Reconstructing the coding and non-coding RNA regulatory networks of miRNAs and mRNAs in breast cancer.

microRNAs (miRNAs) are a class of small non-coding RNAs that deregulate and/or decrease the expression of target messenger RNAs (mRNAs), which specifically contribute to complex diseases. In our study, we reanalyzed an integrated data to promote classification performance by rebuilding miRNA-mRNA modules, in which a group of deregulated miRNAs cooperatively regulated a group of significant mRNAs. In five-fold cross validation, the multiple processes flow considered the biological and statistical significant correlations. First, of statistical significant miRNAs, 6 were identified as core miRNAs. Second, in the 13 significant pathways enriched by gene set enrichment analysis (GSEA), 705 deregulated mRNAs were found. Based on the union of predicted sets and correlation sets, 6 modules were built. Finally, after verified by test sets, three indexes, including area under the ROC curve (AUC), Accuracy and Matthews correlation coefficients (MCCs), indicated only 4 modules (miR-106b-CIT-KPNA2-miR-93, miR-106b-POLQ-miR-93, miR-107-BTRC-UBR3-miR-16 and miR-200c-miR-16-EIF2B5-miR-15b) had discriminated ability and their classification performance were prior to that of the single molecules. By applying this flow to different subtypes, Module 1 was the consistent module across subtypes, but some different modules were still specific to each subtype. Taken together, this method gives new insight to building modules related to complex diseases and simultaneously can give a supplement to explain the mechanism of breast cancer (BC). [ABSTRACT FROM AUTHOR]