Immune marker signature helps to predict survival in uveal melanoma

Abstract

The detailed molecular function of tumor microenvironment (TEM) in uveal melanoma (UVM) remains unclear. This study generated the immune index and the stromal index scores by ESTIMATE algorithm based on RNA-sequencing data with 80 UVM patients. There was no correlation between the immune stromal index and clinical parameters. The differentially expressed genes related to the immune stromal index were calculated and were described by functional annotations and protein-protein interaction network diagrams. After univariate and multivariate Cox regression analyses, there were four genes (HLA-J, MMP12, HES6, and ADAMDEC1) with significant prognostic significance. The prognostic model was constructed using these four characteristic genes, and the KM curve and tROC curve were described to show that the model had a better ability to predict survival outcomes and prognosis. The verification results in GSE62075 showed that HLA-J and HES6 were expressed differently in the cancer group than in the non-cancer group. This study indicates that the risk signature based on the immune index can be used as an indicator to evaluate the prognosis of patients with UVM.