Machine learning-based characterization of stemness features and construction of a stemness subtype classifier for bladder cancer
This study provided valuable insights into the heterogeneity of BLCA stemness, and the stemness subtype classifier may facilitate molecular classification and personalized treatment selection for BLCA patients. Besides, TNFAIP6 may serve as a potential future stemness target guiding bladder cancer chemotherapy and immunotherapy.
Authors
- Heping Qiu (ORCID: https://orcid.org/0000-0003-0652-6858)
- Xinji Zhang
- Lihua Wu (ORCID: https://orcid.org/0000-0002-4660-4059)
- Yichen Lu
- Haonan Liu (ORCID: https://orcid.org/0000-0001-5823-4297)
- Xiaolin Deng (ORCID: https://orcid.org/0000-0003-2146-5459)
- J. Zha
Institutions
- Nanchang University (CN)
- People's Liberation Army 401 Hospital (CN)
- Second Affiliated Hospital of Nanchang University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1186/s12885-025-14109-9
- Citations
- 4
- Primary Topic
- Bladder and Urothelial Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 8.03
Funders
- Natural Science Foundation of Jiangxi Province
- Nanchang University
- Chinese Society of Clinical Oncology