A multiscale agent-based framework integrated with a constraint-based metabolic network model of cancer for simulating avascular tumor growth
Authored by Mehrdad Ghadiri, Mahshid Heidari, Sayed-Amir Marashi, Seyed Hasan Mousavi
Date Published: 2017
DOI: 10.1039/c7mb00050b
Sponsors:
No sponsors listed
Platforms:
MASON
Model Documentation:
Other Narrative
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Model Code URLs:
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Abstract
In recent years, many efforts have been made in the field of
computational modeling of cancerous tumors, in order to obtain a better
understanding and predictions of their growth patterns. Furthermore,
constraint-based modeling of metabolic networks has become increasingly
popular, which is appropriate for the systems-level reconstruction of
cell physiology. The goal of the current study is to integrate a
multiscale agent-based modeling framework with a constraint-based
metabolic network model of cancer cells in order to simulate the three
dimensional early growth of avascular tumors. In order to develop the
integrated model, a previously published generic metabolic network model
of cancer cells was introduced into a multiscale agent-based framework.
This model is initiated with a single tumor cell. Nutrients can diffuse
through the simulation space and the cells uptake or excrete
metabolites, grow, proliferate or become necrotic based on certain
defined criteria and flux values of particular reactions. The simulation
was run for a period of 20 days and the plots corresponding to various
features such as the growth profile and necrotic core evolution were
obtained. These features were compared with the ones observed in other
(experimental) studies. One interesting characteristic of our modeling
is that it provides us with the ability to predict gene expression
patterns through different layers of a tumor, which can have important
implications, especially in drug target selection in the field of cancer
therapy.
Tags
proliferation
environment
Cells
Expression
Cellular-automaton model
Biology
Oxygen
Flux balance analysis
Multicellular
spheroids
Human-origin