Combination of Radiation with Multi-Target Molecular Therapy for Cancer

背景和意义生长因子受体在许多癌症中过度表达，其存在与预后不良有关。生长因子信号通路的激活会增加细胞的增殖、活力以及对化疗和放射治疗的抵抗力。最近的研究表明，肿瘤细胞对旨在阻断单个生长因子信号通路的治疗的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途径的激活干扰了抗EGF途径的治疗。直到最近，适当的软件工具和足够的计算机能力才出现，允许对像EGF/IGF途径这样复杂的信号通路进行定量的计算探索。我们建议使用专门开发的建模和仿真软件，以便对复杂的信号通路进行定量探索。它能够自动将信号通路中双分子相互作用的图解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以前未知的真核化学感觉G蛋白偶联信号通路。经过实验室验证，应用于生长因子信号通路的计算机模型将为更好地了解它们之间的相互作用以及对肿瘤放射和化疗反应的综合影响提供手段，有助于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。实验程序模型的开发和定量模拟基于现有的文献数据，将使用SIMMUNE创建信号通路(最初为EGF和IGF)的详细计算模型，SIMMUNE是用于生化建模和模拟生化相互作用的计算机系统。该模型将用于模拟细胞对生长因子的反应，并对旨在选择性阻断这些途径的可能的治疗干预进行计算探索。其他模拟技术，包括图论的应用、布尔网络、Mote Carlo模拟等，也可以应用，这取决于手头的问题、实验数据的可用性和我们的计算生物学合作者的兴趣。模型的体外验证模拟的预测将与所应用的干预措施对肿瘤细胞的影响进行比较，例如与感兴趣的信号通路相关的基因表达和所选蛋白质的激活，使用包括信号分子的蛋白质印迹、高密度反相蛋白裂解物微阵列、RT-PCR和比较基因表达分析在内的分子生物学方法。将优先考虑新的定量方法。在体外测试多靶点干扰EGF和IGF信号通路与放化疗相结合的治疗效果。多靶点干扰方法被模拟确定为最适合单独使用或提供对放射或化疗最有效的靶乳腺肿瘤细胞增敏的方法，将使用毒性和克隆生存分析进行体外测试。这些实验将确定最佳的组合和时机，以便进一步在体内进行测试。治疗干预措施最佳组合的体内测试初步和转移性乳腺癌动物模型将被用来测试阻断每个受体的信号通路单独和组合的治疗效果，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与化疗和放射治疗相结合的效果将被调查。项目状态免疫系统正在被修改，以适应在EGFR激活期间建立的大型复合体。利用文献资料建立了相关参数数据库。一些文献数据中的巨大差异需要我们的实验室和合作者在良好控制的条件下进行验证。我们正在使用最先进的方法确定要量化的关键参数。PathExplorer是一种相对简单的方法，它使用图论来分析信号转导，允许评估阻断(甚至部分，例如25%或50%)不同信号通路节点对信号转导的影响，并可以识别为了获得受这些通路影响的活性和失活基因的任意组合而必须被阻断的节点组合，该方法已经准备好进行验证。这些发现已经以海报的形式公布了。对组合的EGFR、HER2、IGF-1R和IR进行了模拟。我们正在建立一个模型来进行模拟的实验验证

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. Project Status Simmune system is being modified to accommodate large complexes build during activation of EGFR. Database of relevant parameters have been build using the literature. Large discrepancies in some of the literature data necessitate their verification by our lab and collaborators in well controlled conditions. We are in the process of identification of the crucial parameters to be quantified using the state of the art methods. PathExplorer, a relatively simple approach, using graph theory to analyze signal transduction that allows to assess the effects of blocking (even partial, e.g. 25% or 50%) different nodes of signaling pathways on signal transduction and can identify combinations of nodes that have to be blocked in order to obtain an arbitrary combination of active and inactivated genes influenced by these pathways, is ready for verification. The findings have been presented as poster. Simulations of combined EGFR, HER2, IGF-1R, and IR are carried out. We are establishing a model for experimental verification of the simulations