title: Integrative modelling of the influence of MAPK network on cancer cell fate decision.
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.
authors.affiliation: Aix-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.
authors.forename: Luca
authors.initials: L
authors.lastname: Grieco
authors.forename: Laurence
authors.initials: L
authors.lastname: Calzone
authors.forename: Isabelle
authors.initials: I
authors.lastname: Bernard-Pierrot
authors.forename: François
authors.initials: F
authors.lastname: Radvanyi
authors.forename: Brigitte
authors.initials: B
authors.lastname: Kahn-Perlès
authors.forename: Denis
authors.initials: D
authors.lastname: Thieffry
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D066246:ErbB Receptors / Q000378:metabolism; D006801:Humans; D042541:Intracellular Space / Q000378:metabolism; D020935:MAP Kinase Signaling System / Q000502:physiology*; D008954:Models, Biological; D060066:Protein Interaction Maps / Q000502:physiology*; D051498:Receptor, Fibroblast Growth Factor, Type 3 / Q000378:metabolism; D012984:Software; D001749:Urinary Bladder Neoplasms / Q000378:metabolism*
chemical_list: C512478:EGFR protein, human; D066246:ErbB Receptors; C496365:FGFR3 protein, human; D051498:Receptor, Fibroblast Growth Factor, Type 3