Cross-scale, cross-pathway evaluation using an agent-based non-small cell lung cancer model

Bioinformatics
Zhihui WangThomas S Deisboeck

Abstract

We present a multiscale agent-based non-small cell lung cancer model that consists of a 3D environment with which cancer cells interact while processing phenotypic changes. At the molecular level, transforming growth factor beta (TGFbeta) has been integrated into our previously developed in silico model as a second extrinsic input in addition to epidermal growth factor (EGF). The main aim of this study is to investigate how the effects of individual and combinatorial change in EGF and TGFbeta concentrations at the molecular level alter tumor growth dynamics on the multi-cellular level, specifically tumor volume and expansion rate. Our simulation results show that separate EGF and TGFbeta fluctuations trigger competing multi-cellular phenotypes, yet synchronous EGF and TGFbeta signaling yields a spatially more aggressive tumor that overall exhibits an EGF-driven phenotype. By altering EGF and TGFbeta concentration levels simultaneously and asynchronously, we discovered a particular region of EGF-TGFbeta profiles that ensures phenotypic stability of the tumor system. Within this region, concentration changes in EGF and TGFbeta do not impact the resulting multi-cellular response substantially, while outside these concentration ran...Continue Reading

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Related Concepts

Biochemical Pathway
Fluctuation
Transforming Growth Factor beta
Tumor Expansion
Epidermal Growth Factor
Signal Transduction Pathways
Non-Small Cell Lung Carcinoma
TGFB1 gene
Tumor Cells, Malignant
Epidermal Growth Factor Receptor Binding Activity

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