Construction of hot tumor classification models in gastrointestinal cancers
In conclusion, our established few-gene models, which can be easily integrated into clinical practice, can distinguish hot and cold tumor subgroups, and may serve as potential biomarkers for predicting ICI response.
Authors
- Chien-Jung Huang (ORCID: https://orcid.org/0000-0003-4233-4677)
- Nai‐Jung Chiang (ORCID: https://orcid.org/0000-0003-2743-9702)
- Guan‐Ting Liu (ORCID: https://orcid.org/0000-0002-3342-9431)
- Ming‐Huang Chen (ORCID: https://orcid.org/0000-0003-3187-7393)
- Yu‐Chao Wang (ORCID: https://orcid.org/0000-0002-1574-1691)
- Yu‐Chan Chang (ORCID: https://orcid.org/0000-0003-0474-9935)
- Meng-Lun Lu
- Weining Huang (ORCID: https://orcid.org/0000-0001-6101-3196)
- Shin‐Yi Chung (ORCID: https://orcid.org/0000-0002-6762-530X)
- Yi-Chen Yeh
Institutions
- National Yang Ming Chiao Tung University (TW)
- National Health Research Institutes (TW)
- Taipei Veterans General Hospital (TW)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1186/s12967-025-06230-x
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Applied Research Laboratories
- Shanghai Educational Development Foundation
- National Science and Technology Council