Molecular Genetic Epidemiology of Leading U.S. Cancers

成功地对35个候选基因座进行了基因分型分析。DNA是从全血样本中分离出来的。单核苷酸多态性（SNP）基因型采用同源MassEXTENDTM引物扩展法测定（Sequenom, San Diego， CA; www.sequenom.com）。Sequenom是一种高通量、多重SNP基因分型化学方法，采用基质辅助激光解吸/电离飞行时间质谱法（MALDI-TOF）区分等位基因特异性延伸产物。每个SNP位点可以用2-4 ng的DNA检测。使用定制引物（Applied Biosystems, Foster City， CA）对短串联重复多态性片段（STRPs）进行PCR扩增。PCR产物使用ABI 3730 DNA分析仪（Applied Biosystems, Foster City， CA）检测和分离，使用GeneMapper 3.0软件（Applied Biosystems, Foster City， CA）进行等位基因的大小测定和调用。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，并在基于已有生物学文献的途径中达到高潮。我们已经证明，通过将整个系统作为药物反应的标记，可以克服评估单个遗传变异所固有的局限性，每个遗传变异对临床结果的影响都很小。这一过程的关键是潜在的候选基因方法，从已有的生物学文献中已知的变异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。我们将通路分析应用于他莫昔芬代谢的遗传网络，显示了辨别两种药物暴露差异的能力。

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.