Abstract
Identifying transcription factor and microRNA mediated synergetic regulatory networks in lung cancer
BMC Bioinformatics, Vol.14(17), A14
Annual UT-ORNL-KBRIN Bioinformatics Summit, 12th (Buchanan, United States, 22-Mar-2013–24-Mar-2013)
2013
Abstract
Background: It has been demonstrated that, at the network level, the transcriptional regulation by transcription factors (TFs) and post-transcriptional regulation by microRNAs (miRNAs) are tightly coupled. Aberrant expression of these bio-molecules is linked to several diseases, including lung cancer. In this study, we pursued a regulatory network-based approach mediated by TFs and miRNAs for a comprehensive investigation of gene regulation patterns in lung cancer. Materials and methods: We introduced a directional network that corresponds to significantly differentially expressed (DE) miRNAs and genes between lung tumor and matched normal samples. We predicted miRNA targets in genes by parsing TargetScan prediction results. To find the regulation of TF to genes or miRNAs, we explored the TFs and their binding profiles from the TRANSFAC Professional database. TFs are either significantly DE or have target molecules which are significantly enriched in DE subspace. In this approach, a signed edge of the network illustrates potential repression or activation/repression mediated by a miRNA or TF, respectively, to their target molecules. Results and conclusions: We obtained a significantly enriched set of TF- miRNA mediated three-node based feed forward loops (FFLs) with signed edges. The edges of the signed three-node FFLs were validated using completely independent data set. The observation of critical miRNAs in the Wnt signaling pathway, with partial verification from previous studies, demonstrates that our network-based approach is promising for the identification of new and important miRNAs and their regulation in lung cancer.
Details
- Title
- Identifying transcription factor and microRNA mediated synergetic regulatory networks in lung cancer
- Authors
- Ramkrishna Mitra (Author) - Vanderbilt University, United StatesJingchun Sun (Author) - Vanderbilt University, United StatesMin Zhao (Author) - Vanderbilt University, United StatesZhongming Zhao (Author) - Vanderbilt University, United States
- Publication details
- BMC Bioinformatics, Vol.14(17), A14
- Conference details
- Annual UT-ORNL-KBRIN Bioinformatics Summit, 12th (Buchanan, United States, 22-Mar-2013–24-Mar-2013)
- Publisher
- BioMed Central Ltd.
- Date published
- 2013
- DOI
- 10.1186/1471-2105-14-S17-A14
- ISSN
- 1471-2105
- Copyright note
- Copyright © Mitra et al; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99451096602621
- Output Type
- Abstract
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- Biochemical Research Methods
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