Genetic profiling in PCPT: prostate cancer risk, PSA levels, and chemoprevention

PCPT 中的基因分析：前列腺癌风险、PSA 水平和化学预防

基本信息

批准号：
7696635
负责人：
ELIZABETH A. PLATZ
金额：
$ 64.1万
依托单位：
WAKE FOREST UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-07-01 至 2012-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7696635
关键词：
Address Adult Affect Age Alleles Area Under Curve Biopsy Case-Control Studies Chemoprevention Clinical Data Detection Diagnosis Diagnostic Disease Double-Blind Method European Family history of Finasteride Future Genetic Genetic Risk Genotype Gleason Grade for Prostate Cancer Goals Incidence Individual Joints Logistic Regressions Logistics Malignant neoplasm of prostate Measures Modeling Odds Ratio PSA level PSA screening Performance Phase Placebo Control Placebos Population Population Study Prostate Prostate Cancer Prevention Trial Race Randomized Receiver Operating Characteristics Reporting Research Personnel Risk Risk Reduction Sampling Screening for Prostate Cancer Screening procedure Staging Stratification Testing Upper arm Variant Work base cancer diagnosis cancer risk cohort design double-blind placebo controlled trial follow-up genetic profiling genetic variant genome wide association study high risk men improved interest men men&apos s group mortality prevent prospective prostate cancer prevention public health relevance statistics

项目摘要

DESCRIPTION (provided by applicant): More than a dozen SNPs have been found to be associated with prostate cancer (PCa) risk by genome-wide association studies (GWAS). These reported PCa risk associated SNPs, if not driven by PSA detection bias or not completely correlated with PSA, could be used to improve PSA and other existing clinical variables in predicting positive prostate biopsy (i.e. PCa). These two important questions, however, cannot be addressed by most PCa case-control studies because some cases were diagnosed on the basis of elevated PSA levels. Only studies such as the Prostate Cancer Prevention Trial (PCPT) where men at the end of the trial were biopsied regardless of PSA levels can be used to dissect these two questions. The overall hypothesis of the study is that multiple genetic variants, when combined, can be used to predict men at increased risk for PCa. Specifically, we hypothesize that 1) a subset of genetic variants are associated with PCa risk and are not solely due to PSA detection bias, 2) these genetic variants, when combined, are strongly associated with PCa risk, 3) genetic variants can supplement PSA and other existing clinical variables to improve the predictive performance for PCa and aggressive PCa, and 4) the chemoprevention effect of finasteride is different among men with different genetic risks and the reduction in PCa diagnosis by finasteride is larger for men with higher genetic risk. To test these hypotheses, we will use data and samples from the PCPT study, a phase III randomized, double-blind, placebo-controlled trial of finasteride in the prevention of prostate cancer. We have three specific aims. Aim 1 is to test whether reported prostate cancer risk associated variants from GWAS are associated with PCa risk, free of PSA detection bias. Aim 2 is to estimate the joint predictive performance for prostate cancer diagnosis, overall PCa and aggressive PCa, using genetic variants as well as PSA and other existing clinical variables. Aim 3 is to assess the differential chemoprevention effect of finasteride on prostate cancer diagnosis among men with higher or lower genetic risk for PCa. Results from this study may potentially benefit millions men. Men at highest risk for PCa could be identified at an early age for intensive screening and chemoprevention such as finasteride. Genetic variants could also be used in combination with PSA and other existing clinical variables to considerably improve their predictive accuracy for positive prostate biopsy. PUBLIC HEALTH RELEVANCE: Dozens of prostate cancer risk associated variants, when combined, could be used to identify men at highest risk for prostate cancer. Such men could be identified at an early age for intensive screening and chemoprevention. Prostate cancer risk associated variants could also be used in combination with PSA and other existing clinical variables to considerably improve their predictive accuracy for positive prostate biopsy. 1

描述（由申请人提供）：全基因组关联研究 (GWAS) 发现十多个 SNP 与前列腺癌 (PCa) 风险相关。这些报告的 PCa 风险相关 SNP，如果不是由 PSA 检测偏差驱动或与 PSA 不完全相关，则可用于改善 PSA 和其他现有的临床变量，以预测阳性前列腺活检（即 PCa）。然而，大多数 PCa 病例对照研究无法解决这两个重要问题，因为有些病例是根据 PSA 水平升高来诊断的。只有像前列腺癌预防试验 (PCPT) 这样的研究，无论 PSA 水平如何，在试验结束时对男性进行活检，才能剖析这两个问题。该研究的总体假设是，多种遗传变异结合起来可用于预测男性患前列腺癌的风险增加。具体来说，我们假设 1) 一部分遗传变异与 PCa 风险相关，而不仅仅是由于 PSA 检测偏差，2) 这些遗传变异组合后，与 PCa 风险密切相关，3) 遗传变异可以补充 PSA和其他现有的临床变量，以提高 PCa 和侵袭性 PCa 的预测性能，4) 非那雄胺的化学预防效果在具有不同遗传风险的男性中是不同的，并且非那雄胺对男性 PCa 诊断的减少更大具有较高的遗传风险。为了检验这些假设，我们将使用 PCPT 研究的数据和样本，这是一项非那雄胺预防前列腺癌的 III 期随机、双盲、安慰剂对照试验。我们有三个具体目标。目标 1 是测试 GWAS 报告的前列腺癌风险相关变异是否与 PCa 风险相关，且不存在 PSA 检测偏差。目标 2 是使用遗传变异以及 PSA 和其他现有临床变量来评估前列腺癌诊断、整体 PCa 和侵袭性 PCa 的联合预测性能。目标 3 是评估非那雄胺对 PCa 遗传风险较高或较低的男性前列腺癌诊断的差异化学预防作用。这项研究的结果可能会使数百万男性受益。前列腺癌风险最高的男性可以在很小的时候就被发现，进行强化筛查和非那雄胺等化学预防。遗传变异还可以与 PSA 和其他现有的临床变量结合使用，以显着提高前列腺活检阳性的预测准确性。公共卫生相关性：数十种前列腺癌风险相关变异组合起来，可用于识别前列腺癌风险最高的男性。这些男性可以在很小的时候就被识别出来，进行强化筛查和化学预防。前列腺癌风险相关变异还可以与 PSA 和其他现有临床变量结合使用，以显着提高前列腺活检阳性的预测准确性。 1