Identifying therapeutic targets in a combined EGFR-TGF beta R signalling cascade using a multiscale agent-based cancer model

Authored by Zhihui Wang, Jonathan Sagotsky, Thomas S. Deisboeck, Veronika Bordas

Date Published: 2012-03

DOI: 10.1093/imammb/dqq023

Sponsors: United States National Institutes of Health (NIH)

Platforms: C++

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Applying a previously developed non-small cell lung cancer model, we assess `cross-scale' the therapeutic efficacy of targeting a variety of molecular components of the epidermal growth factor receptor (EGFR) signalling pathway. Simulation of therapeutic inhibition and amplification allows for the ranking of the implemented downstream EGFR signalling molecules according to their therapeutic values or indices. Analysis identifies mitogen-activated protein kinase and extracellular signal-regulated kinase as top therapeutic targets for both inhibition and amplification-based treatment regimen but indicates that combined parameter perturbations do not necessarily improve the therapeutic effect of the separate parameter treatments as much as might be expected. Potential future strategies using this in silico model to tailor molecular treatment regimen are discussed.

Tags

Agent-based model epidermal growth factor receptor Multiscale Transforming growth factor beta signalling pathway non-small cell lung cancer