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Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome
BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40–50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-termi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106876/ https://www.ncbi.nlm.nih.gov/pubmed/30134948 http://dx.doi.org/10.1186/s13062-018-0219-4 |
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author | Hidalgo, Marta R. Amadoz, Alicia Çubuk, Cankut Carbonell-Caballero, José Dopazo, Joaquín |
author_facet | Hidalgo, Marta R. Amadoz, Alicia Çubuk, Cankut Carbonell-Caballero, José Dopazo, Joaquín |
author_sort | Hidalgo, Marta R. |
collection | PubMed |
description | BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40–50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases. RESULTS: Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression. CONCLUSION: We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker. REVIEWERS: This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers’ comments section. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13062-018-0219-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6106876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61068762018-08-29 Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome Hidalgo, Marta R. Amadoz, Alicia Çubuk, Cankut Carbonell-Caballero, José Dopazo, Joaquín Biol Direct Research BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40–50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases. RESULTS: Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression. CONCLUSION: We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker. REVIEWERS: This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers’ comments section. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13062-018-0219-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-22 /pmc/articles/PMC6106876/ /pubmed/30134948 http://dx.doi.org/10.1186/s13062-018-0219-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Hidalgo, Marta R. Amadoz, Alicia Çubuk, Cankut Carbonell-Caballero, José Dopazo, Joaquín Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title | Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title_full | Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title_fullStr | Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title_full_unstemmed | Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title_short | Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
title_sort | models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106876/ https://www.ncbi.nlm.nih.gov/pubmed/30134948 http://dx.doi.org/10.1186/s13062-018-0219-4 |
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