BACKGROUND: Ovarian neoplasms are the fifth most common cancer affecting the health of women, and they are the most lethal gynecologic malignancies; however, the etiology of ovarian neoplasms remains largely unknown. There is an urgent need to further broaden the understanding of the development mechanism of ovarian neoplasms through in vitro research using different cell lines.

MATERIAL AND METHODS: To screen the differentially expressed genes (DEGs) that may play critical roles in OVDM1 (an ovarian cancer cell line), the public microarray data (GSE70264) were downloaded and screened for DEGs. Then, Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. To screen hub genes, the protein–protein interaction network was constructed. The expression level and survival analysis of hub genes in patients with ovarian neoplasms were also analyzed.

RESULTS: There were 79 upregulated and 926 downregulated DEGs detected, and the biological processes of the GO analysis were enriched in extracellular matrix organization, extracellular structure organization, and chromosome segregation, whereas, the KEGG pathway analysis was enriched in cell cycle and cell adhesion molecules. The hub gene BIRC5, which might play a key role in ovarian neoplasms, was further screened.

CONCLUSIONS: The present study could deepen the understanding of the molecular mechanism of ovarian neoplasms using the OVDM1 cell line, which could be useful in developing clinical treatments of ovarian neoplasms.

Keywords: gene ontology, Ovarian Neoplasms, Protein Interaction Maps, Computational Biology, Databases, Genetic, Gene Regulatory Networks, Protein Interaction Mapping