Identification of Iron Metabolism-Related Gene Signatures for Predicting the Prognosis of Patients with Skin Cutaneous Melanoma

Abstract Background Skin cutaneous melanoma (SKCM) is an aggressive form of skin cancer with an elevated risk of metastasis and high mortality rates. Current immunotherapies represented by immune checkpoint inhibitors (ICI), such as anti-CTLA-4 and anti-PD-1/L1, have achieved remarkable durable responses in SKCM treatment. Recent studies have highlighted the biological significance of iron metabolism modification in tumorigenicity and progression. However, there has been insufficient evidence to reveal the prognostic value of iron metabolism-related genes (IMRGs) in SKCM and its relationship with the immune microenvironment and the efficacy of immunotherapy. Methods In this study, we curated 85 iron metabolism-related genes and performed unsupervised consensus analysis to identify iron metabolism modification patterns and the IMRG signature in SKCM. We used the ssGSEA algorithms to quantify the infiltration levels of various immune cells. An IMRG scoring scheme based on the PCA algorithm was used to evaluate the iron metabolism modification patterns of individual tumors. Results We identified three distinct iron metabolism modification patterns among 685 SKCM samples, which were associated with different prognoses and biological pathways. Meanwhile, three distinct iron metabolism modification patterns of SKCM had different immune cell infiltration. Based on the IMRG score, SKCM patients can be divided into high and low score subgroups. Multivariate Cox regression analysis showed that the IMRG score was an independent prognostic indicator. It was concluded that patients with lower IMRG scores had prolonged survival time. We further proved that a lower IMRG score was correlated with PD-L1, PD-1, CTLA4 expression, and better immune responses. Conclusions Our study highlights that iron metabolism is significantly associated with prognosis and immune cell infiltration. What’s more, this analysis of different IMRG patterns in SKCM patients contributed to a deeper understanding of TME and provided new perspectives for predicting prognosis and designing individualized immunotherapy strategies for SKCM patients.