Vollständiger Abstract
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Importance Early liver metastasis (early-LiM) after pancreatectomy represents an aggressive biological phenotype of pancreatic ductal adenocarcinoma (PDAC) and is associated with markedly poor survival. Reliable preoperative biomarkers to identify occult hepatic micrometastasis remain lacking. Objective To develop and externally validate a circulating exosomal microRNA (exo-miRNA)–based machine learning model for preoperative detection of occult early-LiM in PDAC. Design, Setting, and Participants This multicenter retrospective case-control study included 3 phases: genome-wide discovery using exo-miRNA sequencing (discovery cohort), model development (training cohort), and independent external validation (2 validation cohorts). The study took place at 4 medical centers in China, Japan, and South Korea. A total of 372 patients were enrolled between 2011 and 2024. Data were analyzed from July 2024 to November 2025. Exposures Circulating plasma-derived exosomal miRNA expression profiles. Main Outcomes and Measures The primary outcome was early-LiM, defined as liver recurrence within 6 months after curative-intent resection. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and survival outcomes were assessed using Kaplan-Meier analysis. Results Among 372 patients with PDAC (median [IQR] age, 67 [59-73] years; 229 [61.6%] male and 143 [38.4%] female; median follow-up among survivors, 969 days),early-LiM was associated with significantly worse overall survival compared with other recurrence patterns (median OS, 9.1 months vs 26.6-31.8 months; log-rank P < .001). A 7-exo-miRNA extreme gradient boosting model demonstrated discrimination in the training cohort (AUC, 0.899; 95% CI, 0.822-0.976) and maintained performance in external testing cohorts (AUC, 0.876; 95% CI, 0.846-0.951 and AUC, 0.862; 95% CI, 0.744-0.981). The exo-miRNA panel score remained an independent identifier of early-LiM in multivariable analysis (odds ratio, 26.49; 95% CI, 18.45-55.28; P < .001) and stratified overall survival (log-rank P < .001). Decision curve analysis suggested improved net clinical benefit compared with conventional clinicopathologic variables. Conclusion and Relevance In this multicenter study, a circulating exo-miRNA–based machine learning model enabled preoperative detection of occult early liver metastasis risk in PDAC. These findings support the potential of exosomal biomarkers to inform biology-guided treatment sequencing and warrant prospective validation.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Takayuki Noma, Jingyang Yin, Junfeng Zhang, Caiming Xu, Mitsuro Kanda, Song Cheol Kim, Yuji Morine, Mitsuo Shimada, Vincent Chung, Ali H. Zaidi, Daniel Von Hoff, Huaizhi Wang, Ajay Goel
- Quelle
- JAMA Surgery
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 2168-6254
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Zitierfähiger Nachweis
Takayuki Noma, Jingyang Yin, Junfeng Zhang, Caiming Xu, Mitsuro Kanda, Song Cheol Kim, Yuji Morine, Mitsuo Shimada, Vincent Chung, Ali H. Zaidi, Daniel Von Hoff, Huaizhi Wang, Ajay Goel (2026). An Exosomal Signature for Preoperative Detection of Occult Liver Metastasis in Pancreatic Cancer. JAMA Surgery. https://doi.org/10.1001/jamasurg.2026.3840