An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma

Abstract

Abstract Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. In conclusion, the ARG-signature might be a strong predictor for evaluating the prognosis and immune infiltration of UM patients.