Literature DB >> 31981608

An in silico hybrid continuum-/agent-based procedure to modelling cancer development: Interrogating the interplay amongst glioma invasion, vascularity and necrosis.

Jean de Montigny1, Alexandros Iosif2, Lukas Breitwieser3, Marco Manca4, Roman Bauer5, Vasileios Vavourakis6.   

Abstract

This paper develops a three-dimensional in silico hybrid model of cancer, which describes the multi-variate phenotypic behaviour of tumour and host cells. The model encompasses the role of cell migration and adhesion, the influence of the extracellular matrix, the effects of oxygen and nutrient availability, and the signalling triggered by chemical cues and growth factors. The proposed in silico hybrid modelling framework combines successfully the advantages of continuum-based and discrete methods, namely the finite element and agent-based method respectively. The framework is thus used to realistically model cancer mechano-biology in a multiscale fashion while maintaining the resolution power of each method in a computationally cost-effective manner. The model is tailored to simulate glioma progression, and is subsequently used to interrogate the balance between the host cells and small sized gliomas, while the go-or-grow phenotype characteristic in glioblastomas is also investigated. Also, cell-cell and cell-matrix interactions are examined with respect to their effect in (macroscopic) tumour growth, brain tissue perfusion and tumour necrosis. Finally, we use the in silico framework to assess differences between low-grade and high-grade glioma growth, demonstrating significant differences in the distribution of cancer as well as host cells, in accordance with reported experimental findings.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Agent-based method; Brain tumor simulation; Finite element method; Hybrid models; In silico; Multiscale

Year:  2020        PMID: 31981608     DOI: 10.1016/j.ymeth.2020.01.006

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  3 in total

1.  Interrogating and Quantifying In Vitro Cancer Drug Pharmacodynamics via Agent-Based and Bayesian Monte Carlo Modelling.

Authors:  Marios Demetriades; Marko Zivanovic; Myrianthi Hadjicharalambous; Eleftherios Ioannou; Biljana Ljujic; Ksenija Vucicevic; Zeljko Ivosevic; Aleksandar Dagovic; Nevena Milivojevic; Odysseas Kokkinos; Roman Bauer; Vasileios Vavourakis
Journal:  Pharmaceutics       Date:  2022-03-30       Impact factor: 6.525

2.  Biomechanical modelling of spinal tumour anisotropic growth.

Authors:  Ioanna Katsamba; Pavlos Evangelidis; Chrysovalantis Voutouri; Alkiviadis Tsamis; Vasileios Vavourakis; Triantafyllos Stylianopoulos
Journal:  Proc Math Phys Eng Sci       Date:  2020-06-03       Impact factor: 2.704

3.  BioDynaMo: a modular platform for high-performance agent-based simulation.

Authors:  Lukas Breitwieser; Ahmad Hesam; Jean de Montigny; Vasileios Vavourakis; Alexandros Iosif; Jack Jennings; Marcus Kaiser; Marco Manca; Alberto Di Meglio; Zaid Al-Ars; Fons Rademakers; Onur Mutlu; Roman Bauer
Journal:  Bioinformatics       Date:  2021-09-16       Impact factor: 6.937

  3 in total

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