Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling

• DOI: 10.1371/journal.pcbi.1004192
• Publication Date: 2015-04-23T20:22:16Z
• Authors: Lorenza A. D’Ales...; Regina Samaga; Tim Maiwald; Seong-Hwan Rho; Sandra Bonefas; Andreas Raue; Nao Iwamoto; Alexandra Kienast; Katharina Waldow; Rene Meyer; Marcel Schilling; Jens Timmer; Steffen Klamt; Ursula Klingmüller
• Keywords: Crosstalk

Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex cell-context specific signaling networks. Dissecting the underlying relations is crucial predict impact of targeted perturbations. However, a major challenge in identifying networks enormous number potentially possible interactions. Here, we report novel hybrid mathematical modeling strategy systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) mitogen activated protein kinase (MAPK) signaling, which critically contribute liver regeneration. By combining time-resolved quantitative experimental data generated primary mouse hepatocytes with interaction graph ordinary differential equation modeling, identify experimentally validate network structure that represents best indicates crosstalk mechanisms. Whereas identified robust against single perturbations, combinatorial inhibition strategies predicted result strong reduction Akt ERK activation. Thus, capitalizing on advantages two approaches, reduce high complexity