Abstract Background Prostate cancer (PCa) diagnosis relies heavily on PSA screening, which suffers from low specificity, leading to unnecessary biopsies and overdiagnosis. Distinguishing PCa from benign prostatic hyperplasia (BPH) remains a significant clinical challenge. Extracellular vesicles (EVs) protect molecular cargo, such as microRNAs (miRNAs), from degradation and reflect the physiological state of their parental cells. Given their stability and accessibility in biological fluids, EV-associated miRNAs represent ideal liquid biopsy candidates to overcome the limitations of current diagnostic markers and improve risk stratification. Aims This study investigated the potential of a specific plasma EV-derived miRNA panel (miR-16, miR-141, miR-10b, miR-373, miR-409, miR-34a, miR-205, miR-145, and miR-550a) to differentiate between healthy controls, BPH, localized PCa (LPCa), and metastatic PCa (MPCa). Methods Plasma EVs were isolated using a precipitation-based method, followed by total RNA extraction. EV-derived miRNA expression profiles were quantified via qRT-PCR. Statistical analyses were performed to compare expression levels across clinical groups and to assess their diagnostic potential. Results Significant differential expression was observed for EV-derived miR-141, miR-10b, and miR-550a. miR-141 was significantly downregulated in BPH and LPCa compared to healthy controls ( p < 0.05). Notably, EV-derived miR-10b and miR-550a levels were significantly lower in the MPCa group compared to BPH. When comparing all PCa cases (LPCa+MPCa) against non-cancerous groups (BPH+Control), EV-derived miR-10b and miR-550a were significantly downregulated, while miR-16 showed upregulation in the cancer cohort. Conclusion Our findings demonstrate that specific plasma EV-derived miRNA signatures can distinguish prostate pathologies and disease stages. These results suggest that EV-derived miR-10b, miR-141, miR-16 and miR-550a hold promise as non-invasive biomarkers for differentiating PCa from BPH, potentially reducing overdiagnosis and informing clinical management.
Yağcı et al. (Fri,) studied this question.