Screening of key genes in ovarian cancer and their correlation with immune cell infiltration

Objective Bioinformatics method was used to screen the key genes of ovarian cancer (OV) and analyze their correlation with immune cell infiltration. Methods We retrieved and downloaded three OV datasets from GEO, and screened DEGs in OV tissues by the GEO2R online analysis tool, then performed gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on DEGs using the Metascape database; after analyzing the PPI network of DEGs using the STRING database, the results were imported into Cytoscape software, and the MCC algorithm provided by the CytoHubba plugin was used to obtain the top 10 key genes; then we used the Kaplan-Meier Plotter database and GEPIA to perform survival analysis and co-expression analysis of key genes to derive the most highly correlated group of genes before doing their mRNA and protein expression; finally, the TISIDB database was used to explore the association between key genes and OV immune infiltration cell. Results A total of 161 DEGs were obtained in this study, and their GO functions were mainly related to the response of cells to TGF- β stimulation, P53-mediated DNA damage, cell cycle arrest and protein kinase binding caused by signal transduction, etc. KEGG pathway is mainly concentrated in cancer pathway, P53 signaling pathway, complement and coagulation cascade and PI3K-Akt signaling pathway. Among the 10 key genes screened by Cytoscape, only CCNB1, HMMR, KIAA0101, AURKA, CEP55, ECT2 and TOP2A have significant effects on the prognosis of OV patients, among which CCNB1 and AURKA have the highest expression correlation in OV, and their mRNA and protein are highly expressed, which is not conducive to the prognosis of patients. The expression of CCNB1 and AURKA was positively correlated with the abundance of Th2 cells and Act-CD4 cells, but negatively correlated with eosinophils. Conclusion CCNB1 and AURKA are the key genes of OV, which are related to immune cells in OV microenvironment, and can be used as biomarkers for early diagnosis and treatment of OV.