The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data.
The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data.
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DOI：
10.1371/journal.pcbi.1000438
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发表时间：
2009-08
影响因子：
4.3
通讯作者：
Klamt S
中科院分区：
文献类型：
--
作者：
Samaga R;Saez-Rodriguez J;Alexopoulos LG;Sorger PK;Klamt S
表皮生长因子受体（epidermal growth factor receptor，EGFR）信号通路可能是哺乳动物细胞中研究得最多的受体系统，也是细胞信号网络数学建模的一个热门例子。动态模型具有最高的解释和预测潜力;然而，缺乏动力学信息限制了EGFR信号传导的当前模型到较小的子网络。这项工作旨在提供一个大规模的定性模型，包括EGFR/ErbB信号传导的主要途径和侧途径，并且仍然使人们能够获得重要的功能特性和预测。使用最近推出的逻辑建模框架，我们首先研究了一般的拓扑性质和定性的刺激反应行为的网络。与物种等价类，我们介绍了一种新的技术，逻辑网络，揭示了强烈耦合的节点集在他们的行为。我们还分析了一个模型变量，该变量明确说明了模型中信号逻辑组合的不确定性。该模型的预测能力仍然很高，表明网络中存在高度冗余的子结构。最后，这项工作的一个关键进展是引入了新技术，用于评估具有逻辑模型（及其底层交互图）的高吞吐量数据。通过采用这些技术从原代肝细胞和HepG 2细胞系的磷酸化蛋白质组学数据，我们表明，我们的方法使人们能够发现实验结果和我们目前的定性知识之间的不一致，并产生新的假设和结论。我们的研究结果强烈表明，Rac/Cdc 42诱导的p38和JNK级联是独立的PI 3 K在原代肝细胞和HepG 2。此外，我们检测到JNK的激活响应neuregulin遵循PI 3 K依赖性信号通路。表皮生长因子受体（EGFR）信号通路可以说是哺乳动物细胞中最具特征的受体系统，并已成为细胞信号转导数学建模的主要例子。大多数这些模型的构建是为了描述动态和定量的事件，但由于缺乏精确的动力学信息，只关注网络的某些区域。依赖于网络结构的定性建模方法提供了一种合适的方式来处理大规模网络作为一个整体。在这里，我们构建了一个全面的定性模型的EGFR/ErbB信号通路与200多个相互作用，反映了我们目前的知识水平。理论分析揭示了网络的重要拓扑和功能特性，如定性刺激反应行为和冗余子结构。随后，我们展示了如何使用这种定性模型来评估高通量数据，从而获得新的生物学见解：将我们的模型的定性预测（如预期的激活水平的“上升”和“唐斯”）与原代人肝细胞和肝癌细胞系HepG 2的实验数据进行比较，我们发现了测量和模型结构之间的不一致。这些差异导致至少与肝脏生物学相关的EGFR/ErbB信号网络的修改。
The epidermal growth factor receptor (EGFR) signaling pathway is probably the best-studied receptor system in mammalian cells, and it also has become a popular example for employing mathematical modeling to cellular signaling networks. Dynamic models have the highest explanatory and predictive potential; however, the lack of kinetic information restricts current models of EGFR signaling to smaller sub-networks. This work aims to provide a large-scale qualitative model that comprises the main and also the side routes of EGFR/ErbB signaling and that still enables one to derive important functional properties and predictions. Using a recently introduced logical modeling framework, we first examined general topological properties and the qualitative stimulus-response behavior of the network. With species equivalence classes, we introduce a new technique for logical networks that reveals sets of nodes strongly coupled in their behavior. We also analyzed a model variant which explicitly accounts for uncertainties regarding the logical combination of signals in the model. The predictive power of this model is still high, indicating highly redundant sub-structures in the network. Finally, one key advance of this work is the introduction of new techniques for assessing high-throughput data with logical models (and their underlying interaction graph). By employing these techniques for phospho-proteomic data from primary hepatocytes and the HepG2 cell line, we demonstrate that our approach enables one to uncover inconsistencies between experimental results and our current qualitative knowledge and to generate new hypotheses and conclusions. Our results strongly suggest that the Rac/Cdc42 induced p38 and JNK cascades are independent of PI3K in both primary hepatocytes and HepG2. Furthermore, we detected that the activation of JNK in response to neuregulin follows a PI3K-dependent signaling pathway. The epidermal growth factor receptor (EGFR) signaling pathway is arguably the best-characterized receptor system in mammalian cells and has become a prime example for mathematical modeling of cellular signal transduction. Most of these models are constructed to describe dynamic and quantitative events but, due to the lack of precise kinetic information, focus only on certain regions of the network. Qualitative modeling approaches relying on the network structure provide a suitable way to deal with large-scale networks as a whole. Here, we constructed a comprehensive qualitative model of the EGFR/ErbB signaling pathway with more than 200 interactions reflecting our current state of knowledge. A theoretical analysis revealed important topological and functional properties of the network such as qualitative stimulus-response behavior and redundant sub-structures. Subsequently, we demonstrate how this qualitative model can be used to assess high-throughput data leading to new biological insights: comparing qualitative predictions (such as expected “ups” and “downs” of activation levels) of our model with experimental data from primary human hepatocytes and from the liver cancer cell line HepG2, we uncovered inconsistencies between measurements and model structure. These discrepancies lead to modifications in the EGFR/ErbB signaling network relevant at least for liver biology.
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DOI：
10.1049/ip-syb:20050057
发表时间：
2006-01-01
期刊：
IEE PROCEEDINGS SYSTEMS BIOLOGY
影响因子：
--
作者：
Hendriks, BS;Cook, J;de Graaf, D
通讯作者：
de Graaf, D
影响因子：
9.9
作者：
Nelander, Sven;Wang, Weiqing;Nilsson, Bjoern;She, Qing-Bai;Pratilas, Christine;Rosen, Neal;Gennemark, Peter;Sander, Chris
通讯作者：
Sander, Chris
影响因子：
3
作者：
Gagneur J;Klamt S
通讯作者：
Klamt S
影响因子：
2
作者：
Papin, JA;Palsson, BO
通讯作者：
Palsson, BO
影响因子：
64.8
作者：
Jeong, H;Mason, SP;Oltvai, ZN
通讯作者：
Oltvai, ZN