2.8.1 Avadis NGS. Avadis Next Generation Sequencing Software was used to

complete the initial Data-mining analyses. Files containing information regarding the 60

22 base pair reads, identified by sequencing, were uploaded onto this software. Samples

were analyzed by Model-Based Analysis for ChIP-Seq (MACS) to align, map, and

display the reads onto the human reference genome (Hg19) (Zhang et al., 2008).

Each sample was compared to the cell-type specific control which consisted of nickel

bead pull-down of chromatin, targeted by control lentiviral vectors, which did not

contain HBx (background pull-down). MACS allowed for comparison to the control

samples so that resulting data would not contain identical regions also targeted by the

vector, and pulled-down by the beads, without HBx. Resulting data were exported as

excel files and BED files of full-MACS lists by sample, and analyzed further. Global

recruitment by chromosome and within chromosome 1, as well as annotated regions,

binding sites and genes targeted, were also analyzed by Avadis NGS. Genetic Algorithm

guided formation of spaced Dyads coupled with an EM algorithm was used for motif

discovery GANDEM (Li 2009).

2.8.2 UCSC Genome Browser. The UCSC Genome Browser was also used to

visualize resulting data. MACS output lists in the form of BED files were uploaded

onto the website. Publically available datasets of chromatin marks within HepG2 cells, available from the UCSC Genome Browser, were used to predict resulting trans-regulation following HBx binding to regions within the chromatin. Chromatin mark files included four active (H3K4me2, H3K4me3, H3K9ac, H3K36me3) HepG2 files and one repressed

(H3K27me3), file from Broad/MGH ENCODE. To determine the chromatin marks of all top genes by condition, we compared the regions along the genome where the marks

23 spanned, to the regions of HBx binding. This browser was also used to design primers

specific to the binding sites.

2.8.3 Ingenuity Pathway Analysis (IPA). Gene lists pertaining to whole MACS

output lists by sample, as well as lists of only TSS targeted genes segregated by Avadis,

using the annotation regions tool, were uploaded to IPA, to compare sample conditions

and characterize the types of genes targeted. IPA was also used to identify gene

expression and cancer related genes, oncogenes, tumor suppressor genes, and other

categories of genes. IPA was used to identify top networks of recruitment as well as top

nodal points, to identify genes associated with MTA1 and NF-κB, and to characterize

recruitment to molecular and cellular pathways, and canonical pathways.

2.9 PCR, DNA gel Electrophoresis, and qPCR. To confirm binding to identified genes, we designed primers using Invitrogen Perfect Primer and the UCSC genome browser. The

UCSC genome browser allowed us to obtain the DNA sequence pertaining to the binding site that HBx targeted on each identified gene, which was the focus of primer design.

Conventional PCR was completed using Master Mix from Promega (M7502), and the

resulting products (200ng of input DNA, 1µl of 1:10 diluted ChIP DNA) were run on a 1%

agarose gel, visualized by ethidium bromide and UV, and sequenced. Quantitative PCR

(qPCR) was used to confirm binding and the resulting trans-regulation of target genes by

HBx binding through mRNA isolation and cDNA synthesis. Quantitative PCR utilized

SybrGreen Master Mix (Invitrogen) to quantify the presence of double stranded DNA, with

the qPCR program of three cycles plus melt on the CFX96 Real Time PCR machine.

24 Original ChIP samples were analyzed. Binding of HBx to ChIP samples, through qPCR, was calculated using the ΔΔCt method for fold enrichment as described in SABiosciences

Champion ChIP qPCR primers manual, Version 1.2, 2008. Expression was calculated with the average of Ct values as compared to the cell type specific control with the 18s housekeeping gene and the gene of interest.

25 Chapter 3: Results

3.1 Introduction and Experimental Model

3.1.1 Introduction

Preliminary data indicating that HBx interacts with RelA (p65) to target MTA1, and the established roles of these factors in cancer, led us to explore the roles of p65 and

MTA1 in the genome-wide recruitment of HBx, together defining the impact of MTA1. As a trans-activator protein, HBx may target and subsequently alter the expression of numerous cellular genes. Some of these trans-regulated genes may play a role in cancer, which could further characterize the mechanism behind HBx-mediated cellular transformation. The ability of HBx to interact with p65 suggests that HBx uses the NF-κB transcription factor complex (among others) to translocate to the nucleus where it can target cellular chromatin. This interaction may also result in HBx targeting of NF-κB motifs as well as promoter regions of many genes such as MTA1. The ability of HBx to target and increase the expression of MTA1, a master chromatin modifier of the NURD complex, suggests that this viral protein employs a cellular factor to alter the chromatin structure, and so, cellular gene accessibility. With the altered expression of MTA1, which has been found in many types of cancer, the chromatin accessibility changes, allowing HBx to target and alter more or different genes, possibly contributing to cellular transformation. In order to elucidate the roles of these two cellular factors in the ability of HBx to target the genome and contribute to cellular transformation, we analyzed the gene targets of HBx with and without altering the involvement of these factors. To represent a normal, untransformed environment which would be most similar to liver cells during initial stages of infection, we employed primary human hepatocytes (PHH), and to represent a cancerous

26 environment, hepatocellular carcinoma cells (HepG2), in the hopes that these environments

would help us further characterize HBx recruitment both pre- and post- cancer

development. The identified targets were analyzed to reveal a comprehensive view of

genome-wide recruitment as well as more specific recruitment including targeting of genes

with known roles in gene expression and cancer. As HBx is a trans-activator protein, which

has been implicated in cellular transformation, the analysis of genes related to gene

expression, which could further alter this process, as well as genes involved in cancer,

which could contribute to cellular transformation, is desired. Targeting of genes at the TSS

is also of interest, and these genes were chosen for validation. Revealing the genes targeted

by this viral protein and the roles of these two cellular players, could help to elucidate the

mechanisms behind the development of HBV-associated HCC.

3.1.2 Experimental Strategy

The experimental model employed to explore the genome-wide recruitment of HBx

was developed to include HBx expression, altered p65 involvement (HBx Mutant) and

altered MTA1 expression (siRNA), chromatin isolation, deep sequencing and bioinformatic

analyses (Figure 6). For optimal expression of HBx or the HBx Mutant within both PHHs

and HepG2 cells, lentiviral vectors were constructed (Ramezani and Hawley 2002). These

vectors contained HBx or the HBx Mutant fragment as well as GFP for detection (Figure

5). Cells were transduced at a multiplicity of infection (MOI) of 1-3 which allowed for a

55% to 84% transduction rate in primary hepatocytes and a 77% to 94% transduction rate

in HepG2 cells, with minimal effects on cellular viability. Transduction was confirmed with fluorescence activated cell sorting (FACS) (Figure 7). Expression of GFP under a

HBx or HBx Mutant

B C PHH or HepG2

293T

HBx or HBx Mutant

Figure 5

28 Figure 5. Cloning and the Lentiviral Vector System. HBx or the HBx Mutant fragments were isolated from their original vectors and ligated into pcDNA3.1c vector backbone for consistency, using EcoRI restriction enzymes (A). The transgene expression cassette (HIV-

1 transfer backbone) was flanked by two long terminal repeats (LTR), driven by the elongation factor 1α promoter, and included an internal ribosomal entry site (IRES) for the subsequent expression of green fluorescent protein (GFP) for detection (B). Packaging cells

(293T cells) were transfected with the HIV-1 transfer backbone along with envelope and packaging plasmids. Vector supernatants, containing the viral vectors were collected, purified and titrated. Vector particles were used to transduce both PHHs and HepG2 cells

(C). pcDNA3.1c vector image (A) was modified from https://www.lablife.org/g?a=seqa&id=vdb_g2.81SqI8HyiBwlJgny8plBGmQk.Us-

_sequence_de96c67ab7425eee01e6cdab5fe561935d8d7619_10. Lentiviral vector transduction figure (C) was modified from http://www.creative-biogene.com/Lentivirus-

Service.asp.

29 fluorescent microscope was expected with the successful transduction of these cells and was also confirmed (Figure 7). Select samples were also subjected to MTA1 knock-down by utilizing MTA1 specific siRNA, as compared to a nonsense control siRNA. Western blotting immunoassays were conducted to reveal the expression of HBx or the HBx Mutant as well as the reduction in the expression of MTA1, where applicable (Figure 7).

Chromatin Immunoprecipitations (ChIP) utilizing nickel beads were completed on all samples to isolate the chromatin that His-tagged HBx bound to and samples were sent to

Cofactor Genomics for deep sequencing on an Illumina platform (Figure 8). Utilizing the aforementioned strategy, we were able to isolate HBx in both PHHs and HepG2 cells with four levels of MTA1 expression. These conditions included wild-type HBx expression with the involvement of p65 and wild-type MTA1 expression, wild-type HBx expression with wild-type p65 involvement and reduced MTA1 expression, HBx Mutant expression devoid of the ability to interact with p65 and wild-type MTA1 expression (which is reduced by the lack of interaction with p65) and this scenario with additional MTA1 reduction (Figure 9).

By isolating the chromatin that HBx is bound to in all of these conditions, as compared to a control lentiviral vector and recruitment within normal as well as cancer cells, we have isolated the material which is essential for defining the genome-wide recruitment of HBx in relation to the role of MTA1.

To characterize the genome-wide recruitment patterns of the viral trans-activator protein HBx, in response to altered NF-κB (p65) and MTA1 involvement, we applied the experimental strategy previously mentioned. Data-mining analyses were completed by using Avadis Next Generation Sequencing Software (Avadis NGS) where a high quality of alignment to the human reference genome was observed. Overall recruitment patterns were

Figure 6

31 Figure 6. Experimental Strategy - Workflow. The overall experimental model utilizes transduced PHHs and HepG2 cells which express HBx or the HBx Mutant, devoid of the p65 binding site, with MTA1 knock-down in select samples, to isolate the chromatin that

HBx is bound to in various samples (ChIP). The resulting purified DNA was sent for deep sequencing on an Illumina platform, and the data was analyzed bioinformatically with

Avadis Next Generation Sequencing Software (Avadis NGS), Ingenuity Pathway Analysis

Software (IPA) and the UCSC Genome Browser. Data was characterized to reveal overall recruitment patterns of HBx in all conditions to elucidate the roles of MTA1 and p65, and to isolate genes important in gene expression and cancer. Genes targeted at the TSS, which would be of most importance, were focused on for validation experiments by PCR and qPCR of ChIP.

32 analyzed by this software as well (Figure 8). Output files containing detailed recruitment

characteristics, following Model-based Analysis for Chip-Seq (MACS), were also analyzed by Ingenuity Pathway Analysis (IPA) and with the UCSC Genome Browser. HBx recruitment within each sample set was further analyzed by multiple characterizations to reveal the most significant recruitment to genes, with and without p65 and MTA1.

Emphasis was placed on revealing targets of the heaviest recruitment, recruitment to all genes targeted at the TSS, and to genes related to gene expression and cancer.

Bioinformatic analyses of publically available datasets on chromatin marks within HepG2

cells, were used to predict the possible trans-regulation of targeted genes (Figure 10). The

results of these analyses provide a comprehensive, global view of HBx recruitment, with

and without altered MTA1 and p65 involvement. Representative targets by condition,

which had TSS recruitment were chosen for validation. Recruitment to regions within these gene targets and a resulting alteration in expression was validated within ChIP samples.

Using the aforementioned strategies, we have identified intriguing patterns of HBx

recruitment as well as novel HBx targets, dependent on, or independent from, MTA1 and

p65, and more specifically, HBx recruitment with respect to MTA1 status. This study

provides a wealth of information on the global targets of HBx and the roles of two cellular

factors, which further characterizes these host-pathogen interactions that may contribute to

the development of liver cancer.

33 A

Figure 7

34 Figure 7. Detection of HBx Transduction and Reduction of MTA1 Expression. Due to

the GFP sequence present in our lentiviral vectors, we are able to detect successful transductions through the presence of fluorescence. To do this we used FACS analysis to

quantify the percentage of cells that were transduced by the control, HBx and HBx Mutant

lentiviral vectors (A). We also used fluorescence microscopy to detect GFP as well, and a

representative image of transduced PHHs and HepG2 cells is shown (B). To confirm that this transduction resulted in protein expression of HBx or the HBx Mutant, and that treatment with MTA1 siRNA reduced the expression of MTA1, we completed Western blotting (C).

Figure 8

36 Figure 8. The Use of ChIP-Seq to Identify Targeted Genes. The strategy for isolating

HBx targeted chromatin in all conditions employed Chromatin Immunoprecipitation and

Deep Sequencing (ChIP-Seq), resulting in vast amounts of data which had to be aligned to

the Human Hg19 reference genome. Alignment was completed by utilizing Avadis Next

Generation Sequencing Software (C) where data from all sample conditions was compared

to the cell-type specific control, revealing recruitment by reads and enrichment of peaks

and proximity to genes (A). Enrichment peaks where HBx recruitment, in various

conditions, was higher than that of the control, were identified as HBx binding regions and were analyzed further (B). Figure modified from Hoffman et al., 2007; and Avadis NGS,

Accessed at: http://www.avadis-ngs.com/applications/chip_seq.

Figure 9

38 Figure 9. Experimental Strategy - Targets. To elucidate the role of MTA1 in genome- wide targeting by HBx, by knock-down of expression and reduction of an interaction with p65, which is needed for HBx to increase MTA1 expression, we altered these characteristics within both normal (PHH) and cancer (HepG2) cells. This strategy aims to produce conditions with four levels of MTA1 expression which results in four distinct lists of targeted genes per cell type. With the wild-type HBx condition, HBx will bind to the cellular factor p65 to target the MTA1 gene and increase its expression. With an increase in

MTA1 expression, the chromatin structure will be altered. Here, we have also knocked- down MTA1 to reduce this effect and to reduce the ability of MTA1 to alter the chromatin.

With the HBx Mutant, HBx will target host genes without the aid of p65 and this also reduces its ability to target and increase MTA1 expression. With reduced MTA1 expression, the chromatin will be less altered by MTA1. Here, we have also knocked-down

MTA1 expression to reduce MTA1’s involvement to the lowest level, thereby defining the role that MTA1 plays by comparing the resulting gene lists that HBx can target in all conditions and in both normal and cancer cells.

39 3.2 Global Genome-wide Targeting of HBx and the Role of MTA1.

3.2.1 Characteristics of Binding

The global genome-wide recruitment patterns were analyzed to reveal recruitment to total binding sites and genes, recruitment to annotated regions of genes, chromosomal recruitment, recruitment to top nodal points and networks associated with NF-κB and

MTA1, and top unfiltered targets. To begin characterizing the genome-wide binding patterns of HBx and the role of MTA1, we determined the total number of binding sites and genes, targeted in each condition. To do this, we analyzed the MACS output tables to summarize the aforementioned values which were graphed to reveal the change in binding as MTA1 involvement was reduced. These analyses confirmed that recruitment within normal and cancer cells are distinct. For instance, In PHHs, HBx recruitment to the total number of genes increases from 1138 to 4250, 6933 and finally 8771, as the involvement of these factors is reduced, while the total number of binding sites is similar (Figure 11).

