TCGA dataset screening for genes implicated in endometrial cancer using RNA-seq profiling.

The molecular basis of the mechanism and the potential biomarkers of endometrial cancer (EC) remain to be studied. In the present study, we hypothesized that the comprehensive characterization of transcriptional changes in EC could help achieve this aim. By taking advantage of RNA-seq data from The Cancer Genome Atlas, we determined the profile of differently expressed genes (DEGs) between EC tumor tissues and normal samples. On this basis, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analyses. The interacting partners for each of the DEGs were explored and a protein-protein interaction network was constructed. Consequently, 10 hub genes were identified and their association with mortality in EC patients was investigated. The genes, AURKA, CENPA, and KIF2C, were found to be potential biomarkers for EC with a significant prognostic effect. Our work provided a basis for EC studies in both biological and clinical settings.