Urinary DNA Methylation Biomarkers for Noninvasive Prediction of Aggressive Disease in Patients with Prostate Cancer on Active Surveillance

Purpose: Patients with prostate cancer on active surveillance are monitored by repeat prostate specific antigen measurements, digital rectal examinations and prostate biopsies. A subset of patients on active surveillance will later reclassify with disease progression, prompting definitive treatment. To minimize the risk of under treating such patients on active surveillance minimally invasive tests are urgently needed incorporating biomarkers to identify patients who will reclassify. Materials and Methods: We assessed post-digital rectal examination urine samples of patients on active surveillance for select DNA methylation biomarkers that were previously investigated in radical prostatectomy specimens and shown to correlate with an increasing risk of prostate cancer. Post-digital rectal examination urine samples were prospectively collected from 153 men on active surveillance who were diagnosed with Gleason score 6 disease. Urinary sediment DNA was analyzed for 8 DNA methylation biomarkers by multiplex MethyLight assay. Correlative analyses were performed on gene methylation and clinicopathological variables to test the ability to predict patient risk reclassification. Results: Using backward logistic regression a 4-gene methylation classifier panel (APC, CRIP3, GSTP1 and HOXD8) was identified. The classifier panel was able to predict patient reclassification (OR 2.559, 95% CI 1.257e5.212). We observed this panel to be an independent and superior predictor compared to current clinical predictors such as prostate specific antigen at diagnosis or the percent of tumor positive cores in the initial biopsy. Conclusion: We report that a urine based classifier panel of 4 methylation biomarkers predicts disease progression in patients on active surveillance. Once validated in independent active surveillance cohorts, these promising biomarkers may help establish a less invasive method to monitor patients on active surveillance programs.