Melanoma Molecular Subtypes and Development of Prognostic and Immunotherapy-Related Genetic Characteristics by Ferroptosis Gene Analysis.

The dissimilarity is a major problem in clinical therapy of skin cutaneous melanoma (SKCM). Objective and reproducible classification systems may help decode SKCM heterogeneity. ConsensusClusterPlus was used to establish a stable immune molecular classification based on ferroptosis-related genes that had been acquired from FerrDb. Moreover, the prognosis, somatic mutations, immune microenvironment characteristics, functional enrichment, and clinical responsiveness to the immune checkpoint blockade of different subtypes in two independent melanin datasets were compared. Kaplan-Meier curves, univariate, multivariate, least absolute contraction, and selection operator (LASSO) Cox regression analysis were used to develop a molecular model for predicting survival, which was verified by a nomogram on the basis of independent prognostic indicators. Two molecular subtypes (C1 and C2) for SKCM were first identified according to ferroptosis-related genes; C1 showed a poor prognosis, with lower infiltration degree of immune cells and TIED score and higher homologous recombination defects, fraction altered, the number of segments, and copy number amplification and deletion. These characteristics of C2 were the opposite of C1. A ferroptosis-related prognosis risk score (FPRS) model was constructed using 6 of 463 genes with differential expression between C1 and C2. This model splits patients into low- and high-risk cohorts. There were significant differences in the infiltration and proportion of immune cells, immune checkpoint gene expression, responsiveness to immune checkpoint therapy, and sensitivity to chemotherapeutic medications between low- and high-risk cohorts. This model was an independent prognostic marker for SKCM and has a high AUC. In summary, we have identified two subtypes of SKCM with different molecular and immune characteristics on the basis of ferroptosis-related genes and further developed and verified an FPRS model, which might independently serve as a prognostic marker for SKCM.