Author:
He Ya-Di,Tao Wen,He Tao,Wang Bang-Yu,Tang Xiu-Mei,Zhang Liang-Ming,Wu Zhen-Quan,Deng Wei-Ming,Zhang Ling-Xiao,Shao Chun-Kui,Zhou Jing,Rong Li-Min,Gao Xin,Li Liao-Yuan
Abstract
AbstractThe aim of this study was to identify a urine extracellular vesicle circular RNA (circRNA) classifier that could detect high-grade prostate cancer (PCa) of Grade Group (GG) 2 or greater. For this purpose, we used RNA sequencing to identify candidate circRNAs from urinary extracellular vesicles from 11 patients with high-grade PCa and 11 case-matched patients with benign prostatic hyperplasia. Using ddPCR in a training cohort (n = 263), we built a urine extracellular vesicle circRNA classifier (Ccirc, containing circPDLIM5, circSCAF8, circPLXDC2, circSCAMP1, and circCCNT2), which was evaluated in two independent cohorts (n = 497, n = 505). Ccirc showed higher accuracy than two standard of care risk calculators (RCs) (PCPT-RC 2.0 and ERSPC-RC) in both the training cohort and the validation cohorts. In all three cohorts, this novel urine extracellular vesicle circRNA classifier plus RCs was statistically more predictive than RCs alone for predicting ≥ GG2 PCa. This assay, which does not require precollection digital rectal examination nor special handling, is repeatable, noninvasive, and can be easily implemented as part of the basic clinical workflow.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Science and Technology Planning Project of Guangdong Province
Guangzhou Municipal Science and Technology Project
Fundamental Research Funds for the Central Universities
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Oncology,Molecular Medicine
Cited by
46 articles.
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