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Biol Direct. 2018 Aug 22;13(1):16. doi: 10.1186/s13062-018-0219-4.

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

Author information

1
Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, c/Manuel Siurot s/n, 41013, Sevilla, Spain.
2
Igenomix S.A. Ronda Narciso Monturiol, 11 B, Parque Tecnológico Paterna, 46980, Paterna, Valencia, Spain.
3
Centre for Genomic Regulation, Carrer del Dr. Aiguader, 88, 08003, Barcelona, Spain.
4
Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, c/Manuel Siurot s/n, 41013, Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es.
5
Functional Genomics Node (INB). FPS, Hospital Virgen del Rocio, c/Manuel Siurot s/n, 41013, Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es.
6
Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, c/Manuel Siurot s/n, 41013, Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es.

Abstract

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.

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