abstract
- This study aimed to develop an autophagy-associated long non-coding RNA (lncRNA) signature to predict the prognostic outcomes of uveal melanoma (UM). The data of UM from The Cancer Genome Atlas (TCGA) were enrolled to obtain differentially expressed genes (DEGs) between metastasizing and non-metastasizing UM patients. A total of 13 differentially expressed autophagy genes were identified and validated in Gene Expression Omnibus, and 11 autophagy-related lncRNAs were found to be associated with overall survival. Through performing least absolute shrinkage and selection operator regression analyses, a six-autophagy-related lncRNA signature was built, and its efficacy was confirmed by receiver-operating characteristic, Kaplan-Meier analysis, and univariate and multivariate Cox regression analyses. A comprehensive nomogram was established and its clinical net benefit was validated by decision curve analysis. GSEA revealed that several biological processes and signaling pathways including Toll-like receptor signaling pathway, natural killer cell-mediated cytotoxicity, and B- and T-cell receptor signaling pathway were enriched in the high-risk group. CIBERSORT results showed that the signature was related to the immune response especially HLA expression. This signature could be deployed to assist clinicians to identify high-risk UM patients and help scientists to explore the molecular mechanism of autophagy-related lncRNAs in UM pathogenesis.