Cargando…

Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks

Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the li...

Descripción completa

Detalles Bibliográficos
Autores principales: Fischer, Martin, Grossmann, Patrick, Padi, Megha, DeCaprio, James A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994865/
https://www.ncbi.nlm.nih.gov/pubmed/27280975
http://dx.doi.org/10.1093/nar/gkw523
_version_ 1782449383949729792
author Fischer, Martin
Grossmann, Patrick
Padi, Megha
DeCaprio, James A.
author_facet Fischer, Martin
Grossmann, Patrick
Padi, Megha
DeCaprio, James A.
author_sort Fischer, Martin
collection PubMed
description Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest.
format Online
Article
Text
id pubmed-4994865
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-49948652016-08-24 Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks Fischer, Martin Grossmann, Patrick Padi, Megha DeCaprio, James A. Nucleic Acids Res Data Resources and Analyses Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest. Oxford University Press 2016-07-27 2016-06-08 /pmc/articles/PMC4994865/ /pubmed/27280975 http://dx.doi.org/10.1093/nar/gkw523 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Data Resources and Analyses
Fischer, Martin
Grossmann, Patrick
Padi, Megha
DeCaprio, James A.
Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title_full Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title_fullStr Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title_full_unstemmed Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title_short Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
title_sort integration of tp53, dream, mmb-foxm1 and rb-e2f target gene analyses identifies cell cycle gene regulatory networks
topic Data Resources and Analyses
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994865/
https://www.ncbi.nlm.nih.gov/pubmed/27280975
http://dx.doi.org/10.1093/nar/gkw523
work_keys_str_mv AT fischermartin integrationoftp53dreammmbfoxm1andrbe2ftargetgeneanalysesidentifiescellcyclegeneregulatorynetworks
AT grossmannpatrick integrationoftp53dreammmbfoxm1andrbe2ftargetgeneanalysesidentifiescellcyclegeneregulatorynetworks
AT padimegha integrationoftp53dreammmbfoxm1andrbe2ftargetgeneanalysesidentifiescellcyclegeneregulatorynetworks
AT decapriojamesa integrationoftp53dreammmbfoxm1andrbe2ftargetgeneanalysesidentifiescellcyclegeneregulatorynetworks