Literature DB >> 24427527

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

Grazziela P Figueredo1, Tanvi V Joshi1, James M Osborne2, Helen M Byrne3, Markus R Owen1.   

Abstract

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

Entities:  

Keywords:  agent-based simulation; cancer; cell cycle; lattice models; multi-scale model; tumour hypoxia

Year:  2013        PMID: 24427527      PMCID: PMC3638480          DOI: 10.1098/rsfs.2012.0081

Source DB:  PubMed          Journal:  Interface Focus        ISSN: 2042-8898            Impact factor:   3.906


  7 in total

Review 1.  Towards whole-organ modelling of tumour growth.

Authors:  T Alarcón; H M Byrne; P K Maini
Journal:  Prog Biophys Mol Biol       Date:  2004 Jun-Jul       Impact factor: 3.667

Review 2.  Response of tumour cells to hypoxia: role of p53 and NFkB.

Authors:  J A Royds; S K Dower; E E Qwarnstrom; C E Lewis
Journal:  Mol Pathol       Date:  1998-04

3.  A cellular automaton model for tumour growth in inhomogeneous environment.

Authors:  T Alarcón; H M Byrne; P K Maini
Journal:  J Theor Biol       Date:  2003-11-21       Impact factor: 2.691

4.  A mathematical model of the effects of hypoxia on the cell-cycle of normal and cancer cells.

Authors:  T Alarcón; H M Byrne; P K Maini
Journal:  J Theor Biol       Date:  2004-08-07       Impact factor: 2.691

5.  Angiogenesis and vascular remodelling in normal and cancerous tissues.

Authors:  Markus R Owen; Tomás Alarcón; Philip K Maini; Helen M Byrne
Journal:  J Math Biol       Date:  2008-10-22       Impact factor: 2.259

6.  Mathematical modeling predicts synergistic antitumor effects of combining a macrophage-based, hypoxia-targeted gene therapy with chemotherapy.

Authors:  Markus R Owen; I Johanna Stamper; Munitta Muthana; Giles W Richardson; Jon Dobson; Claire E Lewis; Helen M Byrne
Journal:  Cancer Res       Date:  2011-03-01       Impact factor: 12.701

7.  Multiscale modelling of vascular tumour growth in 3D: the roles of domain size and boundary conditions.

Authors:  Holger Perfahl; Helen M Byrne; Tingan Chen; Veronica Estrella; Tomás Alarcón; Alexei Lapin; Robert A Gatenby; Robert J Gillies; Mark C Lloyd; Philip K Maini; Matthias Reuss; Markus R Owen
Journal:  PLoS One       Date:  2011-04-13       Impact factor: 3.240

  7 in total
  5 in total

1.  ChemChaste: Simulating spatially inhomogeneous biochemical reaction-diffusion systems for modeling cell-environment feedbacks.

Authors:  Connah G M Johnson; Alexander G Fletcher; Orkun S Soyer
Journal:  Gigascience       Date:  2022-06-17       Impact factor: 7.658

2.  Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems.

Authors:  Nicholas A Cilfone; Denise E Kirschner; Jennifer J Linderman
Journal:  Cell Mol Bioeng       Date:  2015-03       Impact factor: 2.321

3.  Comparing stochastic differential equations and agent-based modelling and simulation for early-stage cancer.

Authors:  Grazziela P Figueredo; Peer-Olaf Siebers; Markus R Owen; Jenna Reps; Uwe Aickelin
Journal:  PLoS One       Date:  2014-04-21       Impact factor: 3.240

4.  CoGNaC: A Chaste Plugin for the Multiscale Simulation of Gene Regulatory Networks Driving the Spatial Dynamics of Tissues and Cancer.

Authors:  Simone Rubinacci; Alex Graudenzi; Giulio Caravagna; Giancarlo Mauri; James Osborne; Joe Pitt-Francis; Marco Antoniotti
Journal:  Cancer Inform       Date:  2015-09-01

5.  Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment.

Authors:  Kerri-Ann Norton; Chang Gong; Samira Jamalian; Aleksander S Popel
Journal:  Processes (Basel)       Date:  2019-01-13       Impact factor: 2.847

  5 in total

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