ArticleAmerican journal of cancer research2024
Multi-omics and tumor immune microenvironment characterization of a prognostic model based on aging-related genes in melanoma.
Article in American journal of cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- Immunosenescence and cancer: molecular hallmarks, tumor microenvironment remodeling, and age-specific immunotherapy challenges.Journal of hematology & oncology · 2025Review
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5 authors at 1 institution in 1 country.
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Abstract
Melanoma is a common and fatal cutaneous malignancy with strong invasiveness and high mortality rate. Clinically, elderly melanoma patients tend to exhibit stronger invasion ability and poorer prognosis. Given the heterogeneity of tumors, we analyzed the prognosis and risk assessment of melanoma through aging-related genes rather than age stratification. FOXM1 and CCL4 were identified to be closely associated with melanoma prognosis. Single-cell transcriptome analysis showed that FOXM1 was significantly up-regulated in tumor cells, while CCL4 was markedly elevated in immune cells. A melanoma prognostic model was constructed based on the two independent prognostic factors. This model showed a high accuracy in predicting the mortality of melanoma patients over several years. The patients in low-risk group appeared to have more immune cell infiltration and better immune therapy efficacy. Cellular experiments showed that CCL4 could promote apoptosis of melanoma cells through immune cells, and apoptosis could regulate the expression of FOXM1. In addition, the results of the spatial transcriptome and immunohistochemistry suggested that CCL4 was highly expressed in macrophages and the expression of FOXM1 in melanoma cell was negatively correlated with immune cell infiltration, especially macrophages. Here, we established a novel prognostic model for melanoma, which showed promising predictive performance and may serve as a biomarker for the efficacy of immune checkpoint inhibition therapy in melanoma patients. In addition, we explored the function of two genes in the model in melanoma.
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