A novel immune checkpoint-related seven-gene signature for predicting prognosis and immunotherapy response in melanoma

•This study proposed a prognostic immune checkpoint-based gene signature in melanoma.•High risk scores indicate unfavorable prognosis and no response to immunotherapy. New emergence of immunotherapy has significantly improved clinical outcome of melanoma patients with advanced and metastatic diseases. We aimed to develop a gene signature based on the expression of PD-1/PD-L1 signaling pathway genes to predict prognosis and immunotherapy response in melanoma patients. Melanoma samples from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) were used as the training set and external validation sets respectively. Prognostic genes for overall survival (OS) were identified by univariate Cox regression analysis. Then a multi-gene risk signature was established with the Least Absolute Shrinkage and Selector Operation (LASSO) regression and multivariate Cox regression. The predictive and prognostic value of gene signature was evaluated by Kaplan Meier curve, Time-dependent receiver operating characteristic (ROC) curve, and area under curve (AUC). Gene set enrichment analysis (GSEA) was performed to investigate the discrepantly enriched biological processes between low-risk and high-risk group of melanoma patients. A seven-gene risk signature (BATF2, CTLA4, EGFR, HLA-DQB1, IKBKG, PIK3R2, PPP3CA) was constructed. The signature was an independent risk factor for OS (hazard ratio = 1.544, p