A four-group urine risk classifier for predicting outcomes in patients with prostate cancer

Objectives To develop a risk classifier using urine-derived extracellular vesicle (EV)-RNA capable of providing diagnostic information on disease status prior to biopsy, and prognostic information for men on active surveillance (AS). Patients and Methods Post-digital rectal examination urine-derived EV-RNA expression profiles (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based continuation ratio model was built to generate four prostate urine risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation. Results Each PUR signature was significantly associated with its corresponding clinical category (P < 0.001). PUR-4 status predicted the presence of clinically significant intermediate- or high-risk disease (area under the curve = 0.77, 95% confidence interval [CI] 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n = 87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (interquartile range hazard ratio [HR] 2.86, 95% CI 1.83-4.47; P < 0.001). PUR-4, when used continuously, dichotomized patient groups with differential progression rates of 10% and 60% 5 years after urine collection (HR 8.23, 95% CI 3.26-20.81; P < 0.001). Conclusion Urine-derived EV-RNA can provide diagnostic information on aggressive prostate cancer prior to biopsy, and prognostic information for men on AS. PUR represents a new and versatile biomarker that could result in substantial alterations to current treatment of patients with prostate cancer.