epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer

Abstract

Purpose Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine. Patients and Methods Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set. Results Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy. Conclusion epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

Development of a multivariable risk model integrating urinary cell DNA methylation and cell‐free RNA data for the detection of significant prostate cancer

“…ExoMeth was able to correctly predict the presence of significant prostate cancer on biopsy with an AUC of 0.89, representing a significant uplift when compared to other published tests (AUCs for Gs ≥ 7: PUR = 0.77, 23 ProCUrE = 0.73, 14 ExoDX Prostate IntelliScore = 0.77, 13 SelectMDX = 0.78, 12 epiCaPture AUC = 0.73 [Gs ≥4 + 3] 22 ). Furthermore, ExoMeth resulted in accurate predictions even when serum PSA levels alone were inaccurate; where patients with a raised PSA but negative biopsy result possessed similar ExoMeth scores as clinically benign men, while still able to discriminate between Gleason grades (Figure 4).…”

“…Our results show an improved diagnostic marker can be produced from the synergistic relationship of information derived from different urine fractions in men suspected to have prostate cancer. The methylation of six previously identified genes 22 was quantified via methylation‐specific qPCR, while the transcript levels of 167 cf‐RNAs were quantified using NanoString technology. The final model integrating this information with serum PSA levels was deemed ExoMeth.…”

“…It is becoming apparent from published data that urine can contain a wealth of useful cancer biomarkers within RNA, DNA, cellfree DNA, DNA methylation, and proteins. 14,22,23,39,40 However, the analyses presented here are, to the author's knowledge, the first attempt to integrate such biomarker information within the same samples for the detection of prostate cancer before biopsy. There has recently been reported that a combination of miRNA and methylation markers can be used to predict outcome following radical prostatectomy.…”

“…Urine samples were processed according to the Movember GAP1 standard operating procedure (Supporting Information Methods). Hypermethylation at the 5′‐regulatory regions of six genes ( GSTP1, SFRP2, IGFBP3, IGFBP7, APC , and PTSG2 ) in urinary cell‐pellet DNA was assessed using a quantitative methylation‐specific polymerase chain reaction (qPCR) as described by O'Reilly et al 22 cf‐RNA was isolated and quantified from urinary extracellular vesicles using NanoString technology, with 167 gene‐probes (Table S1), as described in Connell et al, 23 with the modification that NanoString data were normalized according to NanoString guidelines using NanoString internal positive controls, and log 2 transformed. Clinical variables considered were serum PSA, age at sample collection, DRE impression, and urine volume collected.…”

“…The prime aim of the GAP1 initiative was to develop a multimodal urine biomarker panel for the discrimination of disease state. The authors have previously published analyses from two of the GAP1 studies that measured differing molecular aspects within urine; epiCaPture assayed hypermethylation of urinary cell DNA, 22 and PUR assessed transcript levels in cell‐free extracellular vesicle messenger RNA (cf‐RNA) using NanoString 23 . Both of these tests were able to discriminate some level of clinically significant disease and exhibited differing characteristics; where epiCaPture was well suited to detecting the highest grade disease (Gs ≥8), PUR was better matched to the deconvolution of lower‐risk and indolent disease, as detailed by its prognostic ability in active surveillance use.…”