Similarly, HBx is recruited to an increasing number of exonic, upstream/promoter/TSS and downstream regions within genes, as MTA1 involvement is reduced, in both cell types

(Figure 11). With a reduction in MTA1 expression, HBx can bind more regions within the genome, whereas with wild-type MTA1 expression, HBx cannot target these regions, suggesting that normally, MTA1 may condense the chromatin, enclosing these regions. In

HepG2 cells, a dissimilar pattern of HBx recruitment was seen. Here, the total number of genes targeted by HBx remains within a difference of 1200 throughout the reduction of these two factors (Figure 11). Although this trend of total recruitment is dissimilar to the recruitment within PHHs, the genes that HBx is being recruited to, is changing as the

Figure 10

41 Figure 10. Chromatin Mark Proximity by Bioinformatics. To predict resulting trans- regulation following HBx targeting of genes, through bioinformatic methods, to characterize a large volume of data, we determined the chromatin mark proximity to regions where HBx bound. To do this, we utilized publically available datasets on chromatin marks within HepG2 cells, provided by the UCSC Genome Browser, corresponding to four activating and one repressive mark. By aligning HBx binding sites with these marks, we predicted whether HBx increases or decreases gene expression of the targeted genes. For example, representative gene ZFYVE19 has HBx binding in Sample A and this binding aligns with three active chromatin marks and the repressive mark, indicating that recruitment in these samples may result in either activation or repression of this gene. Although these predictions provide a lot of information pertaining to the resulting altered trans-regulation, predictions must be validated with qPCR of cDNA taken from all conditions, as done for validation on select genes (discussed below). ZFYVE19 for instance, was shown to be slightly reduced by HBx binding, through qPCR analysis

(Figure 26).

42 involvement of these factors is reduced, as it does within PHHs. In cancer cells, wild-type

HBx is recruited to the highest number of genes but HBx is recruited to more significant annotation regions with the reduction in p65 involvement, indicating that without binding to p65, HBx targets more regions that would allow for a change in gene expression, and this trend is also seen in PHHs (Figure 11). In these cells, the most recruitment to promoter regions of genes occurs with a reduction in the involvement of p65, with 75 targeted genes compared to just 4 with wild-type HBx, indicating that this cellular factor, may assist in blocking HBx from targeting these promoter regions of genes, reducing its ability to trans- regulate them (Figure 11). Recruitment to active chromatin mark regions within genes, increases without this cellular factor as well, although when MTA1 is also reduced, this recruitment diminishes. The overall genome-wide recruitment of HBx varies by whether the cellular environment is pre- or post- cancerous and also is greatly altered by the status of both p65 and MTA1, indicating important roles for these cellular factors in the ability of

HBx to trans-regulate host genes. As the involvement of p65 and MTA1 is reduced in

PHHs, HBx is able to target more genes at the TSS, suggesting that these two cellular players are guidance factors for the genome-wide recruitment of HBx, in pre-cancerous cells. Overall, the ability of HBx to target binding sites and genes within the host cell is altered by MTA1 and p65 involvement. If MTA1 reduction allows HBx to target more and different binding sites and genes, what are these genes and how do they play a role in the ability of HBx to cause cancer?

Figure 11

44 Figure 11. Genome-wide Recruitment Patterns of HBx by Total Binding Sites, Total

Genes and Annotated Regions. Total Binding Sites, Genes, and Annotated Regions were analyzed with Avadis NGS. HBx targeting of total binding sites and total genes by sample condition and cell type reveals clues about the global targeting of this viral protein to the host genome. Annotated regions targeted by HBx segregates targeting by region within the gene, to reveal overall binding patterns and to isolate TSS targeted genes for further study.

45 3.2.2 MTA1 and p65 are Central to the Genome-wide Targeting of HBx, by IPA Network Analysis

Using IPA software to analyze full MACS output lists of wild-type HBx target

genes, we confirmed that MTA1 and the NF-κB complex, which includes p65, are central

to the genome-wide recruitment of HBx as they appear within the top nodal points in

targeted gene networks (Figure 12). Networks described by IPA depict the relationships

between genes, showing those that are connected to numerous other genes in the targeted

lists, thereby revealing their importance. These data represent that the two cellular factors,

MTA1 and p65, are indeed important in the genome-wide recruitment of wild-type HBx. In

PHHs, the NF-κB complex appears within a network representing Immunological Disease,

Organ Injury and Lymphoid Tissue Development. This network includes numerous cellular factors that are also targeted by HBx in the wild-type condition, in PHHs, including EGF,

STAT3, and the PI3K complex, among others. Signal Transducer and Activator of

Transcription 3 (STAT3) for example, was found to be targeted by HBx with enrichment and reads values of 46.0 and 15, respectively, and was targeted in only one other condition.

This condition included HBx wild-type with MTA1 knock-down in HepG2 cells, with enrichment and reads values of 7.0 and 30, respectively. These data indicate that HBx targeting of STAT3 only occurs in PHHs with wild-type recruitment, as well as in HepG2 cells with the first level of MTA1 knock-down, indicating a need for p65 involvement and

MTA1 expression in the ability of HBx to target STAT3 (Figure 13). STAT3 has been shown to play a role in anti-apoptotic effects when over-expressed in many types of cancer.

We found that HBx targets STAT3 in the presence of MTA1, in proximity to active chromatin marks, indicating that with MTA1 expression, HBx targets STAT3 and activates its transcription, increasing the expression of a protein which is involved in cancer.

46 Another representative gene target, Epidermal Growth Factor (EGF), was found to be bound by HBx in PHHs, in all conditions with increasing enrichment and reads values as MTA1 was reduced. This indicates that in normal cells, MTA1 expression hinders the ability of HBx to target this gene. In cancer cells, the pattern is different, with targeting in the HBx wild-type condition also, but no targeting once MTA1 is reduced, indicating that in liver cancer cells, HBx needs wild-type MTA1 expression to target this gene. Targeting of EGF by HBx occurs within proximity to repressed chromatin marks, indicating that as

MTA1 is reduced in PHHs, HBx increases the repression of EGF, possibly repressing proliferation. As an over-expression of MTA1 is involved in cancer progression, HBx repressing a gene involved in proliferation when MTA1 expression is reduced, follows the known functions of MTA1. Here, HBx may repress proliferation by targeting EGF and this repression could be increased with a reduction in MTA1 expression, indicating an important role for MTA1 in HBx mediated gene trans-regulation, in HCC. All of the aforementioned affects of HBx are bioinformatic predictions, which would need to be confirmed, prior to extended research. In HepG2 cells, the NF-κB complex appears in a top network representing Cardiovascular and Immunological Disease, and Connective Tissue

Disorders. Here, HBx targets NF-κB associated factors such as SUMO4, WTAP, and

CAMK2D, among others. Small Ubiquitin Related Modifier 4 (SUMO4) for instance, is an

HBx target gene with wild-type MTA1 expression in HepG2 cells, and is not targeted once

MTA1 is reduced. On the contrary, in PHHs, HBx can’t target SUMO4 until MTA1 expression has been reduced with the HBx Mutant or the HBx Mutant, MTA1 knock-down conditions. This gene acts to control the activity of target genes and is known to alter the activity of IKBα, reducing the transcription of IL12B, by NF-κB. This indicates that HBx

NF-kB MTA1

PHH

Immunological Disease, Organ Injury, Lymphoid Gene Expression, Cell death, Cell Growth Tissue Development and Proliferation

HepG2

Cardiovascular and Immunological Behavior, Reproductive System and Organ Disease, Connective Tissue Disorders Development

Figure 12

48 Figure 12. MTA1 and p65 are Central to the Genome-wide Recritment of HBx by

IPA Network Analysis. Both MTA1 and the NF-κB complex were found to be central nodes of wild-type HBx recruitment by IPA network analysis of full MACS lists, supporting the notion that these cellular components are central to wild-type HBx targeting of host genes. Genes which are linked to these components through gene networks, and are shaded, are also targeted by HBx in this condition, revealing other associated factors which may be involved in HBx targeting of MTA1 and NF-κB.

49 targeting of genes like SUMO4, is dependent on MTA1 status, which differs depending on the cell type. In both cell types, MTA1 was also found as a top nodal point within targeted gene networks. In PHHs, MTA1 is central to a network associated with Gene Expression,

Cell Proliferation and Cell Death whereas in HepG2 cells, the MTA1 associated network represents genes linked to Behavior, the Reproductive System and Organ Development. In

PHHs, MTA1 associated genes include HMGB1, SP1, and BCL2, among others.

Recruitment to Specificity protein 1 (SP1), a known p65 interacting protein and a known target of other viruses (Perkins, ND., et al, 1994), which is involved in modulating gene expression during development, occurs in both cell types with wild-type HBx recruitment. In PHHs, recruitment also occurs when p65 and both p65 and MTA1 are reduced in involvement. Recruitment in PHHs increases as MTA1 is reduced indicating that MTA1 normally condenses the chromatin, hindering heavy recruitment. This recruitment is near active chromatin marks indicating that with a reduction in MTA1 expression, HBx targets and activates SP1 more, altering related gene expression and as

SP1 may act as a tumor suppressor, this recruitment correlates with the known functions of

MTA1. In HepG2 cells HBx targets MTA1 associated genes including SIX3 and MNAT1.

Six Homeobox 3 (SIX3) plays a role in gene transcription and has been linked to repressing

Wnt genes during development. SIX3 has already been shown to be associated with MTA1 in the ability of MTA1 to alter the expression of Wnt targets which are also associated with cancer (Kumar et al., 2010a; Kumar et al., 2010b). Here, with wild-type MTA1 expression, in liver cancer cells, HBx can target this gene, possibly activating it. Increased recruitment is seen in PHHs without p65 involvement, which reduces MTA1 expression. The ability of

Figure 13

EGF STAT3

HMGB1 SP1

Figure 13

52 SUMO4

CAMK2D

BCL2

WTAP

Figure 13

53 MNAT1

SIX3

Figure 13

54 Figure 13. Enrichment and Reads Details of MTA1 and NF-kB Associated Genes,

Targeted in HBx wild-type Conditions. HBx recruitment details including enrichment and reads to target genes, from MACS output lists generated by Avadis NGS, associated with MTA1 and NF-kB centered networks, reveal the importance of these two cellular players in HBx wild-type recruitment while providing information regarding select targeted genes. UCSC Genome Browser snapshots provide binding sites and chromatin mark proximity data by target gene mentioned.

55 HBx to target this MTA1-associated gene depends heavily on the expression of MTA1 in both cell types. Confirming the presence of the two cellular factors of interest by Ingenuity

Pathway Analysis of HBx recruitment to top networks of genes, supports the notion that both MTA1 and the NF-κB complex play important roles in the genome-wide recruitment of HBx, and further defines the MTA1 and NF-κB-associated pathways and more specifically, associated genes which are targeted.

3.2.3 Genome-wide Targeting of HBx to Chromosomes

To further elucidate the genome-wide recruitment patterns of HBx, we analyzed the ability of HBx to target all chromosomes and compared how this targeting changed as

MTA1 involvement was reduced. By percent chromosomal distribution of reads, HBx recruitment was found to occur throughout all chromosomes, with similar patterns of recruitment in both cell types (Figure 14A). Increased recruitment in PHHs occurred in chromosome 9 and the X chromosome with wild-type HBx, and in HepG2 cells with HBx and MTA1 knock-down, increased recruitment occurred to chromosomes 4 and 8 which have been previously connected to liver cancer (Pasquinelli et al., 1988; Becker et al.,

1996). By focusing on recruitment by reads to one chromosome, represented by chromosome 1 in Figure 14B, we revealed distinct patterns of recruitment which differed by cell type. In PHHs, wild-type HBx recruitment was less than within HepG2 cells, but this recruitment drastically increased as MTA1 involvement was reduced in PHHs. With the HBx Mutant and MTA1 knock-down conditions, where MTA1 expression/involvement were reduced, HBx recruitment in PHHs blanketed the chromosomes, where, in HepG2 cells the amount of recruitment remained similar as the involvement of MTA1 was altered.

56 A

Chromosome

Chromosome B

Figure 14

57 Figure 14. Genome-wide Recruitment Patterns of HBx to Chromosomes. HBx recruitment to chromosomes was completed by plotting total reads values per chromosome by sample condition. The genome-wide targeting of HBx occurs throughout all chromosomes with no striking chromosomes being favored or avoided. wild-type HBx in

PHHs may favor regions within chromosome 9 and chromosome X while wild-type HBx with MTA1 k/d may favor chromosomes 4 and 8, which have previously been linked to

HCC. Also, recruitment to all chromosomes individually, represented by chromosome 1, reveal intriguing patterns of HBx targeting. In PHHs, HBx recruitment drastically increases as MTA1 and p65 involvement is reduced, as previously revealed with total genes targeted.

In HepG2 cells this pattern is not seen although targeting is changing as the involvement of these factors is altered.

58 Although the change in this recruitment was not as drastic as in PHHs, the binding regions within HepG2 cells did change by condition, which is apparent in the enlarged panel of

Figure 14B, and is also reflected by changes in annotated regions and genes targeted, as described previously. This data shows that in PHHs, HBx can target a larger area of the genome, as MTA1 involvement is reduced, indicating that as MTA1 is reduced, the chromatin is relaxed, allowing HBx to target more regions. As MTA1 plays a role in condensing the chromatin by recruiting HDACs, the reduction in MTA1, causing an increase in genome-wide targeting of HBx, makes sense. MTA1 may condense the chromatin in wild-type conditions, reducing the ability of HBx to target genes. The regions with the heaviest recruitment, such as within chromosomes 4 and 8, within the MTA1 knock-down condition in HepG2 cells can further be analyzed to reveal the genes which are targeted when MTA1 expression is reduced, and may be known or novel to the development of HCC.

Upon further analysis, it was found that 41 genes were targeted in chromosome 4, with MTA1 knock-down in HepG2 cells, including many with high reads values such as,

Double homeobox 4 (DUX4) and many DUX4-like genes with a total of 2602 reads,

Ubiquitin Specific Peptidase 17 (USP17) and its pseudogene (USP17L6P) with a total of

1613 reads and many uncharacterized genes encoding hypothetical proteins (LOC) with a total of 4117 reads. DUX4 is a transcriptional regulator whereas USP17 plays a role in apoptosis. Recruitment here may be activated or repressed as there is proximity to both chromatin marks, or no chromatin marks at all. Further studies on these genes including genes with no known function as of yet (LOC), would have to be completed to further characterize the ability of HBx to target chromosome 4 more heavily when MTA1

59 expression is reduced, in cancer cells. These data represent targets for future studies in

defining the role of MTA1 in viral trans-activator-induced HCC.

