부산대학교 도서관

Abstract Background Prostate cancer is an extremely heterogeneous disease. Despite being clinically similar, some tumours are more likely to recur after surgery compared to others. Distinguishing those that need adjuvant or salvage radiotherapy will improve patient outcomes. The goal of this study was to identify circulating microRNA that could independently predict prostate cancer patient risk stratification after radical prostatectomy. Methods Seventy-eight prostate cancer patients were recruited at the Odette Cancer Centre in Sunnybrook Health Sciences Centre. All patients had previously undergone radical prostatectomy. Blood samples were collected simultaneously for PSA testing and miRNA analysis using NanoString nCounter technology. Of the 78 samples, 75 had acceptable miRNA quantity and quality. Patients were stratified into high- and low-risk categories based on Gleason score, pathological T stage, surgical margin status, and diagnostic PSA: patients with Gleason ≥ 8; pT3a and positive margin; pT3b and any margin; or diagnostic PSA > 20 µg/mL were classified as high-risk (n = 44) and all other patients were classified as low-risk (n = 31). Results Using our patient dataset, we identified a four-miRNA signature (miR-17, miR-20a, miR-20b, miR-106a) that can distinguish high- and low-risk patients, in addition to their pathological tumour stage. High expression of these miRNAs is associated with shorter time to biochemical recurrence in the TCGA dataset. These miRNAs confer an aggressive phenotype upon overexpression in vitro. Conclusions This proof-of-principle report highlights the potential of circulating miRNAs to independently predict risk stratification of prostate cancer patients after radical prostatectomy.