title: Reconstructing the coding and non-coding RNA regulatory networks of miRNAs and mRNAs in breast cancer.
abstract: 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).
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
authors: Sheng
authors: S
authors: Yang
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
authors: Hui
authors: H
authors: Zhang
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China; Ministry of Education Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China.
authors: Li
authors: L
authors: Guo
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
authors: Yang
authors: Y
authors: Zhao
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China; Ministry of Education Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China. Electronic address: fengchen@njmu.edu.cn.
authors: Feng
authors: F
authors: Chen
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics*; D022661:RNA, Untranslated / Q000235:genetics; D015203:Reproducibility of Results; D028901:alpha Karyopherins / Q000235:genetics; D044844:beta-Transducin Repeat-Containing Proteins / Q000235:genetics
chemical_list: C471644:BTRC protein, human; C490630:KPNA2 protein, human; C542541:MIRN106 microRNA, human; C543350:MIRN93 microRNA, human; D035683:MicroRNAs; D012333:RNA, Messenger; D022661:RNA, Untranslated; D028901:alpha Karyopherins; D044844:beta-Transducin Repeat-Containing Proteins
keywords: Breast cancer (BC); Integrated analysis; miRNA–mRNA