Liu, Xin. / "December 2009." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 119-126). / Abstracts in English and Chinese. / Abstract in English --- p.i / Abstract in Chinese --- p.iv / Acknowledgements --- p.vi / List of abbreviations --- p.vii / List of Tables List of Figures --- p.X xii / List of Publications --- p.xiv / Chapter Chapter 1 --- Literature Review --- p.1 / Chapter 1.1 --- Gastric cancer epidemiology and etiology --- p.1 / Chapter 1.2 --- Molecular carcinogenesis --- p.4 / Chapter 1.3 --- Tumor suppressor gene and the modes of tumor suppressor gene inactivation --- p.4 / Chapter 1.4 --- DNA methylation and carcinogenesis --- p.8 / Chapter 1.5 --- Identification of tumor suppressor genes --- p.15 / Chapter 1.6 --- "Vitamins, vitamin B complex, thiamine transporters and diseases" --- p.18 / Chapter 1.7 --- "Glucose metabolism, glycolysis and carcinogenesis" --- p.22 / Chapter 1.8 --- Clinical implications of DNA methylation --- p.28 / Chapter Chapter 2 --- Research Aim and Procedure --- p.31 / Chapter Chapter 3 --- Materials and Methods --- p.35 / Chapter 3.1 --- Cell lines and human tissue samples --- p.35 / Chapter 3.2 --- Cell culture --- p.35 / Chapter 3.3 --- Total RNA extraction --- p.36 / Chapter 3.4 --- Genomic DNA extraction --- p.37 / Chapter 3.5 --- Reverse transcription PCR (RT-PCR) --- p.38 / Chapter 3.5.1 --- Reverse transcription (RT) --- p.38 / Chapter 3.5.2 --- Semi-quantitative RT-PCR --- p.40 / Chapter 3.5.3 --- Real time RT-PCR --- p.42 / Chapter 3.6 --- General techniques --- p.44 / Chapter 3.6.1 --- DNA and RNA quantification --- p.44 / Chapter 3.6.2 --- Gel electrophoresis --- p.44 / Chapter 3.6.3 --- LB medium and LB plate preparation --- p.44 / Chapter 3.6.4 --- Plasmid DNA extraction --- p.45 / Chapter 3.6.4a --- Plasmid DNA mini extraction --- p.45 / Chapter 3.6.4b --- Plasmid DNA midi extraction --- p.46 / Chapter 3.6.5 --- DNA sequencing --- p.46 / Chapter 3.7 --- Methylation status analysis --- p.49 / Chapter 3.7.1 --- CpG island analysis --- p.49 / Chapter 3.7.2 --- Sodium bisulfite modification of DNA --- p.49 / Chapter 3.7.3 --- Methylation-specific PCR (MSP) --- p.50 / Chapter 3.7.4 --- Bisulfite genomic sequencing (BGS) --- p.53 / Chapter 3.8 --- Construction of expression plasmid DNA --- p.55 / Chapter 3.8.1 --- Construction of the SLC19A3-expressing vector --- p.55 / Chapter 3.8.2 --- Construction of the FBP1-expressing vector --- p.57 / Chapter 3.9 --- Functional analyses --- p.58 / Chapter 3.9.1 --- Monolayer colony formation assay --- p.58 / Chapter 3.9.2 --- Cancer cell growth curve analysis --- p.59 / Chapter 3.9.3 --- Lactate assay --- p.60 / Chapter 3.10 --- Statistical analysis --- p.61 / Chapter Chapter 4 --- Results --- p.62 / Chapter 4.1 --- Identification of novel candidate tumor suppressor genes downregulated by DNA methylation --- p.62 / Chapter 4.2 --- Selection of genes for further study --- p.62 / Chapter 4.3 --- Identification of SLC19A3 as a novel candidate tumor suppressor gene in gastric cancer --- p.64 / Chapter 4.3.1 --- Pharmacological restoration of SLC 19A3 downregulation in gastric cancer --- p.64 / Chapter 4.3.2 --- Methylation analysis of SLC 19A3 promoter region --- p.66 / Chapter 4.3.3 --- Functional analysis of SLC 19A3 in gastric cancer --- p.72 / Chapter 4.3.4 --- Clinicopathologic characteristics of SLC 19A3 promoter methylation in gastric cancer --- p.75 / Chapter 4.3.5 --- Discussion --- p.78 / Chapter 4.4 --- Identification of FBP1 as a novel candidate tumor suppressor gene regulated by NF-kB in gastric cancer --- p.85 / Chapter 4.4.1 --- Pharmacological restoration of FBP1 downregulation in gastric cancer --- p.85 / Chapter 4.4.2 --- Methylation analysis of FBP 1 promoter region --- p.87 / Chapter 4.4.3 --- Functional analysis of FBP 1 in gastric cancer --- p.93 / Chapter 4.4.4 --- Reduction of lactate generation under FBP1 expression --- p.95 / Chapter 4.4.5 --- Clinicopathologic characteristics of FBP 1 promoter methylation in gastric cancer --- p.98 / Chapter 4.4.6 --- NF-kB mediated FBP1 promoter hypermethylation in gastric cancer --- p.104 / Chapter 4.4.7 --- Discussion --- p.106 / Chapter Chapter 5 --- General discussion --- p.112 / Chapter Chapter 6 --- Summary --- p.117 / Reference list --- p.119

