Analysis of differentially expressed genes between endometrial carcinosarcomas and endometrioid endometrial carcinoma by bioinformatics

This study aimed to explore the underlying molecular mechanisms of endometrial carcinosarcomas (ECS) and endometrioid endometrial carcinoma (EEC) by bioinformatics analysis. Gene expression profile GSE33723 was downloaded from the Gene Expression Omnibus. A total of 15 ECS and 23 EEC samples were used to identify the differentially expressed genes (DEGs) by significance analysis of microarrays. After construction of protein-protein interaction (PPI) network, Gene Ontology (GO) functional and pathway enrichment analyses of DEGs were performed, followed by network module analysis. A total of 49 DEGs were identified between EEC and ECS samples. In the PPI network, TP53 (tumor protein p53) was selected as the highest degree, hub centrality and betweenness. The top 10 enriched GO terms including regulation of cell death and top 10 significant pathways including cell cycle were selected. After network module analysis, PIK3R1 (phosphoinositide-3-kinase, regulatory subunit 1) and AKT2 (v-akt murine thymoma viral oncogene homolog 2) were selected as the co-expressed genes in the states of ECS while STAT3 (signal transducer and activator of transcription 3) and JAZF (JAZF zinc finger 1) were selected as the co-expressed genes in the states of EEC. The DEGs, such as TP53, PIK3R1 and AKT2 may be used for targeted diagnosis and treatment of ECS while STAT3 and JAZF1 may be served as a target for EEC.