Genome-scale identification of transcription factors that mediate an inflammatory network during breast cellular transformation
| Autor: | Asaf Rotem, Zhe Ji, Aviv Regev, Lizhi He, Kevin Struhl, Andreas Janzer, Christine S. Cheng |
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| Přispěvatelé: | Massachusetts Institute of Technology. Department of Biology, Koch Institute for Integrative Cancer Research at MIT, Regev, Aviv |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Science genetic processes Gene regulatory network General Physics and Astronomy Breast Neoplasms Computational biology Article General Biochemistry Genetics and Molecular Biology Epigenesis Genetic 03 medical and health sciences Cell Line Tumor Humans Gene Regulatory Networks natural sciences Breast Epigenetics STAT3 lcsh:Science Transcription factor Multidisciplinary Models Genetic biology Genome Human Gene Expression Profiling fungi General Chemistry Chromatin Gene Expression Regulation Neoplastic Gene expression profiling Cell Transformation Neoplastic 030104 developmental biology biology.protein Female Human genome lcsh:Q Transcription Factors Proto-oncogene tyrosine-protein kinase Src |
| Zdroj: | Nature Communications, Vol 9, Iss 1, Pp 1-13 (2018) Nature Communications Nature |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-018-04406-2 |
| Popis: | 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. Systematic analysis of the control of dynamic cellular processes remains a challenge. Here the authors introduce a pipeline enabling them to identify TFs involved in Src-induced cellular transformation, and find that a large number of TFs with diverse DNA binding specificities orchestrate the process. |
| Databáze: | OpenAIRE |
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