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Patients with clinically localized, high-risk prostate cancer are often treated with surgery, but exhibit variable prognosis requiring long-term monitoring. An ongoing challenge for such patients is developing optimal strategies and biomarkers capable of differentiating between men at risk of early recurrence (3 years) that will benefit from adjuvant therapies and men at risk of late recurrence (5 years) who will benefit from long-term monitoring and/or salvage therapies.DNA methylation changes for 12 genes associated with disease progression were analyzed in 453 prostate tumors. A 4-gene prognostic model (4-G model) for biochemical recurrence (BCR) was derived utilizing LASSO from Cohort 1 (n = 254) and validated in Cohort 2 (n = 199). Subsequently, the 4-G model was evaluated for its association with salvage radiotherapy (RT) and/or hormone therapy, and the additive potential to CAPRA-S to develop an integrative gene model was assessed.The 4-G model was significantly associated with BCR in both cohorts (chi-squared analysis P≤ 0.004) and specifically, with late recurrence at 5+ years (P0.001, Cohort 1; P= 0.028, Cohort 2). Multivariable Cox proportional regression analysis identified the 4-G model as significantly associated with salvage RT or hormone therapy in Cohort 1 (hazard ratio (HR) 1.64, 95% confidence interval (CI) 1.29-2.10, P0.001) and further validated in Cohort 2 (HR 1.63, 95% CI 1.18-2.25, P0.001). The integrative model outperformed prostate-specific antigen and the 4-G model alone for predicting BCR and was associated with patients who received hormone therapy 3+ years postsurgery.We have identified and validated a novel integrative gene model as an independent prognosticator of BCR and demonstrated its association with late BCR. These patients require more long-term postsurgical monitoring and could be spared the comorbidities of adjuvant therapies.

Purpose Prostate cancer (CaP) patients with low-grade tumors are enrolled in active surveillance (AS) programs and monitored with digital rectal exams (DREs), prostate-specific antigen (PSA) tests, and periodic invasive biopsies. Patients are “reclassified” with higher-risk disease if they show signs of disease progression. However, AS patients who will reclassify cannot be easily identified upfront and suffer morbidities associated with biopsy. Biomarkers derived from noninvasively obtained specimens such as serum or urine samples are promising alternatives to monitor patients with clinically insignificant cancer. Previously, we have characterized and validated a urinary DNA methylation panel and a serum miRNA panel for the prediction of patient reclassification in 2 independent AS cohorts. In this exploratory study, we have investigated cell-free miRNAs in the urinary supernatant combined with urinary DNA methylation markers to form an integrative panel for prediction of AS patient reclassification. Methods Post-DRE urine was collected from 103 CaP patients on active surveillance. Urinary sediment DNA methylation levels of selected genes were previously analyzed using qPCR-based MethyLight assay. Using qRT-PCR, we analyzed the urinary supernatants for relative quantities of 10 miRNAs previously shown to be associated with AS reclassification. Logistic regression and Receiver Operating Characteristics curve analyses were performed to assess the predictive ability of miRNAs and DNA methylation biomarkers. Results We identified a 3-marker panel, consisting of miR-24, miR-30c and CRIP3 methylation, that was significant for prediction of patient reclassification (Odds ratio = 2.166, 95% confidence interval = 1.22–3.847) with a negative predictive value of 90.9%. Our 3-marker panel also demonstrated additive value to PSA for prediction of patient reclassification (c-statistic = 0.717, ROC bootstrapped 1000 iteration P = 0.041). Conclusion A urinary integrated panel of methylation and miRNA markers is a promising approach to identify AS patients at risk for reclassification. Our 3-marker panel, with its high negative predictive value, would be beneficial to identify and preclude AS patients with truly indolent cancer and to personalize monitoring strategies for AS patients.