In chromosome 8, an increase in recruitment by reads was also seen with

MTA1 knock-down in cancer cells and this recruitment also corresponded to three gene

families. Similarly to chromosome 4, many uncharacterized genes (LOC) were targeted

with a total of 3003 reads. Eight members of an uncharacterized family of genes

(FAM90A) were also targeted with a total of 192 reads. FAM90A genes include a

transposable element L1MB3, a long interspersed repeat element (LINE), which was found

to be targeted by HBx in this condition, by UCSC genome browser analysis, further

characterizing the binding motif responsible for the increase in recruitment to this family of

genes. This recruitment was also seen, only with both p65 reduction and MTA1 knock-

down within the same cell type, although targeting was much less (80 vs.192 total reads).

The highest total number of reads occurred within REX1, RNA exonuclease 1 homolog (S.

cerevisiae)-like 1 (RexO1L1) and related pseudogenes with 8241 reads. RexO1L1 also known as GOR, has been shown to be associated with immunopathogenesis among those

with a chronic hepatitis related to Hepatitis C virus (HCV) (Quiroga et al., 1996). Here,

HBx may be targeting this exonuclease when MTA1 expression is reduced in HepG2 cells, and this may play a role in chronic hepatitis as was found with HCV. These identified target genes and the role that MTA1 plays in the ability of HBx to target them, are ideal

candidates for future studies.

Overall, these data demonstrate that HBx targets all chromosomes and by altering

the involvement of p65 and MTA1, resulting in differing levels of MTA1 expression, the

overall targeting of the genome, represented by chromosome, is drastically altered. By

60 comparing the genes, targeted by HBx within all conditions, we can further delineate the

role of MTA1 in the trans-regulating functions of HBx, as related to the development of

HCC.

3.2.4 Unfiltered Heaviest HBx Recruitment

To elucidate more details of the genome-wide targeting of HBx, we sought to identify genes which were targeted with the highest enrichment and reads values, to represent unfiltered heavy recruitment, prior to narrowing-down to top targets by various criteria. This analysis allowed us to identify those genes targeted the most by HBx, which may also be important targets as increased recruitment may suggest a high probability of resulting trans-regulation. Here, we utilized output files from Avadis NGS, generated following MACS analysis, and sorted descending, by total enrichment and reads. The top ten genes targeted by HBx, by condition and by cell type are listed in Tables 1 and 2.

Recruitment of HBx to these genes, in all other conditions, is also depicted, to reveal the

role of MTA1 on the targeting of these genes. These targets conclude the analysis of global

recruitment patterns as they represent genes which are targeted by HBx and the role of

MTA1 without focusing on any particular characteristic. These tables were constructed to

provide information on additional targets of HBx and the role of MTA1 by each individual

gene, for future study, and are not the immediate focus of this research.

3.3 MTA1 Status Alters the Ability of HBx to Target Categories of Genes

3.3.1 Molecular and Cellular Functions and Canonical Pathways of Targeted Genes

Overall recruitment by top canonical pathways and biological functions, including

molecular and cellular functions, was analyzed with IPA to reveal recruitment categories,

Top 10 Unfiltered Targets of HBx by Condition a. Primary Hepatocytes (PHH)

Table 1

62 Table 1. Unfiltered HBx targets by Sample Condition with Corresponding

Recruitment Data for All Conditions, in PHHs. Top 10 genes by sample condition within PHHs, with unfiltered MACS target gene lists, sorted to focus on the highest enrichment and reads values (recruitment), closest to genes. Heaviest recruitment, regardless of all criteria, may reveal additional targets which are manipulated by HBx and the role of MTA1, to represent individual targets of global recruitment, specific to HBx targeting in normal liver cells, for further study.

Top 10 Unfiltered Targets of HBx by Condition b. Liver Cancer Cells (HepG2)

Table 2

64 Table 2. Unfiltered HBx targets by Sample Condition with Corresponding

Recruitment Data for All Conditions, in HepG2 cells. Top 10 genes by sample condition within HepG2 cells, with unfiltered MACS target gene lists, sorted to focus on the highest enrichment and reads values (recruitment), closest to genes. Heaviest recruitment, regardless of all criteria, may reveal additional targets which are manipulated by HBx and the role of MTA1, to represent individual targets of global recruitment, specific to HBx targeting in liver cancer cells, for further study.

65 and how these categories of gene targets were altered as the involvement of p65 and MTA1 was reduced (Figure 15). This allows us to categorize these large gene lists to elucidate the types of genes targeted in each condition. Here, a similar overall recruitment pattern within both cell types is seen, which includes many cardiac and neuronal related canonical pathways and similar molecular and biological function categories between samples and cell types. In PHHs, molecular mechanisms of cancer (138 genes) appears within the top five canonical pathways following the disruption of both p65 and MTA1 involvement, suggesting that HBx targets more cancer related genes with a disruption in the wild-type involvement of these two cellular factors, which will be discussed further. With wild-type

HBx, gene expression is the top molecular and biological function category within HepG2 cells but this category only appears in PHHs following the reduction in p65 or both cellular factors, with five times the number of related genes. This indicates that in PHHs, HBx may target more gene expression related genes, resulting in increased genome-wide trans- regulation, when p65 and MTA1 are reduced. Within both cell types, the categories of genes representing overall recruitment of HBx is dramatically altered by changing the involvement of these two cellular factors, indicating a significant role for p65 and MTA1 in the ability of HBx to trans-regulate host genes, possibly aiding in the development of cancer.

Figure 15

67 Figure 15. HBx Recruitment to Molecular and Cellular Functions, and Canonical

Pathways Related Gene Groups. Recruitment to associated genes was completed by using IPA on MACS full output lists from Avadis NGS, and plotting details of categorized genes per condition. Global recruitment patterns by Molecular and Cellular Functions and

Canonical Pathways by IPA, reveal an increase in recruitment to cancer related genes in

PHHs following the disruption in p65 and MTA1, with the lowest MTA1 expression. Gene expression related genes are also targeted more in this cell type with a reduction in MTA1 and p65, which are targeted in HepG2 cells without altered involvement or when p65 is reduced. Other categories such as cell assembly and organization appear in HepG2 cells as top gene targeted categories.

Top Nodal points

PHH HepG2 HBx ERBB2, HGF, ZNF143, MLL, YY1, RNA Pol II., PRDM5, NF-ĸBComplex, Mutant, NF-ĸBComplex, SP1 TRAF2, DISC1, IL1RN, LDLR, AKT, MTA1 k/d MARK4

HBx TP53, NR3C1, AR, SERPINE1, SP1, IL-2 ESR1, HNF4A, AR, HSP90, LDLR, Fsh, Mutant REL, JAK1 RNA Pol II., NF-ĸB Complex

HBx wt, E2F1, E2F, ERBB2, AR, NCOR1, Fsh, Lh, RNA Pol II., Actin, Interferon α, AKT, MTA1 k/d Histone H3 NF-ĸBComplex, PI3K Complex, Fsh, Lh, Histone H3, NR3C1 Histone H3, SP1, NF-ĸB Complex, RB1, Actin, Fsh, Lh, RNA Pol. II, HBx wt PI3K Complex, AKT, YWHAG, Histone H3, AKT, EP300, Interferon α, CTNNB1, NR3C1, MTA1 26s Proteasome, MTA1, NF-ĸBComplex

Nodal Point

Key MTA1 NF-kB Cancer-associated Gene expression-associated

Figure 16

69 Figure 16. HBx Recruitment to Top Nodal Points by Sample Condition. Recruitment to top nodal points was completed by using IPA on full MACS output lists from Avadis and analyzing all nodal points within networks. Top nodal points targeted by HBx, by condition, reveal that the NF-κB complex is targeted in most categories. HBx also targets many cancer associated and gene expression associated nodal points, suggesting that HBx may be altering many gene pathways related to these categories. By altering the expression of a nodal point, HBx may be subsequently affecting related genes.

70 3.3.2 HBx Recruitment to Top Nodal Points of Networks

Recruitment to top nodal points within networks revealed MTA1 and p65 to be central to

the genome-wide recruitment of HBx, as previously shown, and revealed genes with many

associated factors to be targeted. These nodes reveal similarities and differences of the top

players in recruitment which are independent of, and dependent on p65 and MTA1 (Figure

16). It is apparent that MTA1 and p65 are important in HBx recruitment as they both were found to be top nodal points in HBx wild-type recruitment, as previously described (Figure

12). The NF-κB complex was central to recruitment within all conditions in both cell types but was not among the top ten networks in PHHs with MTA1 knock-down or without p65

(HBx Mutant). All networks with NF-κB complex as the nodal point, by condition are represented in Figure 17, which shows these networks and their associated factors. Top nodal points can be compared by condition to reveal targets present only in conditions where MTA1 is at wild-type levels or is reduced, allowing for further delineation of the role of this cellular factor in the genome-wide targeting of HBx. Here, we expect that with the HBx Mutant, HBx targets different genes related to the NF-κB complex. When both

MTA1 and p65 involvement are altered, these targeted genes, related to NF-κB, differ as well. For example, in PHHs with MTA1 knock-down, E2F1, a known p65 targeted transcription factor, is among the top nodes of recruitment and when p65 is reduced, this factor is no longer targeted, but instead other genes such as tumor protein 53 (TP53) are targeted. TP53 is the central node within the first network of targeted genes for HBx recruitment, with p65 reduced expression. Another well-known cancer-associated gene,

RB1, was also found as a top nodal point in HepG2 cells with wild-type expression, indicating the role for MTA1 in the targeting of master cancer regulators (Figure 18).

Figure 17

73 Figure 17. Recruitment Networks with the NF-kB Complex as the Central Node by

Sample Condition. Networks of HBx recruitment with the NF-kB complex as the central node, elucidate related components which are also targeted by HBx (shaded), further defining the role that NF-kB plays in the genome-wide recruitment of HBx. Associated factors may also contribute to the phenotypic changes which occur as a result of the functions of HBx. Such targets could be studied further to define their roles.

HBx mutant (-p65) HBx mutant, MTA1 k/d

PHH

Figure 18

75 HBx WT HBx WT, MTA1 k/d A C HepG2

Figure 18

HBx mutant (-p65) HBx mutant, MTA1 k/d F H PHH

E G HepG2

Figure 18

77 Figure 18. Recruitment Networks with TP53 or RB as the Central Node by Sample

Condition. TP53, encoded by p53, a tumor suppressor gene which is implicated in most cancer types, and RB, which is also commonly altered in cancer, are targeted by HBx in the represented conditions and appear as nodal points. These networks, associated with TP53 and RB elucidate the associated factors also targeted by HBx (shaded), revealing other targets in these cancer-associated networks which may play a role in the phenotypic changes which occur as a result of HBx functions. These targets could be studied further to analyze the role that HBx plays in cancer development as alterations in factors associated with p53 and RB may be important in the effects of this viral protein.

78 Such targets and associated networks could be further studied to reveal the role of MTA1.

Overall, network analysis has revealed top nodal points which categorize relative genes that are targeted by HBx in each condition, providing more detail on the types of genes targeted and the role of MTA1.

3.4 HBx Recruitment to Gene Expression and Cancer Related Genes is Dependent on MTA1 Status

3.4.1 HBx Targeting of Cancer Genes

As HBx has been linked with altering cellular gene expression, which aids in the development of liver cancer, we sought to identify genes known to be related to cancer, which are targeted by HBx, in all conditions. This will provide information on the role of

MTA1 for each targeted cancer gene. To identify these genes, we narrowed down to TSS gene lists only, as recruitment to these genes became the focus of this study. To analyze all gene targets, we included genes which are targeted in multiple conditions. Cancer related genes were identified by subjecting TSS recruitment lists, by sample condition to IPA analysis and analyzing all categories of cancer which were presented. Overall patterns of recruitment to this subset of genes revealed that in normal cells, recruitment increased with a reduction in the involvement of MTA1 and p65, with 18 genes targeted (Figure 19). In

HepG2 cells, these genes are targeted more when p65 is reduced with 13 genes, and 5 genes being targeted when both factors are reduced. Also, in PHHs, general categories of cancer are targeted while in HepG2 cells, targeted genes belong to more specific cancer types and diseases. In PHHs, some genes belonging to the tumorigenesis and cancer categories have been revealed in other analyses, including the HOX genes, which are targeted in PHHs at the TSS and were identified in the gene expression related analysis,

79 which will be described further. These genes are not targeted in HepG2 cells. Genes such

as LIMD1 were targeted in both cell types and in multiple conditions. Identifying genes

which are targeted by HBx in each condition, which delineates the role of MTA1 by

individual gene, provides a wealth of information about which cancer related genes may be

altered and subsequently may play a role in HBx-associated HCC.

3.4.2 HBx Targeting of Tumor Suppressor Genes and Oncogenes

As very few tumor suppressor genes and oncogenes were targeted at the TSS, and

recruitment to these genes may be of great interest, as they are most commonly deregulated in a variety of cancers, we sought to elucidate the tumor suppressor genes and oncogenes that are targeted by HBx, regardless of the targeted annotation regions. This information suggests that HBx may alter the expression of genes known to play heavy roles in oncogenesis and defines this recruitment for further studies. To identify this subset of genes we used Venn diagram analysis to compare MACS gene lists by condition to a list of known tumor suppressor genes and oncogenes, revealing those which were targeted. In both scenarios we identified the genes which were shared and specific by condition and categorized them as such, to reveal the importance of MTA1 and p65 to this targeting. For instance, some genes such as oncogenes ABL1 and RAB31, are targeted in HepG2 cells in all conditions except the wild-type, indicating that a reduction in MTA1 is needed for HBx to target these genes. This information also elucidated the types of tumor suppressor genes and oncogenes targeted where many kinases and transcriptional regulator oncogenes were identified. We also identified many Ras family oncogenes which were targeted in PHHs

Figure 19

81 Figure 19. Cancer Related Genes. HBx targeting of cancer related genes by IPA, regardless of annotation region, revealed another set of gene targets which could be studied further. Elucidation of these genes was desired as HBx has been implicated in cellular transformation and these genes are known to play a role in cancer. Analysis of such genes gives further insight into what this viral protein might be doing to aid in cancer progression.

82 with a reduction in MTA1 and/or p65, and some that were targeted with wild-type conditions or with MTA1 and/or p65 reduced involvement in HepG2 cells (Figure 20).

These data define the importance of these cellular factors on the ability of HBx to target each individual gene and this information will be utilized further to study oncogenes targeted by HBx in relation to MTA1 and p65. These studies could further elucidate the mechanisms employed by this viral protein to cause cancer.

The types of tumor suppressor genes targeted by HBx includes those linked to glioblastomas or microtubules, and those that are kinases or that bind proteins.

