Pre-disease Detection Using Dynamical Network Biomarkers in Gene Regulatory Networks with Cell-to-cell Interaction

Abstract

Dynamical Network Biomarkers (DNB) theory has been proposed as a method for detecting diseases at a very early stage. The progression of a disease can be regarded as a bifurcation phenomenon of the underlying dynamical system associated with the corresponding gene network. By identifying large fluctuations of the gene expression level occurring just before the bifurcation, we can detect the pre-disease stage without identifying the mathematical model of the dynamical system. However, the existing DNB theory mainly focuses on a single gene network representing averaged dynamics of multiple cells not explicitly handling a group of cells with cell-to-cell interaction. In this study, we extend the DNB theory to the case where cell-to-cell interaction is also taken into account. Ultimately, our analysis reveals that the pre-disease stage can be detected from the observation of the average gene expression when the bifurcation is induced by the intrinsic dynamics of the cells, whereas it remains undetectable when the bifurcation is produced by the interaction.