Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma
- Published on 04/21/2025
- Reading time: 9 min.
Zhao Songyun 1, Li Zihao 1, Liu Kaibo 1, Wang Gaoyi 1, Wang Quanqiang 2, Yu Hua 1, Chen Wanying 1, Dai Hao 1, Li Yijun 1, Xie Jiaheng 3, He Yucang 1, Li Liqun 1,4
1 https://ror.org/03cyvdv85 Department of Plastic Surgery The First Affiliated Hospital of Wenzhou Medical University Wenzhou China
2 https://ror.org/03cyvdv85 Department of Oncology The First Affiliated Hospital of Wenzhou Medical University Wenzhou China
3 https://ror.org/00f1zfq44 Department of Plastic Surgery, Xiangya Hospital Central South University Changsha China
4 https://ror.org/03cyvdv85 National Key Clinical Specialty (Wound Healing) The First Affiliated Hospital of Wenzhou Medical University Wenzhou China
Abstract
Background Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortality rates, frequent metastasis, and limited treatment options. Our study aims to identify key target genes and enhance the diagnostic accuracy of melanoma prognosis by employing multi-omics analysis and machine learning techniques, ultimately leading to the development of novel therapeutic strategies.
Methods We obtained and processed transcriptomic data, including...
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