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The Arteriovenous AV Loop in a Small Animal Model to Study Angiogenesis and Vascularized Tissue Engineering

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Published on: November 2, 2016

A multi-scale agent-based model for avascular tumour growth.

Sounak Sadhukhan¹, P K Mishra¹, S K Basu¹

¹Department of Computer Science, Banaras Hindu University, Institute of Science, Varanasi 221005, India.

|June 7, 2021

Summary

This study presents a multi-scale agent-based model for avascular tumor growth, simulating intracellular and extracellular dynamics. The model, validated with patient data, accurately mimics complex tumor behaviors and cancer hallmarks.

Keywords:

Agent based model Avascular tumour growth Multi-scale model Signalling pathway

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Area of Science:

Computational Biology
Cancer Research
Mathematical Modeling

Background:

Avascular tumor growth is complex, involving intracellular, cellular, and extracellular dynamics.
Understanding these dynamics is crucial for cancer research and treatment development.

Purpose of the Study:

To develop a multi-scale, lattice-free, agent-based model of avascular tumor growth.
To integrate intracellular (p27 gene expression), cellular (proliferation, phenotype change), and extracellular (oxygen, nutrients) dynamics.
To validate the model against experimental data and assess its ability to replicate cancer hallmarks.

Main Methods:

Developed a multi-scale, agent-based model where each cell is an agent.
Incorporated an age-structured cell cycle model regulated by p27 gene expression.
Modeled oxygen and nutrient dynamics using reaction-diffusion equations and included biophysical forces.

Main Results:

The model successfully integrates diverse biological events, from intracellular protein activity to extracellular microenvironment.
Simulated tumor growth exhibited key cancer hallmarks: nutrient consumption, heterogeneity, proliferation, and apoptosis resistance.
Model outcomes closely matched patient data from immunohistochemistry and histopathology, validating its predictive capability.

Conclusions:

The developed agent-based model provides a biologically realistic framework for studying avascular tumor growth.
The model accurately captures complex biophysical phenomena and cancer hallmarks.
This computational approach is valuable for understanding tumor progression and potentially guiding therapeutic strategies.