Detailed Information

Cited 6 time in webofscience Cited 4 time in scopus
Metadata Downloads

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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Medicine > Department of Medicine > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher HAN, IN WOONG photo

HAN, IN WOONG
Medicine (Medicine)
Read more

Altmetrics

Total Views & Downloads

BROWSE