Elevated miR-615-3p Expression Predicts Adverse Clinical Outcome and Promotes Proliferation and Migration of Prostate Cancer Cells.

miR-615-3p has previously been described as up-regulated in prostate cancer (PC) tissue samples compared with nonmalignant controls; however, its prognostic potential and functional role in PC remain largely unknown. In this study, we investigated the clinical and biological relevance of miR-615-3p in PC. The expression of miR-615-3p was measured in PC tissue specimens from 239 men who underwent radical prostatectomy (RP), and it was investigated if miR-615-3p could predict postoperative biochemical recurrence (BCR). These findings were subsequently validated in three independent RP cohorts (n = 222, n = 273, and n = 387) and functional overexpression studies conducted in PC cells (PC3M). High miR-615-3p expression was significantly associated with BCR in four independent PC patient cohorts (P < 0.05, log-rank test). In addition, high miR-615-3p expression was a significant predictor of PC-specific survival in univariate (hazard ratio, 3.75; P < 0.001) and multivariate (hazard ratio, 2.66; P = 0.008) analysis after adjustment for the Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) nomogram in a merged RP cohort (n = 734). Moreover, overexpression of miR-615-3p in PC cells (PC3M) significantly increased cell viability, proliferation, apoptosis, and migration. Together, our results suggest that miR-615-3p is a significant predictor of postoperative BCR and PC-specific survival and has oncogenic functions in PC cells.

A five-microRNA model (pCaP) for predicting prostate cancer aggressiveness using cell-free urine.

Improved biomarkers for prostate cancer (PC) risk stratification are urgently needed. Here, we aimed to develop a novel multimarker model for prediction of biochemical recurrence (BCR) after curatively intended radical prostatectomy (RP), based on minimally invasive sampling of blood and urine. We initially measured the levels of 45 selected miRNAs by RT-qPCR in exosome enriched cell-free urine samples collected prior to RP from 215 PC patients (Cohort 1, training). We trained a novel logistic regression model (pCaP), comprising five urine miRNAs (miR-151a-5p, miR-204-5p, miR-222-3p, miR-23b-3p and miR-331-3p) and serum prostate-specific antigen (PSA), which significantly predicted time to BCR in Cohort 1 (univariate Cox regression analysis: HR = 3.12, p < 0.001). Next, using the same exact numeric cutoff for dichotomization as trained in Cohort 1, we tested and successfully validated the prognostic potential of pCaP in two additional cohorts, including 199 (Cohort 2, HR = 2.24, p = 0.002) and 205 (Cohort 3, HR = 2.15, p = 0.004) RP patients, respectively. pCaP remained a significant predictor of BCR, also after adjustment for pathological T-stage, surgical margin status and Gleason grade group (p < 0.05 in multivariate Cox regression analysis: HR = 2.72, 1.94 and 1.83 for Cohorts 1, 2 and 3, respectively). Additionally, pCaP scores correlated positively with the established clinical risk stratification nomogram CAPRA in all three PC cohorts (Pearson's rho: 0.45, 0.39 and 0.44). Together, our results suggest that the minimally invasive pCaP model could potentially be used in the future to improve PC risk stratification and to guide more personalized treatment decisions. Further clinical validation studies are warranted.

A novel combined miRNA and methylation marker panel (miMe) for prediction of prostate cancer outcome after radical prostatectomy.

Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top-candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training). Using GLMnet, we trained a novel multimarker model (miMe) comprising nine miRNAs and three methylation markers that predicted postoperative biochemical recurrence (BCR) independently of the established clinicopathological CAPRA-S nomogram in Cox multivariate regression analysis in Cohort 1 (HR [95% CI]: 1.53 [1.26-1.84], p < 0.001). This result was successfully validated in two independent RP cohorts (Cohort 2, n = 159: HR [95% CI]: 1.35 [1.06-1.73], p = 0.015. TCGA, n = 350: HR [95% CI]: 1.34 [1.01-1.77], p = 0.04). Notably, in CAPRA-S low-risk patients, a high miMe score was associated with >6 times higher risk of BCR, suggesting that miMe may help identify PC patients at high risk of progression despite favorable clinicopathological factors postsurgery. Finally, miMe was a significant predictor of cancer-specific survival (p = 0.019, log-rank test) in a merged analysis of 357 RP patients. In conclusion, we trained, tested and validated a novel 12-marker panel (miMe) that showed significant independent prognostic value in three RP cohorts. In the future, combining miMe score with existing clinical nomograms may improve PC risk stratification and thus help guide treatment decisions.

Independent Validation of a Diagnostic Noninvasive 3-MicroRNA Ratio Model (uCaP) for Prostate Cancer in Cell-Free Urine.

