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      The Logic of EGFR/ErbB Signaling: Theoretical Properties and Analysis of High-Throughput Data

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          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.

          Author Summary

          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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          Most cited references 40

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          A comprehensive pathway map of epidermal growth factor receptor signaling

          The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).
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            The multifaceted roles of glycogen synthase kinase 3beta in cellular signaling.

            Glycogen synthase kinase-3beta (GSK3beta) is a fascinating enzyme with an astoundingly diverse number of actions in intracellular signaling systems. GSK3beta activity is regulated by serine (inhibitory) and tyrosine (stimulatory) phosphorylation, by protein complex formation, and by its intracellular localization. GSK3beta phosphorylates and thereby regulates the functions of many metabolic, signaling, and structural proteins. Notable among the signaling proteins regulated by GSK3beta are the many transcription factors, including activator protein-1, cyclic AMP response element binding protein, heat shock factor-1, nuclear factor of activated T cells, Myc, beta-catenin, CCAAT/enhancer binding protein, and NFkappaB. Lithium, the primary therapeutic agent for bipolar mood disorder, is a selective inhibitor of GSK3beta. This raises the possibility that dysregulation of GSK3beta and its inhibition by lithium may contribute to the disorder and its treatment, respectively. GSK3beta has been linked to all of the primary abnormalities associated with Alzheimer's disease. These include interactions between GSK3beta and components of the plaque-producing amyloid system, the participation of GSK3beta in phosphorylating the microtubule-binding protein tau that may contribute to the formation of neurofibrillary tangles, and interactions of GSK3beta with presenilin and other Alzheimer's disease-associated proteins. GSK3beta also regulates cell survival, as it facilitates a variety of apoptotic mechanisms, and lithium provides protection from many insults. Thus, GSK3beta has a central role regulating neuronal plasticity, gene expression, and cell survival, and may be a key component of certain psychiatric and neurodegenerative diseases.
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              Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors.

              We present a computational model that offers an integrated quantitative, dynamic, and topological representation of intracellular signal networks, based on known components of epidermal growth factor (EGF) receptor signal pathways. The model provides insight into signal-response relationships between the binding of EGF to its receptor at the cell surface and the activation of downstream proteins in the signaling cascade. It shows that EGF-induced responses are remarkably stable over a 100-fold range of ligand concentration and that the critical parameter in determining signal efficacy is the initial velocity of receptor activation. The predictions of the model agree well with experimental analysis of the effect of EGF on two downstream responses, phosphorylation of ERK-1/2 and expression of the target gene, c-fos.

                Author and article information

                Role: Editor
                PLoS Comput Biol
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                August 2009
                August 2009
                7 August 2009
                : 5
                : 8
                [1 ]Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
                [2 ]Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
                [3 ]Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
                [4 ]Department of Mechanical Engineering, National Technical University of Athens, Athens, Greece
                California Institute of Technology, United States of America
                Author notes

                Conceived and designed the experiments: JS-R LGA PKS. Performed the experiments: LGA. Analyzed the data: RS JS-R LGA SK. Contributed reagents/materials/analysis tools: RS JS-R LGA PKS SK. Wrote the paper: RS JS-R LGA PKS SK. Software and algorithm development: RS. Software and algorithm development: SK.

                Samaga et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 19
                Research Article
                Cell Biology/Cell Signaling
                Computational Biology
                Computational Biology/Signaling Networks
                Computational Biology/Systems Biology

                Quantitative & Systems biology


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