Figure 1

Computational model of ErbB signaling. (a) Heat map of ligand screen following subtraction of each cell lines median HSA control-based Akt signal and normalizing the signals within a cell line to the maximum ligand activation for that cell line. (b) Schematic depiction of the ErbB signaling network showing the receptors EGFR–ErbB4, BTC binding to EGFR and HRG binding to the ErbB3 receptor, receptor dimerization, dimer internalization and recycling, and interactions leading to activation of the PI3K-Akt cascade. The computational model is an interpretation of this schematic, using mass action kinetics. Because of the low expression observed in vitro, ErbB4 was omitted from the computational model. (c) The computational model was calibrated to a high-density experimental signaling data set. Phosphorylated-EGFR, HER2 and HER3− as well as p-Akt were measured in serum-starved ADRr ovarian cancer cells stimulated with HRG or BTC. The model was built in MATLAB SimBiology v2.1. A genetic algorithm was used to fit key parameters. Both experimental and simulated data are normalized to the largest signal for each target under either stimulus. (d) Sensitivity analysis of the ErbB model. The normalized time-integrated sensitivity of Akt phosphorylation to each non-zero species was determined by varying the amount of each non-zero species and simulating the time course of p-Akt in response to 1 nmol/l HRG or BTC, with the calibrated computational model. The normalized sensitivity integrated over the 2 h time course is shown, with species ranked according to their sensitivity during HRG stimulation. Figures 1b and c from Schoeberl et al.¹ Reprinted with permission from AAAS.