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10.1261/rna.042754.113 http://scihub22266oqcxt.onion/10.1261/rna.042754.113 C4138319!4138319 !25024357     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=25024357 &cmd=llinks): Failed to open stream: HTTP request failed! 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Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer |pdf=|usr=}}{{25024357 }} gab.com Text Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer JO: RNA http://www.kidney.de/pget.php?&tw=1&pmid=25024357 #FOAvip While previous studies reported aberrant expression of microRNAs (miRNAs) in non-small cell lung cancer (NSCLC), little is known about which miRNAs play central roles in NSCLC's pathogenesis and its regulatory mechanisms. To address this issue, we presented a robust computational framework that integrated matched miRNA and mRNA expression profiles in NSCLC using feed-forward loops. The network consists of miRNAs, transcription factors (TFs), and their common predicted target genes. To discern the biological meaning of their associations, we introduced the direction of regulation. A network edge validation strategy using three independent NSCLC expression profiling data sets pinpointed reproducible biological regulations. Reproducible regulation, which may reflect the true molecular interaction, has not been applied to miRNA-TF co-regulatory network analyses in cancer or other diseases yet. We revealed eight hub miRNAs that connected to a higher proportion of targets validated by independent data sets. Network analyses showed that these miRNAs might have strong oncogenic characteristics. Furthermore, we identified a novel miRNA-TF co-regulatory module that potentially suppresses the tumor suppressor activity of the TGF-? pathway by targeting a core pathway molecule (TGFBR2). Follow-up experiments showed two miRNAs (miR-9-5p and miR-130b-3p) in this module had increased expression while their target gene TGFBR2 had decreased expression in a cohort of human NSCLC. Moreover, we demonstrated these two miRNAs directly bind to the 3' untranslated region of TGFBR2. This study enhanced our understanding of miRNA-TF co-regulatory mechanisms in NSCLC. The combined bioinformatics and validation approach we described can be applied to study other types of diseases. Twit Text FOAVip Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer ????RNA http://www.kidney.de/pget.php?&tw=1&pmid=25024357 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25024357 #FOAvip English Wikipedia <ref>{{Cite pmid|25024357 }}</ref> Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer #MMPMID25024357 Mitra R ; Edmonds MD ; Sun J ; Zhao M ; Yu H ; Eischen CM ; Zhao Z RNA 2014[Sep]; 20 (9 ): 1356-68 PMID25024357 show ga While previous studies reported aberrant expression of microRNAs (miRNAs) in non-small cell lung cancer (NSCLC), little is known about which miRNAs play central roles in NSCLC's pathogenesis and its regulatory mechanisms. To address this issue, we presented a robust computational framework that integrated matched miRNA and mRNA expression profiles in NSCLC using feed-forward loops. The network consists of miRNAs, transcription factors (TFs), and their common predicted target genes. To discern the biological meaning of their associations, we introduced the direction of regulation. A network edge validation strategy using three independent NSCLC expression profiling data sets pinpointed reproducible biological regulations. Reproducible regulation, which may reflect the true molecular interaction, has not been applied to miRNA-TF co-regulatory network analyses in cancer or other diseases yet. We revealed eight hub miRNAs that connected to a higher proportion of targets validated by independent data sets. Network analyses showed that these miRNAs might have strong oncogenic characteristics. Furthermore, we identified a novel miRNA-TF co-regulatory module that potentially suppresses the tumor suppressor activity of the TGF-? pathway by targeting a core pathway molecule (TGFBR2). Follow-up experiments showed two miRNAs (miR-9-5p and miR-130b-3p) in this module had increased expression while their target gene TGFBR2 had decreased expression in a cohort of human NSCLC. Moreover, we demonstrated these two miRNAs directly bind to the 3' untranslated region of TGFBR2. This study enhanced our understanding of miRNA-TF co-regulatory mechanisms in NSCLC. The combined bioinformatics and validation approach we described can be applied to study other types of diseases. |*Gene Regulatory Networks [MESH] |*Oncogenes/genetics [MESH] |Carcinoma, Non-Small-Cell Lung/*genetics [MESH] |Computational Biology/methods [MESH] |Gene Expression Profiling/methods [MESH] |Gene Expression Regulation, Neoplastic [MESH] |Genes, Neoplasm [MESH] |Humans [MESH] |Lung Neoplasms/*genetics [MESH] |MicroRNAs/*genetics [MESH] |Reproducibility of Results [MESH] |Systems Integration [MESH]Reproducible combinatorial regulatory networks elucidate novel oncogen(epmc).pdf DeepDyve Pubget Overpricing