ArticleIranian journal of biotechnology2017
Gene Regulation Network Based Analysis Associated with TGF-βeta Stimulation in Lung Adenocarcinoma Cells.
Article in Iranian journal of biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors at 2 institutions in 1 country.
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Abstract
backgroundTransforming growth factor (TGF)-β is over-expressed in a wide variety of cancers such as lung adenocarcinoma. TGF-β plays a major role in cancer progression through regulating cancer cell proliferation and remodeling of the tumor micro-environment. However, it is still a great challenge to explain the phenotypic effects caused by TGF-β stimulation and the effect of TGF-β stimulation on tumor micro-environment.
objectivesTo address this issue, in the present study we used two time-course microarray data in human lung adenocarcinoma cells and applied bioinformatics methods to explore the gene regulation network responding to TGF-β stimulation in lung adenocarcinoma cells. MATERIALS AND
methodsThe time-dependent reverse-engineering method, protein-protein interaction network analyses, and calculation of the similarity measures between the links were used to construct gene regulatory network and to extract gene clusters.
resultsUtilizing the constructed gene regulation network, we predicted NEFL and LUC7A show the opposite and the same change with C21orf90 if HAND2 is knocked-out after treatment with TGF-β
conclusionsOur analysis can help a better understanding regarding how TGF-β stimulation causes the expression change of a number of the genes and provide a novel insight into TGF-β stimulation effect on lung adenocarcinoma cells.
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