Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learning framework
In summary, our study constructed a novel LUAD-CSRS, which is not only expected to be a powerful tool for assisting diagnosis and prognosis evaluation of LUAD, but also may provide guidance for personalized immunotherapy programs.
Authors
- Ting Ge (ORCID: https://orcid.org/0000-0003-0044-8166)
- Jianchun Yu (ORCID: https://orcid.org/0000-0002-3760-9675)
- Shuangcui Wang (ORCID: https://orcid.org/0000-0002-3685-517X)
- Wentao Li (ORCID: https://orcid.org/0000-0001-8980-0909)
- Juan Zhou (ORCID: https://orcid.org/0000-0003-2500-6110)
- Zekun Wang (ORCID: https://orcid.org/0000-0001-5175-4118)
- Guixin He
- Yuanyuan Tian (ORCID: https://orcid.org/0009-0001-0847-0328)
- Yingying Xie (ORCID: https://orcid.org/0000-0001-7575-6185)
- Jun Hu (ORCID: https://orcid.org/0009-0008-5619-7742)
- Qian Cui (ORCID: https://orcid.org/0000-0001-7973-9649)
Institutions
- Tianjin University of Traditional Chinese Medicine (CN)
- The Fourth People's Hospital (CN)
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine (CN)
- New York University (US)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1007/s12672-025-02262-3
- Citations
- 1
- Primary Topic
- Immune cells in cancer
- Type
- article
- Field-Weighted Citation Impact
- 0.80