Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors
Figure 5
A–E: Meso scale networks Ba/F3-p210 cells.
(A) High degree of co-regulation across the protein set for IM, DASA and NILO, which can effectively represented by the mean component of factor analysis. (B) Significant deviations for a small set of proteins for DANU suggesting the use of the more stable factor analysis instead of PCA for reduction of dimension. (C) Analysis quantitatively the amount of induction of protein expression, which is associated with the activation of the dominant mechanisms, quantified by the mean component of factor analysis. Whereas a good and almost similar behaviour for IM, DASA and NILO is observed, DANU activates the proteins in two clearly separated modes (indicated by the upper and lower line of red stars). This finding is supported by quantitatively testing the distribution of the residuals of protein expressions with respect to the linear regression model given by the mean component of factor analysis. (D) Apparently only DANU induces residuals with significant non-gaussian noise indicating the existence of two separate mechanisms of protein induction. (E) Structure of meso scale pathways for induced protein expression. Black block represents induction of the protein expression by the main pathway, whereas the red block is indicating an inhibition via the main pathway.