Machine learning-enhanced discovery of a basement membrane-related gene signature in glioblastoma via single-cell and Spatial transcriptomics
This study elucidates a direct molecular correlation between GBM and BM, establishes a BMRGs signature risk model, and explores their interconnectivity. The findings offer pivotal insights into the clinical outcomes, therapeutic responses, and potential treatment strategies for GBM.
Authors
- Shuai He (ORCID: https://orcid.org/0000-0003-2482-4576)
- Yufan Yang (ORCID: https://orcid.org/0000-0002-9036-2640)
- Meifang Han (ORCID: https://orcid.org/0000-0002-1948-8128)
- Yiqi Fan
- Jianlong Li (ORCID: https://orcid.org/0000-0002-0302-0061)
- Lijie Wang (ORCID: https://orcid.org/0000-0003-4914-9781)
- Peihan Qi (ORCID: https://orcid.org/0009-0007-0076-0500)
- Ziyuan Liu (ORCID: https://orcid.org/0000-0003-2369-4255)
Institutions
- Guangdong Pharmaceutical University (CN)
- Cornell University (US)
- National Medical Products Administration (CN)
- Nanfang Hospital (CN)
- Zhujiang Hospital (CN)
- National Center for Drug Screening (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1186/s12967-025-06918-0
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00