Prognostic value of the tumor-specific ceRNA network in epithelial ovarian cancer

Epithelial ovarian cancer is one of the leading causes of cancer-related death worldwide. Growing evidence indicates that multiple complex altered pathways play important regulatory roles in the development and progression of a variety of cancers, including epithelial ovarian cancer. However, the underlying mechanisms remain unclear. First, we identified differentially expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in epithelial ovarian cancer by comparing the expression profiles between epithelial ovarian cancer samples and normal tissue samples in different GEO datasets. Then, GO- and KEGG-pathway-enrichment analyses were applied to investigate the primary functions of the overlapped differentially expressed mRNAs. Moreover, the primary enriched genes were used to construct the signal-network with Cytoscape software. In addition, we integrated the relationship among lncRNAs-miRNAs-mRNAs to create a competing endogenous RNA network. Finally, mRNAs that were associated with patient prognosis in epithelial ovarian cancer were selected using univariate Cox regression analysis. A total of 2,225 mRNAs, 336 lncRNAs, and 14 miRNAs were shown to be differentially expressed in epithelial ovarian cancer compared with normal tissues. The dysregulated mRNAs were primarily enriched in cell division and signal transduction, according to Gene Ontology, whereas, according to KEGG, they were primarily enriched in metabolic pathways and pathways in cancer. A total of 10 mRNAs were associated with patient prognosis in ovarian cancer. This study identifies a novel lncRNA-miRNA-mRNA network, which may suggest potential molecular mechanisms underlying the development of epithelial ovarian cancer, providing new insights for survival prediction and interventional strategies for epithelial ovarian cancer.