URINARY EXOSOME MICRORNA SIGNATURES AS A NONINVASIVE PROGNOSTIC BIOMARKER FOR PROSTATE CANCER

You have accessJournal of UrologyCME1 May 2022MP45-03 URINARY EXOSOME MICRORNA SIGNATURES AS A NONINVASIVE PROGNOSTIC BIOMARKER FOR PROSTATE CANCER Hyeok Jae Kwon, Chang Eil Yoon, Dongho Shin, Sun Shin, Hyong Woo Moon, Hyuk Jin Cho, U-Syn Ha, Sung-Hoo Hong, Ji Youl Lee, Yeun–Jun Chung, Sae Woong Kim, and Yong Hyun Park Hyeok Jae KwonHyeok Jae Kwon More articles by this author , Chang Eil YoonChang Eil Yoon More articles by this author , Dongho ShinDongho Shin More articles by this author , Sun ShinSun Shin More articles by this author , Hyong Woo MoonHyong Woo Moon More articles by this author , Hyuk Jin ChoHyuk Jin Cho More articles by this author , U-Syn HaU-Syn Ha More articles by this author , Sung-Hoo HongSung-Hoo Hong More articles by this author , Ji Youl LeeJi Youl Lee More articles by this author , Yeun–Jun ChungYeun–Jun Chung More articles by this author , Sae Woong KimSae Woong Kim More articles by this author , and Yong Hyun ParkYong Hyun Park More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002611.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The levels of circulating microRNAs (miRNAs) from body fluids can be used as non-invasive prognostic biomarkers in prostate cancer (PCa). This study aimed to assess the utility of urinary exosomal miRNAs as non-invasive prognostic biomarkers for PCa by observing differentially expressed miRNAs between localized and metastatic PCas and exploring their biological implications. METHODS: Forty-two samples from 19 localized and 23 metastatic PCa patients, 70 samples from 56 localized and 14 metastatic PCa patients, and 37 samples from 27 localized and 10 metastatic PCa patients were used as discovery, independent validation of candidate miRNAs, and external model validation sets, respectively. We used a combined dataset from discovery and validation sets for the model construction, and a dataset combining all three sets for the survival analysis. Exosomes were isolated from 5 mL of urine using the ExoQuick-TC exosome precipitation solution. miRNA profiles were examined and validated using the TLDA and TaqMan microRNA Assay. RESULTS: Urinary exosomal miRNA expression profiles of 149 PCas were determined and the miRNAs associated with metastasis were identified: miR-21, miR-16, miR-142-3p, miR-451, and miR-636. When evaluating clinical factors together, miR-21, miR451, miR-636, and PSA level remained significant in the multivariate analysis. Based on them, we developed a “Prostate Cancer Metastasis Risk Scoring (PCa-MRS)” model. The PCa-MRS showed superior stratification power (AUC =0.925) to preoperative PSA or clinical Gleason score (Figure 1). Patients with high scores showed significantly poorer biochemical recurrence-free survival than those with low scores (P =6.53×10-10). CONCLUSIONS: Our results showed the potential of urinary exosomal miRNAs as non-invasive markers for predicting metastasis and prognosis in PCa patients. Source of Funding: This work was supported by grants from National Research Foundation of Korea (2018R1D1A1B07048552, 2017R1E1A1A01074913, and 2019R1A5A2027588) © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e762 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hyeok Jae Kwon More articles by this author Chang Eil Yoon More articles by this author Dongho Shin More articles by this author Sun Shin More articles by this author Hyong Woo Moon More articles by this author Hyuk Jin Cho More articles by this author U-Syn Ha More articles by this author Sung-Hoo Hong More articles by this author Ji Youl Lee More articles by this author Yeun–Jun Chung More articles by this author Sae Woong Kim More articles by this author Yong Hyun Park More articles by this author Expand All Advertisement PDF DownloadLoading ...