Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence.

ABSTRACT: We report here numerous novel genes and multiple new signatures which robustly predict prostate cancer (PC) recurrence. We extracted 696 differentially expressed genes relative to a reported PC signature from the TCGA dataset (n = 492) and built a 15-gene signature (SigMuc1NW) using Elastic-net with 10-fold cross-validation through analyzing their expressions at 1.5 standard deviation/SD below and 2 SD above a population mean. SigMuc1NW predicts biochemical recurrence (BCR) following surgery with 56.4% sensitivity, 72.6% specificity, and 63.24 median months disease free (MMDF) (P = 1.12e-12). The prediction accuracy is improved with the use of SigMuc1NW's cutpoint (P = 3e-15) and is further enhanced (sensitivity 67%, specificity 75.7%, MMDF 45.2, P = 0) when all 15 genes were analyzed thro

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC6120243 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature