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Updated: Jun 30, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
Published on: March 8, 2022
Driver Mutation Subtypes Differentially Shape Immune Evasion Landscapes in Melanoma: An AI-Driven Inflammatory
Chong Mao1, Guobin Chen2, Jiayu Tang3
1Department of Dermatology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China, uestc.edu.cn.
Background:
Melanoma harbors highly heterogeneous tumor immune microenvironments shaped by driver mutations in BRAF, NRAS, and NF1. How mutational context modulates inflammatory signaling and immune evasion mechanisms of prognosis-related genes remains poorly understood.
Methods:
ssGSEA scored 15 inflammatory pathways across four cohorts (TCGA, GSE19234, GSE22153, and GSE65904). Cross-cohort univariate Cox regression and a 10-algorithm machine learning framework identified and optimized a prognostic model. Immune microenvironment differences across BRAF, NRAS, NF1, and Triple-WT subtypes were characterized using ESTIMATE, CIBERSORT, and GSVA. CCNE1 was validated by shRNA knockdown in melanoma cell lines, and a mutation subtype-specific virtual knockdown model was constructed from scRNA-seq data.
Results:
The prognostic model achieved a 5-year AUC of 0.95 in TCGA and outperformed published signatures in three of four cohorts. High-risk patients showed markedly reduced immune infiltration (ImmuneScore r = -0.51) and an immunosuppressive phenotype. Mutation subtype analysis revealed distinct immune landscapes: NF1-mutant tumors showed the highest antigen presentation and IFN-γ pathway enrichment; BRAF-mutant tumors displayed the highest stromal score and M0 macrophage proportions; and NRAS-mutant tumors exhibited the lowest NK cell activity and most pronounced immunosuppression. CCNE1 was the gene most strongly correlated with the risk score and was validated as an independent poor prognostic marker across all cohorts. shRNA-mediated knockdown inhibited migration and enhanced adhesion in melanoma cell lines. Virtual knockdown modeling showed that CCNE1 suppression upregulated antigen presentation genes (HLA-A/B/C, B2M, and TAP1/2) and downregulated immune checkpoint molecules in a mutation subtype-dependent manner, with the strongest proimmunogenic effects in NF1-mutant cells and LAG3 downregulation predominantly in BRAF-mutant cells.
Conclusion:
This study establishes a high-performance inflammatory pathway-based prognostic model for melanoma and demonstrates that driver mutation subtypes differentially shape the immune microenvironment landscape. CCNE1 functions as a key oncogenic immune regulator whose modulation of antigen presentation and immune checkpoint expression is contingent on mutational context, most prominently in NF1-mutant tumors, underscoring the value of mutation-informed personalized immunotherapy strategies in melanoma.
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