Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:276 |
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| Enthalten in: |
Annals of surgery - 276(2022), 6 vom: 01. Dez., Seite e876-e885 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Nishiwada, Satoshi [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers, Tumor |
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| Anmerkungen: |
Date Completed 10.11.2022 Date Revised 13.12.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1097/SLA.0000000000004993 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM32680319X |
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| 100 | 1 | |a Nishiwada, Satoshi |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
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| 500 | |a Date Completed 10.11.2022 | ||
| 500 | |a Date Revised 13.12.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved. | ||
| 520 | |a OBJECTIVE: We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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) | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 7 | |a MicroRNAs |2 NLM | |
| 650 | 7 | |a Biomarkers, Tumor |2 NLM | |
| 700 | 1 | |a Cui, Ya |e verfasserin |4 aut | |
| 700 | 1 | |a Sho, Masayuki |e verfasserin |4 aut | |
| 700 | 1 | |a Jun, Eunsung |e verfasserin |4 aut | |
| 700 | 1 | |a Akahori, Takahiro |e verfasserin |4 aut | |
| 700 | 1 | |a Nakamura, Kota |e verfasserin |4 aut | |
| 700 | 1 | |a Sonohara, Fuminori |e verfasserin |4 aut | |
| 700 | 1 | |a Yamada, Suguru |e verfasserin |4 aut | |
| 700 | 1 | |a Fujii, Tsutomu |e verfasserin |4 aut | |
| 700 | 1 | |a Han, In Woong |e verfasserin |4 aut | |
| 700 | 1 | |a Tsai, Susan |e verfasserin |4 aut | |
| 700 | 1 | |a Kodera, Yasuhiro |e verfasserin |4 aut | |
| 700 | 1 | |a Park, Joon Oh |e verfasserin |4 aut | |
| 700 | 1 | |a Von Hoff, Daniel |e verfasserin |4 aut | |
| 700 | 1 | |a Kim, Song Cheol |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Goel, Ajay |e verfasserin |4 aut | |
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