BACKGROUND: Detection of prostate cancer (PC) based on serum prostate-specific antigen (PSA) testing leads to many unnecessary prostate biopsies, overdiagnosis, and overtreatment of clinically insignificant tumors. Thus, novel and more accurate molecular biomarkers are required. METHODS: Using reverse transcription quantitative PCR, we measured the concentrations of 45 preselected microRNAs (miRNAs) in extracellular vesicle-enriched cell-free urine samples from 4 independent patient cohorts from Spain and Denmark, including 758 patients with clinically localized PC, 289 noncancer controls with benign prostatic hyperplasia (BPH), and 233 patients undergoing initial transrectal ultrasound (TRUS)-guided prostate biopsy owing to PC suspicion (101 with benign and 132 with malignant outcome). Diagnostic potential was assessed by ROC and decision curve analysis. RESULTS: We identified and successfully validated 8 upregulated and 21 downregulated miRNAs in urine from PC patients. Furthermore, we validated a previously identified 3-miRNA diagnostic ratio model, uCaP (miR-222-3p*miR-24-3p/miR-30c-5p). High uCaP scores were distinctive of PC in urine samples from BPH vs PC patients in 3 independent cohorts [area under the curve (AUC) = 0.84, 0.71, 0.72]. Additionally, uCaP predicted TRUS biopsy results with greater accuracy than PSA (AUC uCaP = 0.644; AUC PSA = 0.527) for patients within the diagnostic gray zone (PSA ≤ 10 ng/mL). CONCLUSIONS: We successfully validated a urine-based diagnostic 3-miRNA signature for PC (uCaP) in 3 independent patient cohorts from 2 countries. In the future, the simple and noninvasive uCaP test may be used to help more accurately select patients for prostate biopsy. Prospective clinical validation is warranted.

Evaluation of mupA EVIGENE assay for determination of high-level mupirocin resistance in Staphylococcus aureus.

Mupirocin is widely used to decolonize patients carrying Staphylococcus aureus, especially methicillin-resistant S. aureus (MRSA). The aim of this study was to determine the presence of high-level mupirocin resistance by a new commercially available mupA genotypic diagnostic product, mupA EVIGENE assay (AdvanDx).

Profiling of Circulating microRNAs in Prostate Cancer Reveals Diagnostic Biomarker Potential.

Early detection of prostate cancer (PC) is paramount as localized disease is generally curable, while metastatic PC is generally incurable. There is a need for improved, minimally invasive biomarkers as current diagnostic tools are inaccurate, leading to extensive overtreatment while still missing some clinically significant cancers. Consequently, we profiled the expression levels of 92 selected microRNAs by RT-qPCR in plasma samples from 753 patients, representing multiple stages of PC and non-cancer controls. First, we compared plasma miRNA levels in patients with benign prostatic hyperplasia (BPH) or localized prostate cancer (LPC), versus advanced prostate cancer (APC). We identified several dysregulated microRNAs with a large overlap of 59 up/down-regulated microRNAs between BPH versus APC and LPC versus APC. Besides identifying several novel PC-associated dysregulated microRNAs in plasma, we confirmed the previously reported upregulation of miR-375 and downregulation of miR-146a-5p. Next, by randomly splitting our dataset into a training and test set, we identified and successfully validated a novel four microRNA diagnostic ratio model, termed bCaP (miR-375*miR-33a-5p/miR-16-5p*miR-409-3p). Combined in a model with prostate specific antigen (PSA), digital rectal examination status, and age, bCaP predicted the outcomes of transrectal ultrasound (TRUS)-guided biopsies (negative vs. positive) with greater accuracy than PSA alone (Training: area under the curve (AUC), model = 0.84; AUC, PSA = 0.63. Test set: AUC, model = 0.67; AUC, PSA = 0.56). It may be possible in the future to use this simple and minimally invasive bCaP test in combination with existing clinical parameters for a more accurate selection of patients for prostate biopsy.

Diagnostic and Prognostic MicroRNA Biomarkers for Prostate Cancer in Cell-free Urine.

BACKGROUND: Widespread use of prostate-specific antigen (PSA) testing for prostate cancer (PC) detection has led to extensive overdiagnosis and overtreatment. Urine-based microRNA (miRNA) biomarkers could be useful in PC diagnosis and prognosis. OBJECTIVE: To train and validate urine-based microRNA (miRNA) biomarkers that may assist in PC diagnosis and prognosis. DESIGN, SETTING, AND PARTICIPANTS: We profiled the expression levels of 92 miRNAs via reverse transcriptase-poymerase chain reaction in cell-free urine samples from 29 patients with benign prostatic hyperplasia (BPH) and 215 patients with clinically localized PC (cohort 1). Our findings were validated in an independent cohort of 29 BPH patients and 220 patients with clinically localized PC (cohort 2). RESULTS AND LIMITATIONS: We identified and validated several deregulated miRNAs in urine samples from PC patients. In addition, we trained a novel diagnostic three-miRNA model (miR-222-3p*miR-24-3p/miR-30c-5p) that distinguished BPH and PC patients with an area under the curve (AUC) of 0.95 in cohort 1, and was successfully validated in cohort 2 (AUC 0.89). Furthermore, we trained a novel prognostic three-miRNA model (miR-125b-5p*let-7a-5p/miR-151-5p) that predicted time to biochemical recurrence after radical prostatectomy independently of routine clinicopathological parameters in cohort 1, and was successfully validated in cohort 2. CONCLUSIONS: Future clinical implementation of our novel diagnostic and prognostic three-miRNA signatures could help in primary diagnosis of PC and guide treatment decisions. Further validation studies are warranted. PATIENT SUMMARY: Using two large patient cohorts, we searched for novel prostate cancer biomarkers in urine. We found two new sets of microRNA biomarkers in urine that could accurately predict the presence of prostate cancer and the likelihood of recurrence after prostatectomy. Further studies are needed before an actual clinical test can be developed.