Molecular Genetic Epidemiology of Primary Hepatocellular

原发性肝细胞的分子遗传学流行病学

• 批准号: 6954016
• 负责人: Kenneth H Buetow
• 金额: --
• 依托单位: DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6954016
• 关键词: aflatoxins; cancer risk; clinical research; environmental exposure; gene environment interaction; gene expression; gene mutation; genetic mapping; genetic markers; genetic polymorphism; genetic susceptibility; hepatitis B virus group; hepatocellular carcinoma; human genetic material tag; human population genetics; human subject; molecular genetics; molecular pathology; neoplasm /cancer epidemiology; neoplasm /cancer genetics; p53 gene /protein; tumor suppressor genes; virus related neoplasm /cancer

The majority of cancer presents as a complex phenotype and is manifest through gene-gene, and/or gene-environment interactions. An ideal paradigm for the investigation of complex cancer phenotypes in humans is primary hepatocellular carcinoma (HCC). Molecular studies of genetic alterations in tumors have identified p53 as a tumor suppressor gene commonly altered in HCC. Epidemiologic studies have firmly established the role of chronic hepatitis B virus infection (HBV) and aflatoxin B1 (AFB1) exposure as environmental risk factors. However, the majority of individuals exposed to HBV and AFB1 do not develop HCC. Genetic analysis is being used to assess the role of genes in well-described pathways in determining disease. This approach merges gene mapping and candidate locus studies by including as candidates all the members of a pathway. Each gene of interest is "tagged" with multiple polymorphic sites, in or near it, to identify genetic factors modulating the risk of developing HCC among populations exposed to AFB1. The individual members of each family (GSTA1, GSTM1, GSTM3, GSTP, GSTT1, GST12, EPHX1, EPHX2, GSTA4, GSTT2, GSTZ1, STP, COMT, ESD, DTD, CYP, MGST1) have been tagged with new or published polymorphisms, and their role in HCC risk examined, in a nested case-control population. The loci GSTM1, GSTP, GSTT1, EPHX1 showed significant association with HCC risk while the EPHX2 locus was associated with age of onset. When results were stratified by the HBV status of the case, GSTM1 and GSTT1 were associated only in the HBV(+) cases, while GSTP was associated in the HBV(-) cases. These results indicate that these genes are candidates for more detailed functional and genetic analysis. Candidate gene variation at the 15 candidate cancer susceptibility loci will also be examined in a large case-control study (n=1000 cases and 1000 controls). Genetic information important in complex trait analysis may be accessible from the joint study of heritable variation and somatic tissue (tumor) variation in cancer. HCC tumor/normal pairs were examined using a collection of genome-wide simple tandem repeat polymorphism (STRP) markers, candidate loci, and the 1,300 single nucleotide polymorphisms (SNPs) present on the Affymetrix HuSNP chip. This data is being analyzed to identify regions of loss of heterozygosity (LOH). A preliminary analysis indicating regions of LOH on chromosomes 3,4,8,9,16 and 17 is being correlated with gene expression data collected from the same samples using Affymetrix HG-U95A chips containing ~12,000 characterized genes. The study will be expanded to include expression data using the Affymetrix HG-U133 chips (~ 45,000 probe sets) and SNP data for refining the regions of LOH using the Affymetrix Mapping 10K Array (~10,000 SNPS). In addition, the larger case-case control study mentioned above will be utilized in this expanded analysis. Data collected on gene expression, candidate loci, and somatic allele loss will be integrated via hierarchical clustering of expression data, and correlation of the resulting clusters with variation at candidate susceptibility loci. This information will be used to develop, test, and validate laboratory strategies for pathway models of the cancer/normal cell.

大多数癌症表现为复杂的表型，并通过基因基因和/或基因环境相互作用表现出来。用于研究人类复杂癌症表型的理想范式是原发性肝细胞癌（HCC）。肿瘤中遗传改变的分子研究已将p53鉴定为通常在HCC中改变的肿瘤抑制基因。流行病学研究已经牢固确定了慢性丙型肝炎病毒感染（HBV）和黄曲霉毒素B1（AFB1）的作用，作为环境风险因素。但是，暴露于HBV和AFB1的大多数人不会发展HCC。 遗传分析用于评估基因在确定疾病中描述的途径中的作用。这种方法通过将途径的所有成员包括在内，将基因映射和候选基因座研究融合在一起。每个感兴趣的基因在其附近或附近都被“标记”，以确定调节暴露于AFB1的种群中HCC的风险的遗传因素。 The individual members of each family (GSTA1, GSTM1, GSTM3, GSTP, GSTT1, GST12, EPHX1, EPHX2, GSTA4, GSTT2, GSTZ1, STP, COMT, ESD, DTD, CYP, MGST1) have been tagged with new or published polymorphisms, and their role in HCC risk examined, in a nested case-control 人口。基因座GSTM1，GSTP，GSTT1，EPHX1与HCC风险显示显着相关，而EPHX2基因座与发病年龄有关。当结果按病例的HBV状态进行分层时，GSTM1和GSTT1仅在HBV（+）情况下关联，而GSTP在HBV（ - ）情况下是相关的。这些结果表明，这些基因是用于更详细的功能和遗传分析的候选者。在大型病例对照研究（n = 1000例和1000例对照）中，还将检查15个候选癌敏感性基因座的候选基因变异。 可以从癌症中可遗传性变异和体细胞（肿瘤）变异的联合研究中获得重要的复杂性状分析中重要的遗传信息。使用全基因组简单串联重复多态性（STRP）标记，候选基因座和1,300个单核苷酸多态性（SNP）的集合来检查HCC肿瘤/正常对。正在分析这些数据以识别杂合性损失区域（LOH）。初步分析表明，使用Affymetrix HG-U95A芯片，染色体上LOH的3,4,8,9,16和17与从相同样品收集的基因表达数据相关联，使用了约12,000个特征基因。该研究将扩展到使用Affymetrix HG-U133芯片（〜45,000个探针集）和SNP数据来包括表达数据，并使用Affymetrix映射10K阵列（约10,000个SNP）来完善LOH的区域。此外，上述较大的病例控制研究将在此扩展的分析中使用。 收集的有关基因表达，候选基因座和体细胞等位基因损失的数据将通过表达数据的层次聚类进行集成，以及在候选敏感性基因座时与所得簇的相关性。该信息将用于开发，测试和验证癌症/正常细胞途径模型的实验室策略。