FOXM1-associated melanoma stratification: integrated multi-omics and experimental validation reveal prognostic significance and therapeutic potential.

Cutaneous melanoma is a highly aggressive malignancy characterized by marked biological heterogeneity and variable clinical outcomes. Reliable biomarkers for prognostic stratification and biological characterization remain limited. This study aimed to investigate the expression pattern, prognostic significance, immune associations, and functional relevance of Forkhead box M1 (FOXM1) in melanoma.

Multi-omics analyses were performed using TCGA, GTEx, GEO, and Human Protein Atlas datasets. Survival analysis, Cox regression, nomogram construction, functional enrichment, immune infiltration, genomic alteration, and drug sensitivity analyses were conducted. FOXM1 expression was further validated by immunohistochemistry. Functional experiments, including qRT-PCR, Western blotting, CCK-8 proliferation assays, and Transwell migration and invasion assays, were performed following FOXM1 knockdown in A375 melanoma cells.

FOXM1 was significantly overexpressed in melanoma and independently associated with poor overall survival. A FOXM1-based prognostic model demonstrated satisfactory predictive performance. Functional analyses indicated that FOXM1 was primarily involved in cell-cycle progression and mitotic regulation. High FOXM1 expression was associated with an immunosuppressive microenvironment characterized by reduced cytotoxic immune infiltration and altered immune scores. Genomic analysis suggested copy-number amplification as a major contributor to FOXM1 overexpression. In vitro experiments confirmed efficient FOXM1 silencing and demonstrated that FOXM1 knockdown significantly inhibited melanoma cell proliferation, migration, and invasion.

FOXM1 is a prognostically relevant and immune-associated biomarker in melanoma. Its overexpression is associated with aggressive tumor behavior, and functional inhibition suppresses malignant phenotypes, highlighting its potential value for risk stratification and therapeutic targeting.
Cancer
Care/Management
Policy

Authors

Li Li, Zhu Zhu, Zhao Zhao, Wang Wang, Huo Huo
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