Identification of prognostic biomarkers associated with T and melanoma cell subpopulations in melanoma through integrating machine learning and multiomics
This study identified MITF + T-cells and M2-cells as key factors in melanoma prognosis and developed a novel PRS model for accurate prediction. These findings could help guide clinical decision-making for melanoma patients.
Authors
- Gang Yu (ORCID: https://orcid.org/0000-0001-9935-9969)
- Chen Shen (ORCID: https://orcid.org/0000-0001-9187-9345)
- Fang Guo (ORCID: https://orcid.org/0000-0002-2792-8015)
- Wěi Li (ORCID: https://orcid.org/0000-0002-9522-4474)
- Jing Li (ORCID: https://orcid.org/0000-0002-3626-5815)
- Sha Zhou (ORCID: https://orcid.org/0000-0002-7468-1924)
- Liming Ma
- Huiwen Zheng (ORCID: https://orcid.org/0000-0001-5184-7226)
Institutions
- Children's Hospital of Zhejiang University (CN)
- Harbin Electric Corporation (China) (CN)
- Zhejiang Lab (CN)
- Harbin Science and Technology Bureau (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1007/s12672-025-03701-x
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00