Machine learning-driven prediction of immune checkpoint inhibitor responses against cholangiocarcinoma: a bile biopsy perspective
Our predictive model offers a robust tool for assessing the sensitivity of CCA patients to PD-1 inhibitors, potentially guiding personalized treatment strategies. Additionally, the integration of bile metabolomics with IF data provides a promising approach for developing preoperative diagnostic models, enhancing early detection and treatment planning for CCA.
Authors
- Zhonglin Wang
- Suxia Han (ORCID: https://orcid.org/0000-0003-0842-3908)
- Shihao Chen (ORCID: https://orcid.org/0000-0001-7646-8003)
- Yan Zhu (ORCID: https://orcid.org/0000-0002-3347-3045)
- Jingyuan Fan (ORCID: https://orcid.org/0000-0001-9080-5053)
- Deng‐Yong Zhang
- Yang Yan (ORCID: https://orcid.org/0000-0002-2663-287X)
- Zhong Liu (ORCID: https://orcid.org/0000-0002-5132-7463)
- Dongdong Wang (ORCID: https://orcid.org/0000-0001-5143-3947)
- Xinrui Li (ORCID: https://orcid.org/0000-0001-7158-4785)
- Yuhang Yang (ORCID: https://orcid.org/0000-0002-3135-5803)
- Shuo Zhou (ORCID: https://orcid.org/0000-0003-2795-6865)
- Zheng Lu (ORCID: https://orcid.org/0009-0003-6923-944X)
- Wanliang Sun
Institutions
- Texas A&M International University (US)
- Vanguard University (US)
- Bates College (US)
- First Affiliated Hospital of Bengbu Medical College (CN)
- Yangzhou University (CN)
- Epigenomics (Germany) (DE)
- Tsinghua University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-06-16
- DOI
- https://doi.org/10.3389/fimmu.2025.1614683
- Citations
- 1
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- Natural Science Foundation of Anhui Province