Data-driven computer simulation of human cancer cell.

Abstract

Using the Diagrammatic Cell Language trade mark, Gene Network Sciences (GNS) has created a network model of interconnected signal transduction pathways and gene expression networks that control human cell proliferation and apoptosis. It includes receptor activation and mitogenic signaling, initiation of cell cycle, and passage of checkpoints and apoptosis. Time-course experiments measuring mRNA abundance and protein activity are conducted on Caco-2 and HCT 116 colon cell lines. These data were used to constrain unknown regulatory interactions and kinetic parameters via sensitivity analysis and parameter optimization methods contained in the DigitalCell computer simulation platform. FACS, RNA knockdown, cell growth, and apoptosis data are also used to constrain the model and to identify unknown pathways, and cross talk between known pathways will also be discussed. Using the cell simulation, GNS tested the efficacy of various drug targets and performed validation experiments to test computer simulation predictions. The simulation is a powerful tool that can in principle incorporate patient-specific data on the DNA, RNA, and protein levels for assessing efficacy of therapeutics in specific patient populations and can greatly impact success of a given therapeutic strategy.