Integrating Single‐Cell Transcriptomics and Machine Learning to Define an <scp>ac4C</scp> Gene Signature in Lung Adenocarcinoma
ac4C modification and its related genes play a critical role in lung adenocarcinoma development. The ARGSig model provides a promising molecular tool for prognosis evaluation and personalized treatment guidance in lung adenocarcinoma patients.
Authors
- Pengpeng Zhang (ORCID: https://orcid.org/0009-0004-6951-2634)
- Chunnuan Wu (ORCID: https://orcid.org/0009-0001-8196-4463)
- Yijie Wang (ORCID: https://orcid.org/0009-0000-8222-4566)
- Wei Su (ORCID: https://orcid.org/0000-0003-2332-0536)
- Lianmin Zhang (ORCID: https://orcid.org/0000-0002-7419-9628)
- Guangyao Zhou
Institutions
- Tianjin Medical University Cancer Institute and Hospital (CN)
Publication Details
- Journal
- Thoracic Cancer
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1111/1759-7714.70140
- Primary Topic
- Lung Cancer Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Tianjin City