Satoshi Nishiwada1, Ya Cui, Masayuki Sho, Eunsung Jun, Takahiro Akahori, Kota Nakamura, Fuminori Sonohara, Suguru Yamada, Tsutomu Fujii, In Woong Han, Susan Tsai, Yasuhiro Kodera, Joon Oh Park, Daniel Von Hoff, Song Cheol Kim, Wei Li, Ajay Goel. 1. Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA, USA Department of Surgery, Nara Medical University, Nara, Japan Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX, USA Department of Biological Chemistry, University of California, Irvine, CA, USA Department of Convergence Medicine and Division of Hepato-Biliary and Pancreatic Surgery, Department of Surgery, University of Ulsan College of Medicine, Asan Institute for Life Sciences, AMIST, Asan Medical Center, Seoul, Korea Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan Department of Surgery and Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan Division of Hepato-Biliary Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea Pancreatic Cancer Program, Department of Surgery, The Medical College of Wisconsin, Milwaukee, WI, USA Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea Translational Genomics Research Institute, Phoenix, AZ, USA Division of Hepato-Biliary and Pancreatic Surgery, Department of Surgery, University of Ulsan College of Medicine, Asan Biomedical Engineering Research Center, AMIST, Asan Medical Center, Seoul, Korea.
Abstract
OBJECTIVE: We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC. SUMMARY BACKGROUND DATA: Pre-treatment risk stratification is essential for offering individualized treatments to patients with pancreatic ductal adenocarcinoma (PDAC), but predicting recurrence following surgery remains clinically challenging. METHODS: We analyzed 210 plasma and serum specimens from four 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 (AUC: 0.81, 95% 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 (HR: 2.84, 95% CI: 1.30-6.20). CONCLUSIONS: We identified a novel, non-invasive exosomal 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.
OBJECTIVE: We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC. SUMMARY BACKGROUND DATA: Pre-treatment risk stratification is essential for offering individualized treatments to patients with pancreatic ductal adenocarcinoma (PDAC), but predicting recurrence following surgery remains clinically challenging. METHODS: We analyzed 210 plasma and serum specimens from four 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 (AUC: 0.81, 95% 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 (HR: 2.84, 95% CI: 1.30-6.20). CONCLUSIONS: We identified a novel, non-invasive exosomal 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.
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