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Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth

AML is a heterogenous disease caused by different mutations. We have previously shown that each mutational sub-type develops its specific gene regulatory network (GRN) with transcription factors interacting with multiple gene modules, many of which are transcription factor genes themselves. Here we...

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Autores principales: Coleman, Daniel J.L., Keane, Peter, Luque-Martin, Rosario, Chin, Paulynn S, Blair, Helen, Ames, Luke, Kellaway, Sophie G., Griffin, James, Holmes, Elizabeth, Potluri, Sandeep, Assi, Salam A., Bushweller, John, Heidenreich, Olaf, Cockerill, Peter N., Bonifer, Constanze
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370108/
https://www.ncbi.nlm.nih.gov/pubmed/37503022
http://dx.doi.org/10.1101/2023.07.18.549495
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author Coleman, Daniel J.L.
Keane, Peter
Luque-Martin, Rosario
Chin, Paulynn S
Blair, Helen
Ames, Luke
Kellaway, Sophie G.
Griffin, James
Holmes, Elizabeth
Potluri, Sandeep
Assi, Salam A.
Bushweller, John
Heidenreich, Olaf
Cockerill, Peter N.
Bonifer, Constanze
author_facet Coleman, Daniel J.L.
Keane, Peter
Luque-Martin, Rosario
Chin, Paulynn S
Blair, Helen
Ames, Luke
Kellaway, Sophie G.
Griffin, James
Holmes, Elizabeth
Potluri, Sandeep
Assi, Salam A.
Bushweller, John
Heidenreich, Olaf
Cockerill, Peter N.
Bonifer, Constanze
author_sort Coleman, Daniel J.L.
collection PubMed
description AML is a heterogenous disease caused by different mutations. We have previously shown that each mutational sub-type develops its specific gene regulatory network (GRN) with transcription factors interacting with multiple gene modules, many of which are transcription factor genes themselves. Here we hypothesized that highly connected nodes within such networks comprise crucial regulators of AML maintenance. We tested this hypothesis using FLT3-ITD mutated AML as a model and conducted an shRNA drop-out screen informed by this analysis. We show that AML-specific GRNs predict identifying crucial regulatory modules required for AML but not normal cellular growth. Furthermore, our work shows that all modules are highly connected and regulate each other. The careful multi-omic analysis of the role of one (RUNX1) module by shRNA and chemical inhibition shows that this transcription factor and its target genes stabilize the GRN of FLT3-ITD AML and that its removal leads to GRN collapse and cell death.
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spelling pubmed-103701082023-07-27 Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth Coleman, Daniel J.L. Keane, Peter Luque-Martin, Rosario Chin, Paulynn S Blair, Helen Ames, Luke Kellaway, Sophie G. Griffin, James Holmes, Elizabeth Potluri, Sandeep Assi, Salam A. Bushweller, John Heidenreich, Olaf Cockerill, Peter N. Bonifer, Constanze bioRxiv Article AML is a heterogenous disease caused by different mutations. We have previously shown that each mutational sub-type develops its specific gene regulatory network (GRN) with transcription factors interacting with multiple gene modules, many of which are transcription factor genes themselves. Here we hypothesized that highly connected nodes within such networks comprise crucial regulators of AML maintenance. We tested this hypothesis using FLT3-ITD mutated AML as a model and conducted an shRNA drop-out screen informed by this analysis. We show that AML-specific GRNs predict identifying crucial regulatory modules required for AML but not normal cellular growth. Furthermore, our work shows that all modules are highly connected and regulate each other. The careful multi-omic analysis of the role of one (RUNX1) module by shRNA and chemical inhibition shows that this transcription factor and its target genes stabilize the GRN of FLT3-ITD AML and that its removal leads to GRN collapse and cell death. Cold Spring Harbor Laboratory 2023-07-19 /pmc/articles/PMC10370108/ /pubmed/37503022 http://dx.doi.org/10.1101/2023.07.18.549495 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Coleman, Daniel J.L.
Keane, Peter
Luque-Martin, Rosario
Chin, Paulynn S
Blair, Helen
Ames, Luke
Kellaway, Sophie G.
Griffin, James
Holmes, Elizabeth
Potluri, Sandeep
Assi, Salam A.
Bushweller, John
Heidenreich, Olaf
Cockerill, Peter N.
Bonifer, Constanze
Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title_full Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title_fullStr Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title_full_unstemmed Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title_short Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth
title_sort gene regulatory network analysis predicts cooperating transcription factor regulons required for flt3-itd+ aml growth
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370108/
https://www.ncbi.nlm.nih.gov/pubmed/37503022
http://dx.doi.org/10.1101/2023.07.18.549495
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