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Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes

Global network modeling of distal regulatory interactions is essential in understanding the overall architecture of gene expression programs. Here, we developed a Bayesian probabilistic model and computational method for global causal network construction with breast cancer as a model. Whereas physi...

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Autores principales: Kim, Kwoneel, Yang, Woojin, Lee, Kang Seon, Bang, Hyoeun, Jang, Kiwon, Kim, Sang Cheol, Yang, Jin Ok, Park, Seongjin, Park, Kiejung, Choi, Jung Kyoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4499150/
https://www.ncbi.nlm.nih.gov/pubmed/26001967
http://dx.doi.org/10.1093/nar/gkv532
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author Kim, Kwoneel
Yang, Woojin
Lee, Kang Seon
Bang, Hyoeun
Jang, Kiwon
Kim, Sang Cheol
Yang, Jin Ok
Park, Seongjin
Park, Kiejung
Choi, Jung Kyoon
author_facet Kim, Kwoneel
Yang, Woojin
Lee, Kang Seon
Bang, Hyoeun
Jang, Kiwon
Kim, Sang Cheol
Yang, Jin Ok
Park, Seongjin
Park, Kiejung
Choi, Jung Kyoon
author_sort Kim, Kwoneel
collection PubMed
description Global network modeling of distal regulatory interactions is essential in understanding the overall architecture of gene expression programs. Here, we developed a Bayesian probabilistic model and computational method for global causal network construction with breast cancer as a model. Whereas physical regulator binding was well supported by gene expression causality in general, distal elements in intragenic regions or loci distant from the target gene exhibited particularly strong functional effects. Modeling the action of long-range enhancers was critical in recovering true biological interactions with increased coverage and specificity overall and unraveling regulatory complexity underlying tumor subclasses and drug responses in particular. Transcriptional cancer drivers and risk genes were discovered based on the network analysis of somatic and genetic cancer-related DNA variants. Notably, we observed that the risk genes were functionally downstream of the cancer drivers and were selectively susceptible to network perturbation by tumorigenic changes in their upstream drivers. Furthermore, cancer risk alleles tended to increase the susceptibility of the transcription of their associated genes. These findings suggest that transcriptional cancer drivers selectively induce a combinatorial misregulation of downstream risk genes, and that genetic risk factors, mostly residing in distal regulatory regions, increase transcriptional susceptibility to upstream cancer-driving somatic changes.
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spelling pubmed-44991502015-09-28 Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes Kim, Kwoneel Yang, Woojin Lee, Kang Seon Bang, Hyoeun Jang, Kiwon Kim, Sang Cheol Yang, Jin Ok Park, Seongjin Park, Kiejung Choi, Jung Kyoon Nucleic Acids Res Computational Biology Global network modeling of distal regulatory interactions is essential in understanding the overall architecture of gene expression programs. Here, we developed a Bayesian probabilistic model and computational method for global causal network construction with breast cancer as a model. Whereas physical regulator binding was well supported by gene expression causality in general, distal elements in intragenic regions or loci distant from the target gene exhibited particularly strong functional effects. Modeling the action of long-range enhancers was critical in recovering true biological interactions with increased coverage and specificity overall and unraveling regulatory complexity underlying tumor subclasses and drug responses in particular. Transcriptional cancer drivers and risk genes were discovered based on the network analysis of somatic and genetic cancer-related DNA variants. Notably, we observed that the risk genes were functionally downstream of the cancer drivers and were selectively susceptible to network perturbation by tumorigenic changes in their upstream drivers. Furthermore, cancer risk alleles tended to increase the susceptibility of the transcription of their associated genes. These findings suggest that transcriptional cancer drivers selectively induce a combinatorial misregulation of downstream risk genes, and that genetic risk factors, mostly residing in distal regulatory regions, increase transcriptional susceptibility to upstream cancer-driving somatic changes. Oxford University Press 2015-07-13 2015-05-22 /pmc/articles/PMC4499150/ /pubmed/26001967 http://dx.doi.org/10.1093/nar/gkv532 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Kim, Kwoneel
Yang, Woojin
Lee, Kang Seon
Bang, Hyoeun
Jang, Kiwon
Kim, Sang Cheol
Yang, Jin Ok
Park, Seongjin
Park, Kiejung
Choi, Jung Kyoon
Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title_full Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title_fullStr Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title_full_unstemmed Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title_short Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
title_sort global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4499150/
https://www.ncbi.nlm.nih.gov/pubmed/26001967
http://dx.doi.org/10.1093/nar/gkv532
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