Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort
Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway.
Authors
- Chaoqun Lian (ORCID: https://orcid.org/0000-0003-4914-020X)
- Mei Tian (ORCID: https://orcid.org/0000-0002-1587-2114)
- Luyao Wang (ORCID: https://orcid.org/0000-0003-1595-6593)
- Xiaojing Wang (ORCID: https://orcid.org/0000-0001-6285-9193)
- Jing Zhang
- Huili Chen
- Yiluo Xie
- Ziqang Wang
Institutions
- Bengbu Medical College (CN)
- First Affiliated Hospital of Bengbu Medical College (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.3389/fimmu.2024.1460547
- Citations
- 13
- Primary Topic
- Ferroptosis and cancer prognosis
- Type
- article
- Field-Weighted Citation Impact
- 5.45