Objective To search for the hub genes for the prognosis of ovarian cancer and provide new targets for the treatment of ovarian cancer. Methods Ovarian cancer related data were downloaded from Gene Expression Omnibus (GEO) database (GSE18520 and GSE14407 datasets), The Cancer Genome Atlas (TCGA) database and the Genotype-Tissue Expression (GTEx) database. Differentially expressed genes were analyzed with limma package of R 3.6.2 software, and then clusterProfiler package was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these genes. Meanwhile, STRING was used to establish the protein-protein interaction network, and cytoHubba package of Cytoscape software was used to screen the hub genes. Gene Expression Profile Interaction Analysis (GEPIA) database was used to verify the expression of hub genes in ovarian cancer tissues. Then, Kaplan-Meier Plotter database was used to perform survival analysis on the hub genes. Results A total of 69 differentially expressed genes were screened by GEO (GSE18520 and GSE14407), TCGA and GTEx databases, and they were mainly enriched in the ABC transporter, retinol metabolism and Wnt signaling pathways. Protein-protein interaction network analysis showed that there were 9 hub genes, which were verified in GEPIA. Kaplan-Meier Plotter database analysis showed that the overall survival was shorter in the ovarian cancer patients with high expression of centrosomal protein 55 (CEP55), family with sequence similarity 83, member D (FAM83D), kinesin family member 20A (KIF20A), cyclin dependent-kinase subunit protein 2 (CKS2) and NIMA related kinase 2 (NEK2) genes; and the progression-free survival was shorter in patients with high expression of CEP55, FAM83D, KIF20A, forkhead box protein M1 (FOXM1) and TTK protein kinase (TTK) than those with low expression. Conclusion The expression of CEP55, FAM83D, KIF20A, CKS2, NEK2, FOXM1 and TTK are closely related to the prognosis of ovarian cancer patients.