A computational model of off-target drug effects due to retroactive signaling

MICHELLE WYNN; ALEJANDRA C VENTURA; HECTOR GARCIA; SOFIA D MERAJVER

Simposio; Cancer Research Symposium; 2009

A majority of targeted cancer therapeutics involve the specific inhibition of a molecular target in a signal transduction pathway known to be activated in cancer.  It is well known that targeted therapies, such as kinase inhibitors, may have effects on pathways other than those specifically targeted, whether by non-specific interactions or by indirect pathway cross-talk effects.  The simplest view of signal transduction entails a cascade of molecular events initiated by the recognition of a stimulus and culminating in the chemical alteration of an effector molecule. We have recently shown via a theoretical model that cascades can exhibit bidirectional signal propagation without the addition of regulatory feedback connections via a phenomenon termed retroactivity.  These results challenge the notion that information in cascades only flows in the cell surface-to-nucleus direction and suggests that a perturbation applied within a cascade can produce both an upstream and a downstream effect.  The notion of an upstream off-target effect is completely novel and may have significant implications if the perturbation takes the form of an inhibitory therapeutic drug.    We have extended our previous work to a model which allows us to computationally characterize the significance of the upstream off-target effect via retroactivity with a series of simple signaling networks using physiologically relevant parameters values.   One of the signaling networks studied takes the form of two independent signaling cascades which have no regulatory feedback connections but are activated by the same upstream kinase.  Our results suggest that under physiologically relevant conditions the application of an inhibitor near the bottom of one cascade can produce a significant change in concentration of a protein in the other cascade.  Developing a deeper understanding of bidirectional signal propagation in signal transduction pathways will be vitally important in the effort to develop safer and more effective targeted cancer therapies.