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Uncovering MicroRNA and Transcription Factor Mediated Regulatory Networks in Glioblastoma

Overview of attention for article published in PLoS Computational Biology, July 2012
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Title
Uncovering MicroRNA and Transcription Factor Mediated Regulatory Networks in Glioblastoma
Published in
PLoS Computational Biology, July 2012
DOI 10.1371/journal.pcbi.1002488
Pubmed ID
Authors

Jingchun Sun, Xue Gong, Benjamin Purow, Zhongming Zhao

Abstract

Glioblastoma multiforme (GBM) is the most common and lethal brain tumor in humans. Recent studies revealed that patterns of microRNA (miRNA) expression in GBM tissue samples are different from those in normal brain tissues, suggesting that a number of miRNAs play critical roles in the pathogenesis of GBM. However, little is yet known about which miRNAs play central roles in the pathology of GBM and their regulatory mechanisms of action. To address this issue, in this study, we systematically explored the main regulation format (feed-forward loops, FFLs) consisting of miRNAs, transcription factors (TFs) and their impacting GBM-related genes, and developed a computational approach to construct a miRNA-TF regulatory network. First, we compiled GBM-related miRNAs, GBM-related genes, and known human TFs. We then identified 1,128 3-node FFLs and 805 4-node FFLs with statistical significance. By merging these FFLs together, we constructed a comprehensive GBM-specific miRNA-TF mediated regulatory network. Then, from the network, we extracted a composite GBM-specific regulatory network. To illustrate the GBM-specific regulatory network is promising for identification of critical miRNA components, we specifically examined a Notch signaling pathway subnetwork. Our follow up topological and functional analyses of the subnetwork revealed that six miRNAs (miR-124, miR-137, miR-219-5p, miR-34a, miR-9, and miR-92b) might play important roles in GBM, including some results that are supported by previous studies. In this study, we have developed a computational framework to construct a miRNA-TF regulatory network and generated the first miRNA-TF regulatory network for GBM, providing a valuable resource for further understanding the complex regulatory mechanisms in GBM. The observation of critical miRNAs in the Notch signaling pathway, with partial verification from previous studies, demonstrates that our network-based approach is promising for the identification of new and important miRNAs in GBM and, potentially, other cancers.

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Geographical breakdown

Country Count As %
United States 7 4%
United Kingdom 3 2%
Brazil 2 1%
Turkey 1 <1%
Hungary 1 <1%
India 1 <1%
Finland 1 <1%
Australia 1 <1%
Denmark 1 <1%
Other 3 2%
Unknown 142 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 29%
Student > Ph. D. Student 41 25%
Professor > Associate Professor 12 7%
Student > Master 12 7%
Student > Doctoral Student 10 6%
Other 22 13%
Unknown 19 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 71 44%
Biochemistry, Genetics and Molecular Biology 29 18%
Medicine and Dentistry 13 8%
Computer Science 10 6%
Engineering 4 2%
Other 13 8%
Unknown 23 14%