SearcharxivSearch

arXiv · 1509.06304

A biophysical model of cell evolution after cytotoxic treatments: damage, repair and cell response

Abstract

We present a theoretical agent-based model of cell evolution under the action of cytotoxic treatments, such as radioteraphy or chemoteraphy. The major features of cell cycle and proliferation, cell damage and repair, and chemical diffusion are included. Cell evolution is based on a discrete Markov chain, with cells stepping along a sequence of discrete internal states from 'normal' to 'inactive'. Probabilistic laws are introduced for each type of event a cell can undergo during its life cycle: duplication, arrest, apoptosis, senescence, damage, healing. We adjust the model parameters on a series of cell irradiation experiments, carried out in a clinical LINAC at 20 MV, in which the damage and repair kinetics of single- and double-strand breaks are followed. Two showcase applications of the model are then presented. In the first one, we reconstruct the cell survival curves from a number of published low- and high-dose irradiation experiments. We reobtain a very good description of the data without assuming the well-known linear-quadratic model, but instead including a variable DSB repair probability, which is found to spontaneously saturate with an exponential decay at increasingly high doses. As a second test, we attempt to simulate the two extreme possibilities of the so-called 'bystander' effect in radiotherapy: the 'local' effect versus a 'global' effect, respectively activated by the short-range or long-range diffusion of some factor, presumably secreted by the irradiated cells. Even with an oversimplified simulation, we could demonstrate a sizeable difference in the proliferation rate of non-irradiated cells, the proliferation acceleration being much larger for the global than the local effect, for relatively small fractions of irradiated cells in the colony.

Explore related subjects

Keep this discovery

BibTeXRIS

Maxime Tomezak, Corinne Abbadie, Eric Lartigau, Fabrizio Cleri. 2015-09-21. A biophysical model of cell evolution after cytotoxic treatments: damage, repair and cell response. https://arxiv.org/abs/1509.06304

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Modeling Tissue Detachment and Rupture Using an Extended Vertex Model with T2-inverse Transitions

The vertex model is widely used to describe the mechanics of epithelial tissues, but its conventional formulation assumes that all cells remain tightly packed and always share edges with their neighbors, making it difficult to represent local detachment or gap formation. Here, we propose a minimal extension of the vertex model that enables cell detachment by introducing a new topological transformation, T2-inverse, which acts as the inverse of the classical T2 transition. When the imbalance of forces acting on a vertex, quantified by a tension metric $T$, exceeds a threshold, the T2-inverse splits the vertex into multiple vertices and creates a closed polygon that is incorporated as a pseudo-cell. This operation allows the model to represent the emergence and propagation of local detachment events. Using this framework, we simulate the stretching of a cell sheet and show that force-induced local detachments can accumulate to produce macroscopic tissue rupture. These results demonstrate that the proposed model extends the capability of the vertex model to describe tissue-level breakdown processes, including detachment and tearing, and provides a foundation for studying a broader class of epithelial mechanical phenomena.

q-bio.CB

3D hybrid cellular Potts model with a discrete deformable fiber network: modeling cell contraction and extracellular matrix remodeling

The extracellular matrix (ECM) is a fibrous and dynamic network that plays a critical role in development, homeostasis, and disease. Cells both respond to and remodel the ECM, engaging in a mechanical reciprocity that shapes tissues. To study these interactions, computational models have been developed that simulate either ECM mechanics or cell behavior. The Cellular Potts Model (CPM) is a flexible cell-based framework that has been extended to many biological processes, including coupling to a discrete deformable fiber network. So far, however, this extension has only been applied in two dimensions, even though a three-dimensional setting is biologically more relevant. Here, we present a 3D hybrid framework that couples the CPM with a discrete and deformable representation of the ECM. This model enables explicit simulation of cell-induced ECM remodeling, including fiber reorientation and matrix densification. By incorporating contractile forces through static adhesion points, the model captures how ECM elasticity and fiber stiffness influences cell shape. The simulations show that ECM stiffness, controlled by fiber crosslinking, resists contraction and reaches equilibrium, while crosslink density modulates fiber alignment and local matrix accumulation. This framework provides a versatile platform for studying cell-ECM mechanics and supports future studies of multicellular behavior in realistic 3D environments.

q-bio.CB

Coarse-Graining Agent-Based Models of Bacterial Infections

Agent-based models (ABMs) provide a natural framework for representing cell-level rules and spatial heterogeneity in bacterial infections, but their computational cost limits their use for macroscopic tissue-scale simulations and broad parameter exploration. We derive a deterministic coarse-grained description for a class of bacterial-infection ABMs in which immune cells and extracellular bacteria diffuse, immune cells ingest nearby bacteria, and intracellular bacterial loads evolve through prescribed birth and clearance processes. The first coarse-grained model is a semidiscrete reaction--diffusion system that retains a discrete internal state for each immune-cell bacterial load while representing cell and bacterial populations by continuum concentration fields. The key technical step is the derivation of state-dependent effective ingestion rates from the microscopic ABM parameters: these rates are obtained by solving an auxiliary diffusion problem around a single bacterium and computing the flux of immune cells into the interaction region. We then take a continuum limit in the internal state variable, yielding a state-structured reaction--diffusion system in which intracellular dynamics appear as advection and diffusion in state space. Numerical comparisons with ensemble-averaged ABM simulations show close agreement in biologically motivated parameter regimes. The resulting framework preserves the rule-based structure of the ABM while producing PDE models that are substantially more tractable for large-scale simulation and parameter studies.

q-bio.CB