Evidence map›Paper›PMID 24250280›Full record

ArticlePLoS computational biology2013

Integrative modelling of the influence of MAPK network on cancer cell fate decision.

Luca Grieco, Laurence Calzone, Isabelle Bernard-Pierrot, François Radvanyi, Brigitte Kahn-Perlès, Denis Thieffry

Erratum issuedAbstract read
In one paragraph

Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

71 citing papers in PubMed.

  1. Article
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  7. Review
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  11. Heliyon · 2023
    Article
  12. Normalizing Input-Output Relationships of Cancer Networks for Reversion Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer.International journal of molecular sciences · 2021
    Review

11 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

6 authors.

Luca GriecoAix-Marseille Université, Marseille, France ; TAGC - Inserm U1090, Marseille, France ; Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Paris, France ; UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France ; Inserm 1024, Paris, France ; Institut Curie, Paris, France.
Laurence Calzone
Isabelle Bernard-Pierrot
François Radvanyi
Brigitte Kahn-Perlès
Denis Thieffry

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Mitogen-Activated Protein Kinase (MAPK) network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision) in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR) over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3) activating mutations.

Indexed as

Models, BiologicalAlgorithmsComputational BiologyComputer SimulationErbB ReceptorsHumansIntracellular SpaceMAP Kinase Signaling SystemProtein Interaction MapsReceptor, Fibroblast Growth Factor, Type 3SoftwareUrinary Bladder NeoplasmsEGFR protein, humanErbB ReceptorsFGFR3 protein, humanReceptor, Fibroblast Growth Factor, Type 3

Identifiers

PMID24250280
PMCPMC3821540

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.