Receptor Tyrosine Kinase Signaling Networks

描述（由申请人提供）：由于受体酪氨酸激酶（RTK）在控制关键细胞过程（包括增殖、分化、代谢、存活和凋亡）中的重要作用，本项目具有健康相关性。表皮生长因子受体（EGFR）和胰岛素受体（IR）的异常信号是许多人类疾病的主要原因，从糖尿病到慢性炎症综合征和癌症。尽管我们对RTK信号网络中涉及的蛋白质和脂质成分的知识迅速增长，但它们的动态行为和通路间串扰的综合定量图像仍然难以捉摸。计算模型，包括我们小组开发的EGFR通路模型，已经成为一种新的工具，可以深入了解外部刺激和细胞反应之间的复杂关系，并揭示使RTK网络能够放大和处理信号、减少噪声和产生双稳态动态或振荡的机制。最近的发现改变了我们对信号特异性本质的看法，并表明参与EGFR和IR信号网络的相同蛋白质库的不同时空激活谱导致不同的基因激活模式和不同的生理反应。在之前的支持期间，我们的工作已经证明了一种新的跨学科方法的巨大潜力，该方法结合了实验研究、非线性系统分析和交互式计算模型，以实现对RTK信号网络的定量理解。在本应用中，我们将确定控制对EGF和胰岛素的不同反应模式的分子和动力学因素，验证计算模型提出的关于时空动力学和EGFR-IR串扰调节的假设，并研究细胞如何以上下文依赖的方式解释信号。与时间反应一起，将分析EGFR和ir介导的信号传导的空间模式，以理解关键的细胞命运决定。这一发现将为预测细胞对生长因子和胰岛素的反应提供有力的工具，这一分析是理解导致癌症和糖尿病的机制的关键。具体目的是：(1)扩展EGFR网络的定量分析，阐明有丝分裂（Ras/ERK）和生存（PI3K/Akt）信号通路之间的功能相互作用；(2)确定MARK级联的时空动态对转录因子反应的影响，包括亚细胞定位和潜在的可测试性；(3)阐明胰岛素对EGF有丝分裂信号的增强作用，并将EGFR和IR网络整合到我们的实验和计算分析中。

DESCRIPTION (provided by applicant): The present project has health relevance due to the important role of receptor tyrosine kinases (RTK) in control of pivotal cellular processes, including proliferation, differentiation, metabolism, survival, and apoptosis. Aberrant signaling by the epidermal growth factor receptor (EGFR) and insulin receptor (IR) is a leading cause of many human diseases that range from diabetes to chronic inflammatory syndromes and cancer. Despite a rapid growth of our knowledge of protein and lipid components involved in RTK signaling networks, an integrative, quantitative picture of their dynamic behavior and interpathway crosstalk remains elusive. Computational models, including EGFR pathway models developed by our group, have emerged as a novel tool to provide insights into the intricate relationships between external stimuli and cellular responses and reveal mechanisms that enable RTK networks to amplify and process signals, reduce noise and generate bistable dynamics or oscillations. Recent discoveries have changed our perception of the nature of signal specificity and showed that distinct spatio-temporal activation profiles of the same repertoire of proteins involved in the EGFR and IR signaling networks result in different gene activation patterns and diverse physiological responses. During the previous period of support, our work has demonstrated the considerable potential of a novel cross-disciplinary approach that combines experimental studies, nonlinear systems analysis and interactive computational models to achieve a quantitative understanding of RTK signaling networks. In this application we will determine the molecular and kinetic factors controlling the different response patterns to EGF and insulin, validate hypotheses about the regulation of the spatio- temporal dynamics and EGFR-IR crosstalk suggested by computational modeling, and examine how cells interpret signals in a context-dependent manner. Together with temporal responses, the spatial pattern of the EGFR- and IR-mediated signaling will be analyzed to comprehend critical cell fate decisions. The findings will provide a powerful tool to predict cellular responses to growth factors and insulin, and this analysis is the key to understanding the mechanisms causing cancer and diabetes. The Specific Aims are: (1) To extend the quantitative analysis of the EGFR network and elucidate functional interactions between mitogenic (Ras/ERK) and survival (PI3K/Akt) signaling pathways; (2) To determine the consequences of the spatio- temporal dynamics of the MARK cascade, including subcellular localization and potential testability, on transcription factor responses; (3) To elucidate the potentiation by insulin of EGF mitogenic signaling and integrate the EGFR and IR networks into our experimental and computational analyses.