Molecular Genetic Epidemiology of Primary Hepatocellular

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。研究人类复杂癌症表型的理想范例是原发性肝细胞癌（HCC）。肿瘤遗传改变的分子研究已经确定p53是HCC中常见改变的肿瘤抑制基因。流行病学研究已经确定了慢性B肝炎病毒感染（HBV）和黄曲霉毒素B1（AFB 1）暴露作为环境危险因素的作用。然而，大多数暴露于HBV和AFB 1的个体不会发生HCC。 遗传分析被用来评估基因在确定疾病的明确途径中的作用。这种方法将基因定位和候选基因座研究结合起来，将一条通路的所有成员都作为候选基因。每个感兴趣的基因都在其内部或附近用多个多态性位点“标记”，以确定在暴露于AFB 1的人群中调节发生HCC风险的遗传因素。每个家族（GSTA 1，GSTM 1，GSTM 3，GSTP，GSTT 1，GST 12，EPHX 1，EPHX 2，GSTA 4，GSTT 2，GSTZ 1，STP，COMT，ESD，DTD，ESTZ，MGST 1）的个体成员已被标记新的或已发表的多态性，并在巢式病例对照人群中研究了它们在HCC风险中的作用。GSTM 1、GSTP、GSTT 1、EPHX 1基因座与肝癌发病风险显著相关，EPHX 2基因座与发病年龄显著相关。当结果按HBV状态分层时，GSTM 1和GSTT 1仅在HBV（+）病例中相关，而GSTP在HBV（-）病例中相关。这些结果表明，这些基因是更详细的功能和遗传分析的候选人。 在复杂性状分析中重要的遗传信息可以从癌症的遗传变异和体细胞组织（肿瘤）变异的联合研究中获得。使用全基因组简单串联重复多态性标记和候选基因座的集合检查HCC肿瘤/正常对。最近，对遗传调节剂的研究已经扩大到包括AffytechnologyHuSNP芯片上可用的1,300个SNP。该数据将用于鉴定杂合性缺失（洛）区域。此外，这些信息将与使用含有12，000个已知或特征化基因的Affytelium HG-U95 A芯片收集的相同样品的基因表达数据相关联。 为了评估可能在显示洛的区域中改变的肿瘤抑制基因和有丝分裂检查点基因的表达，已经开发了rtPCR测定法。目前正在通过层次聚类和自组织映射分析异常产物的表达和存在的模式。

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. 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 markers, and candidate loci. More recently the search for genetic modulators has been expanded to include the 1,300 SNPs available on the Affymetrix HuSNP chip. This data will be used to identify regions of loss of heterozygosity (LOH). In addition the information will be correlated with gene expression data, collected for the same samples using the Affymetrix HG-U95A chip containing 12,000 known or characterized genes. To assess the expression of tumor suppressor and mitotic checkpoint genes that might be altered in the regions showing LOH, rtPCR assays have been developed. The pattern of expression and presence of aberrant products is currently being analyzed by hierarchical clustering and self-organizing maps.