Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.

TitleModels of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.
Publication TypeJournal Article
Year of Publication2018
AuthorsHidalgo, MR, Amadoz, A, Cubuk, C, Carbonell-Caballero, J, Dopazo, J
JournalBiol Direct
Date Published2018 08 22
KeywordsComputational Biology; Gene Expression Regulation, Neoplastic; Humans; JNK Mitogen-Activated Protein Kinases; Models, Theoretical; Neuroblastoma; Signal Transduction

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.

Alternate JournalBiol Direct
PubMed ID30134948
PubMed Central IDPMC6106876
Grant ListBIO2014-57291-R / / Ministerio de Economía y Competitividad / International
PT13/0001/0007 / / Instituto de Salud Carlos III / International
676559 / / Horizon 2020 Framework Programme / International
SAF2017-88908-R / / Ministerio de Economía, Industria y Competitividad, Gobierno de España / International