Identification of Anti-PD-1 Immunotherapy Response-related Features as Prognostic Biomarkers in Melanoma and Associated with Tumor Immune Microenvironment

Background: Although immune checkpoint inhibitor (ICB) therapy has exhibited prolonged efficacy, it may have unexpected effects, particularly resistance development. The purpose of the study is to explore the specific prognostic value of anti-programmed cell death 1 (anti-PD-1) immunotherapy treatment response-related genes in melanoma and investigate the correlation of prognostic signature with immunotherapy and the tumor immune microenvironment (TIME). Methods: The GSE78220 dataset was used for screening anti-PD-1 immunotherapy treatment response-related genes. The Cancer Genome Atlas specimens of patients with melanoma act as the training cohort, while the GSE65904 served as the validation cohort. Prognostic signatures based on seven anti-PD-1 immunotherapy treatment reaction-related genes were constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) regression. The overall survival of different risk groups was compared by Kaplan-Meier analysis. The effect of their clinicopathologic features and survival risk scores were evaluated using Cox regression. The immune microenvironment was analyzed using the CIBERSORT algorithm. The connection among clinical characteristics, gene expression level at checkpoints, and risk score was evaluated by correlation analysis. Immunohistochemistry and real-time quantitative polymerase chain reaction (RT-qPCR) were employed to verify the expression level of seven genes. Results: The prognostic signature, comprising COL6A3, CCL8, FETUB, AGBL1, KIR3DL2, TMEM158, and NXT2, predicted poorer overall survival in the high-risk group. The results were consistent in the validation cohort. Different risk groups significantly changed the immune microenvironment and checkpoint gene expression. The risk score exhibited significantly negative correlation with T-cell and M1 macrophages, while displaying significantly positive correlation with M2 macrophages. Several immune checkpoint genes, such as CTL-4, PD-L1, and B7-H3 showed low expression patterns in the high-risk group. RT-qPCR and immunohistochemistry results further verified the feature gene. Conclusions: The prognostic features associated with anti-PD-1 immunotherapy treatment response-related genes can serve as innovative prognostic predictors, immune microenvironment, and responsiveness to ICB in patients with melanoma.