Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer

Abstract

Background: Ovarian cancer (OC) ranks fifth as a cause of gynecological cancer-associated death globally. Until now, the molecular mechanisms underlying the tumorigenesis and prognosis of OC have not been fully understood. This study aims to identify hub genes and therapeutic drugs involved in OC.

Methods: Four gene expression profiles (GSE54388, GSE69428, GSE36668, and GSE40595) were downloaded from the Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) in OC tissues and normal tissues with an adjusted P-value < 0.05 and a |log fold change (FC)| > 1.0 were first identified by GEO2R and FunRich software. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment analysis of these DEGs. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein-protein interaction (PPI) network analysis, module analysis, survival analysis, and miRNA-hub gene network construction was also performed. Finally, the GEPIA2 and DGIdb databases were utilized to verify the expression levels of hub genes and to select the candidate drugs for OC, respectively.

Results: A total of 171 DEGs were identified, including 114 upregulated and 57 downregulated DEGs. The results of the GO analysis indicated that the upregulated DEGs were mainly involved in cell division, nucleus, and protein binding, whereas the biological functions showing enrichment in the downregulated DEGs were mainly negative regulation of transcription from RNA polymerase II promoter, protein complex and apicolateral plasma membrane, and glycosaminoglycan binding. As for the KEGG-pathway, the upregulated DEGs were mainly associated with metabolic pathways, biosynthesis of antibiotics, biosynthesis of amino acids, cell cycle, and HTLV-I infection. Additionally, 10 hub genes (KIF4A, CDC20, CCNB2, TOP2A, RRM2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1) were identified and survival analysis of these hub genes showed that OC patients with the high-expression of CCNB2, TYMS, KIF11, KIF4A, BIRC5, BUB1B, FOXM1, and CDC20 were statistically more likely to have poorer progression free survival. Meanwhile, the expression levels of the hub genes based on GEPIA2 were in accordance with those based on GEO. Finally, DGIdb database was used to identify 62 small molecules as the potentially targeted drugs for OC treatment.

Conclusions: In summary, the data may produce new insights regarding OC pathogenesis and treatment. Hub genes and candidate drugs may improve individualized diagnosis and therapy for OC in future.

Keywords: Differentially expressed genes; Functional enrichment analysis; Ovarian cancer; Protein-protein interaction; Survival analysis; miRNA-hub gene network.

Fig. 1

Venn diagram for overlapping differentially expressed genes (DEGs) based on datasets. The intersection of downregulated (a) and upregulated (b) DEGs was identified from the four datasets, namely, GSE54388, GSE69428, GSE36668, and GSE40595

Fig. 2

Bubble map for GO and KEGG pathway analyses of upregulated DEGs. The top 10 items of the GO and KEGG pathway enrichment analyses are illustrated in the form of a bubble plot using the ggplot2 package for R software. A P-value < 0.05 was considered statistically significant. a biological processe, b cellular components, c molecular function, and d KEGG pathways. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes

Fig. 3

PPI network and coexpression analysis of the hub genes in OC. a The PPI network of the hub genes using the STRING online database. b The interaction network of the hub genes and their related neighboring genes using the FunRich software. c The coexpression analysis of the hub genes using the STRING online database

Fig. 4

Progression free survival analyses of hub genes in patients with stage 1 or 2 OC. a Survival prognosis forest map of the hub genes related to prognosis in OC patients. Each point in the forest plot represents the hazard ratio (HR) of the gene, and the line on both sides of the point represents the 95% confidence interval (95% CI). b-k Survival curves were constructed by the Kaplan-Meier plotter online database based on the low and high expression of the hub genes in OC patients. Log-rank P < 0.05 was considered statistically significant

Fig. 5

Information on the genetic alterations of the hub genes. a The association between the hub genes and related drugs was identified by cBioPortal, and the network of 10 hub genes and the 50 most frequently altered neighboring genes was also constructed. b The genetic alterations related to the hub genes are shown through a visual summary across a set of ovarian serous cystadenocarcinoma samples (data from TCGA, PanCancer Atlas). c An overview of the alterations of the 10 hub genes in the genomics datasets of ovarian serous cystadenocarcinoma in the TCGA database

Fig. 6

The expression level of hub genes in OC tissues and normal tissues from patients (a-j). To further verify the expression level of the hub genes between OC tissues and normal tissues, the hub genes were analyzed by the GEPIA2 online database. P < 0.01 was considered statistically significant

Fig. 7

The expression level of hub genes in OC tissues at different stages (a-j). To further verify the expression level of the hub genes in OC tissues at different stages, the hub genes were analyzed by the GEPIA2 online database. ANOVA was performed to assess the statistical significance of the variations. Pr (>F) < 0.05 was considered statistically significant

Fig. 8

Interaction network between hub genes and targeted miRNAs. Hub genes are presented in yellow circles, whereas targeted miRNAs are shown in blue circles. The interaction between the hub genes and related miRNAs is shown in the form of arrows