Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis
The MLLS represents a promising prognostic biomarker and may support personalized treatment strategies in breast cancer, particularly for identifying candidates who may benefit from immunotherapy.
Authors
- Meng Sun (ORCID: https://orcid.org/0000-0001-6550-7396)
- Jingwen Guan (ORCID: https://orcid.org/0000-0003-1759-2172)
- Yuling Liu (ORCID: https://orcid.org/0000-0002-2740-9362)
- Simin Min
- Xiaonan Zhang (ORCID: https://orcid.org/0000-0003-0155-776X)
- Ziheng Wang (ORCID: https://orcid.org/0000-0001-8873-732X)
- Weiqiang Wang (ORCID: https://orcid.org/0000-0001-5734-1226)
- Yuyan Chen (ORCID: https://orcid.org/0000-0002-8081-1916)
- Tao Wang (ORCID: https://orcid.org/0000-0003-4140-8734)
Institutions
- Bengbu Medical College (CN)
- Anhui Medical University (CN)
- Guizhou Provincial People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-05-08
- DOI
- https://doi.org/10.3389/fimmu.2025.1540018
- Citations
- 3
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 2.42