Germline Determinants of Prostate Cancer Evolution

摘要 前列腺癌是男性最常见的非皮肤癌，也是第二常见的病因。 男性死于癌症的风险。它是一种正在增长的高发病率、高死亡率、高发病率和高成本的癌症。 在我们老龄化的人口中越来越频繁。临床上，大多数前列腺癌表现为无痛，并且 不太可能在一个人的一生中显著影响他的健康。尽管如此，相当数量的 前列腺癌虽然是局部性的，但有很大的转移潜力。一旦这些生物殖民 在遥远的地方，它们几乎都是致命的。目前的临床风险分层护理标准包括 血清前列腺特异性抗原(PSA)测定、直肠指检和活检。虽然这些都是有益的， 约30%-40%的男性治疗过多或过少。因此，前列腺癌的一个中心问题仍然存在。 了解局限性前列腺癌侵袭性的这种戏剧性差异。我们假设 生殖系基因组决定了局限性前列腺癌的临床和分子进化 功能。强劲的初步数据支持这一观点。前列腺癌是最易遗传的实体癌症。它显示了 在祖先之间有很强的变异性，特定的遗传特征可以预测发病率和疾病风险 攻击性。我们将用三个互补的目标来检验我们的假设。目的#1量化生殖系--体细胞 使用转录组广泛关联研究(TWAS)和途径-体细胞相互作用分析的相互作用。 目标2然后确定基于祖先的生殖系-体细胞相互作用。最后，目标3将评估 通过开发靶向DNA来研究种系-体细胞相互作用对临床风险预测的普适性 在大的患者队列中测序面板和评估生物标记物的潜力。为了实现这些目标，我们将 利用加州大学洛杉矶分校的公开可用的数据集和生物库，链接到已建立的和 新的生物信息学方法。总而言之，这些目标提供了三个互补的战略，以量化 局限性前列腺癌的特异性临床和分子进化特征受特异性 胚系多态性。

Abstract Prostate cancer is the most commonly diagnosed non-skin cancer in men, and the second most common cause of cancer death for men. It is a high-incidence, high-fatality, high-morbidity and high-cost cancer that is growing increasingly frequent in our aging population. Clinically, the majority of prostate cancers present as indolent, and are unlikely to significantly influence a man’s health over his lifetime. Nevertheless, a significant number of prostate tumors are diagnosed while localized but have substantial metastatic potential. Once these colonize distant sites, they become almost uniformly lethal. Current standard of care for clinical risk-stratification involves serum abundance of prostate specific antigen (PSA), a digital rectal exam and biopsy. While these are beneficial, ~30-40% of men are over- or under-treated. Therefore, a central problem in prostate cancer remains understanding this dramatic variability in the aggressiveness of localized prostate cancers. We hypothesize that the clinical and molecular evolution of localized prostate cancers are shaped by germline genomic features. Strong preliminary data support this idea. Prostate cancer is the most heritable solid cancer. It shows strong variability across ancestries, and specific genetic features predict both risk of incidence and disease aggression. We will test our hypothesis with three complementary aims. Aim #1 quantifies germline-somatic interactions using transcriptome-wide association studies (TWAS) and pathway-somatic interaction analysis. Aim #2 then identifies ancestry-based germline-somatic interactions. Finally Aim #3 will assess the generalizability of germline-somatic interactions for clinical risk prediction by developing a targeted DNA- sequencing panel and evaluating biomarker potential in large patient cohorts. To achieve these aims, we will leverage publicly available datasets as well as biobanking repositories at UCLA, linked to both established and novel bioinformatics methods. Together, these aims provide three complementary strategies to quantify how the specific clinical and molecular evolutionary features of localized prostate cancer are influenced by specific germline polymorphisms.