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Background  miRNAs are proved to have causal roles in tumorgenesis involving various types of human cancers, but the mechanism is not clear. We aimed to explore the effect of miRNAs on the development of ovarian cancer and the underlying mechanism.    Methods  The miRNA expression profile GSE31801 was downloaded from GEO (Gene Expression Omnibus) database. Firstly, the differentially expressed miRNAs were screened. Target genes of the miRNAs were collected from TargetScan, PicTar, miRanda, and DIANA-microT database, then the miRNA-miRNA co-regulating network was constructed using miRNA pairs with common regulated target genes. Next, the functional modules in the network were studied, the miRNA pairs regulated at least one modules were enriched to form the miRNA functional synergistic network (MFSN).    Results  Risk miRNA were selected in MFSN according to the topological structure. Transcript factors (TFs) in MFSN were identified, followed by the miRNA-transcript factor networks construction. Totally, 42 up- and 61 down-regulated differentially expressed miRNAs were identified, of which 68 formed 2292 miRNA pairs in the miRNA-miRNA co-regulating network. GO: 0007268 (synaptic transmission) and GO: 0019226 (transmission of nerve impulse) were the two common functions of miRNAs in MFSN, and hsa-miR-579 (36), hsa-miR-942 (31), hsa-miR-105 (31), hsa-miR-150 (34), and hsa-miR-27a* (32) were selected as the hub nodes in MFSN.    Conclusions  In all, 17 TFs, including CREM, ERG, and CREB1 were screened as the cancer related TFs in MFSN. Other TFs, such as BIN1, FOXN3, FOXK1, FOXP2, and ESRRG with high degrees may be inhibited in ovarian cancer. MFSN gave us a new shed light on the mechanism studies in ovarian cancer.

Risk miRNA screening of ovarian cancer based on miRNA functional synergistic network