Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study
Through integrated bioinformatics analysis and a large-sample retrospective clinical study, we successfully established RCC-TSC and a diagnostic kit, which could stratify RCC patients with different prognosis and to guide personalized treatment.
Authors
- Keqin Dong (ORCID: https://orcid.org/0000-0002-2783-1635)
- Yuntao Yao (ORCID: https://orcid.org/0009-0001-4057-9470)
- Sanfang Tu (ORCID: https://orcid.org/0000-0001-8834-6839)
- Xiuwu Pan (ORCID: https://orcid.org/0000-0001-5268-0886)
- Guo Ji (ORCID: https://orcid.org/0000-0001-6060-4066)
- Runzhi Huang (ORCID: https://orcid.org/0000-0003-2302-7305)
- Xingang Cui (ORCID: https://orcid.org/0000-0002-0920-9439)
- Yifan Liu (ORCID: https://orcid.org/0000-0003-0516-1922)
- Zhou Wang (ORCID: https://orcid.org/0000-0002-4369-1337)
- Guofeng Xu (ORCID: https://orcid.org/0000-0002-5104-5386)
- Bing-Nan Lu
- Zihui Zhao (ORCID: https://orcid.org/0009-0005-9834-2379)
- Maodong Wei
- Yuanan Li
- Donghao Lyu
- Xukun Lyu
- Lei Wang (ORCID: https://orcid.org/0000-0003-0734-7026)
Institutions
- Tongji University (CN)
- Shanghai Jiao Tong University (CN)
- XinHua Hospital (CN)
- Shanghai Tenth People's Hospital (CN)
Publication Details
- Journal
- Cellular Oncology
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1007/s13402-024-01030-9
- Citations
- 3
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- National Natural Science Foundation of China
- Shanghai Rising-Star Program