Although immune checkpoint inhibitors have improved the overall survival rate of skin cutaneous melanoma (SKCM) patients, there is a wide variation and low response rate to these treatments in clinical immunotherapy for melanoma patients. These problems can be addressed through the induction of immunogenic cell death (ICD).We constructed an ICD-based prognostic model to predict the prognosis of SKCM patients and the efficacy of immunotherapy. Information on melanoma and normal samples obtained by TCGA and GTEx was stratified by ICD-related genes. The samples were divided into two subtypes according to high and low expression of ICD using an unsupervised clustering method (K-means). Patients with ICD-high subtype showed longer overall survival. We found that the ICD-related differential genes were associated with several cell death and immune-related pathways through GO, KEGG and GSEA. Immunoscore and tumor purity of ICD-associated genes was calculated using ESTIMATE, and ICD-high subtypes had higher immunoscore and lower tumor purity than ICD-low subtypes. Seven ICD-associated genes were obtained by one-way Cox regression and Lasso regression of ICD genes. Risk models were constructed to classify melanoma patients into high- risk and low-risk groups. The expression of ICD-related pivotal genes was lower in the high-risk group than in the low-risk group, and the survival time was significantly higher in the low-risk group than in the high-risk group. We then found that ICD risk characteristics had predictive value for the clinical efficacy of immunotherapy, with higher ICD risk scores in the immunotherapy non-responsive group. Combined with clinicopathological factors, a nomogram was established. the ROC and calibration curves assessed the ability of the nomogram to predict prognosis. We developed a new classification system for SKCM based on the characteristics of ICDs. This stratification has important clinical implications for estimating the prognosis and immunotherapy of SKCM patients.
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