Genetic Epidemiology of Primary Hepatocellular Carcinoma

大多数癌症表现为复杂的表型。复杂的表型通过基因-基因和/或基因-环境相互作用来表现。原发性肝细胞癌（HCC）是研究人类复杂癌症表型的理想范例。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。 遗传分析正被用来评估基因在确定疾病的详细描述的途径中的作用。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。每一个感兴趣的基因是“标签”与多个多态性位点中或附近it. This方法已被应用于识别遗传因素的人群中暴露于肝癌的致癌物质黄曲霉毒素B1（AFB 1）的发展HCC的风险。每个家族的个体成员（GSTA 1、GSTM 1、GSTM 3、GSTP、GSTT 1、GST 12、EPHX 1、EPHX 2）已经用新的或公开的多态性标记。为了评估它们在HCC风险中的作用，在嵌套病例对照人群中对其进行了检查。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序列多态性标记和候选位点对HCC肿瘤/正常对进行检查。观察到等位基因丢失模式是复杂的。为了评估数据中是否存在潜在的遗传模式，使用进化树构建算法来检查数据。该树的分支在等位基因丢失的位置上具有系统的、非重叠的差异，并且观察到不同分支的全基因组等位基因丢失率也具有显著不同的比率。最后，不同的候选基因座风险等位基因分布EPHX 1之间观察到不同的树枝，这表明，包括这样的信息可能是重要的基因发现。 为了补充这一努力，我们开发了rtPCR检测，使我们能够评估肿瘤抑制基因和有丝分裂检查点基因的表达，这些基因可能在显示遗传物质丢失的区域发生改变。在有丝分裂检查点基因中，我们检测了BUB家族的三个成员（BUB 1，BUB 1B和BUB 3），MAD家族的两个成员（MAD 1，MAD 2），SMAD家族的八个成员（SMAD 1-SMAD 7，SMAD 9），以及SIX 1，MPS 1 L1和MAPK 9。在肿瘤抑制基因/癌基因中，我们检测了CDKN家族的8个成员（CDKN 1A、CDKN 1B、CDKN 1C、CDKN 2A、CDKN 2B、CDKN 2C、CDKN 2D和CDKN 3）p53、p63、p73、PTEN、FHIT、TSG 101、BIN 1、ZAC、CTNNB 1、APC、DELC 1、DLC 1、DMBT 1、LAP 18、STST 3、PTPRG、BF 2和MDM 2。目前正在通过层次聚类方法和自组织映射方法分析异常产物的表达和存在模式。

The majority of cancer presents as a complex phenotype. A complex phenotype is manifest through gene-gene, and/or gene-environment interactions. Primary hepatocellular carcinoma (HCC) is an ideal paradigm for the investigation of complex cancer phenotypes in humans. 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. This approach has been applied to identify genetic factors modulating the risk of developing HCC among populations exposed to the hepatocarcinogen aflatoxin B1 (AFB1). The individual members of each family (GSTA1, GSTM1, GSTM3, GSTP, GSTT1, GST12, EPHX1, EPHX2) have been tagged with new or published polymorphisms. To assess their role in HCC risk, they have been 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 genome-wide simple tandem repeat polymorphism markers and candidate loci. Allele loss patterns are observed to be complex. To assess whether underlying genetic patterns existed within the data, evolutionary tree building algorithms were used to examine the data. The branches of the tree had systematic, non-overlapping differences in the location of allele loss and the different branches also were observed to have significantly different rates of genome-wide allele loss rates. Finally, different candidate locus risk allele distributions for EPHX1 were observed among the different tree branches, suggesting that inclusion of such information may be important for gene discovery. To complement this effort, we have developed rtPCR assays that permit us to assess the expression of tumor suppressor genes and mitotic checkpoint genes that might be altered in the regions showing loss of genetic material. Among the mitotic checkpoint genes, we have examined three members of the BUB family (BUB1, BUB1B, AND BUB3), two members of the MAD family (MAD1, MAD2), eight members of the SMAD family (SMAD1-SMAD7, SMAD9), as well SIX1, MPS1L1, and MAPK9. Among the tumor suppressor/oncogenes we have examined eight members of the CDKN family (CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, and CDKN3) p53, p63, p73, PTEN, FHIT, TSG101, BIN1, ZAC, CTNNB1, APC, DELC1, DLC1, DMBT1, LAP18, STST3, PTPRG, BF2, and MDM2. The pattern of expression and presence of aberrant products is currently being analyzed by hierarchical clustering methods and self-organizing map methods.