| Literature DB >> 27264179 |
Kaitlyn M Gayvert1, Etienne Dardenne2, Cynthia Cheung2, Mary Regina Boland3, Tal Lorberbaum4, Jackline Wanjala5, Yu Chen5, Mark A Rubin6, Nicholas P Tatonetti3, David S Rickman7, Olivier Elemento8.
Abstract
Mutations in transcription factor (TF) genes are frequently observed in tumors, often leading to aberrant transcriptional activity. Unfortunately, TFs are often considered undruggable due to the absence of targetable enzymatic activity. To address this problem, we developed CRAFTT, a computational drug-repositioning approach for targeting TF activity. CRAFTT combines ChIP-seq with drug-induced expression profiling to identify small molecules that can specifically perturb TF activity. Application to ENCODE ChIP-seq datasets revealed known drug-TF interactions, and a global drug-protein network analysis supported these predictions. Application of CRAFTT to ERG, a pro-invasive, frequently overexpressed oncogenic TF, predicted that dexamethasone would inhibit ERG activity. Dexamethasone significantly decreased cell invasion and migration in an ERG-dependent manner. Furthermore, analysis of electronic medical record data indicates a protective role for dexamethasone against prostate cancer. Altogether, our method provides a broadly applicable strategy for identifying drugs that specifically modulate TF activity.Entities:
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Year: 2016 PMID: 27264179 PMCID: PMC4912004 DOI: 10.1016/j.celrep.2016.05.037
Source DB: PubMed Journal: Cell Rep Impact factor: 9.423