Combination of Radiation with Multi-Target Molecular Therapy for Cancer

背景与意义生长因子受体在许多癌症中过度表达，其存在与不良预后相关。生长因子信号通路的激活导致细胞增殖、运动和对化疗和放疗的耐药性增加。最近的研究表明，肿瘤细胞对旨在阻断个体生长因子信号通路的治疗产生耐药性可能是由与另一种生长因子通路的串扰引起的。例如，IGF通路的激活会干扰抗egf通路的治疗。直到最近，才有了合适的软件工具和足够的计算机能力，可以对像EGF/IGF通路这样复杂的信号通路进行定量计算探索。我们建议使用专门开发的建模和仿真软件来定量探索复杂的信号传导途径。它能够自动将信号通路内的双分子相互作用的图表表示集转换为完整生化网络的定量模拟。该软件已成功地用于预测真核化学感觉g蛋白偶联信号通路以前未知的方面。在实验室验证后，应用于生长因子信号通路的计算机模型将为更好地理解它们之间的相互作用以及对肿瘤对放疗和化疗反应的综合影响提供手段，从而通过阻断这些通路的选定信号分子来设计有效的多靶点靶向治疗方法。基于现有文献数据，将使用SIMMUNE（用于生化建模和生化相互作用模拟的计算机系统）创建信号通路（最初是EGF和IGF）的详细计算模型。该模型将用于模拟细胞对生长因子的反应，以及针对选择性阻断这些途径的可能治疗干预的计算探索。其他模拟技术，包括图论、布尔网络、蒙特卡罗模拟等，也可以应用，这取决于手头的问题、实验数据的可用性以及我们计算生物学合作者的兴趣。模型的体外验证模拟预测将与应用干预对肿瘤细胞的影响进行比较，如与感兴趣的信号通路相关的基因表达和使用分子生物学方法激活选定的蛋白质，包括信号分子的western blots，高密度“反相”蛋白裂解物微阵列，RT-PCR和比较基因表达分析。将优先考虑新的定量方法。多靶点干扰EGF和IGF信号通路以及联合放疗和化疗的治疗效果的体外测试。通过模拟确定的多靶点方法对于单独使用或提供最有效的靶乳腺肿瘤细胞对放疗或化疗的致敏性是最佳的，将在体外通过毒性和克隆生存试验进行测试。这些实验将确定最佳的组合和时间，以进一步在体内进行测试。原发性和转移性乳腺癌动物模型将用于测试单独或联合阻断每种受体信号通路的治疗效果，通过计算机模拟优化并通过体外测试验证。优化的分子靶向单独或联合化疗和放疗的效果将被研究。一个结合EGF、IGF和胰岛素通路的简单模型已经被创建，并用于模拟这些通路的不同刺激/阻断的结果。一篇描述这第一步的手稿已经在《科学信号》杂志上发表，该模型是对三种通路之间的串扰进行迭代实验计算建模的

Background and Significance Growth factor receptors are overexpressed in many cancers and their presence correlates with poor prognosis. Activation of growth factors signaling pathways results in increased proliferation, motility and resistance to chemo - and radiation therapies. It has been shown recently that the resistance of tumor cells to therapy aimed at blocking individual growth factor signaling pathways may be caused by cross-talk with another growth factor pathway. For example, activation of IGF pathway interferes with anti-EGF pathway therapy. Only very recently, appropriate software tools and sufficient computer power have become available that allow a quantitative computational exploration of signaling pathways as complex as the EGF/IGF pathway. We propose to use modeling and simulation software which has been developed specifically to allow quantitative exploration of complex signaling pathways. It is capable of automatically transforming sets of diagrammatical representations of bimolecular interactions within signaling pathways into quantitative simulations of the complete biochemical network. The software has successfully been used to predict previously unknown aspects of eukaryotic chemosensory G-protein coupled signaling pathway. After verification in the laboratory, the computer model applied to growth factor signaling pathways will provide means for a better understanding of their interactions and the combined effect on tumor response to radiation and chemotherapy facilitating design of an efficient multi-target approach to targeted therapy by blocking selected signaling molecules of these pathways. Experimental procedures Development of the model and quantitative simulations Based on available literature data, a detailed computational model of signaling pathways (initially EGF and IGF) will be created using SIMMUNE, a computer system for biochemical modeling and simulation of biochemical interactions. The model will be used to simulate cellular response to growth factors and computational exploration of possible therapeutic interventions aiming at selective blocking of these pathways. Other simulation techniques, including application of graph theory, boolenian networks, Mote Carlo simulations, etc, may be applied, depending on the problem at hand, availability of experimental data, and interest of our computational biology collaborators. In vitro verification of the model Prediction of the simulation will be compared with the effects of applied interventions on tumor cells such as gene expression associated with signaling pathways of interest and activation of selected proteins using molecular biology methods including western blots of signaling molecules, high density 'reverse-phase' protein lysate microarrays, RT-PCR, and comparative gene expression analysis. Preference will be given to new quantitative methods. In vitro testing of the therapeutic efficacy of multitarget interference with EGF and IGF signaling pathways alone on in combination with radiation and chemotherapy The multitarget approach identified by the simulations as optimal for stand-alone or providing most potent sensitization of target breast tumor cells to radiation or chemotherapy will be tested in vitro using toxicity and clonogenic survival assays. These experiments will identify the optimal combinations and timing to be further tested in vivo. In vivo testing of the optimal combinations of therapeutic interventions Primary and metastatic breast cancer animal models will used to test the therapeutic efficacy of blocking signaling pathways for each receptor alone and in combination, as optimized by the computer simulations and validated by the in vitro testing. The effects of optimized molecular targeting alone or in combinations with chemo- and radiation therapy will be investigated. Accomplishments A simplistic model combing EGF, IGF, and Insulin pathways have been created and used to simulate the results of differential stimulation/blockage of these pathways. A manuscript describing this first step towards iterative experiment-computation modeling of the crosstalk between the three pathways has been submitted for publication in Science Signaling