Molecular Genetic Epidemiology of Leading U.S. Cancers

对35个候选基因座进行了基因分型。从全血样本中分离出DNA。单核苷酸多态(SNP)基因分型采用均相MassEXTENDTM分析方法(Sequenom，San Diego，CA；www.equenom.com)。Sequenom是一种高通量、多重SNP基因分型化学方法，它使用基质辅助激光解吸/电离飞行时间质谱仪(MALDI-TOF)区分等位基因特异性延伸产物。每个SNP基因座可以用2-4 ng的DNA进行检测。使用定制的引物(应用生物系统公司，福斯特市，CA)进行短串联重复序列多态片段(STRP)的PCR扩增，用ABI 3730 DNA分析仪(应用生物系统公司，加利福尼亚州福斯特市)检测和分离PCR产物，并使用GeneMapper 3.0软件(应用生物系统公司，加利福尼亚州福斯特市)进行等位基因大小和呼叫。我们同时评估了多个基因变体之间的相关性，将它们视为一个复合系统，并在基于先前存在的生物学文献的途径中达到顶峰。我们已经证明，通过将整个系统视为药物反应的标记，可以克服评估单个遗传变异的固有限制，每个遗传变异对临床结果都有轻微影响。对这一过程至关重要的是潜在的候选基因方法，从先前存在的生物学文献中已知的变体提供了一个定性框架，在此基础上对实际数据进行定量建模。我们对他莫昔芬代谢的遗传网络的路径分析已经显示了区分两种药物暴露之间的差异的能力。

Genotyping assays were successfully carried out for 35 candidate loci. DNA was isolated from samples of whole blood. Single Necleotide polymorphism (SNP)genotypes were determined using homogeneous MassEXTENDTM assays with primer extension (Sequenom, San Diego, CA; www.sequenom.com). Sequenom is a high-throughput, multiplex SNP genotyping chemistry, which employs matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF)distinguish between the allele-specific extension products. Each SNP locus could be assayed with 2-4 ng of DNA. PCR amplification of short tandem repeat polymorphic fragments (STRPs) was performed using custom primers (Applied Biosystems, Foster City, CA) PCR products were detected and separated with an ABI 3730 DNA Analyzer (Applied Biosystems, Foster City, CA) and allele sizing and calling was carried out using GeneMapper 3.0 software (Applied Biosystems, Foster City, CA). We have evaluated correlations between variants of multiple genes simultaneously, viewing them as a composite system, and culminating in a pathway based on the pre-existing biological literature. We have shown that by treating the entire system as a marker of drug response, the limitations inherent in evaluating individual genetic variants, each conferring a minor effect on clinical outcome, can be overcome. Critical to this process is the underlying candidate gene approach, with variants known from pre-existing biological literature offering a qualitative framework on which to quantitatively model actual data. Our application of pathway analysis to the genetic network underlying tamoxifen metabolism has shown the ability to discern differences between two drug exposures.