Bioinformatics analysis of gene expression profile of serous ovarian carcinomas to screen key genes and pathways

Background Serous ovarian carcinomas (SCA) are the most common and most aggressive ovarian carcinoma subtype which etiology remains unclear. To investigate the prospective role of mRNAs in the tumorigenesis and progression of SCA, the aberrantly expressed mRNAs were calculated based on the NCBI-GEO RNA-seq data. Results Of 21,755 genes with 89 SCA and SBOT cases from 3 independent laboratories, 59 mRNAs were identified as differentially expressed genes (DEGs) (|log(2)Fold Change| > 1.585, also |FoldChange| > 3 and adjustedP < 0.05) by DESeq R. There were 26 up-regulated DEGs and 33 down-regulated DEGs screened. The hierarchical clustering analysis, functional analysis and pathway enrichment analysis were performed on all DEGs and found that Polo-like kinase (PLK) signaling events are important. PPI network constructed with different filtration conditions screened out 4 common hub genes (KIF11,CDC20,PBKandTOP2A). Mutual exclusivity or co-occurrence analysis of 4 hub genes identified a tendency towards co-occurrence betweenKIF11andCDC20orTOP2Ain SCA (p < 0.05). To analyze further the potential role ofKIF11in SCA, the co-expression profiles ofKIF11in SCA were identified and we found thatCDC20co-expressed withKIF11also is DEG that we screened out before. To verify our previous results in this paper, we assessed the expression levels of 4 hub DEGs (all up-regulated) and 4 down-regulated DEGs in Oncomine database. And the results were consistent with previous conclusions obtained from GEO series. The survival curves showed thatKIF11,CDC20andTOP2Aexpression are significantly related to prognosis of SCA patients. Conclusions From all the above results, we speculate thatKIF11,CDC20andTOP2Aplayed an important role in SCA.