Abstract
BackgroundProstate 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.MethodsSeventy-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).ResultsUsing 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.ConclusionsThis proof-of-principle report highlights the potential of circulating miRNAs to independently predict risk stratification of prostate cancer patients after radical prostatectomy.
Highlights
IntroductionSome tumours are more likely to recur after surgery compared to others
Prostate cancer is an extremely heterogeneous disease
MicroRNA profiling The primary objective of this study was to identify circulating miRNAs in the post-radical prostatectomy setting that could be used to independently predict risk stratification. To identify such miRNAs, of 78 patients, 75 samples had acceptable miRNA quality and quantity. We stratified these 75 patients into high-risk (n = 44) and low-risk (n = 31) categories based on their surgical pathology (i.e. Gleason score, pathological T stage, and margin status) and diagnostic prostate-specific antigen (PSA) (Fig. 1)
Summary
Some tumours are more likely to recur after surgery compared to others Distinguishing those that need adjuvant or salvage radiotherapy will improve patient outcomes. Despite possessing similar clinicopathological features, some prostate cancer patients are at high risk of developing local and/or distant recurrence and succumbing to their disease, whereas many others. It uses surgical tissue to predict disease aggressiveness and the probability of progression after radical prostatectomy This test is very valuable to guide treatment decisions, it cannot be used to monitor treatment response and disease progression over time, as samples are taken from a single timepoint. There is a significant clinical need to find non-invasive biomarkers to identify patients at a high risk of recurrence, monitor their disease progression and treatment response, and optimize their personalized treatment regimens. There is recent evidence that liquid biopsies (biomarkers found in patient biofluids, i.e. blood and urine) are likely to be more representative of the whole tumour’s genomic landscape compared to tumour sampling [13, 14]
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