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Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia

Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their...

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Autores principales: Hajingabo, Leon Juvenal, Daakour, Sarah, Martin, Maud, Grausenburger, Reinhard, Panzer-Grümayer, Renate, Dequiedt, Franck, Simonis, Nicolas, Twizere, Jean-Claude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4244205/
https://www.ncbi.nlm.nih.gov/pubmed/25273558
http://dx.doi.org/10.1091/mbc.E14-06-1038
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author Hajingabo, Leon Juvenal
Daakour, Sarah
Martin, Maud
Grausenburger, Reinhard
Panzer-Grümayer, Renate
Dequiedt, Franck
Simonis, Nicolas
Twizere, Jean-Claude
author_facet Hajingabo, Leon Juvenal
Daakour, Sarah
Martin, Maud
Grausenburger, Reinhard
Panzer-Grümayer, Renate
Dequiedt, Franck
Simonis, Nicolas
Twizere, Jean-Claude
author_sort Hajingabo, Leon Juvenal
collection PubMed
description Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their products is challenging because diseased phenotypes are likely dependent of complex molecular interaction networks. Using as models three different chromosomal translocations—ETV6-RUNX1 (TEL-AML1), BCR-ABL1, and TCF3-PBX1 (E2A-PBX1)—frequently found in precursor-B-cell acute lymphoblastic leukemia (preB-ALL), we develop an approach to extract perturbed molecular interactions from gene expression changes. We show that the MYC and JunD transcriptional circuits are specifically deregulated after ETV6-RUNX1 and TCF3-PBX1 gene fusions, respectively. We also identified the bulk mRNA NXF1-dependent machinery as a direct target for the TCF3-PBX1 fusion protein. Through a novel approach combining gene expression and interactome data analysis, we provide new insight into TCF3-PBX1 and ETV6-RUNX1 acute lymphoblastic leukemia.
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spelling pubmed-42442052015-02-16 Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia Hajingabo, Leon Juvenal Daakour, Sarah Martin, Maud Grausenburger, Reinhard Panzer-Grümayer, Renate Dequiedt, Franck Simonis, Nicolas Twizere, Jean-Claude Mol Biol Cell Articles Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their products is challenging because diseased phenotypes are likely dependent of complex molecular interaction networks. Using as models three different chromosomal translocations—ETV6-RUNX1 (TEL-AML1), BCR-ABL1, and TCF3-PBX1 (E2A-PBX1)—frequently found in precursor-B-cell acute lymphoblastic leukemia (preB-ALL), we develop an approach to extract perturbed molecular interactions from gene expression changes. We show that the MYC and JunD transcriptional circuits are specifically deregulated after ETV6-RUNX1 and TCF3-PBX1 gene fusions, respectively. We also identified the bulk mRNA NXF1-dependent machinery as a direct target for the TCF3-PBX1 fusion protein. Through a novel approach combining gene expression and interactome data analysis, we provide new insight into TCF3-PBX1 and ETV6-RUNX1 acute lymphoblastic leukemia. The American Society for Cell Biology 2014-12-01 /pmc/articles/PMC4244205/ /pubmed/25273558 http://dx.doi.org/10.1091/mbc.E14-06-1038 Text en © 2014 Hajingabo et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0). “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology.
spellingShingle Articles
Hajingabo, Leon Juvenal
Daakour, Sarah
Martin, Maud
Grausenburger, Reinhard
Panzer-Grümayer, Renate
Dequiedt, Franck
Simonis, Nicolas
Twizere, Jean-Claude
Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title_full Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title_fullStr Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title_full_unstemmed Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title_short Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
title_sort predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4244205/
https://www.ncbi.nlm.nih.gov/pubmed/25273558
http://dx.doi.org/10.1091/mbc.E14-06-1038
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