Major depression disorder (MDD) has become increasingly common in patients with ovarian cancer, which complicates the treatment course. The microRNA (miRNA)-mRNA regulation network may help elucidate the potential mechanism of MDD in ovarian cancer. The differentially expressed microRNAs (DEmiRs) and mRNAs (DEmRNAs) were therefore identified from the GSE61741, GSE58105 and GSE9116 ovarian cancer datasets using GEO2R. The target genes of the DEmiRs were then obtained using the TargetScan, microRNAorg, microT-CDS, miRDB and miRTarBase prediction tools. The DAVID program was used to identify the KEGG pathways of target genes, and the core genes of major depressive disorder (MDD) were identified using the Kaplan-Meier Plotter for ovarian cancer. A total of 5 DEmiRs (miR-23b-3p, miR-33b-3p, miR-1265, miR-933 and miR-629-5p) were obtained from GSE61741 and GSE58105. The target genes of these DEmiRs were enriched in pathways that were considered high risk for developing MDD in ovarian cancer. A total of 11 risk genes were selected from these pathways as the core genes in the miRNA-mRNA network of MDD in ovarian cancer, and eventually identified the following 12 miRNA-mRNAs pairs: miR-629-5p-FGF1, miR-629-5p-AKT3, miR-629-5p-MAGI2, miR-933-BDNF, miR-933-MEF2A, miR-23b-3p-TJP1, miR-23b-3p-JMJD1, miR-23b-3p-APAF1, miR-23b-3p-CAB39, miR-1265-CDKN1B, miR-33b-3p-CDKN1B, and miR-33b-3p-F2R. These results may provide novel insights into the mechanisms of developing MDD in ovarian cancer patients.
Keywords: KEGG pathway; gene ontology; major depressive disorder; miRNA-mRNA regulation network; ovarian cancer.