Model-based translation of DNA damage signaling dynamics across cell types

Abstract

Interindividual variability in DNA damage response (DDR) dynamics may evoke differences in susceptibility to cancer. However, pathway dynamics are often studied in cell lines as alternative to primary cells, disregarding variability. To compare DDR dynamics in the cell line HepG2 with primary human hepatocytes (PHHs), we developed a HepG2-based computational model that describes the dynamics of DDR regulator p53 and targets MDM2, p21 and BTG2. We used this model to generate simulations of virtual PHHs and compared the results to those for PHH donor samples. Correlations between baseline p53 and p21 or BTG2 mRNA expression in the absence and presence of DNA damage for HepG2-derived virtual samples matched the moderately positive correlations observed for 50 PHH donor samples, but not the negative correlations between p53 and its inhibitor MDM2. Model parameter manipulation that affected p53 or MDM2 dynamics was not sufficient to accurately explain the negative correlation between these genes. Thus, extrapolation from HepG2 to PHH can be done for some DDR elements, yet our analysis also reveals a knowledge gap within p53 pathway regulation, which makes such extrapolation inaccurate for the regulator MDM2. This illustrates the relevance of studying pathway dynamics in addition to gene expression comparisons to allow reliable translation of cellular responses from cell lines to primary cells. Overall, with our approach we show that dynamical modeling can be used to improve our understanding of the sources of interindividual variability of pathway dynamics.

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“…1b ), and subsequent activation of the DNA damage response were established by modifying existing models (Supplementary Fig. 1 ) 58 , 68 and applying them to individual hepatocytes, while accounting for the zonal differences in GSH and cytochrome P450 concentrations.

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“…Because p53 induces the expression of p21, p53 influences the likelihood of senescence and proliferation events during regeneration. Previously, we suggested that the feedback strength of MDM2 on p53 could vary among cell types and play a role in interindividual variability 68 . Therefore, we decreased and increased the MDM2 feedback on p53 and phospho-p53 with a factor 10 and 100 and examined the effect of an APAP insult on p21, senescence and recovery from damage.…”

“…To model the impact of NAPQI-cys and the resulting oxidative stress induced nuclear DNA damage 140 , 141 on subsequent cellular demise, we adapted our previously created DNA damage model 68 and incorporated the ODE equations into our intracellular dynamics model of the hepatocytes. Specifically, we removed the mRNA state variables from the model and re-estimated the parameters of this reduced model (Supplementary Fig.…”

“…1 and Supplementary Methods ). For re-estimation of the parameters, we employed our previously established in-house derivative-based optimization method, that uses the least squares minimization function from the SciPy package in Python version 3.7.3 in combination with Latin hypercube sampling for efficient sampling of the parameter space 68 . Subsequently, we further adapted this reduced model to integrate it in our spatial model, as described below.…”

“…However, none of these published models integrates spatial organization of hepatocytes and metabolic zonation with senescence, necrosis and regeneration, taking the influence of immunosurveillance by KCs and mϕs on outcome into account. Therefore, we built a comprehensive spatial model of a human liver lobule that incorporates an intracellular APAP metabolism model 58 , our previously constructed model for the activation of the DDR 68 , hepatocyte damage, and interaction with KCs and mϕs. We used this model to study the regenerative capacity of the system by manipulation of zonation and perturbation of parameters, thereby demonstrating that senescence and proliferation events are expected to be influenced by alterations in intracellular metabolic and stress signaling dynamics, in addition to extracellular stimulants.…”