Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma
This study not only uncovers the diversity and complexity of melanoma molecular subtypes but also underscores the crucial role of the TME in melanoma progression. It provides new insights and tools for personalized treatment and prognostic assessment of SKCM.
Authors
- Gaoyi Wang
- Yucang He (ORCID: https://orcid.org/0000-0003-3643-3564)
- Songyun Zhao (ORCID: https://orcid.org/0000-0003-0542-1085)
- Wanying Chen (ORCID: https://orcid.org/0000-0002-8650-4888)
- Jiaheng Xie (ORCID: https://orcid.org/0000-0002-4992-498X)
- Quanqiang Wang
- Yijun Li (ORCID: https://orcid.org/0000-0003-0513-9565)
- Hao Dai (ORCID: https://orcid.org/0009-0000-5916-258X)
- Kaibo Liu
- Hua Yu
- Zihao Li (ORCID: https://orcid.org/0000-0001-9633-9823)
- Liqun Li (ORCID: https://orcid.org/0009-0002-8222-3736)
Institutions
- Central South University (CN)
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
- Xiangya Hospital Central South University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1186/s12885-025-14012-3
- Citations
- 8
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 7.49