Glioblastoma tumor suppressor 2 (GLTSCR2) for example was targeted in HepG2 cells with a reduction in both MTA1 and p65, indicating that HBx can only target this gene when both factors are reduced. This gene is particularly of interest because it is also among the genes targeted at the TSS and has been chosen as a validation target. Overall, we have defined the global targeting of tumor suppressor genes and oncogenes by the viral protein

HBx and the roles of MTA1 and p65 in this targeting to each individual gene, which provides a wealth of information for further study.

3.4.3 HBx Targeting of Gene Expression Related Genes

As HBx is a viral trans-activator protein, capable of altering the expression of viral and cellular genes, we wanted to take a closer look at expression and regulation related genes that HBx is recruited to, to characterize the recruitment of HBx to genes that could further alter expression, with the idea that without p65 and/or MTA1, HBx may target different cellular players, involved in gene expression, that could contribute to its trans- regulation functions. We selected genes using IPA where four categories of genes

Targeted Oncogenes HepG2 PHH HBx wild‐type (A, B) CRKL, MET, RAB27B, RAB9B, RAP2C, MAFF SET, USP4 Enzymes HBx wt, MTA1 k/d (C, D) EGR, FGR, MRTK, RAB6B, THRB ERG ‐RAS Oncogene Family HBx Mutant (E, F) AKT, BRAF, MPL, PIM1, RAB10, ABL2, CRKL, MAFG, MYBL1, RAB14, Growth Factors RAB40B, RAB4B, RAB7A, SKIL RAB2B, RAB30, REL, TET3 ‐PDGFB HBx Mutant, MTA1 k/d (G, H) ERBB2, FYN, TET1 CRK, ETS2, FOSB, JUN, KIT, MAFA, MYCN, YES1, PDGFB, PIM2, RAB39B, Kinases RAB3B, RAB5B, RAB6A, RAB7A, ‐MET, FYN, LYN, RAF1, CRKL, AKT2,3, RAB8B, RAP2B, RELB, RRAS2, SKI, FGR, MERTK, ERBB2,4, ABL1,2, SRC THRA PIM1,2, KIT, YES1 HBx wt and without both LYN, RAB19, RAF1 ABL1 (A,G E, H) Ligand‐dependent Nuclear Receptor MTA1 k/d, regardless of HBx RAB11A ERBB2, LYN, MAFK, RAB33A, RAF1, ‐THRA, B status (C,G D, H) SRC, TET2 HBx Mutant (E, G F, H) MYBL1, RAB11B, RAB2B, RABL3, BMI1, FEV, FOS, MERTK, RAB11A, Peptidase RALA RAB1A, RAB28, RAB31, RAB8A, ‐USP4, 6 RAP1A, RAP7B, SSPN All but without both AKT3 Phosphatase (A, C, E, B, D, F) ‐SET All but without mutant RAB37 ECT2L Transcription Regulator A, C, G, B, D, H) ‐MAFF,K,G,A ERG, SKIL, MYBL1, All but without wt MTA1 k/d ERBB4, RAB3C RAB3C, SET REL,B, BMI1, FEV, FOS, SKI, MYCN, (A, E, G, B, F, H) FOSB, JUN, ETS1,2, All but without wt ABL1, RAB31 AKT3, BRAF, ERBB4, ETS1, MET, Transmembrane Receptor (C, E, G, D, F, H) RAB10, RAB2A, RAB37, RAB39, RAB9B, RAP2C, TET1, THRB, USP6 ‐MPL MTA1 k/d or Mutant RAB27B Other (DF, CE) ‐ TET1,2,3, ECT2L, RAB8A, SSPN, All RAB5C, FYN CRK, FAT3, GLTSCR1,2, MTUS1,2 (A, C, E, G B, D, F, H)

Targeted Tumor Suppressor Genes

HBx HBx HBx HBx wild‐type MTA1 k/d Mutant Mutant PHH MTA1 k/d ‐FH (GLTSCR1) PHH MTUS1 MTUS1 GLTSCR1 GLTSCR1 ‐BDFH (MTUS1, FAT3) (NORMAL) FAT3 FAT3,4 MTUS1 MTUS1 ‐H (LATS2) FAT3,4 LATS1,2 ‐F (LATS1) TUSC3 FAT3,4 TUSC3 ‐DFH (FAT4) HEPG2 GLTSCR1 FAT3,4 GLTSCR1 GLTSCR1,2 HepG2 (CANCER) MTUS1,2 MTUS1,2 MTUS1,2 LATS1,2 LATS1 TUSC3 ‐AEG (GLTSCR1, MTUS1,2) FAT3,4 TUSC3 ‐G (GLTSCR2)

‐A (LATS2) Glioblastoma: TUSC3, GLTSCR1,2 ‐AC (FAT3/4) Microtubule associated: MTUS1,2, LATS1 ‐AE (LATS1) Kinase: MTUS1, LATS1 Protein Binding: GLTSCR1, MTUS2, LATS1 HepG2 and PHH Known for Liver cancer: MTUS1 ‐ EG,FH (TUSC3) Known for HBx: None Figure 20

84 Figure 20. HBx Recruitment to Oncogenes and Tumor Suppressor Genes. As the identification of targeted cancer related genes may aid in defining how HBx plays a role in cellular transformation, recruitment to this category but more specifically, tumor suppressor genes and oncogenes, further elucidates this function. Comparison of genes targeted with different levels of MTA1 involvement, further defines the role of MTA1 on the effects of

HBx.

85 were extracted by sample. These categories included transcription, transcription of gene, trans-activation and expression of gene, and the total recruitment to these gene groups can be seen in Figure 21. Gene lists were narrowed down by removing duplicates and recruitment to genes shared in multiple sample condition lists by Venn diagram analysis, as described previously. This allowed us to narrow down to 3, 3, 77, and 198 genes within these samples from HBx wild-type, HBx wild-type with MTA1 k/d, HBx Mutant, and HBx

Mutant with MTA1 k/d, respectively, that were related to gene expression and regulation in

PHHs. Recruitment to these genes shows an increasing trend as these factors are reduced in

PHHs. In HepG2 cells, only wild-type HBx showed recruitment to gene expression related genes of the aforementioned categories with a total of 114 genes targeted. Targets were then narrowed down to genes targeted at transcription start sites, to include details of proximity to chromatin marks.

In PHHs, only three expression related genes identified by IPA in the aforementioned categories were specific for wild-type HBx recruitment which includes

STAT3, SUB1, and TAF4, with only SUB1 exhibiting recruitment with proximity to the transcription start site in the upstream region, as determined by the UCSC Genome

Browser. None of these genes were shown to target the TSS by Avadis NGS. HBx recruitment to STAT3 is known for HBx (Lee and Yun 1998) and this recruitment is not seen in any other sample, indicating that wild-type p65 and MTA1 involvement are required for this recruitment. STAT3 was also identified by analyzing networks associated with MTA1 and the NF-kB complex, in wild-type HBx recruitment. Both SUB1 and

TAF4 have HBx recruitment to intronic regions so an alteration in expression may not result. Interestingly, a transcription factor

Figure 21

87 Figure 21. HBx Recruitment to Gene Expression Related Genes by Condition. As HBx is a viral trans-activator protein, recruitment to genes involved in gene expression could allow for further trans-regulation effects. Recruitment to four categories of gene expression related genes by IPA in PHHs (a) and HepG2 cells (b) followed by venn diagram analysis

to isolate genes targeted in one condition only, which were then narrowed down to those

with upstream/promoter/TSS targeting, revealed top targets of HBx recruitment which

were related to gene expression. Lists include genes with TSS recruitment as identified by

Avadis NGS, which was used to identify Tables 3 and 4, and then expanded by searching

for recruitment upstream of the TSS, to broaden parameters and identify additional targets

which may also be significant in the trans-regulation effects of HBx.

88 E2F1, which is known to be a direct target of p65 (Ching-Aeng et al., 2007), is targeted by

HBx only with wild-type NF-kB involvement. This target was also a central node within the top networks of recruitment in PHHs. HBx recruitment with MTA1 knock-down increases from a total of 19 to 115 targeted genes, which are related to gene expression and regulation. Within these 115 genes, all but 2 are shared among other conditions leaving

POU3F2 and XRCC6 as the only gene expression related genes with HBx recruitment specific to MTA1 knock-down, and POU3F2 as the only gene with recruitment which is upstream to the TSS. With HBx recruitment independent of p65 involvement, HOXB7 and

MYF6 are targeted at the TSS, with NPAS1, ZIC3, DLX4 and ILF2 being targeted upstream of the TSS, out of a total of 77 genes targeted. Out of 197 genes targeted by HBx, independent of MTA1 and p65, three had recruitment to the TSS including TBR1, HOXC5 and HOXC6, with 11 more exhibiting recruitment upstream of the TSS. Overall, the recruitment of HBx to gene expression and regulation related genes increases in PHHs as these factors are removed and all top targeted genes can be seen in Figure 21, which further characterizes the recruitment of HBx to gene expression related genes with proximity to chromatin marks, possibly predicting resulting trans-regulation. These genes may be further analyzed for their role in HBx trans-activation activities leading to HCC.

In HepG2 cells, only wild-type HBx recruitment could target genes determined by

IPA as being gene expression and regulation related genes, indicating that both factors are needed for this recruitment in transformed cells. Of 114 gene expression related genes, targeted by wild-type HBx, four were found to have recruitment upstream of the TSS of genes, including MMP9, DET1, TFAP2A, and TRIM29. Recruitment of HBx to MMP9

(Chung et al., 2004) and TFAP2A are already known and serve as a proof of principle of

89 this analysis, as most studies of HBx are completed within HepG2 cells. Overall, recruitment to gene expression related genes reveals interesting patterns and has identified novel HBx targets both dependent on and independent from two cellular factors, in both cell types and when p65 and MTA1 status is altered.

3.5 MTA1 Status Alters HBx Recruitment to Target the TSS of Host Genes

3.5.1 Shared and Specific Genes Targeted by Venn Diagram Analysis

Following characterization of global recruitment patterns, we sought to narrow- down to top targets of HBx recruitment that would represent the best novel candidates to initially study further, without focusing on any gene category such as cancer or gene expression. This will allow us to identify novel gene types which may be important in

HBV-associated HCC. To begin, we completed a Venn Diagram analysis to segregate shared and specific genes, targeted by HBx in all conditions (Figure 22). For this we separated the conditions by cell type and compared all full MACS lists of recruitment to determine not only the patterns of recruitment, as MTA1 involvement was reduced, but also to generate lists of genes that were targeted in only one condition. These genes would be easiest to define, for instance, if a gene appears only in the wild-type condition, it could be categorized as dependent on both wild-type MTA1 and p65 interactions. This analysis revealed patterns similar to those previously mentioned, where in PHHs, HBx targets more genes specific to one condition as MTA1 and p65 are reduced. In HepG2 cells, the pattern of specific recruitment also correlates with what was previously shown. These data support previously revealed patterns of recruitment while allowing us to isolate the genes targeted

90 All Genes

Recruitment to Transcription Start Sites (TSS) with Chromatin Mark Proximity

Repressed (4) Repressed (6) Poised (9) Poised (52) Poised (13) Poised (5) Active (2) Active (17) Poised (1) Poised (1)

Figure 22

91 Figure 22. Venn Diagram Analysis of All Shared and Specific HBx Targeted Genes by

Sample Condition and Those Targeted at the TSS. Using venn diagram analysis, we compared all four conditions representing different levels of MTA1 involvement, by cell type, to isolate genes which HBx targets only in one condition. By doing this, genes can be characterized as being dependent on one level of MTA1 involvement. Isolation of specific genes from full MACS output lists resulted in large lists which we wished to further reduce, to identify top targets for future research. To do this, we completed venn diagram analysis on only those genes with HBx recruitment to the TSS, where trans-regulation is most likely to result. This reduced our top target list to between 0 and 69 genes per condition.

92 in only one condition, making it easier to characterize the recruitment of HBx in each

condition separately and to reveal the roles of MTA1 and p65. As these lists were still too

long to analyze completely, we sought to narrow-down again, by filtering these data to

isolate genes that are targeted at the TSS. To do this, we isolated those genes with TSS

recruitment as defined by analyzing annotated regions, as previously mentioned. Again, we

employed Venn Diagram analysis to isolate the genes with TSS recruitment by sample

condition. This shortened our gene lists from between 196 and 2376 genes to 0 and 69 genes. Here, we included the details of how many of these TSS targeted genes had recruitment with proximity to chromatin marks. By narrowing down to genes targeted at the TSS, we have isolated those genes which may be the most novel as they may represent genes unrelated to the expected categories of gene expression and cancer. These genes are also the most likely to have a resulting change in gene expression and the details of these

targets will be discussed further.

3.5.2 All Genes Targeted at the TSS

As mentioned, HBx target genes with recruitment to transcriptional start sites or upstream

regions within genes, were focused on, to reveal those that are most likely to be trans- regulated by HBx. As seen in Figure 22, the total number of genes with recruitment near these regions, increases as these factors are reduced, in PHHs, which is similar in HepG2 cells except for an increase in recruitment without both factors. Also, some genes are in multiple lists indicating that recruitment occurs to the TSS, independent of p65 and/or

MTA1. Here, we will focus on genes specific to one condition and look into the identity of

these genes.

Primary Human Hepatocytes (PHH) HBx wt Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description No Transcription Start Site Targets Following Filtering HBx wt, MTA1 k/d Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description No Transcription Start Site Targets Following Filtering HBx mutant - NF-kB Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 114905 C1QTNF7 162.1 10 chr4 Repressed C1q and tumor necrosis factor related protein 7 2660 MSTN 105.7 5 chr2 myostatin 3216 HOXB6 84.6 10 chr17 Repressed homeobox B6 3212 HOXB2 84.6 4 chr17 Repressed homeobox B2 8609 KLF7 64.8 4 chr2 Poised Kruppel-lik e factor 7 (ubiquitous) 79618 HMBOX1 63.4 4 chr8 Poised homeobox containing 1 26135 SERBP1 63.4 4 chr1 Poised SERPINE1 mRNA binding protein 1 115111 SLC26A7 63.4 4 chr8 solute carrier family 26, member 7 4808 NHLH2 46.3 5 chr1 Repressed nescient helix loop helix 2 3214 HOXB4 42.3 4 chr17 Repressed homeobox B4 84107 ZIC4 42.3 4 chr3 Repressed Zic family member 4 3217 HOXB7 32.4 4 chr17 Poised homeobox B7 10891 PPARGC1A 24.3 4 chr4 Poised peroxisome proliferator-activated receptor γ 4618 MYF6 14.4 8 chr12 myogenic factor 6 (herculin) HBx mutant - NF-kB, MTA1 K/D Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 4921 DDR2 299.1 6 chr1 discoidin domain receptor tyrosine kinase 2 653 BMP5 199.4 4 chr6 bone morphogenetic protein 5 389941 C1QL3 199.4 4 chr10 Poised complement component 1, q subcomponent-like 3 2251 FGF6 191.1 8 chr12 Repressed fibroblast growth factor 6 3236 HOXD10 152.8 5 chr2 Repressed homeobox D10 403314 APOBEC4 152.8 4 chr1 apolipoprotein B mRNA editing enzyme 4211 MEIS1 149.5 5 chr2 Poised Meis homeobox 1 3203 HOXA6 134.9 4 chr7 Poised homeobox A6 8929 PHOX2B 127.4 14 chr4 Repressed paired-like homeobox 2b 399909 PCNXL3 127.4 4 chr11 Poised pecanex-like 3 (Drosophila) 57167 SALL4 114.6 4 chr20 Poised sal-like 4 (Drosophila) 4958 OMD 99.7 4 chr9 osteomodulin 83860 TAF3 99.7 4 chr10 Poised TAF3 RNA polymerase II, TATA box bp (TBP)-as soc . 7514 XPO1 95.5 4 chr2 Poised exportin 1 (CRM1 homolog, yeast) 3223 HOXC6 76.4 7 chr12 Poised homeobox C6 3222 HOXC5 76.4 4 chr12 Poised homeobox C5 345222 C4orf44 60.8 6 chr4 Poised chromosome 4 open reading frame 44 1828 DSG1 50.9 4 chr18 Poised desmoglein 1 8839 WISP2 43.7 4 chr20 Repressed WNT1 inducible signaling pathway protein 2 4212 MEIS2 43.2 5 chr15 Poised Meis homeobox 2 3146 HMGB1 31.9 19 chr13 Active high-mobility group box 1 10716 TBR1 30.6 4 chr2 Poised T-box, brain, 1 80059 LRRTM4 17.5 31 chr2 leucine rich repeat transmembrane neuronal 4

Table 3

94 Table 3. All Genes with TSS Recruitment by Sample Condition with Chromatin

Mark Proximity, in PHHs. By annotating target regions, we isolated all TSS targeted genes by sample condition (MTA1 status) and cell type. All TSS targeted genes were compared by cell type using venn diagram analysis to isolate those specific by condition.

All genes identified in normal liver cells, which represent the top genes of HBx recruitment for validation, are listed in this table. This table provides targets for validation and future research, which may connect these genes with the outcome of HCC, following HBV infection.

Hepatocellular Carcinoma (HepG2) HBx wt Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 84936 ZFYVE19 24.2 5 chr15 Poised zinc finger, FYVE domain containing 19 HBx wt, MTA1 k/d Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 3689 ITGB2 32.6 9 chr21 Poised integrin, β 2 (complement component 3) 254958 REXO1L1 3.9 2312 chr8 REX1, RNA exonuclease 1 homolog -like 1 HBx mutant - NF-kB Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 154467 C6orf129 26.1 21 chr6 Poised chromosome 6 open reading frame 129 64798 DEPDC6 21.8 14 chr8 Poised DEP domain containing 6 731 C8A 20.1 28 chr1 Active complement component 8, alpha polypeptide 27107 ZBTB11 19.9 32 chr3 Poised zinc finger and BTB domain containing 11 91687 CENPL 19.9 13 chr1 Poised centromere protein L 9857 CEP350 19.9 9 chr1 Poised centrosomal protein 350kDa 115098 CCDC124 16.7 39 chr19 Poised coiled-coil domain containing 124 57599 WDR48 16.0 10 chr3 Poised WD repeat domain 48 163 AP2B1 15.5 20 chr17 Active adaptor-related protein complex 2, beta 1 subunit 55278 QRSL1 15.5 15 chr6 Poised glutaminyl-tRNA synthase -like 1 84816 RTN4IP1 15.5 15 chr6 Poised reticulon 4 interacting protein 1 819 CAMLG 15.5 12 chr5 Active calcium modulating ligand 7709 ZBTB17 15.5 10 chr1 Poised zinc finger and BTB domain containing 17 9810 RNF40 15.0 12 chr16 Poised ring finger protein 40 56899 AIDA 14.2 10 chr12 Poised ankyrin repeat and sterile α motif domain containing 391356 C2orf79 14.0 8 chr2 Active chromosome 2 open reading frame 79 7539 ZFP37 14.0 32 chr9 Poised zinc finger protein 37 homolog (mouse) 11143 MYST2 13.6 32 chr17 Poised MYST histone acetyltransferase 2 23192 ATG4B 13.5 30 chr2 Poised ATG4 autophagy related 4 homolog B (S. cerevisiae) 55183 RIF1 13.5 16 chr2 Poised RAP1 interacting factor homolog (yeast) 55669 MFN1 13.4 13 chr3 Active mitofusin 1 10399 GNB2L1 13.3 14 chr5 Poised guanine nucleotide, beta polypeptide 2-like 1 2957 GTF2A1 13.3 13 chr14 Active general transcription factor IIA, 1, 19/37kDa 51078 THAP4 13.3 11 chr2 Poised THAP domain containing 4 7365 UGT2B10 13.3 11 chr4 Active UDP glucuronosyltransferase 2 family, B10 7415 VCP 13.3 11 chr9 Active valosin-containing protein 124936 CYB5D2 13.3 9 chr17 Active cytochrome b5 domain containing 2 5683 PSMA2 13.3 9 chr7 Poised proteasome (prosome, macropain), alpha type, 2 2193 FARSA 13.1 19 chr19 Poised phenylalanyl-tRNA synthetase, alpha subunit 10489 LRRC41 12.7 32 chr1 Active leucine rich repeat containing 41 10972 TMED10 12.5 21 chr14 Poised transmembrane emp24-like trafficking protein 10 57147 SCYL3 12.5 44 chr1 Poised SCY1-like 3 (S. cerevisiae) 54534 MRPL50 12.3 10 chr9 Poised mitochondrial ribosomal protein L50 9877 ZC3H11A 12.0 10 chr1 Poised zinc finger CCCH-type containing 11A 23381 SMG5 12.0 18 chr1 Poised nonsense mediated mRNA decay factor 84283 TMEM79 12.0 18 chr1 Poised transmembrane protein 79

Table 4

84922 FIZ1 11.9 48 chr19 Poised FLT3-interacting zinc finger 1 148362 C1orf58 11.9 30 chr1 Poised chromosome 1 open reading frame 58 5469 MED1 11.7 18 chr17 Poised mediator complex subunit 1 55755 CDK5RAP2 11.6 33 chr9 Poised CDK5 regulatory subunit associated protein 2 51079 NDUFA13 11.6 12 chr19 Active NADH dehydrogenase 1 alpha subcomplex, 13 1201 CLN3 11.5 22 chr16 Poised ceroid-lipofuscinosis, neuronal 3 83444 INO80B 11.5 24 chr2 Active INO80 complex subunit B 25957 SFRS18 11.5 13 chr6 Poised splicing factor, arginine/serine-rich 18 64897 C12orf43 11.1 10 chr12 Poised chromosome 12 open reading frame 43 161779 PGBD4 10.4 9 chr15 Poised piggyBac transposable element derived 4 57828 CATSPERG 10.2 9 chr19 Active cation channel, sperm-associated, gamma 6257 RXRB 10.2 21 chr6 Poised retinoid X receptor, beta 7922 SLC39A7 10.2 21 chr6 Poised solute carrier family 39 (zinc transporter), member 7 201562 PTPLB 10.0 32 chr3 Poised protein tyr. phosphatase-like, b 54482 CCDC76 10.0 11 chr1 Poised coiled-coil domain containing 76 9527 GOSR1 10.0 9 chr17 Poised golgi SNAP receptor complex member 1 57418 WDR18 10.0 9 chr19 Poised WD repeat domain 18 6908 TBP 9.7 48 chr6 Poised TATA box binding protein 6426 SRSF1 9.4 16 chr17 Poised serine/arginine-rich splicing factor 1 23524 SRRM2 9.4 9 chr16 Active serine/arginine repetitive matrix 2 84311 MRPL45 9.2 19 chr17 Active mitochondrial ribosomal protein L45 5635 PRPSAP1 9.1 32 chr17 Poised phosphoribosyl pyrophosphate synthetase assoc. 9221 NOLC1 9.0 9 chr10 Active nucleolar and coiled-body phosphoprotein 1 27131 SNX5 9.0 15 chr20 Poised sorting nexin 5 57456 KIAA1143 8.8 8 chr3 Poised KIAA1143 56992 KIF15 8.8 8 chr3 Poised kinesin family member 15 259 AMBP 8.4 8 chr9 Poised alpha-1-microglobulin/bikunin precursor 64427 TTC31 8.3 20 chr2 Poised tetratricopeptide repeat domain 31 7879 RAB7A 8.2 13 chr3 Poised RAB7A, member RAS oncogene family 6240 RRM1 7.6 14 chr11 Poised ribonucleotide reductase M1 3661 IRF3 7.2 34 chr19 Active interferon regulatory factor 3 55145 THAP1 7.0 18 chr8 Poised THAP domain containing, apoptosis assoc. protein 1 80110 ZNF614 5.2 23 chr19 Poised zinc finger protein 614 HBx mutant - NF-kB, MTA1 K/D Identifier Gene Name Enrichment Reads Chr Chromatin Mark Description 4212 MEIS2 25.6 7 chr15 Poised Meis homeobox 2 199704 ZNF585A 22.8 9 chr19 Poised zinc finger protein 585A 127253 TYW3 22.8 8 chr1 Poised tRNA-yW synthesizing protein 3 homolog 10607 TBL3 19.0 9 chr16 Poised transducin (beta)-like 3 81545 FBXO38 19.0 7 chr5 Poised F-box protein 38 4677 NARS 19.0 7 chr18 Poised asparaginyl-tRNA synthetase 3646 EIF3E 16.2 10 chr8 Poised eukaryotic translation initiation factor 3, subunit E 6877 TAF5 13.6 7 chr10 Active TAF5 RNA pol. II, TATA box bp (TBP)-assoc. 53 ACP2 12.5 8 chr11 Poised acid phosphatase 2, lysosomal 10062 NR1H3 12.5 8 chr11 Poised nuclear receptor subfamily 1, group H, mb 3 29997 GLTSCR2 10.5 25 chr19 Active glioma tumor suppressor candidate region gene 2

Table 4

97 Table 4. All Genes with TSS Recruitment by Sample Condition with Chromatin

Mark Proximity, in HepG2 cells. By annotating target regions, we isolated all TSS targeted genes by sample condition (MTA1 status) and cell type. All TSS targeted genes were compared by cell type using venn diagram analysis to isolate those specific by condition. All genes identified in liver cancer cells, which represent the top genes of HBx recruitment for validation, are listed in this table. This table provides targets for validation and future research, which may connect these genes with the outcome of HCC, following

HBV infection.

98 Overall recruitment values can be seen for each sample and each individual gene, with all genes with this recruitment (near transcription start sites), listed in Tables 3 and 4.

These genes are of the most interest and were the focus of validation, which is discussed below. These tables provide an overview of whether recruitment to these genes is altered by p65 and/or MTA1 involvement. Here, as well as in other characterizations, HBx recruitment, based on these factors, varies for each individual gene, in both cell types.

Wild-type HBx recruitment in PHHs to these regions, is the lowest with only two genes being targeted, PAR5 and ACCN1. Similar recruitment to PAR5 is also found without

MTA1 but recruitment is abolished when p65 is reduced, indicating that recruitment to this gene is dependent on p65. HBx recruitment to some genes occurs in only specific conditions, revealing whether p65 and/or MTA1 are required for this recruitment. In PHHs, with wild-type HBx alone, there are no genes with specific recruitment to these regions, which increases to one gene, LOC728855, with MTA1 knock-down, and 14 genes with a reduction in p65 involvement, including 4 HOX genes which are transcription factors that also alter gene expression. When both factors are reduced, recruitment to these regions increases still, to 29, which also includes many HOX genes, as well as other homeobox containing transcription factor genes such as MEIS1 and MEIS2, which have roles in development. The finding that HBx targets HOX genes is interesting as other developmental genes such as WNT genes exhibit reduced expression in the adult organism but when over-expressed, they aid in cancer development. This connection between HBx,

HOX genes and MTA1, found within normal liver cells, is a novel axis which could be explored further. In HepG2 cells HBx is recruited to 4, 8, 75, and 13 TSS/upstream regions, in the wild-type, with MTA1 knock-down, with reduced p65 and with both factors reduced,

C N C N H H B B t M x RNA t M x w T w C w T w C N x A t Exonuclease N x A t B 1 B 1 ITGB2 H k H k Transcription / REXO1L1 / d d HMBOX1 Expression Immune System HOXB7 nt nt H uta H uta KLF7 Bx M Bx M M x /d M x /d MSTN u HB 1 k u HB 1 k N ta A N ta A MYF6 nt MT C nt MT C Trans-activation RNA HOXB7 Dendritic Cell PPARGC1A HOXB7 TAF5 C TranscriptionN Viral C N NARS MSTN RNA Pol. II Trans- HIV infectivity HMGB1 Trans-activation PPARGC1A GTF2A1 activation FGF6 HOXC5/6 NOLC1 TBP NR1H3 HMGB1 MEIS2 ZBTB17 WISP2 C N Viral PHOX2B GTF2A1 H XPO1 B Trans-activation TAF3 TBP M x Inflammatory t T C NOLC1 TBR1 IRF3 N w A w HMGB1 Bx 1 t ZBTB17 H k Viral Exit / GTF2A1 Complement d XOP1 Cancer TBP Key C8A nt H uta IRF3 N Normal cells (PHH) Bx M Interferon Regulator M Bx k/d ut H 1 Expression C Cancer cells (HepG2) IRF3 N an TA C t M Cancer GTF2A1 C N EIF3E HCC Cancer HCC NR1H3 EIF3E ZFYVE19 GNB2L1 AMBP HMGB1 C N RRM1 GLTSCR2 H Oncogene NDUFA13 Cancer B C N t M x RAB7A MFN1 FGF6 w T w C H N x A t B MYAT2 WISP2 B 1 M x H k t T C PSMA2 /d N w A w Bx 1 t RXRB Zinc Finger H k nt /d ZFP37 H uta Development Bx M t M Bx k/d an ut H 1 H ut N an TA C Bx M t M M Bx k/d ZNF585A ut H 1 N an TA C C N Homeodomain t M Homeodomain SALL4 ZFP37 HMBOX1 MEIS2 C N ZBTB17 HOXB2/4/6/7 Homeodomain HMGB1 ZBTB11 HOXC5/6 ZC3H11A C N ZNF614 MEIS1/2 H PHOX2B B t M x w T w C HOXD10 N A t Bx 1 HOXA6 H k /d Skeletal Liver BMP5 nt H uta Bx M Wnt Signaling M Bx k/d Fatty Liver ut H 1 WISP2 N an TA C PPARGC1A t M Cholestasis C N NR1H3 WHV Activator Cholestasis XPO1 UGT2B10 Liver Damage HMGB1

Figure 23

100 Figure 23. Categorization of TSS Targeted Genes Based on Function by IPA.

Categorization of TSS targeted genes, specific by condition, reveals that HBx targets many genes involved in cancer, gene expression, development, the immune system, and zinc finger containing genes. Select genes are described further to help elucidate the types of genes targeted, to give insight into what HBx may be doing to aid in the outcome of cancer.

101 respectively. In the wild-type condition, this includes genes such as transcription factor AP-

4, and a zinc finger, ZFYVE19. With a reduction in MTA1 involvement, genes such as ubiquitin specific peptidase 17 (USP17) and an RNA exonuclease (REXO1L1) are targeted. These genes were also identified by analyzing recruitment to chromosomes 4 and

8 within HepG2 cells. With a reduction in p65 binding, many uncharacterized open reading

frames are targeted and with a reduction of both factors, genes such as NR1H3, a nuclear

receptor, and GLTSCR2, a glioma tumor suppressor candidate, are targeted. All TSS

targeted genes by condition and cell type, with proximity to chromatin marks can be seen

in Tables 3 and 4, with a categorization of these genes based on function, shown in Figure

23. Overall, the recruitment of HBx to the TSS/upstream regions of genes, by condition,

provides a global view of the genes that are most likely being trans-regulated by HBx and

connects the importance of p65 and MTA1 involvement for recruitment to each individual

gene target. Due to the known trans-regulation functions of HBx and the ability of the

recruitment of cofactors to the TSS of genes, causing trans-regulation, genes mentioned

here with TSS recruitment are of high interest and were the focus of validation, which will

be described further.

3.5.3 Binding Motifs of TSS Targeted Genes

As proteins commonly bind specific motifs, we used GANDEM to complete motif

discovery through Avadis NGS, to identify common motifs within the host DNA, which is

targeted by HBx. We also sought to determine whether different motifs are targeted when

MTA1 and p65 involvement is altered. Surprisingly, we found that in all levels of MTA1

and p65 involvement, HBx targeted similar motifs, where representative motifs are

102 depicted in Figure 24A. These motifs represent HBx targeting throughout the genome, without focus being placed on particular targets. These data reveal novel insight into the cellular motifs, at the base pair level, that HBx can target. To further elucidate the role of

MTA1 on the ability of HBx to target these motifs, we narrowed down to genes targeted at the TSS in each condition and used Expasy Prosite and the Expasy Translator Tool to reveal the binding motifs and signatures, and protein sequence translation of these binding sites per gene, respectively. Interestingly, we found that all TSS targeted genes, which we expected to be targeted through the previously defined binding motifs, were targeted within binding regions which included one of a few common motifs. These motif signatures, identified by analyzing all TSS targeted genes per condition (Tables 3 and 4), include ferredoxin-type iron-sulfur binding signatures, EGF-like domain signature 1, the mammalian defensin signature, and the C-terminal cysteine know signature, among others.

All signatures are shown in Figure 24B, with respect to all sample conditions. It was found that wild-type HBx can only target a few motifs, which increased as MTA1 involvement was reduced.

Due to the fact that HBx targets only specific motifs/domains, the difference in the ability of HBx to target these sites, must be dependent on MTA1 as these sample conditions differ only by the level of involvement of this master chromatin modifier.

Differences are also due to whether the cells are pre- or post- cancerous, as apparent by comparing like sample conditions between these cell types. This may be explained by a difference in MTA1 expression between pre- and post- cancerous cells.

103 A

Figure 24

104 B

X X X X X X X X X X

HBx Mutant MTA1 k/d

X X X X X X X X X X X HepG2

HBx Mutant X X X X X X X X X X X X HBx wt k/d MTA1

X X X X X X

HBx wt Samples X X X X X X X X X X X HBx Mutant k/d MTA1

X X X X X X X X

HBx Mutant PHH X X X X X HBx wt k/d MTA1

X X

HBx wt

-x-C-x-C-x(2)- -x(2)-C-x(2)-C-x-

C-x(6)-C-x-C-x(6,9)-C Agouti domain signature domain Agouti C-x(6)-C-x(6)-C-C VWFCsignature domain C-x(2,3)-C-{CG}-C-x(6,14)-C- x(3,4)-C-x(2,10)-C-x(9,16)-C-C- x(2,4)-C C-x-C Insulin-like growthfactor- binding protein (IGFBP) N- domainterminal signature [GP]-C-[GSET]-[CE]-[CA]-x(2)-C- [ALP]-x(6)-C Mammalian defensins signature C-x-C-x(3,5)-C-x(7)-G-x-C-x(9)-C- C C-terminal cystine knot signature C-C-x(13)-C-x(2)-[GN]-x(12)-C-x- C-x(2,4)-C Thiolases site active [AG]-[LIVMA]-[STAGCLIVM]- [STAG]-[LIVMA]-C-{Q}-[AG]-x- [AG]-x-[AG]-x-[SAG] Integrins chain beta cysteine- rich domain signature C-x-[GNQ]-x(1,3)-G Tubulin subunits alpha, beta, and gamma signature [SAG]-G-G-T-G-[SA]-G Domain Name / Sequence / Name Domain EGF-like domain signature 1 C-x-C-x(2)-{V}-x(2)-G-{C}-x-C 2Fe-2S ferredoxin-type iron- ferredoxin-type 2Fe-2S signature region binding sulfur C-{C}-{C}-[GA]-{C}-C-[GAST]- {CPDEKRHFYW}-C iron- ferredoxin-type 4Fe-4S signature region binding sulfur C-x-{P}-C-{C}-x-C-{CP}-x-{C}-C- [PEG] Anaphylatoxin domain signature [CSH]-C-x(2)-[GAP]-x(7,8)- [GASTDEQR]-C-[GASTDEQL]- x(3,9)-[GASTDEQN]-x(2)-[CE]- x(6,7)-C-C

AGOUTI_1 Repeats: GAGA/CACA/CG CG/ CTCT… VWFC_1 INTEGRIN_BETA IGFBP_N_1 DEFENSIN CTCK_1 THIOLASE_3 TUBULIN Domain Abbr. AAAAA… EGF_1 2FE2S_FER_1 4FE4S_FER_1 ANAPHYLATOXI N_1

Figure 24

105 Figure 24. Binding Motifs of All genes and TSS Targeted Genes by Sample Condition.

Analysis of binding motifs of all genes targeted by HBx revealed few motifs which HBx targets in all sample conditions. By Expasy Prosite of binding sites within TSS targeted genes, we found a few motif signatures that were bound by HBx, further defining HBx targeting of the genome and the role of MTA1. A decrease in MTA1 involvement resulted in increased targeting of these regions. MTA1 acts to condense the chromatin in wild-type conditions, preventing HBx from targeting the genome within these binding regions.

106 Overall, these results suggest that HBx targets only a limited number of binding motifs,

with MTA1 controlling accessibility. As MTA1 expression is at wild-type levels, these

regions are condensed, keeping HBx from targeting them but when MTA1 expression is

reduced, these regions are not as condensed, allowing HBx access. This analysis provides

novel information regarding the genome-wide targeting of HBx and the role of MTA1.

3.6 Validation of HBx Binding and Resulting Altered Gene Expression of Representative Genes

3.6.1 Validation of HBx Binding to Representative Genes

In the initial analysis of our datasets, we revealed intriguing patterns of HBx

recruitment and recruitment to many target genes in response to an alteration in the

involvement of p65 and MTA1. To validate our findings, we have completed PCR and

qPCR on select genes that represent one gene per condition, with TSS recruitment. Genes

chosen for validation represent all conditions, as we chose one gene from each category

with TSS recruitment. This analysis serves as a proof of principle of these bioinformatic

methods, and confirms binding to identified targets that will be analyzed further. Some

genes such as HOXB7 were identified by multiple methods such as gene expression related

targets and genes with TSS recruitment and are of great interest. These genes, shown in

Figures 25 and 26 were validated by confirming the binding of HBx to the gene of interest

by PCR and DNA gel electrophoresis (Figure 25) as well as by quantitative PCR (qPCR), and altered gene expression by qPCR, as predicted bioinformatically with chromatin mark

proximity (Figure 26). These results, support the notion that the bioinformatic analyses,

which have identified numerous targets of HBx and the role of MTA1 on each individual

gene target, are actually targeted by HBx and trans-regulated as predicted. Select targets to

107 represent HBx wild-type and HBx wild-type with MTA1 knock-down conditions, in PHHs, without specific recruitment to the TSS were analyzed by evaluating expression (qPCR).

Resulting data was not as convincing as those with TSS targeting in other samples (Figure

27). This completes our global characterization of HBx targeted genes, dependent on or independent from two cellular factors, p65 and MTA1, which possibly contributes to the development of cancer. This information will be used in biological endpoint studies where individual validated gene targets will be characterized further, to reveal the mechanism behind this targeting and whether HBx trans-regulation alters the cellular phenotype, leading to cancer.

108

PHH HepG2

ZFYVE19

Input

ChIP

HBx wild-type M 1 2 3 4 5 REXO1L1

Input

ChIP

wild-type, HBx k/d MTA1 M 1 2 3 4 5

HOXB7 GNB2L1 Input Input

ChIP M 1 2 3 4 5

HBx Mutant

ChIP M 1 2 3 4 5 HOXD10 GLTSCR2 Input Input

HBx Mutant, k/d MTA1 ChIP ChIP M 1 2 3 4 5 M 1 2 3 4 5

Key

M – 100 base pair Marker 1 – HBx wild-type 2 – HBx wild-type, MTA1 k/d 3 – HBx Mutant 4 – HBx Mutant, MTA1 k/d 5 – Cell type specific control Figure 25

109 Figure 25. Validation Using PCR and DNA Gel Electrophoresis, of Target Genes by

Sample Condition. Input (200ng) and ChIP (1µl of 1:10 diluted DNA) DNA were amplified with binding site/gene specific primers using PCR and visualized with DNA gel electrophoresis using ethidium bromide and UV. Semi-quantitative PCR revealed clear products in some analyses such as for HOXB7 where a clear product band is seen in lane three, representing the sample condition that HOXB7 was predicted to be targeted in, by

HBx. A clear product is also seen for GLTSCR2 in lane four of ChIP, also revealing HBx binding in the predicted sample. Due to high background product formation, which is commonly seen with ChIP samples, qPCR was also run to confirm binding, followed by qPCR of cDNA for resulting trans-regulation, shown in Figure 26.

110

PHH

Recruitment Binding Expression

HOXB7 A Poised 1 2 3 4 5 HBx mutant

HOXD10 B RepressedRepressed 1 2 3 4 5 HBx mutant, k/d HBx MTA1

Figure 26

HepG2

111

A Recruitment Binding Expression

ZFYVE19 Poised 1 2 3 4

HBx wt 5

RexO1L1 B No Marks

1 2 3 4 5

HBx wt, MTA1 k/d wt, MTA1 HBx

GNB2L1 C Poised

1 2 3 4 5

HBx mutant

GLTSCR2 D Active 1 2 3 4 5

HBx mutant, k/d MTA1

Figure 26

112 Figure 26. Validation using qPCR, of Representative Target Genes by Sample

Condition. HBx binding to select predicted targets with resulting altered gene expression

in PHHs, representing HBx Mutant (A), and HBx Mutant, MTA1 knock-down (B) conditions. This is followed by HepG2 in the following order, HBx wt (A), HBx wt, MTA1

k/d (B), HBx Mutant (C), HBx Mutant, MTA1 k/d (D). UCSC Genome Browser snapshots

are in order from top to bottom of PHH HBx wt (1), HBx MTA1 k/d (2), HBx Mutant (3),

HBx Mutant, MTA1 k/d (4). The last two samples in these snapshots are PHH or HepG2

specific controls (5). As no genes were targeted at the TSS in HBx wild-type and HBx

wild-type, MTA1 knock-down samples in PHHs, validation was not completed for these

categories.

113

Expression PRPSAP2 Prp Exp F CCTCACCTTTCCTGCTTCAG Prp Exp R GTCTCTCCGCATAGGACTGG

TCERG1 TCE EXP F CCACCCCTTCCTCTACCACT TCE EXP R TGGCTGTAGGAGCAGGAGTT

ACCN1 ACCN1 exp F CGATCAACCTGAAGCCAGTT ACCN1 exp R GTGGAGGTGTTGGCAAAGAT RASA1 RAS EXP F TAACAGCATTGGGGACATC A RAS EXP R TTGCCATCCACTGTGTCATT

STAG2 STAG2 exp F CTCGTTGCTGCCTCTGTGT A STAG2 exp R TAAAATGGTGGCTTGCCTTC

SH3KBP1 SH3KBP1 exp F CAACGGGAAGACTGGAATGT SH3KBP1 exp R CTTGAGTCACCCCCATCACT Table 5

114 Table 5. PCR Primers for qPCR Validation of HBx Targeting of Representative

Genes. Primers were designed by obtaining the DNA sequence corresponding to the binding site within the TSS of the associated gene, from UCSC Genome Browser, and using that DNA to search for possible primer pairs with Invitrogen Perfect Primer, online tool. Resulting primers were analyzed with UCSC Genome Browser to confirm specificity to the region of interest.

115

Recruitment Expression Recruitment Expression PRPSAP2 RASA1 1 2 3 Exonic 1 Exonic 4 2 5 Active 3 4 Active 5

Exonic TCERG1 STAG2 TSS Shared Poised 1 1 2 Also in HBx Mutant

HBx wtHBx 3 2 4 3 5 Poised 4 5

k/d MTA1 wt, HBx

TSS Shared in All Conditions TSS Shared ACCN1 SH3KBP1 No Marks 1 Also with HBx Mutant 2 1 Active 2 3 3 4 4 5 5

ConditionsAll

Figure 27

116 Figure 27. Expression of Genes Representing HBx wild-type and HBx wild-type,

MTA1 knock-down Conditions in PHHs. As there weren’t any genes that were targeted

at the TSS in HBx wild-type and HBx wild-type, MTA1 knock-down samples in PHHs,

validation was not completed for these categories, in Figure 26. Validation of targets was

attempted for genes which shared HBx targeting among multiple categories or with

recruitment to exonic regions instead of the TSS. Successful binding results were not established and altered expression results may or may not follow what was predicted by chromatin mark proximity. HBx altered gene expression in PHHs, representing HBx wt

(A), and HBx wt, MTA1 k/d (B), conditions in PHHs, where specific validation to TSS targeted genes was not available, are shown. UCSC Genome Browser snapshots are in order from top to bottom of PHH HBx wt (1), HBx MTA1 k/d (2), HBx Mutant (3), HBx

Mutant, MTA1 k/d (4). The last two samples in these snapshots are PHH or HepG2 specific controls (5).

117 Chapter 4: Discussion

This genome-wide analysis of the viral trans-regulator protein HBx, provides a detailed view of the recruitment and resulting change in gene expression of targeted genes, dependent on, and independent from, the transcription factor component p65 (which acts to increase MTA1 transcription) and the master chromatin modifier, MTA1, with a goal to define the role of MTA1 on the genome-wide recruitment of HBx. Interestingly, HBx recruitment to the genome was increased upon compromising the levels of MTA1 and p65, indicating a proposed suppressive function for these factors on HBx recruitment to the host’s genome. Also, overall recruitment patterns and patterns with respect to gene expression and development (HOX genes), revealed that HBx could target the indicated genes in PHHs only when MTA1 and/or p65 was reduced. Some patterns of recruitment correlated with wild-type HBx recruitment (with intact p65 and MTA1 involvement) in the transformed cells (HepG2), suggesting similarities between normal cells with altered p65 and MTA1 functions, and HBx recruitment in liver cancer cells. HBx recruitment to TSS regions of genes with proximity to chromatin marks appeared to be correlative with a resulting change in gene expression, suggesting that HBx may utilize MTA1 to modify the chromatin and p65 to target these regions, as well as chromatin marks to access and alter the expression of target genes. A contribution of MTA1 to alter gene expression is also apparent, revealing a multifactorial process, significant for this outcome. Our data have revealed numerous novel targets of HBx that may also further alter gene expression, both with and without previously known roles in cancer development.

118 This report also provides a wealth of information regarding HBx target genes

dependent on, and independent from, p65 and MTA1 with details of annotation region and

chromatin mark proximity to predict the possible trans-regulation of gene expression,

which for select genes, was validated by qPCR. These data also reveal significant roles for these two cellular players in the genome-wide recruitment of HBx but do not suggest that they are the only contributors in the process. These results conclude that p65 and MTA1 are central to the genome-wide recruitment of HBx, which is drastically altered following a reduction in their involvement, in both pre- and post- cancerous cells. Here we have shown that p65 and MTA1 play important roles in the ability of HBx to target the host’s genome, possibly contributing to the transformation of hepatocytes into cancer cells.

To begin, we sought to develop an experimental model that would allow us to not only identify the genes that HBx targets, within both normal and cancerous cells, but would also allow us to characterize the involvement of two host factors, p65 and MTA1

(Specific Aim 1). Our experimental strategy successfully produced the material needed to study the question at hand. The use of a lentiviral vector system allowed for not only high transduction and so, expression rate of HBx or the HBx Mutant, but also allowed the viral components to enter the cell, similarly to how they normally would. The use of this system introduces both desired and undesired effects as the system itself may initially alter the normal entry and effects of HBx through the use of viral components from a different virus

(HIV-1). Effects, however, should be minimal due to the short-lived nature of these components (Ramezani and Hawley 2002). The use of chromatin immunoprecipitation

(ChIP) was ideal in the isolation of material required to identify the chromatin targets of this viral protein. The use of the HBx Mutant vector allowed us to reveal the involvement

119 of p65, as this mutation has been shown to reduce HBx/p65 binding and resulting increased

expression of MTA1 (Bui-Nguyen et al., 2009a). Deep sequencing completed by Cofactor

Genomics, on an Illumina platform, by 60 base pair reads, allowed for a comprehensive

identification of these targets. The use of multiple bioinformatics tools (Avadis NGS, IPA,

UCSC Genome Browser), allowed for the resulting data to be effectively interpreted, revealing what we thought would be the best place to start, when aiming to define the genome-wide targeting of HBx and the roles of these two cellular factors. The resulting data provides invaluable information that will be used for further biological endpoint studies, and may lead to the identification of select molecules of great importance, in the

HBV-associated development of HCC. The experimental strategy was carefully constructed to provide the ideal components needed for this global characterization of HBx.

Improvements could only stem from the incorporation of additional conditions, to further explain the findings. For instance, the analysis of MTA1 overexpression in regards to the genome-wide targeting of HBx, would not only help to confirm the findings but may also provide more information which could better tie the results with cancer, as MTA1 overexpression is a hallmark of many cancer types. Global genome-wide targeting of p65 and MTA1, separately and without HBx, could also provide information for comparison as it was difficult to deduce if the HBx targets, being altered by the involvement of p65 and

MTA1, were direct binding targets of these cellular factors or if other players were involved in this targeting. These additions, however, could complicate the story beyond our aims, and presently, these data were not desired. By reducing the involvement of MTA1, through p65 and otherwise, we have achieved the desired outcome, although MTA1

120 overexpression, or comparative recruitment of these factors alone, could help to explain our findings.

To begin elucidating the global targeting of the host chromatin, by HBx, we aimed to characterize overall recruitment patterns (Specific Aim 2). This aim allowed us to describe the global effects of this viral trans-activator protein, in relation to p65 and MTA1, revealing how this protein may alter gene expression, which could result in cellular transformation. The characteristics of binding, to include targeting of binding sites and genes, revealed that MTA1 and p65 play an important role in the ability of HBx to target the host genome. Recruitment to total binding sites suggests that this experimental model was successful, as results were high for all conditions (Figure 11). With wild-type p65 and

MTA1, HBx targeting of the host genome is drastically reduced compared to other conditions, suggesting that these factors act to hinder accessibility. As these factors were reduced, further diminishing the effects of MTA1, HBx was able to target more genes and more important regions of genes (TSS) for trans-regulation. Recruitment to top networks of genes revealed that MTA1 and the NF-κB complex (p65) were central to the genome-wide recruitment of HBx, supporting our study of the roles of these cellular factors (Figure 12).

Further analysis of the associated networks revealed gene targets which could be further explored in relation to MTA1 and NF-κB, to further elucidate their effects on the functions of HBx. Chromosomal targeting supported the finding that HBx binds throughout all chromosomes with increased or altered binding patterns as the involvement of both cellular factors was altered (Figure 14). Increased targeting to the X chromosome in PHHs may reveal additional information to support the finding that HCC develops more commonly and is more severe in males than in females (Tangkijvanich et al., 1999; Bosch et al.,

121 2004). Increased recruitment of HBx to chromosomes 4 and 8 in liver cancer cells with

MTA1 knock-down, may reveal why these chromosomes have also been implicated in the

development of HCC, by identifying the genes which are targeted, as previously discussed

(Figure 14). These patterns of recruitment help to reveal specific gene targets which will

be studied further. Revealing the top unfiltered targets by total reads and enrichment by

sample condition, has also identified gene targets for further study as heavy recruitment

throughout a gene may result in trans-regulation (Tables 1 and 2). Overall, revealing these

global recruitment patterns elucidates the effects that this viral protein has on the genome,

while defining the role of MTA1.

To define HBx recruitment to categories of genes, we analyzed molecular and

cellular functions, canonical pathways, top nodal points of networks, NF- κB, p53 and RB

associated networks, cancer genes, tumor suppressor genes and oncogenes, and gene

expression related genes. These analyses revealed global recruitment patterns such as an

increase in cancer related targets in PHHs following the reduction in both cellular factors,

and genes which were central to HBx targeting, as well as those which are known to play a

role in cancer and gene expression, possibly contributing the most to cellular

transformation, or reduced transformation, resulting from these effects of HBx (Figures 19,

20, 21). By revealing these genes, we can describe the overall effects of HBx and hypothesize how this viral protein may contribute to the outcome of cancer. Recruitment to any of these targets may be significant for this outcome, and this provides a wealth of information for future analysis. These results were provided as such, to further define targets which would make sense in relation to the known functions of HBx, but they were not the focus of immediate validation.

122 This broad view of targeting begins to elucidate the patterns of HBx recruitment

and the role of MTA1. Our model compares wild-type HBx recruitment with wild-type involvement of p65 and MTA1, to that with reduced MTA1 involvement (through p65 and otherwise), which inhibits MTA1 from acting on the chromatin as it normally would. The

known functions of MTA1 are vast, and are difficult to relate to the current situation as

these functions often involve individual factors, not addressed here. These functions,

however, may provide clues into the outcome which we are describing. For instance,

MTA1 depletion has been shown to cause a hypersensitivity to ionizing radiation exposure,

which was concluded as possibly resulting from a defect in double strand break repair (Li

et al., 2010). The hypersensitivity to radiation may also be due to the reduced closure of the

chromatin caused by the reduction in MTA1. As MTA1 normally condenses the chromatin,

this closed structure may protect these regions of the DNA from external stimuli. In the

same sense, with reduced MTA1, the chromatin is more open to receive HBx, which will

target a select number of binding motifs (Figure 24), which may have been previously

covered or protected by condensed chromatin. Open chromatin may make the chromatin

and targeted DNA more vulnerable, if you will, to external stimuli such as radiation or viral

proteins like HBx. HBx has also been linked to the inhibition of DNA repair enzymes

(Qadri et al., 1996; Qadri et al., 2011; Cheng et al., 2009) and so, both factors may play a

role in reducing gene integrity and stability. In our case however, the result may not be

DNA injury which leads to cancer as MTA1 reduced expression is not thought to promote

cancer. The result instead, allows HBx to target these motifs on genes that may repress the

outcome of cancer, such as reducing the expression of an oncogene or increasing the

expression of a tumor suppressor gene. Although this may need further validation, the

123 identified TSS targeted genes follow such a pattern. Of interest would be if these genes are targeted differently when MTA1 is overexpressed, or as expected, the overexpression of

MTA1 may actually allow HBx to target fewer or different genes leading to cancer development. With an overexpression of MTA1, the chromatin is more condensed in

MTA1 targeted regions. It would be interesting to find out if this would reduce the targeting of HBx all together or if it would allow for a select few genes to be targeted?

Would these genes include some which have been identified here? As MTA1 has been shown to play multiple roles in the cell, the effect of the overall expression of MTA1 on specific targets, known to play a role in cancer, may also be of interest. For instance,

MTA1 deacetylates, and so inactivates, tumor suppressor p53 (Manavathi and Kumar

2006). With reduced MTA1, it may be possible that p53 may have altered activity than exhibited in wild-type conditions. As an example, altering the functions of p53 and its downstream effects may alter the ability of HBx to target the genome. The project at hand only aims to define the targeting of HBx in response to the involvement of p65 and MTA1, and the mechanism behind the observed recruitment patterns remains to be seen. The results of this project however, provide important clues of the functions of HBx in regards to p65 and MTA1, and act as a baseline for further exploration. As we show here, HBx can target more overall genes and more genes at the TSS (trans-regulation), possibly increasing its ability to alter gene expression, when MTA1 involvement is reduced. Recruitment to a drastically higher number of binding sites, genes, and within chromosomes, within normal cells (PHHs), with MTA1 reduction, suggests that MTA1’s wild-type role in normal cells is very important for HBx targeting, in a pre-cancer setting. As discussed further, the

124 targeted genes appear to be altered in the favor of a reduced outcome of cancer, which, with

MTA1 reduction, follows the known functions of MTA1.

To identify genes which may or may not have been implicated in cancer or gene expression, which would be novel to this outcome and may be the best candidates to focus on for future studies, we isolated genes with TSS recruitment (Aim 3). This list provides what we deem as the most significant and novel targets for immediate study, as an alteration in their gene expression may describe players which have never been connected to HCC before. Categorization of these targets revealed genes involved in gene expression and cancer, as expected, but also those involved in the immune system or those that are viral related, as well as those related to development (HOX genes), as identified in PHHs

(Figure 23). Such homeodomain containing targets (HOX and other genes), revealed in

PHHs, with reduced MTA1 expression, may alter the balance between differentiation and proliferation which is needed for development, but is thought to play a role in neoplasia

(Lappin et al., 2006). Although currently unexplored in humans, the connection between

MTA1 and development/HOX genes, have been suggested. It is known that a C. elegans gene, egl-27, which has similarities (c-terminal domain) to the mammalian MTA1, interacts with the Wnt signaling pathway (possibly cancer related), as MTA1 has also been shown to (Kumar et al., 2010). It was also shown that defects in egl-27 altered the expression of related HOX genes important for cell migration and polarity (Herman et al.,

1999). The discovery that in normal cells with reduced MTA1 expression, HBx targets a large set of homeodomain containing/HOX genes is an interesting avenue for further research as previously mentioned, but also in the context of its currently unexplored association with HBx and cancer.

125 To further describe the binding of HBx, as we know that this viral protein may target specific binding motifs, we revealed the motifs targeted in these TSS targeted genes from Tables 3 and 4. As expected, very few binding sites could be targeted with wild-type

HBx, to include only GAGA/CACA/CGCG/CTCT repeats and the 4FE4S_FER_1 binding signature in PHHs and EGF_1, VWCF_1 and a few others in HepG2 cells (Figure 24).

Targeting of binding signatures increased, as the cellular factors were reduced. The ability of HBx to target overall binding motifs does not change significantly, suggesting that by altering MTA1, those modifications alter the chromatin accessibility, resulting in increased binding, by increasing the accessible motifs. Targeting of specific motifs or repeat elements was the focus of another article which analyzed the global recruitment of different viral trans-activator protein. In this study, the genome-wide targeting of HIV-1 Trans-activator of Transcription (Tat) revealed that over half of the regions targeted were repeat elements, with the majority of those containing Alu sequences. The targeted genes were important for the immune system and cell death and only about seven percent of all targets had targeting at the TSS (Marban et al., 2011). This study is similar in that it uses the same methods to identify the genome-wide targets of a viral trans-activator protein, and they showed that the

TSS was targeted in a low percentage of genes, as do we. They also show that the protein targets specific repeat elements or motifs, as we also found, which defines the regions that the viral proteins are capable of binding. This comparison may suggest that viral trans- activator proteins bind specific sequences in the genome, which is different based on the protein (Tat or HBx or others), and the identification of these motifs as well as the associated targeted genes, may provide clues about their functions. The purpose of

Specific Aim 3 was to identify specific targets of HBx in relation to p65 and MTA1

126 involvement, and the aforementioned results provide not only the basics of this targeting

but reveal novel binding motifs and their associated gene targets, ready for confirmation

and further analysis.

To insure that genes identified by bioinformatic methods were actually targeted in

our samples, we completed PCR and qPCR, revealing binding to representative genes and

resulting gene trans-regulation as predicted by chromatin mark proximity (Specific Aim 4).

