The crosstalk between EGF, IGF, and Insulin cell signaling pathways--computational and experimental analysis.
The crosstalk between EGF, IGF, and Insulin cell signaling pathways--computational and experimental analysis.
复制标题
DOI：
10.1186/1752-0509-3-88
复制
发表时间：
2009-09-04
影响因子：
--
通讯作者：
Capala J
中科院分区：
文献类型：
--
作者：
Zielinski R;Przytycki PF;Zheng J;Zhang D;Przytycka TM;Capala J
细胞对外界刺激的反应需要通过分子信号通路传播相应的信号。然而，信令路径并不是孤立的信息高速公路，而是以多种方式相互作用，形成复杂的信令网络。由于信号通路的缺陷与许多严重疾病有关，了解它们之间的串扰是设计分子靶向治疗的基础。不幸的是，我们仍然缺乏能够对单个信号分子的活性及其相互作用进行高通量详细测量的技术。这就需要开发方法来优先选择分子，这样测量它们的活性将是理解串扰的最有用的信息。此外，由于缺乏对信号传播进行详细建模所需的反应系数，因此提出了一个问题，即简单的无参数模型是否可以提供有关此类路径的有用信息。我们研究了三个主要促生存信号通路的联合信号网络：表皮生长因子受体(EGFR)、胰岛素样生长因子-1受体(IGF-1R)和胰岛素受体(IR)。我们的研究包括对这个网络的静态分析和动态建模，以及通过测量选定的信号分子对EGF、IGF和胰岛素受体的不同刺激的反应来对该模型进行实验验证。在这种串扰的背景下，我们引入了两个衡量节点重要性的新方法。基于这些测量，选择了几个分子，即ERK1/2、Akt1、JNK、P70S6K进行网络模拟和实验研究。我们的仿真方法依赖于布尔网络模型和信号的随机传播。模拟提出的大多数(尽管不是全部)趋势已经得到了实验的证实。本文实现的简单模型为信令网络建模提供了有价值的第一步。然而，为了获得一个完全可预测的模型，可能需要更详细的关于单个交互作用参数的知识。
Cellular response to external stimuli requires propagation of corresponding signals through molecular signaling pathways. However, signaling pathways are not isolated information highways, but rather interact in a number of ways forming sophisticated signaling networks. Since defects in signaling pathways are associated with many serious diseases, understanding of the crosstalk between them is fundamental for designing molecularly targeted therapy. Unfortunately, we still lack technology that would allow high throughput detailed measurement of activity of individual signaling molecules and their interactions. This necessitates developing methods to prioritize selection of the molecules such that measuring their activity would be most informative for understanding the crosstalk. Furthermore, absence of the reaction coefficients necessary for detailed modeling of signal propagation raises the question whether simple parameter-free models could provide useful information about such pathways. We study the combined signaling network of three major pro-survival signaling pathways: Epidermal Growth Factor Receptor (EGFR), Insulin-like Growth Factor-1 Receptor (IGF-1R), and Insulin Receptor (IR). Our study involves static analysis and dynamic modeling of this network, as well as an experimental verification of the model by measuring the response of selected signaling molecules to differential stimulation of EGF, IGF and insulin receptors. We introduced two novel measures of the importance of a node in the context of such crosstalk. Based on these measures several molecules, namely Erk1/2, Akt1, Jnk, p70S6K, were selected for monitoring in the network simulation and for experimental studies. Our simulation method relies on the Boolean network model combined with stochastic propagation of the signal. Most (although not all) trends suggested by the simulations have been confirmed by experiments. The simple model implemented in this paper provides a valuable first step in modeling signaling networks. However, to obtain a fully predictive model, a more detailed knowledge regarding parameters of individual interactions might be necessary.
登录
查看更多内容
影响因子：
4.3
作者：
Batada NN;Hurst LD;Tyers M
通讯作者：
Tyers M
DOI：
10.1016/j.bbrc.2003.12.007
发表时间：
2004-01-16
影响因子：
3.1
作者：
Lu, YH;Zi, XL;Pollak, M
通讯作者：
Pollak, M
影响因子：
1.7
作者：
Janes, KA;Kelly, JR;Lauffenburger, DA
通讯作者：
Lauffenburger, DA
影响因子：
7
作者：
Janes, KA;Albeck, JG;Yaffe, MB
通讯作者：
Yaffe, MB
影响因子：
64.8
作者：
Jeong, H;Tombor, B;Barabási, AL
通讯作者：
Barabási, AL