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首页> 外文会议>International Conference on Algebraic and Numeric Biology >Computational Modeling and Verification of Signaling Pathways in Cancer
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Computational Modeling and Verification of Signaling Pathways in Cancer

机译：癌症中信号通路的计算建模与验证

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We propose and analyze a rule-based model of the HMGB1 signaling pathway. The protein HMGB1 can activate a number of regulatory networks - the p53, NFKB, Ras and Rb pathways - that control many physiological processes of the cell. HMGB1 has been recently shown to be implicated in cancer, inflammation and other diseases. In this paper, we focus on the NFkB pathway and construct a crosstalk model of the HMGB1-p53-NFkB-Ras-Rb network to investigate how these couplings influence proliferation and apoptosis (programmed cell death) of cancer cells. We first built a single-cell model of the HMGB1 network using the rule-based BioNetGen language. Then, we analyzed and verified qualitative properties of the model by means of simulation and statistical model checking. For model simulation, we used both ordinary differential equations and Gillespie's stochastic simulation algorithm. Statistical model checking enabled us to verify our model with respect to behavioral properties expressed in temporal logic. Our analysis showed that HMGB1-activated receptors can generate sustained oscillations of irregular amplitude for the NFKB, IKB, A20 and p53 proteins. Also, knockout of A20 can destroy the IKB-NFKB negative feedback loop, leading to the development of severe inflammation or cancer. Our model also predicted that the knockout or overexpression of the IKB kinase can influence the cancer cell's fate - apoptosis or survival - through the crosstalk of different pathways. Finally, our work shows that computational modeling and statistical model checking can be effectively combined in the study of biological signaling pathways.
机译：我们提出并分析了HMGB1信令路径的基于规则的模型。蛋白质HMGB1可以激活许多调节网络 - P53，NFKB，RAS和RB途径 - 控制细胞的许多生理过程。最近已显示HMGB1涉及癌症，炎症和其他疾病。在本文中，我们专注于NFKB途径，构建HMGB1-P53-NFKB-RAS-RB网络的串扰模型，以研究这些偶联如何影响癌细胞的增殖和凋亡（编程细胞死亡）。我们首先使用基于规则的Bionetgen语言构建了HMGB1网络的单个单元格模型。然后，我们通过模拟和统计模型检查分析和验证了模型的定性特性。对于模型仿真，我们使用了普通微分方程和Gillespie的随机仿真算法。统计模型检查使我们能够验证我们的模型是否相对于在时间逻辑中表达的行为属性。我们的分析表明，HMGB1活化受体可以为NFKB，IKB，A20和P53蛋白产生不规则振幅的持续振荡。此外，A20的敲除可以破坏IKB-NFKB负反馈回路，导致严重炎症或癌症的发展。我们的模型还预测，IKB激酶的敲除或过表达可以影响癌细胞的命运 - 细胞凋亡或存活 - 通过不同途径的串扰。最后，我们的工作表明，在生物信号传导途径的研究中可以有效地结合计算建模和统计模型检查。

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