Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer.

ABSTRACT:

Background

Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients 'sera using a multi-omics discovery platform.

Methods

Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan-Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics

SUBMITTER: Kiebish MA 

PROVIDER: S-EPMC6945688 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature