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

Journal of Ovarian Research
Hongjun FeiChenming Xu

Abstract

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. Of 21,755 genes with 89 SCA and SBOT cases from 3 independent laboratories, 59 mRNAs were identified as differentially expressed genes (DEGs) (|log2Fold Change| > 1.585, also |FoldChange| > 3 and adjusted P < 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, PBK and TOP2A). Mutual exclusivity or co-occurrence analysis of 4 hub genes identified a tendency towards co-occurrence between KIF11 and CDC20 or TOP2A in SCA (p < 0.05). To analyze further the potential role of KIF11 in SCA, the co-expression profiles of KIF11 in SCA were identified and we found that CDC20 co-expressed with KIF11 also is DEG that we...Continue Reading

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Datasets Mentioned

BETA
GSE36668
GSE27651
GSE12471
GSE17308
GPL570

Methods Mentioned

BETA
RNA-seq

Software Mentioned

OncoPrints
KM plotter
Affy package
R
Bioconductor
Oncomine
cBioportal
Surrogate Variable Analysis
Limma
R Limma

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