Screening of potential biomarkers for chemoresistant ovarian carcinoma with miRNA expression profiling data by bioinformatics approach.

The aim of the present study was to screen out the biomarkers associated with chemoresistance in ovarian carcinomas and to investigate the molecular mechanisms. microRNA (miRNA) expression data was obtained from published microarray data of the GSE43867 dataset from Gene Expression Omnibus (GEO), including the data of 86 chemotherapy-treated patients with serous epithelial ovarian carcinomas (response group, 36 complete response cases and 12 partial response cases; non-response group, 10 stable cases and 28 progressive disease cases), and identification of differentially-expressed miRNAs were conducted with a GEO2R online tool based on R language. TargetScan 6.2 was used to predict the targets of differentially-expressed miRNAs. Protein-protein interaction network analysis was conducted by STRING 9.1, while functional enrichment [Gene Ontology (GO) biological process terms] and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted by GeneCodis3 for the target genes. A total of 6 differentially-expressed miRNAs were screened out, with 317 target genes obtained. It was found that 67 interactions existed among 76 genes/proteins through the PPI network analysis, and that 6 of these were potential key genes (PIK3R5, MAPK3, PTEN, S1PR3, BDKRB2 and NCBP2). The main biological processes involved in chemoresistant ovarian carcinoma were apoptosis, programmed cell death, cell migration, cell death and cell motility. The miRNA target genes were found to be associated with the ErbB signaling pathway, the gonadotropin-releasing hormone signaling pathway and other pathways in cancer. IK3R5, MAPK3 and PIK3R5 are involved in the majority of GO terms and KEGG pathways associated with chemoresistance in ovarian carcinoma.