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Purpose: A 2-gene, urine based molecular test that combines mRNA biomarkers with clinical factors can risk stratify patients for clinically significant prostate cancer. To ensure the generalizability of assay results we optimized and validated the clinical model for men with serum prostate specific antigen less than 10 ng/ml who were undergoing initial prostate biopsy., Materials and Methods: Urine samples were collected from 1,955 men from The Netherlands, France and Germany prior to an initial prostate biopsy and study subjects were divided into training and validation cohorts. Urinary HOXC6 and DLX1 mRNA levels were quantified and RNA results were then combined with other risk factors in a clinical model optimized to detect ISUP (International Society of Urological Pathology) Grade Group 2 or greater prostate cancer in men with prostate specific antigen less than 10 ng/ml. Results in the validation cohort were compared with the PCPTRC (Prostate Cancer Prevention Trial Risk Calculator), version 2.0., Results: The optimal clinical model included urinary HOXC6 and DLX1 mRNA levels, patient age, digital rectal examination and prostate specific antigen density (serum prostate specific antigen/prostate volume). In the 715 validation cohort subjects with prostate specific antigen less than 10 ng/ml the AUC was 0.82 with 89% sensitivity, 53% specificity and 95% negative predictive value. The PCPTRC AUC was 0.70. The full validation cohort of 916 men including all prostate specific antigen levels yielded an AUC of 0.85 with 93% sensitivity, 47% specificity and 95% negative predictive value. The PCPTRC AUC was 0.76., Conclusions: The 2-gene based urine assay, which is optimized for biopsy naïve patients with serum prostate specific antigen less than 10 ng/ml, demonstrated high sensitivity and negative predictive value to detect clinically significant prostate cancer. These data support using the test to help guide initial prostate biopsy decisions.

Background: To reduce overdiagnosis and overtreatment, a test is urgently needed to detect clinically significant prostate cancer (PCa)., Objective: To develop a multimodal model, incorporating previously identified messenger RNA (mRNA) biomarkers and traditional risk factors that could be used to identify patients with high-grade PCa (Gleason score ≥7) on prostate biopsy., Design, Setting, and Participants: In two prospective multicenter studies, urine was collected for mRNA profiling after digital rectal examination (DRE) and prior to prostate biopsy. The multimodal risk score was developed on a first cohort (n=519) and subsequently validated clinically in an independent cohort (n=386)., Outcome Measurements and Statistical Analysis: The mRNA levels were measured using reverse transcription quantitative polymerase chain reaction. Logistic regression was used to model patient risk and combine risk factors. Models were compared using the area under the curve (AUC) of the receiver operating characteristic, and clinical utility was evaluated with a decision curve analysis (DCA)., Results and Limitations: HOXC6 and DLX1 mRNA levels were shown to be good predictors for the detection of high-grade PCa. The multimodal approach reached an overall AUC of 0.90 (95% confidence interval [CI], 0.85-0.95) in the validation cohort (AUC 0.86 in the training cohort), with the mRNA signature, prostate-specific antigen (PSA) density, and previous cancer-negative prostate biopsies as the strongest, most significant components, in addition to nonsignificant model contributions of PSA, age, and family history. For another model, which included DRE as an additional risk factor, an AUC of 0.86 (95% CI, 0.80-0.92) was obtained (AUC 0.90 in the training cohort). Both models were successfully validated, with no significant change in AUC in the validation cohort, and DCA indicated a strong net benefit and the best reduction in unnecessary biopsies compared with other clinical decision-making tools, such as the Prostate Cancer Prevention Trial risk calculator and the PCA3 assay., Conclusions: The risk score based on the mRNA liquid biopsy assay combined with traditional clinical risk factors identified men at risk of harboring high-grade PCa and resulted in a better patient risk stratification compared with current methods in clinical practice. Therefore, the risk score could reduce the number of unnecessary prostate biopsies., Patient Summary: This study evaluated a novel urine-based assay that could be used as a noninvasive diagnostic aid for high-grade prostate cancer (PCa). When results of this assay are combined with traditional clinical risk factors, risk stratification for high-grade PCa and biopsy decision making are improved., (Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Purpose: Early detection of prostate cancer can increase the curative success rate for prostate cancer. We studied the diagnostic usefulness of TMPRSS2-ERG fusion transcripts as well as the combination of prostate cancer antigen 3 (PCA3) RNA and TMPRSS2-ERG fusion transcripts in urinary sediments after digital rectal examination (DRE)., Experimental Design: A total of 78 men with prostate cancer-positive biopsies and 30 men with prostate cancer-negative biopsies were included in this study. After DRE, the first voided urine was collected, and urinary sediments were obtained. We used semiquantitative reverse transcription-PCR (RT-PCR) analysis followed by Southern blot hybridization with a radiolabeled probe for the detection TMPRSS2-ERG fusion transcripts in these urinary sediments. A quantitative RT-PCR assay for PCA3 was used to determine the PCA3 score in the same sediments., Results: TMPRSS2-ERG fusion transcripts can be detected in the urine after DRE with a sensitivity of 37%. In this cohort of patients, the PCA3-based assay had a sensitivity of 62%. When both markers were combined, the sensitivity increased to 73%. Especially in the cohort of men with persistently elevated serum prostate-specific antigen levels and history of negative biopsies, the high positive predictive value of 94% of TMPRSS2-ERG fusion transcripts could give a better indication which patients require repeat biopsies., Conclusion: In this report, we used for the first time the combination of the prostate cancer-specific biomarkers TMPRSS2-ERG and PCA3, which significantly improves the sensitivity for prostate cancer diagnosis.