Zhao Linjie, Sun Tanlin, Pei Jianfeng, Ouyang Qi
State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China;
Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China;
Proc Natl Acad Sci U S A. 2015 Jul 28;112(30):E4046-54. doi: 10.1073/pnas.1502126112. Epub 2015 Jul 13.
It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant-wild-type and 16 matched SNP--wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation.
癌症研究中的一个共识是,癌症是一种主要由基因组改变引起的疾病,尤其是体细胞突变。然而,突变诱导肿瘤发生的机制尚未完全了解。在此,我们以线粒体凋亡途径为例进行研究,并对途径动力学与蛋白质相互作用动力学进行系统整合分析,以定量研究突变诱导肿瘤发生的因果分子机制。构建了调控网络的数学模型,以确定动态分岔在凋亡过程中的功能作用。发现所涉及的每个蛋白质功能域的致癌突变富集与分岔点的参数敏感性密切相关。我们通过分子动力学模拟评估突变对蛋白质相互作用动力学的影响,进一步剖析了这种相关性背后的因果机制。我们分析了29对匹配的突变型-野生型和16对匹配的单核苷酸多态性-野生型蛋白质系统。我们发现,蛋白质相互作用突变引起的自由能变化的改变所反映的结合动力学变化,会诱导分岔点敏感参数的变化,这是凋亡途径功能障碍的主要原因,且涉及敏感相互作用域的突变具有很高的致癌潜力。我们的分析为连接蛋白质突变、蛋白质相互作用动力学、网络动力学特性和调控网络的生理功能提供了分子基础。这些见解为将突变基因型与肿瘤发生表型联系起来提供了一个框架,并有助于阐明癌症发生的逻辑。