Dynamic modeling of cellular response to DNA damage based on p53 stress response networks

Abstract

Under acute perturbations from the outside, cells can trigger self-defensive mechanisms to fight against genome stress. To investigate the cellular response to continuous ion radiation (IR), a dynamic model for p53 stress response networks at the cellular level is proposed. The model can successfully be used to simulate the dynamic processes of double-strand breaks (DSBs) generation and their repair, switch-like ataxia telangiectasia mutated (ATM) activation, oscillations occurring in the p53-MDM2 feedback loop, as well as toxins elimination triggered by p53 stress response networks. Especially, the model can predict the plausible outcomes of cellular response under different IR dose regimes.

Kinetic Theory Approach to Modeling of Cellular Repair Mechanisms under Genome Stress

“…In accordance with experimental results that measured 30–40 DSBs per Gy occur as external acute IR is applied into a single cell [3], [4], [5], we consider that the initial number of resulting DSBs per time scale is proportion to the number generated by Poisson random function with a mean of 35 × , in which x is strengths of IR dose [22]–[26]. Meanwhile, we deal repair gene as a part of DNA within a special cell, which means that repair gene also can be damaged by external IR.…”

“…More specifically, 70% of the initial DSBs is fixed by the fast repair kinetics, and the ratio of the fast rate over the slow one is chosen to be ≈10 [22]–[26].…”

A novel framework for modeling Tumor Radiotherapy mechanism based on Gene-Environment Network (GEN) and Kinetic Theory

“…The main parameters used in our simulations are shown in Appendix A, which are derived from existing studies on P53 signal network and cellular response kinetics in [3,[6][7][8][9]20]. …”

“…For instance, several existing methods are used to represent the stochastic dynamics of complicated cellular activities in response to genome stress, such as Monte Carlo simulation methods in [6], as well as Gene Regulatory Network (GRN) model and Ordinary Differential Equations (ODE) methods in [3,[7][8][9]. However, most of these methods are deterministic, and cannot well describe the stochastic interactions among large-scale active particles at molecular level, as well as the * This paper is supported by National Natural Science Foundation of China (No.61104154), and the Fundamental Research Funds for the Central Universities.…”

A Novel Method for Modelling Cellular Response Genome Stress by Combined Gene-Environment Network (GEN) and Kinetic Theory Framework

“…For example, the stochastic models of p53 system were proposed in (Puszyński, Hat et al 2008;Cai and Yuan 2009;Leenders and Tuszynski 2013). Also, other models of p53 were investigated, such as in (Batchelor, Loewer et al 2011), (Kim, Rho et al 2009), (Qi, Shao et al 2007;Qi, Shao et al 2008;Qi, Ding et al 2009;Zhang, Liu et al 2012), and (Ma, Wagner et al 2005).…”