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。对肿瘤遗传改变的分子研究已经证实，P53是一种肿瘤抑制基因，在肝细胞癌中通常会改变。流行病学研究已经确定慢性乙肝病毒感染(乙肝病毒)和黄曲霉毒素B1(AFB1)暴露是环境风险因素。然而，大多数暴露在乙肝病毒和黄曲霉毒素B受体1下的人不会患上肝癌。 基因分析正被用来评估基因在确定疾病的过程中所起的作用。这种方法融合了基因作图和候选基因座研究，将一条路径的所有成员都作为候选。每个感兴趣的基因都被标记了多个多态位点，在其内部或附近，以确定在暴露于AFB1的人群中调节发生肝癌风险的遗传因素。在嵌套病例对照人群中，每个家族的个体成员(GSTA1、GSTM1、GSTM3、GSTP、GSTT1、GST12、EPHX1、EPHX2、GSTA4、GSTT2、GSTZ1、STP、COMT、ESD、DTD、CYP、MGST1)都被标记了新的或已公布的多态，并研究了它们在肝癌风险中的作用。GSTM1、GSTP、GSTT1、EPHX1基因座与肝癌风险显著相关，EPHX2基因座与发病年龄相关。当结果按患者的乙肝病毒状态分层时，GSTM1和GSTT1仅在乙肝病毒(+)病例中相关，而GSTP在乙肝病毒(-)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基因。 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。使用一组全基因组的简单串联重复序列多态标记和候选基因座来检测肝癌肿瘤/正常配对。最近，对遗传调节器的搜索已经扩大到包括Affymetrix HuSNP芯片上的1300个SNP。这些数据将被用来识别杂合性缺失(LOH)区域。此外，这些信息将与使用Affymetrix HG-U95A芯片收集的相同样本的基因表达数据相关联，该芯片包含12,000个已知或表征的基因。 为了评估可能改变的肿瘤抑制基因和有丝分裂检查点基因在LOH区域的表达，建立了RT-PCR检测方法。异常产物的表达和存在的模式目前正在通过层级聚类和自组织映射进行分析。

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.