Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model
Our findings highlight the utility of MLTS as a robust prognostic biomarker for breast cancer. The ability of MLTS to predict patient outcomes and its association with key genomic and cellular features underscore its potential as a target for personalized therapy. Future research may focus on integrating MLTS with additional molecular signatures to enhance its clinical application in precision oncology.
Authors
- Xiao Guo
- Jiaying Xing
- Chuanbo Feng
- Xinlin Shi (ORCID: https://orcid.org/0000-0003-4058-8067)
- Yuyan Cao (ORCID: https://orcid.org/0000-0003-3872-7523)
- Tao Wang (ORCID: https://orcid.org/0009-0003-1825-0163)
Institutions
- Beihua University (CN)
- Guizhou Provincial People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-11-28
- DOI
- https://doi.org/10.3389/fimmu.2024.1462953
- Citations
- 1
- Primary Topic
- Telomeres, Telomerase, and Senescence
- Type
- article
- Field-Weighted Citation Impact
- 0.33