A new pyroptosis model can predict the immunotherapy response and immune microenvironment characteristics and prognosis of patients with cutaneous melanoma based on TCGA and GEO databases

Background: Recent studies have shown that pyroptosis is related to cancer development. Our previous study also found that gasdermins (GSDMs) was associated with the tumor immune microenvironment. Therefore, we wanted to observe the relationship between pyroptosis and the immune microenvironment and prognosis of skin cutaneous melanoma (SKCM). Methods: Pyroptosis-related genes were used for pan-cancer prognostic analysis using the GEPIA2 online analysis website. Prognosis-related genes were clustered using R software and related R packages, and the best clustering results were screened for prognosis analysis. The prognosis-related genes were also used to establish a prognosis-related model. Assess the predictive power of a model by comparing area under the curve (AUC). The t-test was used to analyze the differences of immune-related indicators between the two clusters and between high and low risk groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed on the differential genes. Results: By clustering the prognosis-related genes, SKCM could be divided into 2 clusters with significant differences in prognosis P<0.05. A prognostic model can be established using prognosis-related genes. The AUC value of 1 year, 2 years and 3 years was 0.696, 0.702 and 0.664, respectively. The risk score was significantly associated with prognosis in both univariate and multivariate Cox analyses P<0.001. The low risk group or C2 cluster with better prognosis had higher expression of pyroptosis-related genes, and tended to have a lower exclusion score, greater chemokine expression, more immune cells and higher immune score. However, the C2 cluster or low-risk group was also associated with a higher dysfunction score. At the same time, the C2 or low-risk group was more suitable for immunotherapy because of the higher immunophenoscore (IPS) score P<0.001. Correlation analysis also demonstrated that the risk score was positively correlated with the gene expression of most immunoinhibitors, MHC molecules, immunostimulators, and chemokines and their receptors. Conclusions: Pyroptosis is associated with melanoma immune microenvironment, immunotherapy response, and prognoses. The constructed risk scores could effectively predict the characteristics of the immune microenvironment, the sensitivity to immunotherapy, and the prognosis of melanoma patients.