A machine learning-based prognostic model integrating mRNA stemness index, hypoxia, and glycolysis‑related biomarkers for colorectal cancer
This innovative prognostic model, incorporating <i>ALDOB</i>, <i>AQP1</i>, <i>IL1A</i>, <i>PHGDH</i>, and <i>PTGIS</i>, is highly accurate in predicting patient survival.
Authors
- W F Liu (ORCID: https://orcid.org/0000-0002-0497-8247)
- Liling Yue (ORCID: https://orcid.org/0000-0002-6041-821X)
- Xiang-Ling Meng (ORCID: https://orcid.org/0000-0002-3528-4037)
- Qingbu Mei (ORCID: https://orcid.org/0000-0002-6932-552X)
- M. Zhang (ORCID: https://orcid.org/0009-0007-6627-0774)
- Xiaoling Li (ORCID: https://orcid.org/0000-0002-3408-7066)
- Lulu Wang (ORCID: https://orcid.org/0009-0006-2325-0733)
- Dan Liu (ORCID: https://orcid.org/0000-0001-7023-6471)
- Penghui Li (ORCID: https://orcid.org/0000-0001-6816-6996)
- Ying Nie (ORCID: https://orcid.org/0009-0002-3576-6746)
Institutions
- Weihai Chest Hospital (CN)
- Qiqihar Medical University (CN)
Publication Details
- Journal
- Open Medicine
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1515/med-2025-1247
- Primary Topic
- Cancer, Hypoxia, and Metabolism
- Type
- article
- Field-Weighted Citation Impact
- 0.00