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RNA. 2014 Sep;20(9):1356-68. doi: 10.1261/rna.042754.113. Epub 2014 Jul 14.

Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer.

Author information

1
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.
2
Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.
3
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee 37212, USA Center for Quantitative Sciences, Vanderbilt University, Nashville, Tennessee 37232, USA.

Abstract

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-β 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.

KEYWORDS:

feed-forward loop; lung cancer; microRNA; regulatory network; transcription factor

PMID:
25024357
PMCID:
PMC4138319
DOI:
10.1261/rna.042754.113
[Indexed for MEDLINE]
Free PMC Article

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