Multi-omics approaches including single-cell analysis and machine learning were used to identify the roles of telomere-related genes in esophageal squamous cell carcinoma
Through a systematic analysis of TRGs expression patterns, we successfully developed a prognostic prediction model that effectively captures the heterogeneity in survival outcomes, TIME characteristics, and drug sensitivity among patients with ESCC.
Authors
- Nan Wang (ORCID: https://orcid.org/0000-0002-0983-3389)
- Shuang Li (ORCID: https://orcid.org/0000-0002-1933-679X)
- Haitao Ma (ORCID: https://orcid.org/0000-0002-9107-2928)
- Tao Zheng (ORCID: https://orcid.org/0000-0002-1820-1762)
- Yazhou Liu (ORCID: https://orcid.org/0000-0002-0135-210X)
- Kai Xie
Institutions
- Wannan Medical College (CN)
- Jiangsu University (CN)
- Soochow University (CN)
- Affiliated Hospital of Jiangsu University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1007/s12672-025-04047-0
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81