Earlier ecological studies on the relation between H. pylori infection and stomach cancer have considered that the relation between these two variables, as estimated by the exposure coefficient, is constant. However, there is evidence to suggest that this relation changes geographically due to differences in strains of H. pylori. Since the prevalence of H. pylori varies with socio-economic status, the association between the latter and stomach cancer mortality may also vary geographically. This thesis studies stomach cancer by taking into account the geographical variability of the exposure coefficients. The study proposes the use of regression mixtures, clustering models and spatially varying regressions for the study of varying exposure coefficients. The effect of transformations of variables in these models appears to have been little considered. We provide new necessary conditions for invariance under transformations of variables for mixed effect models in general, and for the proposed models in particular. In addition, we show that varying exposure coefficients may induce a varying baseline risk. The regression mixtures and the clustering model are applied to a data set on stomach cancer incidence and H. pylori prevalence in 57 countries worldwide. We extend the clustering model to reflect any distance measure between the geographical units, including the Euclidean distance, in the formation of clusters. We also show that the clustering model performs better than the regression mixture model when the aim is to identify connected clusters and the observations present large variance. The results obtained with the clustering model supported the existence of three clusters where the interaction between the human and H. pylori populations have similar characteristics. Spatially varying regressions are applied to a data set of areal death counts of stomach cancer and spending power in 275 counties in continental Portugal. We provide an original strategy for implementing multivectorial intrinsic autoregressions as the distribution for the random effects. The results obtained with the application of this methodology were consistent with a varying exposure coefficient of spending power.

Tang Angie. / Thesis submitted in: November 2005. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 151-172). / Abstracts in English and Chinese. / Acknowledgements --- p.i / Abstract --- p.iii / Abstract in Chinese --- p.vi / Table of Contents --- p.vii / List of Publications --- p.xi / Awards --- p.xii / List of Abbreviations --- p.xiii / List of Tables --- p.xv / List of Figures --- p.xvi / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Literature Review --- p.3 / Chapter 2.1 --- Gastric cancer-overview --- p.3 / Chapter 2.1.1 --- Epidemology --- p.3 / Chapter 2.1.2 --- Pathology --- p.3 / Chapter 2.1.3 --- Etiologies and Risk Factors --- p.4 / Chapter I. --- Environmental factors --- p.4 / Chapter a. --- Helicobacter pylori infections --- p.4 / Chapter b. --- Epstein-Barr virus (EBV) --- p.6 / Chapter c. --- Dietary factors --- p.6 / Chapter d. --- Smoking --- p.6 / Chapter II. --- Genetic Factors --- p.7 / Chapter a. --- Hereditary Gastric Cancer --- p.7 / Chapter b. --- Genetic polymorphism --- p.8 / Chapter III. --- Cyclooxygenases (COX) enzymes --- p.10 / Chapter IV. --- Molecular carcinogenesis --- p.11 / Chapter a. --- Activation of proto-oncogenes --- p.11 / Chapter b. --- Candidate tumor suppressor genes --- p.12 / Chapter 1. --- Gene mutation and deletion --- p.12 / Chapter 2. --- Epigenetic Silencing --- p.13 / Chapter 2.2 --- Epigenetics --- p.14 / Chapter 2.2.1 --- DNA methylation --- p.15 / Chapter 2.2.2 --- Histone modification --- p.28 / Chapter I. --- Histone acetylation and deacetylation --- p.32 / Chapter II. --- Histone methylation --- p.32 / Chapter III. --- Histone phosphorylation --- p.34 / Chapter IV. --- Histone ubiquitylation --- p.34 / Chapter 2.3 --- "HAT, HDAC and HDAC inhibitors" --- p.36 / Chapter 2.3.1 --- HAT --- p.38 / Chapter 2.3.2 --- HDAC --- p.39 / Chapter (a) --- Class I --- p.40 / Chapter (b) --- Class II --- p.41 / Chapter (c) --- Class III --- p.42 / Chapter (d) --- Mammalian HDAC and their mechanism of deacetylation --- p.44 / Chapter 2.3.3 --- HDAC inhibitors --- p.45 / Chapter I. --- Class I/II natural inhibitors --- p.47 / Chapter II. --- Class I/II synthetic inhibitors --- p.48 / Chapter III. --- Sirtuins inhibitors --- p.49 / Chapter IV. --- Activity of HDAC inhibitors in vitro --- p.50 / Chapter a. --- Effect in the gene expression --- p.50 / Chapter b. --- Non-transcriptional effects --- p.55 / Chapter c. --- Activity of HDAC inhibitors with other agents --- p.57 / Chapter d. --- Effects in xenograft tumor models --- p.57 / Chapter V. --- Clinical trials of HDAC inhibitors --- p.59 / Chapter Chapter 3 --- Aims of the study --- p.63 / Chapter Chapter 4 --- Materials and Methods --- p.64 / Chapter 4.1 --- Cell culture --- p.64 / Chapter 4.2 --- Drug treatment --- p.64 / Chapter 4.2.1 --- Suberoylanilide Hydroxamic Acid treatment --- p.64 / Chapter 4.2.2 --- Trichostatin A treatment --- p.65 / Chapter 4.3 --- Cell proliferation assay --- p.66 / Chapter 4.4 --- Apoptotic assay --- p.67 / Chapter 4.5 --- Flow cytometry --- p.67 / Chapter 4.5.1 --- Cell preparation --- p.67 / Chapter 4.5.2 --- Propidium Iodide staining --- p.68 / Chapter 4.5.3 --- Annexin V-FITC staining --- p.68 / Chapter 4.5.4 --- Flow cytometer analysis --- p.69 / Chapter 4.6 --- Total RNA extraction --- p.70 / Chapter 4.7 --- DNA extraction --- p.71 / Chapter 4.8 --- Protein extraction --- p.72 / Chapter 4.9 --- Western blottng --- p.72 / Chapter 4.10 --- Microarray analysis --- p.74 / Chapter 4.10.1 --- Sample preparation for microarray --- p.74 / Chapter 4.10.2 --- Hybridization --- p.75 / Chapter 4.10.3 --- Scanning and data processing --- p.75 / Chapter 4.10.4 --- Data analysis --- p.76 / Chapter 4.11 --- Primer design --- p.77 / Chapter 4.12 --- RT-PCR --- p.77 / Chapter 4.12.1 --- Reverse transcription --- p.77 / Chapter 4.12.2 --- Quantitative RT-PCR --- p.78 / Chapter 4.13 --- Methlyation study --- p.79 / Chapter 4.13.1 --- Demethylation by 5-aza-2'deoxycytidine --- p.79 / Chapter 4.13.2 --- Bisulfite modification --- p.79 / Chapter 4.13.3 --- Methylation-specific PCR (MSP) --- p.79 / Chapter Chapter 5 --- Results --- p.81 / Chapter 5.1 --- Morphological changes in AGS cells --- p.81 / Chapter 5.2 --- Anti-cancer effects of HDAC inhibitors --- p.81 / Chapter 5.2.1 --- Effect of HDAC inhibitors on cell growth --- p.81 / Chapter a. --- SAHA inhibits cell proliferation --- p.82 / Chapter b. --- TSA inhibits cell proliferation --- p.82 / Chapter 5.2.2 --- Cell cycle analysis --- p.87 / Chapter a. --- Effect of SAHA on cell cycle --- p.87 / Chapter b. --- Effect of TSA on cell cycle --- p.88 / Chapter 5.2.3 --- Induction of apoptosis on AGS cells --- p.92 / Chapter a. --- SAHA induces apoptotic cell death --- p.92 / Chapter b. --- TSA induces apoptotic cell death --- p.94 / Chapter 5.3 --- Induction of histone expression on AGS cells --- p.102 / Chapter 5.3.1 --- HDAC inhibitors induced acetylation of histone H3 --- p.102 / Chapter 5.3.2 --- HDAC inhibitors induced acetylation of histone H4 --- p.103 / Chapter 5.4 --- SAHA- and TSA-induced gene expression profiles --- p.106 / Chapter 5.5 --- Verification of gene expression by quantitative RT-PCR --- p.108 / Chapter 5.6 --- Methylation study --- p.113 / Chapter Chapter 6 --- Discussion --- p.116 / Chapter 6.1 --- Improved treatment strategy is needed for gastric cancer. --- p.116 / Chapter 6.2 --- HDAC inhibitors as potential anti-cancer agents --- p.117 / Chapter 6.3 --- Potential anti-cancer effect of TSA and SAHA on AGS cells --- p.120 / Chapter I. --- Morphological changes of AGS gastric cancer cells --- p.120 / Chapter II. --- Inhibition of cell proliferation --- p.120 / Chapter III. --- Induction of cell cycle arrest --- p.121 / Chapter IV. --- Induction of apoptosis --- p.122 / Chapter 6.4 --- Expression of acetylated histones upon treatment with TSA and SAHA --- p.124 / Chapter 6.5 --- Identify potential target genes upon treatment with TSA and SAHA --- p.125 / Chapter 6.5.1 --- Candidate genes involved in cell cycle --- p.126 / Chapter a. --- P21WAF1 --- p.126 / Chapter b. --- p27kip1. --- p.128 / Chapter c. --- Cyclin E & Cyclin A --- p.128 / Chapter d. --- Signal-induced proliferation-associated gene 1 (SIPA1) .… --- p.129 / Chapter 6.5.2 --- Candidate genes involved in apoptosis and anti-proliferation --- p.130 / Chapter a. --- BCL2-interacting killer (apoptosis-inducing) (BIK) (Pro-apoptotic gene) --- p.131 / Chapter b. --- Thioredoxin interacting protein (TXNIP) (Proapoptotic gene) / Chapter c. --- Cell death-inducing DFFA-like effector b (CIDEB) (apoptosis induction) --- p.132 / Chapter d. --- B-cell translocation gene 1 (BTG1) - (anti-proliferation) --- p.133 / Chapter e. --- Quiescin 6 (QSCN6) (anti-proliferation) --- p.133 / Chapter f. --- "Cysteine-rich, angiogenic inducer, 61 (CYR61) (anti-proliferative)" --- p.134 / Chapter g. --- Metallothionein 2A (MT2A) (apoptosis induction and anti-proliferative) --- p.134 / Chapter 6.5.3 --- Other genes reported to be up-regulated with HDAC inhibitors treatment --- p.135 / Chapter a. --- Glia maturation factor-gamma (GMFG) --- p.135 / Chapter b. --- v-fos FBJ murine osteosarcoma viral oncogene homolog (FOS) / Chapter c. --- Interleukin 8 (IL-8) --- p.136 / Chapter d. --- Insulin-like growth factor binding protein- 2 (IGFBP2) --- p.137 / Chapter e. --- Integrin alpha chain 7 (ITGA7) --- p.138 / Chapter 6.5.4 --- Selected highly up-regulated genes with HDAC inhibitors treatment --- p.139 / Chapter a. --- Aldo-keto reductase family 1，member C3 (AKR1C3) --- p.139 / Chapter b. --- GPI-anchored metastasis-associated protein homolog (C4.4A) --- p.139 / Chapter c. --- "Serine (or cysteine) proteinase inhibitor，clade I (neuroserpin), member 1 (SERPINI1)" --- p.140 / Chapter d. --- "Serine (or cysteine) proteinase inhibitor，clade E (nexin, plasminogen activator inhibitor type 1), member 1 (SERPINE1)" --- p.140 / Chapter e. --- Adrenomedullin (ADM) --- p.141 / Chapter f. --- Dehydrogenase/reductase (SDR family) member 2 (HEP27) --- p.142 / Chapter g. --- Cholecystokinin (CCK) --- p.142 / Chapter h. --- Silver homolog (mouse) (SILV) --- p.143 / Chapter 6.6 --- Genes regulated by gene promoter hypermethylation in AGS cells --- p.143 / Chapter Chapter 7 --- Conclusion --- p.147 / Chapter Chapter 8 --- Further Studies --- p.150 / References --- p.151 / Appendix I --- p.151 / Appendix II --- p.III / Appendix III --- p.IV / Appendix IV --- p.VI

