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.
PLoS Comput Biol. 2013 Oct;9(10):e1003286. doi: 10.1371/journal.pcbi.1003286. Epub 2013 Oct 24.
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.
丝裂原活化蛋白激酶 (MAPK) 网络由紧密相互连接的信号通路组成,参与多种细胞过程,如细胞周期、存活、凋亡和分化。尽管有几项研究报道了这些信号级联在癌症失调中的参与,但它们对病理情况下细胞增殖和细胞死亡(细胞命运决定)之间平衡的影响的确切机制仍不清楚。基于对已发表数据的广泛分析,我们使用 CellDesigner 软件为 MAPK 信号网络构建了一个全面而通用的反应图。为了探索 MAPK 对不同刺激的反应,并更好地理解它们对细胞命运决定的贡献,我们考虑了最关键的组件和相互作用,并使用软件 GINsim 将它们编码为逻辑模型。我们的逻辑模型分析特别关注膀胱癌,其中 MAPK 网络失调经常与特定表型相关。为了应对状态数量的组合爆炸,我们应用了新的算法来减少模型和压缩状态转换图,这些算法都在软件 GINsim 中实现。不同信号组合和网络扰动的系统模拟结果与已发表的数据在全局上一致。在计算机上进行的实验进一步使我们能够描绘特定组件、串扰和调节反馈在细胞命运决定中的作用。最后,可以将推定的增殖或抗增殖机制与已建立的膀胱癌失调联系起来,即表皮生长因子受体 (EGFR) 过表达和成纤维细胞生长因子受体 3 (FGFR3) 激活突变。