| Summary: | Prostate Cancer (PCa) overdiagnosis and overtreatment, as a consequence of the limited specificity of current detection and prognostication methods, remains a major challenge in clinical practice. Therefore, development and validation of new molecular biomarkers amenable of detecting clinically significant disease is crucial. MicroRNAs (miRNA) deregulation is common in cancer, constituting potential non-invasive biomarkers for PCa detection and prognostication. Herein, we evaluated the screening and prognostic biomarker potential of two onco-microRNAs (miR-182-5p and miR-375-3p) in liquid biopsies (plasma) of PCa patients with clinically localized disease undergoing curative-intent treatment. A first cohort of 98 PCa and 15 normal prostates were used to assess PCa-specificity of miR-182-5p in tissues. A cohort composed of PCa 252 patients and 52 asymptomatic controls allowed for assessment of diagnostic and prognostic value in plasmas. After RNA extraction from tissue and plasma samples, cDNA synthesis specific for miRNAs was performed followed by measurement of miR-182-5p and miR-375-3p relative expression by RT-qPCR, using U6 snRNA gene as reference. MiR-182-5p was significantly overexpressed in PCa tissues (p < 0.0001) and in plasma of PCa patients (p = 0.0020), compared to respective controls. Moreover, miR-182-5p expression identified PCa with AUC = 0.81 (95% CI: 0.725–0.892, p = 0.0001) in tissue and with 77% specificity and 99% NPV (AUC = 0.64, 95% CI: 0.561–0.709, p = 0.0021) in plasma. Both circulating miR-182-5p and miR-375-3p levels associated with more advanced pathologic stage and the former was significantly higher in patients that developed metastasis (p = 0.0145). Indeed, at the time of diagnosis, circulating miR-375-3p levels predicted which patients would develop metastasis, with almost 50% sensitivity, 76% specificity, and a NPV of 89% (AUC = 0.62, 95% CI: 0.529–0.713, p = 0.0149). We conclude that these two circulating miRNAs might be clinical useful as non-invasive biomarkers for detection and prediction of metastasis development at the diagnosis together with clinical variables used in routine practice.
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