Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients with Pancreatic Ductal Adenocarcinoma
- Authors
- Nishiwada, S.[Nishiwada, S.]; Cui, Y.[Cui, Y.]; Sho, M.[Sho, M.]; Jun, E.[Jun, E.]; Akahori, T.[Akahori, T.]; Nakamura, K.[Nakamura, K.]; Sonohara, F.[Sonohara, F.]; Yamada, S.[Yamada, S.]; Fujii, T.[Fujii, T.]; Han, I.W.[Han, I.W.]; Tsai, S.[Tsai, S.]; Kodera, Y.[Kodera, Y.]; Park, J.O.[Park, J.O.]; Von, Hoff D.[Von, Hoff D.]; Kim, S.C.[Kim, S.C.]; Li, W.[Li, W.]; Goel, A.[Goel, A.]
- Issue Date
- Dec-2022
- Publisher
- Wolters Kluwer Health
- Keywords
- exosomal miRNAs; neoadjuvant therapy; pancreatic ductal adenocarcinoma; recurrence prediction biomarkers
- Citation
- Annals of Surgery, v.276, no.6, pp.E876 - E885
- Indexed
- SCIE
SCOPUS
- Journal Title
- Annals of Surgery
- Volume
- 276
- Number
- 6
- Start Page
- E876
- End Page
- E885
- URI
- https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/101151
- DOI
- 10.1097/SLA.0000000000004993
- ISSN
- 0003-4932
- Abstract
- Objective: We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC. Summary of Background Data: Pretreatment risk stratification is essential for offering individualized treatments to patients with PDAC, but predicting recurrence following surgery remains clinically challenging. Methods: We analyzed 210 plasma and serum specimens from 4 cohorts of PDAC patients. Using a discovery cohort (n = 25), we performed genome-wide sequencing to identify candidate exosomal miRNAs (exo-miRNAs). Subsequently, we trained and validated the predictive performance of the exo-miRNAs in two clinical cohorts (training cohort: n = 82, validation cohort: n = 57) without neoadjuvant therapy (NAT), followed by a post-NAT clinical cohort (n = 46) as additional validation. Results: We performed exo-miRNA expression profiling in plasma specimens obtained before any treatment in a discovery cohort. Subsequently we optimized and trained a 6-exo-miRNA risk-prediction model, which robustly discriminated patients with recurrence [area under the curve (AUC): 0.81, 95% confidence interval (CI): 0.70-0.89] and relapse-free survival (RFS, P < 0.01) in the training cohort. The identified exo-miRNA panel was successfully validated in an independent validation cohort (AUC: 0.78, 95% CI: 0.65-0.88, RFS: P < 0.01), where it exhibited comparable performance in the post-NAT cohort (AUC: 0.72, 95% CI: 0.57-0.85, RFS: P < 0.01) and emerged as an independent predictor for RFS (hazard ratio: 2.84, 95% CI: 1.30-6.20). Conclusions: We identified a novel, noninvasive exo-miRNA signature that robustly predicts recurrence following surgery in patients with PDAC; highlighting its potential clinical impact for optimized patient selection and improved individualized treatment strategies. © 2022 Lippincott Williams and Wilkins. All rights reserved.
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