Molecular Genetic Epidemiology of Leading U.S. Cancers

对35个候选位点进行了基因分型。分离DNA 从全血样本中。单核苷酸多态性（SNP）基因型测定 使用具有引物延伸的均相MassEXTENDTM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， 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位点可以是 用2-4 ng DNA测定。短串联重复序列多态性片段的PCR扩增 使用定制引物（Applied Biosystems，Foster City，CA）进行STRP。 用ABI 3730 DNA分析仪（Applied Biosystems，Foster City， CA），并使用GeneMapper 3.0软件（Applied Inc. Biosystems，Foster City，CA）。我们已经评估了多个变量之间的相关性， 基因，将它们视为一个复合系统，并最终形成一个基于 已经存在的生物学文献。我们已经证明，通过将整个系统视为 药物反应的标志物，评估个体遗传变异的固有局限性， 每一种对临床结果的影响都很小。对这一进程至关重要 是潜在的候选基因方法，从预先存在的生物学已知的变体 文献提供了一个定性的框架，在此基础上对实际数据进行定量建模。我们 将途径分析应用于他莫昔芬代谢的遗传网络， 显示出辨别两种药物暴露之间差异的能力。

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.