Integrated machine learning survival framework develops a prognostic model based on macrophage-related genes and programmed cell death signatures in a multi-sample Kidney renal clear cell carcinoma
We used a powerful machine learning framework to highlight the great potential of MacPCD in providing personalised risk assessment and immunotherapy intervention recommendations for KIRC patients.
Authors
- Yanan Ge
- Xuefei Liu (ORCID: https://orcid.org/0000-0003-1541-2529)
- Limin Yang (ORCID: https://orcid.org/0000-0002-8980-1976)
- Xing Luo (ORCID: https://orcid.org/0000-0003-1096-6629)
- Jianong Li
- Tingting Li (ORCID: https://orcid.org/0000-0002-6319-9518)
- Jiang Zhao (ORCID: https://orcid.org/0000-0002-7588-9612)
- Min Deng (ORCID: https://orcid.org/0000-0001-5993-9723)
Institutions
- Army Medical University (CN)
- General Hospital of Shenyang Military Region (CN)
Publication Details
- Journal
- Cell Biology and Toxicology
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1007/s10565-025-10023-9
- Citations
- 2
- Primary Topic
- Ferroptosis and cancer prognosis
- Type
- article
- Field-Weighted Citation Impact
- 3.04