Genetic Predictors of Prostate Cancer Survival

项目摘要/摘要 尽管大多数被诊断患有前列腺癌的男性不会死于这种疾病，但前列腺癌仍然是 美国男性癌症死亡的第二大原因。在筛查前列腺癌的同时 减少死于疾病，这是以不必要的活组织检查为代价的，因为没有证据表明 癌症和其他惰性癌症的治疗会导致不必要的不良事件。因此，在那里 是对改进前列腺癌筛查工具的需求尚未得到满足。为了满足这一需求，我们以前已经 开发了一种四激肽释放酶生物标志物面板，现已商业化，可作为反射测试，用于在 最初的PSA筛查；发现四种激肽释放酶模型改善了预测，在任何诊断之前 前列腺癌，其中男性可能死于前列腺癌；并确定了与生存时间相关的SNPs 确诊后，独立于已知的预后因素。结合这些SNPs和四个激肽释放酶小组 进一步提高我们识别有死于前列腺癌风险的男性的能力。基于这些发现， 我们在这里提出了一种生殖系基因组方法来识别有死于前列腺癌风险的男性。通过 利用基因组分析中最新的计算进展，我们将采取以基因为中心的方法 识别基因受基因控制的转录改变和/或功能性编码突变 影响前列腺癌患者的生存时间。利用这些基因和已知的前列腺癌遗传风险因素 癌症和四个激肽释放酶小组，我们将建立和测试旨在识别男性临床风险的模型 重大前列腺癌，以便更好地在活检前的筛查背景下对男性进行分层。具体来说， 我们将：1)识别基因控制的表达水平变化和/或罕见的编码变体 改变死于前列腺癌的风险；2)确定这些基因在疾病进展的哪个阶段(S) 改变起作用；以及3)改进我们的4-激肽释放酶生物标志物对致命前列腺癌的预测 纳入遗传数据。这将通过进行转录组范围的关联研究来实现 (Twas)前列腺特异性模型和一组注释良好的队列中的整个外显子组测序研究 前列腺癌确诊后有较长的随访时间。这些目标的成功实现将使 在前列腺癌诊断前对男性进行更好的风险分层。我们预计这些发现将对 筛查背景，使更准确地识别死于前列腺癌的高风险男性 在接下来的二十年里，由于早期发现的好处，从而减少了前列腺癌的死亡 避免不必要的活组织检查和不必要的惰性癌症治疗。此外，这些 这些发现将有助于理解致命性前列腺癌的生物学，因为我们预计这些发现将 准确定位在前列腺癌进展中发挥重要作用的新基因和新途径。

Project Summary / Abstract Even though most men diagnosed with prostate cancer will not die of the disease, prostate cancer is still the second leading cause of cancer death among men in the United States. While screening for prostate cancer reduces death from disease, this comes at the price of both unnecessary biopsies that reveal no evidence of cancer and treatment of otherwise indolent cancer resulting in unnecessary adverse events. Therefore, there is an unmet need for improved screening tools for prostate cancer. To address this need, we have previously developed a four-kallikrein biomarker panel that is now commercially available as a reflex test for use after an initial PSA screening; found that the four kallikrein model improves the prediction, prior to any diagnosis of prostate cancer, of which men may die of prostate cancer; and identified SNPs associated with survival time after diagnosis, independent of known prognostic factors. Combining these SNPs and the four kallikrein panel improves our ability to identify men at risk of dying from prostate cancer even further. Based on these findings, we propose here a germline genomic approach to identify men at risk of dying from prostate cancer. By leveraging recent computational advances in genomic analysis, we will take a gene-centered approach to identify genes for which genetically controlled transcriptional alterations and/or functional coding mutations influence survival time in prostate cancer. Using these genes, along with known genetic risk factors for prostate cancer and the four kallikrein panel, we will build and test models designed to identify men at risk for clinically significant prostate cancer in order to better stratify men in the screening context prior to biopsy. Specifically, we will: 1) Identify genes for which genetically controlled expression level changes and/or rare coding variants alter the risk of dying from prostate cancer; 2) Determine at what stage(s) of disease progression these genetic changes operate; and 3) Improve our 4-kallikrein biomarker predictor of lethal prostate cancer through incorporation of genetic data. This will be achieved by conducting both a transcriptome-wide association study (TWAS) with prostate specific models and a whole exome sequencing study in a set of well-annotated cohorts with long follow-up time after prostate cancer diagnosis. Successful completion of these aims will enable better risk stratification of men prior to prostate cancer diagnosis. We envision these findings being useful in the screening context, enabling more precise identification of men at high risk of dying from prostate cancer in the next two decades, thereby reducing death from prostate cancer due to the benefits of early detection while avoiding unnecessary biopsies and unneeded treatment of otherwise indolent cancers. Furthermore, these findings will be useful in understanding the biology of lethal prostate cancer as we anticipate these findings will pinpoint new genes and pathways that play important roles in prostate cancer progression.