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Simple Summary Active surveillance (AS) has evolved as an alternative to radical treatment for potentially indolent prostate cancer. However, current selection criteria for entering AS are suboptimal, and a significant percentage of patients discontinue AS because of disease reclassification. Hence, there is an unmet need for novel biomarkers for the accurate identification of high-risk PCa and the unequivocal classification of indolent disease. Circulating biomarkers, including microRNAs identified through liquid biopsies, represent a valuable approach to improve on currently available clinicopathological risk-stratification tools. In an attempt to identify specific microRNA signatures as potential circulating biomarkers, the authors performed an unprecedented analysis of the global microRNA profile in plasma samples from AS patients and identified and validated a three-microRNA signature able to predict patient reclassification. The addition of the three-microRNA signature was able to improve the performance of currently available clinicopathological variables, thus showing potential for the refinement of AS patients’ selection. Abstract Active surveillance (AS) has evolved as a strategy alternative to radical treatments for very low risk and low-risk prostate cancer (PCa). However, current criteria for selecting AS patients are still suboptimal. Here, we performed an unprecedented analysis of the circulating miRNome to investigate whether specific miRNAs associated with disease reclassification can provide risk refinement to standard clinicopathological features for improving patient selection. The global miRNA expression profiles were assessed in plasma samples prospectively collected at baseline from 386 patients on AS included in three independent mono-institutional cohorts (training, testing and validation sets). A three-miRNA signature (miR-511-5p, miR-598-3p and miR-199a-5p) was found to predict reclassification in all patient cohorts (training set: AUC 0.74, 95% CI 0.60–0.87, testing set: AUC 0.65, 95% CI 0.51–0.80, validation set: AUC 0.68, 95% CI 0.56–0.80). Importantly, the addition of the three-miRNA signature improved the performance of the clinical model including clinicopathological variables only (AUC 0.70, 95% CI 0.61–0.78 vs. 0.76, 95% CI 0.68–0.84). Overall, we trained, tested and validated a three-miRNA signature which, combined with selected clinicopathological variables, may represent a promising biomarker to improve on currently available clinicopathological risk stratification tools for a better selection of truly indolent PCa patients suitable for AS.

Speckle-type POZ (pox virus and zinc finger protein) protein (SPOP) is the most commonly mutated gene in prostate cancer (PCa). Recent evidence reports a role of SPOP in DNA damage response (DDR), indicating a possible impact of SPOP deregulation on PCa radiosensitivity. This study aimed to define the role of SPOP deregulation (by gene mutation or knockdown) as a radiosensitizing factor in PCa preclinical models. To express WT or mutant (Y87N, K129E and F133V) SPOP, DU145 and PC-3 cells were transfected with pMCV6 vectors. Sensitivity profiles were assessed using clonogenic assay and immunofluorescent staining of &gamma, H2AX and RAD51 foci. SCID xenografts were treated with 5 Gy single dose irradiation using an image-guided small animal irradiator. siRNA and miRNA mimics were used to silence SPOP or express the SPOP negative regulator miR-145, respectively. SPOP deregulation, by either gene mutation or knockdown, consistently enhanced the radiation response of PCa models by impairing DDR, as indicated by transcriptome analysis and functionally confirmed by decreased RAD51 foci. SPOP silencing also resulted in a significant downregulation of RAD51 and CHK1 expression, consistent with the impairment of homologous recombination. Our results indicate that SPOP deregulation plays a radiosensitizing role in PCa by impairing DDR via downregulation of RAD51 and CHK1.