ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
This article is part of the Research TopicFormation and Remodeling of Immunological Niches in Tumors: Organ-Specific Mechanisms and Inflammatory Parallels: Volume IIView all 18 articles
Organ-Specific Role of Neutrophil Extracellular Traps in Shaping the Postoperative Thrombo-Inflammatory Niche in Pancreatic Ductal Adenocarcinoma: A Multi-Model Machine Learning and Mechanistic Study
Provisionally accepted
- 1Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China
- 2Tianjin First Central Hospital, Tianjin, China
- 3Massachusetts General Hospital Cancer Center, Boston, United States
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: Neutrophil extracellular traps (NETs) play a crucial role in thrombosis formation and tumor progression. However, the association between NETs and portal vein thrombosis (PVT) is not well understood. Methods: We retrospectively and prospectively developed and validated a predictive model for postoperative PVT following radical surgery for pancreatic ductal adenocarcinoma (PDAC) from Jan. 2011 to Dec. 2022 and Jan. 2023 to Dec. 2023. 30 clinicopathological variables, including the novel biomarker NETs, were evaluated. 11 ML algorithms were compared based on several evaluation indexes including AUC. SHapley Additive exPlanations (SHAP) analysis was utilized for feature ranking and interpretability. Results: In the retrospective study, a total of 306 patients were included, among which 70 (22.9%) developed PVT. In the prospective study, a total of 64 patients were enrolled and the incidence of PVT was 25%. eXtreme gradient boosting (XGBoost) demonstrated superior discriminative performance among 11 evaluated ML-models. After feature reduction based on ranked feature importance, a final interpretable XGBoost model comprising 7 variables was established. This model accurately predicted postoperative PVT in both training (AUC=0.906) and validation (AUC=0.823) cohorts, and has been translated into a convenient tool to facilitate its utility in clinical settings. Conclusion: In patients with PDAC, higher NETs levels are correlated with an increased risk of developing PVT and are indicative of poor prognosis. Assessment of Cit-H3 and D-dimer levels may aid clinicians in predicting PVT.
Keywords: neutrophil extracellular traps, Portal vein thrombosis, Pancreatic Ductal Adenocarcinoma, prognosis, Explainable artificial intelligence
Received: 19 Oct 2025; Accepted: 17 Nov 2025.
Copyright: © 2025 Cui, Wang, Lyu, Huang, Lang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ren Lang, dr_langren@126.com
Jing Wang, 1252741372@qq.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.