Genome-scale identification of transcription factors that mediate an inflammatory network during breast cellular transformation

Zhe Ji, Lizhi He, Asaf Rotem, Andreas Janzer, Christine S. Cheng, Aviv Regev and Kevin Struhl ()
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Zhe Ji: Harvard Medical School
Lizhi He: Harvard Medical School
Asaf Rotem: Harvard Medical School
Andreas Janzer: Harvard Medical School
Christine S. Cheng: Broad Institute of MIT and Harvard
Aviv Regev: Broad Institute of MIT and Harvard
Kevin Struhl: Harvard Medical School

Nature Communications, 2018, vol. 9, issue 1, 1-13

Abstract: Abstract Transient activation of Src oncoprotein in non-transformed, breast epithelial cells can initiate an epigenetic switch to the stably transformed state via a positive feedback loop that involves the inflammatory transcription factors STAT3 and NF-κB. Here, we develop an experimental and computational pipeline that includes 1) a Bayesian network model (AccessTF) that accurately predicts protein-bound DNA sequence motifs based on chromatin accessibility, and 2) a scoring system (TFScore) that rank-orders transcription factors as candidates for being important for a biological process. Genetic experiments validate TFScore and suggest that more than 40 transcription factors contribute to the oncogenic state in this model. Interestingly, individual depletion of several of these factors results in similar transcriptional profiles, indicating that a complex and interconnected transcriptional network promotes a stable oncogenic state. The combined experimental and computational pipeline represents a general approach to comprehensively identify transcriptional regulators important for a biological process.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04406-2

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DOI: 10.1038/s41467-018-04406-2

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