Screening and identification of key genes between high-grade and low-grade serous ovarian carcinomas using integrated bioinformatics

Epithelial ovarian cancer (EOC) is one of the most aggressive tumors in women. The most common pathological type of EOC is high-grade serous carcinoma (HGSC), which is often diagnosed at an advanced stage. Low-grade serous carcinoma (LGSC) is estimated to account for 10% of all serous carcinomas. Previous studies have demonstrated that molecular and clinical characteristics differences are apparent between these two subtypes of EOC. The objective of this study was to screen and identify key genes between HGSC and LGSC, and to explore potential molecular mechanisms in the pathogenesis of EOC. The microarray datasets GSE27651 and GSE14001, with a total of 23 LGSC tissue samples and 32 HGSC tissue samples, were obtained from the Gene Expression Omnibus (GEO). The differentially-expressed genes (DEGs) were selected out through the “affy” and “limma” package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) analysis of DEGs was carried out through the Cytoscape software. Finally, survival analysis of some key geneswas conducted using the Kaplan Meier Plotter Online Tool. A total of 357 DEGs were found in HGSC, of which 181 were up regulated and 176 were down regulated. GO functional enrichment analysis showed that the DEGs were mainly associated with nucleus, cell proliferation and protein binding. KEGG pathway analysis showed that these genes were enriched in the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, cell cycle, microRNAs in cancer. Twelve hub genes (TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2 and PBK) were screened out from PPI network. The mRNA expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2, and PBK were significantly increased in tumor tissues. The protein expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1 and PBK were distinctly higher in serous ovarian cancer tissues than non-serous ovarian cancer tissues detected by immunohistochemical staining. Survival analysis showed that TOP2A, CCNB1, KIF11, AURKA, and BUB1 were significantly associated with clinical survival outcome. In addition, there is a significant correlation between the expression levels of twelve hub-genes and immune cell infiltration in serous ovarian cancer. In summary, the present study identified DEGs and hub genes by two GEO datasets mining, which might offer new insights into the molecular mechanisms of these two subtypes of EOC and provide some prognostic biomarkers for the treatment of EOC.