Bioinformatics Screening Of Prognostic Genes Of Ovarian Cancer Based On Database

Objective:Ovarian cancer is one of the most deadly and common gynecologic malignancies.Because of lacking accurate prognostic m arkers,ovarian cancer has a poor prognosis generally.The purpose of this study is to identify the potential key genes related to the prognosis of ovarian cancer through integrated bioinformatics analysis.Methods:The differential expression genes(DEG s)with P < 0.05 and |log FC|> 1.5were identified from the Gene Expressi on Omnibus(GEO)database.Functional enrichment,protein-protein interaction(PPI)network construction,functional modules analy sis,survival analysis and correlation analysis were perfo rmed.Results:First of all,135 genes with consistent exp ression were identified.33up-regulated DEGs was mainly enriched in mitotic spindle assembly checkpoint,regulation of chromosome segregation and so on.102down-regulated DEGs was mainly concentrat ed in the regulation of neurotransmitter levels,regulation of protein serine/threonine kinase activity etc.After that,we constructed the PPI network,screened top 20 hub genes and performed the survival analysis and expression correlation analysis.At the same time,the modules that meet the requirements were scr eened and the pathway enrichment analysis was carrie d out for the genes.Finally,UBE2 C,TTK and CP genes were found to be highly expressed in ovarian cancer and lead to poor prognosis.Conclusion:We have identified key candidate genes that affect the prognosis of patients with ovarian cancer and provide new ideas for treatment.