[Show abstract][Hide abstract] ABSTRACT: An important challenge in prostate cancer research is to develop effective predictors of tumor recurrence following surgery to determine whether immediate adjuvant therapy is warranted. To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed, paraffin-embedded radical prostatectomy specimens with known long-term outcomes to perform DASL expression profiling with a custom panel that we designed of 522 prostate cancer-relevant genes. We identified a panel of 10 protein-coding genes and two miRNA genes (RAD23B, FBP1, TNFRSF1A, CCNG2, NOTCH3, ETV1, BID, SIM2, LETMD1, ANXA1, miR-519d, and miR-647) that could be used to separate patients with and without biochemical recurrence (P < 0.001), as well as for the subset of 42 Gleason score 7 patients (P < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of biochemical recurrence for all cases (P = 0.013) and for a subset of 19 Gleason score 7 cases (P = 0.010), both of which were adjusted for relevant clinical information including T-stage, prostate-specific antigen, and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason score 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens.