LAUSR

Melanoma is becoming increasingly common worldwide, with high rates of transformation into malignancy compared to other skin lesions. The prognosis of patients with melanoma at an advanced stage is highly unsatisfying despite the development of immunotherapy, target therapy, or combinative therapy. The major barrier to exploiting immune checkpoint therapies and achieving the best benefits clinically is resistance that can easily develop if regimens are not selected appropriately. In this study, we investigated the possibility of using immune-related genes to predict patient survival and their responses to immune checkpoint blocker therapies with the expression profiles available at The Cancer Genome Atlas (TCGA) Program plus expression data from the Gene Expression Omnibus (GEO) for validation. A five gene signature that is highly correlated with the local infiltration of cytotoxic lymphocytes in the tumor microenvironment was identified, and a scoring model was developed with stepwise regression after multivariate Cox analyses. The score calculated strongly correlates with Breslow depth, and this model effectively predicts the prognosis of patients with melanoma, whether primary or metastasized. It also depicts the heterogenous immune-related nature of melanoma by revealing different predicted responses to immune checkpoint blocker therapies through its correlation to tumor immune dysfunction and exclusion (TIDE) score.