Abstract
Epithelial ovarian cancer (EOC) is one of the malignancies in women, which has the highest mortality. However, the microlevel mechanism has not been discussed in detail. The expression profiles GSE27651, GSE38666, GSE40595, and GSE66957 including 188 tumor and 52 nontumor samples were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were filtered using R software, and we performed functional analysis using the clusterProfiler. Cytoscape software, the molecular complex detection plugin and database STRING analyzed DEGs to construct protein-protein interaction network. We identified 116 DEGs including 81 upregulated and 35 downregulated DEGs. Functional analysis revealed that they were significantly enriched in the extracellular region and biosynthesis of amino acids. We next identified four bioactive compounds (vorinostat, LY-294002,trichostatin A, and tanespimycin) based on ConnectivityMap. Then 114 nodes were obtained in protein–protein interaction. The three most relevant modules were detected. In addition, according to degree ≥ 10, 14 core genes including FOXM1, CXCR4, KPNA2, NANOG, UBE2C, KIF11, ZWINT, CDCA5, DLGAP5, KIF15, MCM2, MELK, SPP1, and TRIP13 were identified. Kaplan–Meier analysis, Oncomine, and Gene Expression Profiling Interactive Analysis showed that overexpression of FOXM1, SPP1, UBE2C, KIF11, ZWINT, CDCA5, UBE2C, and KIF15 was related to bad prognosis of EOC patients. CDCA5, FOXM1, KIF15, MCM2, and ZWINT were associated with stage. Receiver operating characteristic (ROC) curve showed that messenger RNA levels of these five genes exhibited better diagnostic efficiency for normal and tumor tissues. The Human Protein Atlas database was performed. The protein levels of these five genes were significantly higher in tumor tissues compared with normal tissues. Functional enrichment analysis suggested that all the hub genes played crucial roles in citrate cycle tricarboxylic acid cycle. Furthermore, the univariate and multivariate Cox proportional hazards regression showed that ZWINT was independent prognostic indictor among EOC patients. The genes and pathways discovered in the above studies may open a new direction for EOC treatment.
Highlights
Ovarian cancer is the second most common female malignant tumor in the world and the most common cause of death among female malignant tumors (McAlpine et al, 2014)
Overexpression of Cell-division cycle-associated 5 (CDCA5), FOXM1, KIF11, KIF15, MCM2, SPP1, UBE2C, and ZWINT in tumors was significantly associated with progression-free survival in Epithelial ovarian cancer (EOC) patients (Figure 10)
We found that five genes CDCA5, FOXM1, KIF15, MCM2, and ZWINT were relative to EOC stage by Gene Expression Profiling Interactive Analysis (GEPIA) analysis (Figure 12)
Summary
Ovarian cancer is the second most common female malignant tumor in the world and the most common cause of death among female malignant tumors (McAlpine et al, 2014). As a means of efficient large-scale acquisition of genetic data, has been generally used to collect and study gene chip expression profiling data of many human cancers. New methods are provided by microarrays for studying tumorassociated genes, molecular targeting, molecular prediction, and therapy. The integration of databases where researchers have published their research data containing several gene expression chips allows for a more in-depth study of molecular mechanisms (Nannini et al, 2009; Petryszak et al, 2014). R software and Bioconductor software package was used to integrate chip data, combined with R package clusterProfiler, to mine gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway. The genes and pathways discovered in the above studies may open a new direction for EOC treatment
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