A new method for shrinking tumor based on microenvironmental factors: Introducing a stochastic agent-based model of avascular tumor growth
Authored by S H Sabzpoushan, Fateme Pourhasanzade
Date Published: 2018
DOI: 10.1016/j.physa.2018.05.131
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Abstract
In this paper, by using cellular automata formalism, a two-dimensional
stochastic agent based model for avascular tumor growth is presented.
The model is based on biological assumptions, physical structure, agents
and their states, and transition rules. The interaction between immune
and cancer cells is probabilistic. The immune cell recruitment, which
usually occurs after the detection of tumor cells, is considered. The
insights gain in the proposed work to model the immune-tumor interaction
is of great importance to control the tumor growth via micro-environment
factors. The parameters used in the present model are in compatible with
cancer biology using in vivo experimental data. The results show that
the proposed model not only is able to simulate the tumor growth
graphically, but also the in vivo tumor growth quantitatively and
qualitatively. In this paper, by introducing a new concept; critical
point, a new idea is proposed to shrink the tumor or slow down its
growth rate. The tumor will grow slowly if the division probability of
the proliferative tumor cells depends on the microenvironmental
conditions. The proposed idea has been validated using an in silico
simulation. (C) 2018 Elsevier B.V. All rights reserved.
Tags
Simulation
Mathematical model
Dynamics
networks
cancer
stochastic agent-based model
Tumor growth
Cells
Cellular-automaton
Mathematical-models
Biology
Therapies
Hallmarks