Background & aims. DNA methylation induced tumor suppressor gene silencing plays an important role in carcinogenesis. By using methylation-sensitive representational difference analysis, we identified paired box gene 5 (PAX5) being methylated in human cancer. PAX5 locates at human chromosome 9p13.2 and encodes a 391 amino acids transcription factor. However, the role of PAX5 in gastric cancer is still unclear. Hence, we analyzed its epigenetic inactivation, biological functions, and clinical implications in gastric cancer. / Conclusions. Our results demonstrated that PAX5 promoter methylation directly mediates its transcriptional silence and commonly occurs in gastric cancer. PAX5 gene can act as a functional tumor suppressor in gastric carcinogenesis by playing an important role in suppression of cell proliferation, migration, invasion, and induction of cell apoptosis. Detection of methylated PAX5 may be utilized as a biomarker for the prognosis of gastric cancer patients. / Methods. Methylation status of PAX5 promoter in gastric cancer cell lines and clinical samples was evaluated by methylation specific polymerase chain reaction (MSP) and bisulfite genomic sequencing (BGS). The effects of PAX5 re-expression in cancer cell lines were determined in proliferation, cell cycle, apoptosis, migration and invasion assays. Its in vivo tumorigenicity was investigated by injecting cancer cells with PAX5 expression vector subcutaneously into the dorsal flank of nude mice. Chromosome Immunoprecipitation (ChIP) and cDNA expression array were performed to reveal the molecular mechanism of the biological function of PAX5. / Results. PAX5 was silenced or down-regulated in seven out of eight of gastric cancer cell lines examined. A significant down-regulation was also detected in paired gastric tumors compared with their adjacent non-cancer tissues (n = 18, P = 0.0196). In contrast, PAX5 is broadly expressed in all kinds of normal adult and fetal tissues. The gene expression of PAX5 in the gastric cancer cell line is closely linked to the promoter hypermethylation status. In addition, the expression levels could be restored by exposure to demethylating agents 5-aza-21-deoxycytidine. Re-expression of PAX5 in AGS, BGC823 and HCT116 cancer cells reduced colony formation (P < 0.01) and cell viability (P < 0.05), arrested cell cycle in G0/G1 phase (P = 0.0055), induced cell apoptosis (P < 0.05), repressed cell migration and invasion (P = 0.0218) in vitro. It also inhibited tumor growth in nude mice (P < 0.05). The molecular basis of its function were investigated by cDNA expression array and demonstrated that ectopic expression of PAX5 up-regulated tumor suppressor gene P53, anti-proliferation gene P21, pro-apoptosis gene BAX, anti-invasion gene MTSS1 and TIMP1; and down-regulated anti-apoptosis gene BCL2, cell cycle regulator cyclinD1, migration related gene MET and MMP1. ChIP assay indicated that P53 and MET are direct transcriptional target of PAX5. Moreover, PAX5 hypermethylation was detected in 90% (145 of 161) of primary gastric cancers compared with 16% (3 of 19) of non-cancer tissues (P < 0.0001). After a median follow-up period of 15.4 months, multivariate analysis revealed that gastric cancer patients with PAX5 methylation had a significant poor overall survival compared with the unmethylated cases (P = 0.0201). / Li, Xiaoxing. / Advisers: Hsiang Fu Kung; Jun Yu. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 134-159). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

published_or_final_version / Medicine / Master / Doctor of Medicine

