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. 2022 Jun 30;479(12):1361-1374.
doi: 10.1042/BCJ20210548.

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

Lorenza A D'Alessandro  1 , Ursula Klingmüller  1 , Marcel Schilling  1
Affiliations

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

Lorenza A D'Alessandro et al. Biochem J. .

Abstract

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

Keywords: cytokines; growth factors; hepatocellular carcinoma; hepatocytes; liver; mathematical modelling.

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Conflict of interest statement

The authors declare that there are no competing interests associated with the manuscript.

Figures

Figure 1.
Figure 1.. Biological questions addressed with mechanistic mathematical modelling.
Cytokines activate identical or overlapping transcription factors; interaction of the HGF receptor MET with other receptors influences its signalling strength; EGF induces internalization of its cognate receptor EGFR; TNFα-induced signal transduction is subject to complex feedback regulation.
Figure 2.
Figure 2.. Cytokine waves augment or diminish pathway activation.
Pre-stimulation and stimulation are indicated as consecutive waves, shades of red indicate the extent of activation of the JAK/STAT pathways. Data taken from references [34, 43–45].
Figure 3.
Figure 3.. Modular approaches that were used for mechanistic mathematical modelling.
On the left side, the core model is shown (dark cyan). On the right side, additional species and reactions that were used to extend the model are shown in orange. Top: HGF-induced ERK and AKT activation extended by interaction of MET with integrin α5β1 [60]. Middle: EGFR activation by multisite phosphorylation extended by CBL-based ubiquitination and internalization of EGFR [69]. Bottom: TNFα-induced NFκB signal transduction extended by specific A20 regulation mechanisms [75].
See this image and copyright information in PMC

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