sábado, 2 de marzo de 2019

Combining urinary DNA methylation and cell-free microRNA biomarkers for improved monitoring of prostate cancer patients on active surveillance. - PubMed - NCBI

2019 Feb 15. pii: S1078-1439(19)30052-3. doi: 10.1016/j.urolonc.2019.01.031. [Epub ahead of print]

Combining urinary DNA methylation and cell-free microRNA biomarkers for improved monitoring of prostate cancer patients on active surveillance.

Zhao F1, Vesprini D2, Liu RSC1, Olkhov-Mitsel E1, Klotz LH2, Loblaw A2, Liu SK2, Bapat B3.

Author information

Abstract

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.