Multi-omics analysis for ferroptosis-related genes as prognostic factors in cutaneous melanoma

Melanoma is highly malignant and heterogeneous. It is essential to develop a specific prognostic model for improving the patients' survival and treatment strategies. Recent studies have shown that ferroptosis results from the overproduction of lipid peroxidation and is an iron-dependent form of programmed cell death. Despite this, ferroptosis-related genes (FRGs) and their clinical significances remain unknown in malignant melanoma. This study aims to assess the role of FRGs in melanoma, with the goal of developing a novel prognostic model that provides new insights into personalized treatment and improvement of therapeutic outcomes for melanoma.

We systematically characterized the genetic alterations and mRNA expression of 73 FRGs in The Cancer Genome Atlas (TCGA)-skin cutaneous melanoma (SKCM) dataset in this study. The results were validated with real-time RT-PCR and Western blotting. Subsequently, a multi-gene feature model was constructed using the TCGA-SKCM cohort. Melanoma patients were classified into a high-risk group and a low-risk group based on the feature model. As a final step, correlations between ferroptosis-related signatures and immune features, immunotherapy efficacy, or drug response were analyzed.

By analyzing melanoma samples from TCGA-SKCM dataset, FRGs exhibited a high frequency of genetic mutations and copy number variations (CNVs), significantly impacting gene expression. Additionally, compared with normal skin tissue, 30 genes with significantly differential expression were identified in melanoma tissues. A prognostic model related to FRGs, constructed using the LASSO Cox regression method, identified 13 FRGs associated with overall survival prognosis in patients and was validated with external datasets. Finally, functional enrichment and immune response analysis further indicated significant differences in immune cell infiltration, mutation burden, and hypoxia status between the high-risk group and the low-risk group, and the model was effective in predicting responses to immunotherapy and drug sensitivity.

This study develops a strong ferroptosis-related prognostic signature model which could put forward new insights into target therapy and immunotherapy for patients with melanoma.