Although radical prostatectomy is associated with good long-term oncological outcomes, approximately 30% of patients present biochemical recurrence, whereupon salvage treatments are required. Identification of novel molecular biomarkers to predict cancer behavior is clinically important. Here, we developed a novel miRNA-based prognostic model for patients who underwent radical prostatectomy.

Total RNA was extracted from 300 μL of serum using the 3DGene RNA Extraction Reagent (Toray Industries, Inc.). The comprehensive miRNA profiles of patients with bladder cancer were analyzed using the 3D-Gene miRNA Labelling kit and the 3D-Gene Human miRNA.　We retrospectively investigated the clinical records of 295 patients who underwent radical prostatectomy between 2009 and 2017. We randomly assigned these cases into training or validation sets. The prognostic model was constructed using Fisher linear discriminant analysis in the training set, and we evaluated its performance in the validation set. To normalize the signals among the microarrays tested, three preselected internal control miRNAs (miR-149-3p, miR-2861, and miR-4463) were used.

Overall, 72 patients had biochemical recurrence. A prediction model was constructed using a combination of three miRNAs (miR-3147, miR-4513, and miR-4728-5p) and two pathological factors (pathological T stage and Gleason score). In the validation set, the predictive performance of the model was confirmed to be accurate (AUC, 0.80; sensitivity, 0.78; specificity, 0.76) (Figure 1a). Additionally, Kaplan–Meier analysis revealed that the patients with a low prediction index had significantly longer recurrence-free survival than those with a high index (P<0.001) (Figure 1b).

We established a prognostic model using serum miRNAs that can be used to stratify postoperative patients with PCa as having a high risk or a low risk of BCR. This model may be helpful for physicians in determining a follow-up strategy for patients after RP.