In the past, patients with peritoneal surface malignancy were considered incurable and were only offered palliative treatments. However, in a substantial number of patients, disease progression that is isolated to peritoneum may occur. It has been realised that elimination of peritoneal surface tumours may have an impact on the survival of these cancer patients, in whom a prominent cause of death is peritoneal carcinomatosis. The focus of this PhD. thesis is on the combined treatment of cytoreductive surgery and perioperative intrapersonal chemotherapy for diffuse malignant peritoneal mesothelioma, pseudomyxoma peritonei, colorectal peritoneal carcinomatosis and resectable gastric cancer. Section one describes the major principles of management for peritoneal surface malignancy, covering the historical perspectives, the treatment rationales and the learning curve associated with the combined procedure. Section two is devoted to peritoneal mesothelioma, in trying to examine this disease from its clinical, radiologic and histopathologic aspects. A radiologic classification and a histopathologic staging system for this disease are proposed. In section three, the results of the combined treatment for pseudomyxoma peritonei are presented, including a systematic review of the literature, a case series of 50 patients from our Australian centre and a treatment failure analysis of 402 patients from the Washington Cancer Institute. These studies suggest that a disease-free state is important for long-term survival for patients with pseudomyxoma peritonei. In section four, the current evidence on the combined treatment for colorectaI peritoneal carcinomatosis is demonstrated by conducting a systematic review of the literature and survival and perioperative outcome analyses of two separate patient cohorts. These results suggest that the combined treatment is associated with an improved survival, as compared with historical controls. In the last section, a metaanalysis of the randomised controlled trials on adjuvant intraperitoneal chemotherapy for resectable gastric cancer shows that a significant improvement in survival is associated with hyperthermic intraoperative intraperitoneal chemotherapy alone or in combination with early postoperative intraperitoneal chemotherapy.

Viruses are known to be associated with 20% of human cancers. Epstein Barr virus (EBV) in particular is the first virus associated with human cancers. Here, we computationally detect EBV and explore the effects of this virus across cancers by taking advantage of the fact that EBV microRNAs (miRNAs) and Epstein Barr virus small RNAs (EBERs) are expressed at all viral latencies. We identify and characterize two sub-populations of EBV positive tumors: those with high levels of EBV miRNA and EBERS expression and those with medium levels of expression. Based on principal component analysis (PCA) and hierarchical clustering of viral miRNAs across all samples we observe a pattern of expression for these EBV miRNAs which is correlated with both the tumor cell type (B cell versus epithelial cell) and with the overall levels of expression of these miRNAs. We further investigated the effect of the levels of EBV miRNAs with the overall survival of patients across cancers. Through Kaplan Meier survival analysis we observe a significant correlation with levels of EBV miRNAs and lower survival in adult AML patients. We also designed a machine learning model for risk assessment of EBV in association with adult AML and other clinical factors. Our next aim was to identify targets of EBV miRNAs, hence, we used a combination of previously known methodologies for miRNA target detection in addition to a multivariable regression approach to identify targets of these viral miRNAs in stomach cancer. Finally, we investigate the variations across EBV subtype specific EBNA3C gene which interacts with the host immune system. Preliminary data suggests potential regional variations plus higher pathogenicity of subtype 1 in comparison to subtype 2 EBV. Overall, these studies further our understanding of how EBV manipulates the tumor microenvironment across cancer subtypes.