BACKGROUND: Esophageal carcinoma (ESCA) is associated with a poor prognosis and high mortality rate. Autophagy plays important roles in promoting or suppressing tumor cell survival at different stages of cancer development. However, the roles of autophagy-related genes (ARGs) during ESCA progression and in patient prognosis remain unclear. Accordingly, in this study, we aimed to identify the relationships of ARGs with ESCA progression and patient prognosis.

MATERIAL AND METHODS: Clinicopathological information for patients with ESCA was downloaded from The Cancer Genome Atlas (TCGA) database. Transcriptome expression profiles were downloaded from TCGA and GTEx databases, and ARGs were downloaded from the Human Autophagy Database. We investigated the functions of ARGs by bioinformatics analysis. Moreover, statistical analysis of these genes was performed to identify independent prognostic markers.

RESULTS: Differentially expressed genes between normal and tumor tissues were detected and identified. GO and KEGG analyses of differentially expressed ARGs were performed. Moreover, we derived a risk signature based on the identified independent prognostic markers. The identified genes also could predict the clinicopathological features of ESCA.

CONCLUSIONS: ARGs were key participants in the tumorigenesis and development of ESCA. Our findings may be useful for developing improved therapeutic approaches for ESCA.

Keywords: Biological Markers, Esophageal Neoplasms, Carcinoma, Computational Biology, Databases, Factual, Databases, Genetic, Gene Regulatory Networks