Abstract: Objective: To analyze the key genes and candidate pathways related to the occurrence and development of endometrial cancer(EC) with the bioinformatics methods, and to explore the pathogenesis and the therapeutic targets of EC. Methods: The EC datasets (GSE17025 and GSE63678) were downloaded from the Gene Expression Omnibus (GEO), and the GEO2R online analysis tools and R software were used to screen for the differential expression genes (DEGs) in the EC tissue and the adjacent normal tissue. The GO enrichment analysis and KEGG pathway analysis of DEGs were performed with the String database for protein-protein interaction network (PPI) analysis. Finally, the PPI network was analyzed and visualized by Cytoscape software. Results: After the DEGs analysis of the datasets GSE17025 and GSE63678, 100 co-upregulated genes and 106 co-downregulated genes were obtained. The results of GO enrichment analysis indicated that DEGs were mainly enriched in mitotic chromosome segregation, nuclear division, organelle division and other biological processes. The result of KEGG signaling pathway analysis showed that DEGs were mainly enriched in cell cycle, miRNA, p53 signaling pathway, type Ⅱ diabetes signal pathway. Through Cytoscape software analysis,CDC20, AURKA, CCNB1, DTL, CEP55, CDK1, KIF11, MELK, CCNB2, and BUB1 in the PPI network were screened as the key genes. Conclusion: The imbalance of cell cycle-related genes and pathway regulatory networks may be involved in the occurrence of EC.

Key words: bioinformatics, endometrial cancer, differential gene, Gene Expression Omnibus dataset