| Literature DB >> 28886276 |
Haloom Rafehi1, Antony Kaspi1, Mark Ziemann1, Jun Okabe1, Tom C Karagiannis1,2, Assam El-Osta1,2,3,4.
Abstract
Given the skyrocketing costs to develop new drugs, repositioning of approved drugs, such as histone deacetylase (HDAC) inhibitors, may be a promising strategy to develop novel therapies. However, a gap exists in the understanding and advancement of these agents to meaningful translation for which new indications may emerge. To address this, we performed systems-level analyses of 33 independent HDAC inhibitor microarray studies. Based on network analysis, we identified enrichment for pathways implicated in metabolic syndrome and diabetes (insulin receptor signaling, lipid metabolism, immunity and trafficking). Integration with ENCODE ChIP-seq datasets identified suppression of EP300 target genes implicated in diabetes. Experimental validation indicates reversal of diabetes-associated EP300 target genes in primary vascular endothelial cells derived from a diabetic individual following inhibition of HDACs (by SAHA), EP300, or EP300 knockdown. Our computational systems biology approach provides an adaptable framework for the prediction of novel therapeutics for existing disease.Entities:
Keywords: HDAC inhibitors; SAHA; computation biology; diabetes; endothelial dysfunction; epigenomics; histone acetylation; meta-analysis; network analysis; pathway analysis
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Year: 2017 PMID: 28886276 PMCID: PMC5788408 DOI: 10.1080/15592294.2017.1371892
Source DB: PubMed Journal: Epigenetics ISSN: 1559-2294 Impact factor: 4.528