Integrated bioinformatic analysis for the screening of hub genes & therapeutic drugs in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) accounts for nearly ۶۰% of total cases of epithelial ovarian cancer, the highest frequent malignant gynecologic tumor. It is the most aggressive subtype which shows poor prognosis and low patient survival. This study aims to identify hub genes and therapeutic drugs involved in HGSOC. The gene expression profile (GSE۲۳۵۵۲۵) was obtained from the Gene Expression Omnibus (GEO), which included miRNA expression data from ۷۰ serum samples, comprising ۳۶ HGSOC cases and ۳۴ normal ovarian samples. Differentially expressed (DE) miRNAs between ovarian cancer tissues and normal tissues were identified using GEO۲R analysis, with a P-value < ۰.۰۵ and -۱ < |log fold change (FC)| < ۱. A total of ۷۶ hsa-miRNAs were identified and subsequently analyzed in the DIANA-miRPath database to validate miRNA interactions. Four hsa-miRNAs were highlighted for their extensive interactions: hsa-miR-۱۲۵b-۵p, hsa-miR-۱۴۵-۵p, hsa-miR-۲۱-۵p, and hsa-miR-۱۵۵-۵p. The MultiMiR package in R software was employed to determine gene targets, while the Interactive Venn Diagram was utilized to assess gene sharing among these miRNAs. Functional enrichment analysis of these genes was conducted through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments using the Enrichr online tool. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein-protein interaction (PPI) network analysis via STRING and survival analysis. Finally, the GEPIA (Gene Expression Profiling Analysis) and DGIdb (Drug-Gene Interaction database) databases were utilized to verify the expression levels of hub genes and to select the candidate drugs for HGSOC, respectively. A total of ۴۹ differentially expressed genes (DEGs) were identified. The GO analysis indicated that the molecular functions of these DEGs predominantly pertained to the negative regulation of cell population proliferation. As for the KEGG pathways, the DEGs were primarily linked to human cytomegalovirus infection, pancreatic cancer, and the role of proteoglycans in cancer. Furthermore, ten hub genes (CTNNB۱, STAT۳, CDKN۱A, EGFR, CD۴۴, CDK۶, THBS۱, SP۱, NF۲, and MUC۱) were identified, and survival analysis revealed that high expression levels of CDK۶, EGFR, STAT۳, and THBS۱ in patients with HGSOC were statistically associated with poorer survival outcomes. Lastly, DGIdb database was used to identify ۱۲۶ small molecules as the potentially targeted drugs for HGSOC treatment. In summary, the Hub genes and candidate drugs may improve individualized diagnosis and therapy for HGSOC in future.

کلیدواژه ها:

High-grade serous ovarian cancer ، hub genes ، therapeutic drugs ، bioinformatics analysis ، miRNA ، gene expression ، cytoHubba ، protein-protein interaction ، survival analysis ، differentially expressed genes ، GO analysis ، KEGG pathways ، DGIdb database