Machine learning-driven SLC prognostic signature for glioma: predicting survival and immunotherapy response
Our findings highlight SLCFPS as a robust biomarker for glioma prognosis and treatment response. By providing insights into tumor immunity, this model may aid in the development of personalized therapeutic strategies. Further validation in clinical settings is necessary to explore its full potential in guiding glioma management.
Authors
- Xiao Yang (ORCID: https://orcid.org/0000-0002-5429-9162)
- Jianghua Lin
- Yue Liu (ORCID: https://orcid.org/0000-0002-9240-869X)
- Kaijun Zhao (ORCID: https://orcid.org/0000-0002-1001-4591)
Institutions
- Boston Children's Hospital (US)
- Harvard University (US)
- Shanghai East Hospital (CN)
Publication Details
- Journal
- Frontiers in Pharmacology
- Published
- 2025-06-06
- DOI
- https://doi.org/10.3389/fphar.2025.1585639
- Citations
- 2
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.25