The MRI of the prostate is the gold standard for the detection of clinically significant prostate cancer (csPCa). Nonetheless, MRI still misses around 11% of clinically significant disease. The aim was to comprehensively integrate tissue and circulating microRNA profiling, MRI biomarkers and clinical data to implement PCa early detection. In this prospective cohort study, 76 biopsy naïve patients underwent MRI and MRI directed biopsy. A sentinel sample of 15 patients was selected for a pilot molecular analysis. Weighted gene coexpression network analysis was applied to identify the microRNAs drivers of csPCa. MicroRNA-target gene interaction maps were constructed, and enrichment analysis performed. The ANOVA on ranks test and ROC analysis were performed for statistics. Disease status was associated with the underexpression of the miRNA profiled; a correlation was found with ADC (r = -0.51, p = 0.02) and normalized ADC values (r = -0.64, p = 0.002). The overexpression of miRNAs from plasma was associated with csPCa (r = 0.72; p = 0.02), and with PI-RADS assessment score (r = 0.73; p = 0.02); a linear correlation was found with biomarkers of diffusion and perfusion. Among the 800 profiled microRNA, eleven were identified as correlating with PCa, among which miR-548a-3p, miR-138-5p and miR-520d-3p were confirmed using the RT-qPCR approach on an additional cohort of ten subjects. ROC analysis showed an accuracy of >90%. Provided an additional validation set of the identified miRNAs on a larger cohort, we propose a diagnostic paradigm shift that sees molecular data and MRI biomarkers as the prebiopsy triage of patients at risk for PCa. This approach will allow for accurate patient allocation to biopsy, and for stratification into risk group categories, reducing overdiagnosis and overtreatment.
Biomedicines. 2021 Oct 14*** epublish ***
Valeria Panebianco, Paola Paci, Martina Pecoraro, Federica Conte, Giorgia Carnicelli, Zein Mersini Besharat, Giuseppina Catanzaro, Elena Splendiani, Alessandro Sciarra, Lorenzo Farina, Carlo Catalano, Elisabetta Ferretti
Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, 00161 Rome, Italy., Department of Computer, Control and Management Engineering, Sapienza University, 00161 Rome, Italy., Institute for Systems Analysis and Computer Science "Antonio Ruberti", 00185 Rome, Italy., Department of Experimental Medicine, Sapienza University, Policlinico Umberto I, 00161 Rome, Italy., Department of Molecular Medicine, Sapienza University, Policlinico Umberto I, 00161 Rome, Italy., Department of Maternal-Infant and Urological Sciences, Sapienza University, Policlinico Umberto I, 00161 Rome, Italy.