Mitochondria, MicroRNA, and Metabolites in Predicting Aggressive Prostate Cancer

项目总结(项目4) 由于常规的PSA筛查，前列腺癌在早期阶段越来越多地被发现，导致5年的 存活率接近100%。然而，许多筛查发现的前列腺癌是懒惰的，但约有90% 的患有局限性前列腺癌的男性接受了积极的前期治疗，这些治疗通常会导致显着的 发病率。相反，一些患有潜在侵袭性前列腺癌的患者将从早期受益 干预可能会选择推迟治疗。这种治疗过度和治疗不足的两难境地尤其突出 急性适用于临床定义为中等风险的患者。仅有临床变量不足以 准确区分侵袭性疾病和惰性疾病。迫切需要生物标记物来细化风险 分层。在这个项目中，我们将集中在三个有前途的生物标记物上：线粒体dna、microRNA和 代谢物。这些多功能和相互关联的分子与肥胖有关，肥胖是一种既定的风险 导致侵袭性前列腺癌的因素。利用美国两个最大的前列腺癌患者队列， 该项目将对这些生物标记物与临床变量进行综合分析，以更准确地定义 侵袭性前列腺癌。我们将在诊断时使用通过比较极端表型获得的知识 (高危前列腺癌与低风险前列腺癌)以更好地对临床定义的患者进行分层 中等风险特征。有四个具体目标：1)确定新的遗传易感因素 确诊时患有侵袭性前列腺癌。我们将使用三阶段设计：发现、内部复制和 外部验证。这一目标的患者总数将为4200人(3000名白人和1200名非洲人-- 美国人[AA])。我们已经设计了大约20,000个单核苷酸多态(SNPs)的定制阵列， 其中包括miRNA调控途径中的SNPs，mtDNA中的SNPs，以及肥胖和前列腺癌- 易患单核苷酸多态性。2)确定新的中间生物标记，包括mtDNA拷贝数 外周血白细胞DNA、循环miRNAs和循环代谢产物作为侵袭性的预测因子 确诊时患有前列腺癌。我们将再次使用三阶段设计。3)检验高血压病患者预后价值 在特殊患者群体中验证的生物标记物，包括GS 7患者，接受 前列腺摘除或放射治疗，以及参加MD Anderson积极监测研究的特殊人群。 4)构建包括流行病学危险因素、临床变量、 以及这个项目中的生物标记物。我们将改进临床变量来预测GS患者的预后 7例和接受前列腺切除术或放射治疗的局部性患者。我们将比较预测的准确性 我们的诺模图与现有的仅基于临床变量的诺模图。

PROJECT SUMMARY (Project 4) Prostate cancer is increasingly detected at early stages due to routine PSA screening, leading to a 5-year survival rate of nearly 100%. However, many screening-detected prostate cancer are indolent, yet about 90% of men with localized prostate cancer receive upfront aggressive treatments that often cause significant morbidity. Conversely, some patients with potentially aggressive prostate cancer who would benefit from early intervention may choose to delay treatment. This dilemma of overtreatment and undertreatment is particularly acute for patients with clinically defined intermediate risk. Clinical variables alone are not sufficient to accurately differentiate aggressive and indolent diseases. Biomarkers are urgently needed to refine risk stratification. In this project, we will focus on three promising biomarkers: mitochondrial DNA, microRNA, and metabolites. These multi-functional and interconnected molecules are related to obesity, an established risk factor to aggressive prostate cancer. Leveraging two of the largest prostate cancer patient cohorts in the U.S., this project will perform integrative analyses of these biomarkers with clinical variables to more precisely define aggressive prostate cancer. We will use knowledge gained from comparing extreme phenotypes at diagnosis (high-risk prostate cancer versus low-risk prostate cancer) to better stratify patients with clinically defined intermediate risk profiles. There are four specific aims: 1) To identify novel genetic susceptibility factors for aggressive prostate cancer at diagnosis. We will use a three-phase design: discovery, internal replication, and external validation. The total number of patients in this aim will be 4,200 (3,000 whites and 1,200 African- Americans [AA]). We have designed a custom array of about 20,000 single-nucleotide polymorphisms (SNPs), which include SNPs in miRNA regulatory pathways, SNPs in mtDNA, and obesity- and prostate cancer- predisposing SNPs. 2) To identify novel intermediate biomarkers, including the mtDNA copy number in peripheral blood leukocyte DNA, circulating miRNAs, and circulating metabolites as predictors of aggressive prostate cancer at diagnosis. We will again use a three-phase design. 3) To test the prognostic value of validated biomarkers in special patient populations, including GS 7 patients, localized patients receiving prostatectomy or radiotherapy, and a special population enrolled in an MD Anderson active surveillance study. 4) To construct multivariate prognostic nomograms that include epidemiological risk factors, clinical variables, and biomarkers from this project. We will refine clinical variables in predicting the prognosis in patients with GS of 7 and in localized patients receiving prostatectomy or radiotherapy. We will compare the predictive accuracy of our nomograms with existing ones that are based solely on clinical variables.