Functional aspects of the EGF-induced MAP kinase cascade: a complex self-organizing system approach

• Published in: PloS one 2014-11, Vol.9 (11), p.e111612-e111612
• Main Authors: Kosmidis, Efstratios K, Moschou, Vasiliki, Ziogas, Georgios, Boukovinas, Ioannis, Albani, Maria, Laskaris, Nikolaos A
• Format: Article
• Language: English
• Subjects: Activation; Algorithms; Analysis; Bioinformatics; Biology; Biology and Life Sciences; Cancer therapies; Cluster Analysis; Clustering; College campuses; Computer applications; Control theory; Deregulation; Epidermal growth factor; Epidermal Growth Factor - metabolism; Epidermal Growth Factor - pharmacology; Epidermal growth factors; Functional groups; Functional morphology; Gene expression; Informatics; Intracellular signalling; Kinases; Laboratories; Ligands; MAP kinase; MAP Kinase Signaling System - drug effects; Medicine; Models, Biological; Multivariate analysis; Physiology; Precision medicine; Protein Binding; Protein Interaction Maps; Proteins; Self organizing systems; Signal transduction; Studies; Topology
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0111612

The EGF-induced MAP kinase cascade is one of the most important and best characterized networks in intracellular signalling. It has a vital role in the development and maturation of living organisms. However, when deregulated, it is involved in the onset of a number of diseases. Based on a computational model describing a "surface" and an "internalized" parallel route, we use systems biology techniques to characterize aspects of the network's functional organization. We examine the re-organization of protein groups from low to high external stimulation, define functional groups of proteins within the network, determine the parameter best encoding for input intensity and predict the effect of protein removal to the system's output response. Extensive functional re-organization of proteins is observed in the lower end of stimulus concentrations. As we move to higher concentrations the variability is less pronounced. 6 functional groups have emerged from a consensus clustering approach, reflecting different dynamical aspects of the network. Mutual information investigation revealed that the maximum activation rate of the two output proteins best encodes for stimulus intensity. Removal of each protein of the network resulted in a range of graded effects, from complete silencing to intense activation. Our results provide a new "vista" of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems. Functional grouping of the proteins reveals an organizational scheme contrasting the current understanding of modular topology. The six identified groups may provide the means to experimentally follow the dynamics of this complex network. Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.