Prediction of Grade Reclassification of Prostate Cancer Patients on Active Surveillance through the Combination of a Three-miRNA Signature and Selected Clinical Variables

Abstract

Active surveillance (AS) has evolved as a strategy alternative to radical treatments for very low risk and low-risk prostate cancer (PCa). However, current criteria for selecting AS patients are still suboptimal. Here, we performed an unprecedented analysis of the circulating miRNome to investigate whether specific miRNAs associated with disease reclassification can provide risk refinement to standard clinicopathological features for improving patient selection. The global miRNA expression profiles were assessed in plasma samples prospectively collected at baseline from 386 patients on AS included in three independent mono-institutional cohorts (training, testing and validation sets). A three-miRNA signature (miR-511-5p, miR-598-3p and miR-199a-5p) was found to predict reclassification in all patient cohorts (training set: AUC 0.74, 95% CI 0.60–0.87, testing set: AUC 0.65, 95% CI 0.51–0.80, validation set: AUC 0.68, 95% CI 0.56–0.80). Importantly, the addition of the three-miRNA signature improved the performance of the clinical model including clinicopathological variables only (AUC 0.70, 95% CI 0.61–0.78 vs. 0.76, 95% CI 0.68–0.84). Overall, we trained, tested and validated a three-miRNA signature which, combined with selected clinicopathological variables, may represent a promising biomarker to improve on currently available clinicopathological risk stratification tools for a better selection of truly indolent PCa patients suitable for AS.

Pan-Cancer Analysis Reveals the Relation between TRMT112 and Tumor Microenvironment

“…Hence, it is crucial to further explore whether TRMT112 promotes tumorigenesis and development by interacting with SART1. As oncogenes or tumor suppressor genes [ 42 , 43 ], noncoding RNAs, such as lncRNA, miRNA, and tRNA, participate in the regulation of cell proliferation [ 44 , 45 ], apoptosis [ 46 ], metastasis [ 47 , 48 ], differentiation [ 49 ], and other biological processes. GO enrichment and KEGG analyses illustrated that TRMT112 might be implicated in tumorigenesis and development through modulating RNA metabolism and transport pathways.…”

MiRNA biomarkers in cancers of the male reproductive system: Are we approaching clinical application?

“…16 After assessment of global miRNA profiles in plasma samples prospectively collected from patients in AS, a 3-miRNA signature (miR-511-5p, miR-598-3p and miR-199a-5p) was found to predict GS reclassification at the first repeated biopsy in all independent cohorts (training set: AUC 0.74, testing set: AUC 0.65, validation set: AUC 0.68), and the addition of this signature improved the performance of the clinicopathological model (including age, PSA density [PSAD] and maximum percentage of tumour in core biopsies) (AUC 0.70 vs. AUC 0.76). 17 Using ddPCR, the assessment of miR-26b-5p and miR-98-5p in plasma samples achieved a remarkable AUC of 0.94 in discriminating PCa from BPH, compared to an AUC of 0.5 for PSA. 18 Using the same technology, plasma miR-375-3p, miR-182-5p and PSA discriminated PCa from BPH with AUC of 0.674, which was improved to 0.694 when selecting only patients with PSA < 10 μg/L, compared with AUC of 0.504 for PSA alone.…”

“…The 4‐miRNA diagnostic ratio model ‘bCaP’ (miR‐375*miR‐33a‐5p/miR‐16‐5p*miR‐409‐3p) in plasma combined with PSA, digital‐rectal examination (DRE) and age also predicted histology of biopsies with greater accuracy than PSA alone (AUC model 0.67, AUC PSA 0.56) 16 . After assessment of global miRNA profiles in plasma samples prospectively collected from patients in AS, a 3‐miRNA signature (miR‐511‐5p, miR‐598‐3p and miR‐199a‐5p) was found to predict GS reclassification at the first repeated biopsy in all independent cohorts (training set: AUC 0.74, testing set: AUC 0.65, validation set: AUC 0.68), and the addition of this signature improved the performance of the clinicopathological model (including age, PSA density [PSAD] and maximum percentage of tumour in core biopsies) (AUC 0.70 vs. AUC 0.76) 17 …”

Current understanding of prostate cancer biomarkers

“…В проспективном исследовании P. Gandellini и соавт. показано, что у пациентов с РПЖ низкого риска уровень экспрессии miR-511-5p, -598-3p и -199a-5p в сочетании с клинико-патологическими переменными является перспективным инструментом стратификации риска и может служить критерием отбора пациентов для активного наблюдения [32].…”