As mentioned earlier, HOX genes were identified as being targeted following MTA1

reduction in PHHs. To represent the two categories without p65 involvement, HOXB7 and

HOXD10 were validated. HOXB7 was found to be increased in expression with a

reduction in p65, whereas HOXD10 was found to be repressed, with a reduction in both

factors. HOXB7 has been studied in relation to other cancers, revealing its increased

expression in multiple myeloma and oral cancer, due to its role in cell proliferation

(Fernandez et al., 2008; Destro et al., 2010). It has also been suggested to be an oncogene

in melanoma where it was found to trans-activate bFGF (Fernandez et al., 2008). It has not,

however, been linked to liver cancer or to HBx. The known role for HOXB7 in other

cancers, make it an interesting gene to study in the context of HBx and MTA1. HOXD10,

which was repressed in our study with the reduction in both p65 and MTA1, has been

suggested to be a candidate tumor suppressor. This gene was shown to be down-regulated

in gastric cancer and was shown to reduce migration and angiogenesis as well as FGF2 and

Cyclin D expression (Wang et al., 2010; Myers et al., 2002; Cho et al., 2008). This gene

has not been connected to liver cancer or HBx, and would also be an interesting gene to

study in this regard. Further studies on these gene targets will elucidate the effects of

altering developmental genes which may play a role in liver cancer.

127 For HepG2 cells, a zinc finger FYVE domain containing gene ZFYVE19, was found to be repressed. This gene is not well characterized and would be an interesting target to study, as it needs the wild-type expression of both factors for HBx to target it. It

has been connected to one type of cancer, leukemia, which is characterized by a fusion between this gene and the mixed lineage leukemia gene (Vandana et al., 2003). An association between HBx or liver cancer and this gene, have not been revealed until now,

which makes this gene an interesting target for future research. RexO1L1 or GOR,

targeted by HBx with MTA1 knock-down, was found to be reduced in expression. This

gene has previously been connected to HCV-associated liver disease (Quiroga et al., 1996)

and would be another novel target to study in relation to HBx and MTA1. GNB2L1 or

Guanine-nucleotide binding protein subunit beta-2-like 1, was found to be reduced without p65 involvement. This gene plays a role in many signaling pathways and is part of the 40S ribosomal subunit, important for repression of gene expression (Coyle et al., 2009). It has been implicated in reducing cell growth, and it plays a role in migration (Bourd-Boittin et al., 2008), which correlates with the known functions of MTA1 as MTA1 is reduced in this sample condition. It has been connected to HBV-associated HCC where it was found to be upregulated in HCC tissues as well as related cell lines (Ruan et al., 2012). It has not, however, been connected to HBx or MTA1. GLTSCR2 was found to have increased expression in HepG2 cells with the reduction in both cellular factors. This gene, glioma

tumor suppressor candidate 2, is not well characterized, although it was identified as being

down-regulated in glioblastomas (Kim et al., 2008). This gene has been shown to stabilize

PTEN, another tumor suppressor (Okahara et al., 2004). Altered function of PTEN has

been implicated in many cancer types and targeting of this gene while MTA1 involvement

128 is reduced, follows the known functions of MTA1 as well. MTA1 over-expression has been

implicated in cancer, so the reverse, with reduced MTA1 expression, may occur as a result

of HBx binding to cancer repressors. This gene has not been connected to either HBx or

MTA1. Many of these top targets (TSS recruitment) have another characteristic in

common, as they are associated with the Phosphatidylinositol 3-kinases pathway, which is known to play a role in cancer as associated with differentiation, migration, and cell proliferation. This pathway has been associated with HBx (Wang et al., 2011), but the aforementioned, related genes, have not been identified until now. This suggests that not only do our data correlate with what is known about HBx, but they also provide more

specific information into what HBx may be doing in regard to these known pathways.

Overall, the downstream effects of HBx targeting of these representative genes, as well as

all other genes identified by this bioinformatic study, will need to be explored further to

characterize their effects on resulting changes within the cell.

The role of MTA1 in the genome-wide recruitment of HBx was analyzed by reducing its involvement through diminishing the ability of HBx to interact with p65 from the NF-κB transcription factor complex, which keeps HBx from increasing the expression of MTA1, as previously described (Bui-Nguyen et al., 2009a), as well as reducing MTA1 expression with MTA specific siRNA. Four levels of MTA1 expression were analyzed in the context of HBx targeting of the host genome. By reducing the involvement of MTA1 we were able to characterize its role, with respect to HBx targeted genes and characteristics of binding. In summary, we found that MTA1 plays a crucial role in the ability of this viral

factor to gain access to the host genome. Intact wild-type MTA1 expression and function

are needed to hinder accessibility of the genome to HBx. This study has delineated the

129

Wild-type MTA1 Reduction

MTA1 MTA1

Open Chromatin Reduced Accessibility Increased Accessibility

Other factors

Cancer develops over time

Reduced positive regulators of cancer Æ Reduced cancer Activated negative regulators of cancer

Altered gene expression of many other genes

Figure 28

130 Figure 28. Schematic of Proposed Effects of MTA1 on the Functions of HBx with

Respect to Cancer. The aforementioned findings suggest that with wild-type MTA1 expression, the chromatin is condensed at regions containing the motifs that HBx binds, leaving few binding sites/genes targeted by HBx. Over time, alterations in these factors or in other factors may allow for the outcome of cancer. With a reduction in MTA1 expression, the chromatin is more relaxed, with increased accessibility to the HBx targeted motifs. By analyzing chromatin mark proximity and confirming the resulting trans- regulation in select genes, it was found that with MTA1 reduction, HBx may be targeting genes that would reduce the outcome of cancer. This follows the known functions of

MTA1 as an over-expression has been found in many types of cancer. Here, we would expect that an over-expression of cancer would result in genes being targeted that would increase the probability of cancer development.

131 impact that this cellular factor has on genome accessibility and possibly the ability of HBx

to contribute to cellular transformation (Figure 28). Further studies to characterize this

mechanism and to determine the outcome following the targeting of these identified genes,

in relation to MTA1, will solidify these findings to support the notion that the

HBx/p65/MTA1 axis is instrumental in HCC.

Chapter 5: Future Directions

Future directions of this line of investigation are vast due to the nature of genome-

wide studies, and identification of a spectrum of targets, responsible for a wide variety of

cellular functions. For instance, Specific Aim 2 was successful in defining the genome-

wide recruitment patterns and potential targets of HBx with respect to MTA1. Further, our

initial genome-wide analysis narrowed down to top targets by further analyzing genes with

TSS recruitment of HBx, to most likely reveal resulting trans-regulation. Besides TSS

targeted genes, which we studied with the inclusion of upstream targeted genes, there are

three other annotation categories. As seen in Figure 11, HBx targets intronic regions more

heavily than any other annotated region. The recruitment of HBx to introns increases in

PHHs as MTA1 involvement is reduced, and is similar throughout the alteration of MTA1 in HepG2 cells. This pattern correlates with the overall genome-wide recruitment patterns.

Recruitment of HBx to intronic regions and the affects of MTA1 altered involvement would be interesting to study further as these regions have been found to play a role in transcription, splicing and protein diversity. Non-coding intronic regions within genes, play a role in protein diversity by alternative splicing and are also important in regulation with respect to microRNAs (Gromak, 2012). Introns are important for mRNA processing and

132 resulting gene expression as it was shown that genes with introns were expressed

significantly more than those without (Buchman and Berg, 1988). Studies have revealed

that intronic regions affect all aspects of mRNA maturation from the initiation of transcription to stability (Chorev and Camel, 2012). The recruitment of HBx to these regions within genes, may indicate a role for this viral protein in altering functions that would further control gene expression. A detailed analysis of HBx recruitment to introns and the resulting affects on gene expression could be a separate study which would yield significant insight into these diverse functions of HBx. Recruitment to exonic regions is also of interest as these coding regions within genes are important in the resulting transcript. With alternative splicing, exons can be included in the resulting transcript or not, resulting in different mRNA transcripts which are translated into various forms of proteins.

The ability of HBx to target exonic regions may indicate a role for HBx in regulating the inclusion of these exons. Also, some transcription factor binding sites or other regulatory regions have also been shown to reside within exonic regions, other than the TSS. Overall, this study has identified the genome-wide binding patterns with respect to many categories, including annotation region, and has focused on those with the most immediate interest, revealing many avenues which could be explored further.

Another avenue which is of great interest for future studies includes the results from the analysis of percent chromosomal distribution of reads. This analysis revealed global recruitment patterns through out all chromosomes, which further identified a few chromosomes that were targeted more heavily in specific conditions. For instance, in

PHHs, chromosomes 9 and X were targeted more heavily by wild-type HBx than any other condition. Recruitment to the X chromosome for instance, may have implications for the

133 gender discrepancy identified by the worldwide prevalence of HCC (Tangkijvanich et al.,

1999; Bosch et al, 2004). Identification and analysis of targeted genes which are located in

chromosome X, could reveal novel genes which are deregulated in HBV-associated HCC.

This may define a role for HBx in HCC susceptibility of the human host. In liver cancer

cells with a reduction in MTA1 involvement (MTA1 knock-down by siRNA), we

identified an increase in recruitment to genes in chromosomes 4 and 8, which have been

implicated in liver cancer previously (Nishimori et al., 1994; Roessler et al., 2012; Marchio

et al., 1997).

The link between HBx-mediated chromosomal alterations, especially with respect to MTA1, has not been explored. Further analysis of overall recruitment to gene networks also provides an avenue for novel characterization of HBx. Widespread targeting could

result in the modulation of many factors within a single pathway, which could drastically

alter resulting function within the cell. For instance, the networks targeted by HBx provide

information on a nodal point which has many associated genes, also targeted by HBx.

Where the NF-κB complex was found to be a top nodal point, studies of the associated

genes could further define how HBx modulates NF-κB signaling and which associated

genes are involved. Extensive analysis could reveal the outcome of HBx targeting of these

factors to define the roles of the revealed nodal point. Of great interest would be targeting

of the genes associated with TP53 (p53), where TP53 was found as a top nodal point for

PHHs with the two lowest involvement levels of MTA1. Associations of this nodal point

with numerous genes, with many also being targeted by HBx (shaded), may further explain

their roles in HBx, MTA1 and p53-mediated HCC (Figure 18). Due to the accepted role

for p53 in numerous cancer types, and its previously defined role in HBx and also MTA1

134 mediated cellular functions, characterization of this axis would be highly desired. Overall,

these data provide ample targets for further study on HBx-associated HCC.

As mentioned previously, recruitment of HBx to specific gene categories,

especially those involved in gene expression and cancer, may be significant in the affects of

HBx on the outcome of HCC. This is due to the knowledge that HBx is a trans-activator

protein, involved in altering gene expression (Figure 21). It is possible that HBx is not only

altering the gene expression of targeted genes, but maybe HBx is also targeting genes

which encode proteins that could further enhance this effect. Since HBx has been

implicated in cellular transformation, the analysis of genes involved in cancer (Figure 19), to include oncogenes and tumor suppressor genes (Figure 20), is also of great interest. For the purpose of this initial genome-wide analysis, we identified these gene targets, by category, and propose that their trans-regulation may be significant in the outcome of HBx- associated cancer. Gene expression related genes which were identified here and were targeted in PHHs, included those which were associated with RNA polymerase II, indicating a role in the regulation of transcription, as well as many developmental genes, which were also identified in the TSS targeted gene lists and have been discussed previously. In HepG2 cells, two of the four targets identified for wild-type HBx recruitment were already known for HBx (MMP9, TFAP2A) with two novel to this recruitment (DET1, TRIM29). Recruitment to DET1 may have implications for protein regulation through ubiquitination and degradation. TRIM29 has been shown to bind nucleic acids and regulate transcription, possibly with an influence on cellular transformation. Both genes were identified in liver cancer cells with wild-type HBx recruitment, indicating a need for MTA1 expression for this targeting. These genes represent interesting gene

135 expression related targets for further study. In the analysis which revealed genes associated with cancer, to include tumor suppressor genes and oncogenes, we identified some LIM domain containing genes (LIMD1) which contain a domain that has been shown to interact with MTA1 previously (Manavathi et al., 2007). These analyses have also identified many oncogenes of the RAS family as well as transcriptional regulators and kinases for further study. Each analysis, completed in this initial study of HBx targeting of the genome, provides another avenue for extensive study. This also includes the motifs revealed to be targeted by HBx. These motifs, if found to be necessary and sufficient for the functions of

HBx, could be targeted by therapeutics to stop HBx binding. Revealing the binding motifs of HBx not only defines the regions that HBx is capable of targeting but opens up a new avenue of future research of therapeutic importance.

Of most interest to us initially, was the targeting of HBx to the TSS of genes.

Targets chosen for validation represent each category with TSS targeting, but also represent genes that could be playing a significant role in the overall effects of HBx. Categorization of TSS targeted genes suggest overall effects of HBx may be attributed to the trans- regulation of genes involved in cancer and gene expression, as was evident by many analyses in this study, but also may be attributed to targeting genes containing zinc finger motifs, those with a role in the immune system, in liver damage and development. Genes containing zinc finger motifs were targeted at the TSS more heavily with a reduction in

MTA1 involvement and may reveal an interaction between HBx and genes encoding DNA binding proteins. Recruitment to genes involved in the immune system are also of interest as both MTA1 and HBx have been shown to modulate the immune system reaction to infection. Interestingly these targets also included many which are known to be involved in

136 viral trans-activation, including some which have not been identified for HBx-associated

HCC (Figure 23). Clearly, the vast amount of information provided by this study could be

followed further in multiple studies to further define the widespread effects of HBx within

the host cell.

Ultimately, this research provides ample targets for therapeutic application following

biological endpoint studies, to correlate altered gene expression with the outcome of HCC,

as associated with HBV. Validation of the aforementioned targets within patient samples,

from those with HBV-associated HCC, would be the first step in revealing the significance

of HBx targeting, on the outcome of cancer. This would directly connect the identified

targets with patients suffering from this disease, supporting the notion that these genes

could be targeted therapeutically. Also, as MTA1 is a master co-regulator, which has been

shown to play a role in a wide array of cellular processes, identifying and targeting genes

associated with its functions, especially in the context of a viral trans-activator protein,

would be more beneficial than targeting and disrupting the master chromatin modifier

itself, which may result in unfavorable outcomes. Among these targets, those which were

validated; HOXB7, HOXD10, ZFYVE19, REXO1L1, GNB2L1 and GLTSCR2, would be

of immediate interest. Further characterization may identify these genes as central players

in the cellular transformation effects of HBx. Many targets mentioned throughout this

analysis could also be validated and analyzed in patient samples for further study. Due to

the severity of this disease, HBx specific therapies are highly desired. It is known that over

400,000 people worldwide, are chronically infected with HBV, putting them at risk for

HCC. Completing biological endpoint studies on genes found to be important in patient

samples may allow for these specific therapies to be developed. The emerging model

137 identified by this study connects a viral trans-activator protein, HBx, with two cellular components, p65 and MTA1, which more specifically defines MTA1 wild-type expression as a strong inhibitor of HBx genome-wide targeting. Elucidating the critical role of MTA1 as well as identifying HBx targeted genes, may allow for more specific HBV-associated

HCC therapies to be developed.

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