Mitochondria, MicroRNA, and Metabolites in Predicting Aggressive Prostate Cancer

项目总结（项目四）

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.