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Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

BACKGROUND: The tumour stroma -or tumour microenvironment- is an important constituent of solid cancers and it is thought to be one of the main obstacles to quantitative translation of drug activity between the preclinical and clinical phases of drug development. The tumour-stroma relationship has b...

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Autores principales: Delgado-SanMartin, J. A., Hare, J. I., Davies, E. J., Yates, J. W. T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450227/
https://www.ncbi.nlm.nih.gov/pubmed/28558757
http://dx.doi.org/10.1186/s12911-017-0461-1
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author Delgado-SanMartin, J. A.
Hare, J. I.
Davies, E. J.
Yates, J. W. T.
author_facet Delgado-SanMartin, J. A.
Hare, J. I.
Davies, E. J.
Yates, J. W. T.
author_sort Delgado-SanMartin, J. A.
collection PubMed
description BACKGROUND: The tumour stroma -or tumour microenvironment- is an important constituent of solid cancers and it is thought to be one of the main obstacles to quantitative translation of drug activity between the preclinical and clinical phases of drug development. The tumour-stroma relationship has been described as being both pro- and antitumour in multiple studies. However, the causality of this complex biological relationship between the tumour and stroma has not yet been explored in a quantitative manner in complex tumour morphologies. METHODS: To understand how these stromal and microenvironmental factors contribute to tumour physiology and how oxygen distributes within them, we have developed a lattice-based multiscalar cellular automaton model. This model uses principles of cytokine and oxygen diffusion as well as cell motility and plasticity to describe tumour-stroma landscapes. Furthermore, to calibrate the model, we propose an innovative modelling platform to extract model parameters from multiple in-vitro assays. This platform provides a novel way to extract meta-data that can be used to complement in-vivo studies and can be further applied in other contexts. RESULTS: Here we show the necessity of the tumour-stroma opposing relationship for the model simulations to successfully describe the in-vivo stromal patterns of the human lung cancer cell lines Calu3 and Calu6, as models of clinical and preclinical tumour-stromal topologies. This is especially relevant to drugs that target the tumour microenvironment, such as antiangiogenics, compounds targeting the hedgehog pathway or immune checkpoint inhibitors, and is potentially a key platform to understand the mechanistic drivers for these drugs. CONCLUSION: The tumour-stroma automaton model presented here enables the interpretation of complex in-vitro data and uses it to parametrise a model for in-vivo tumour-stromal relationships. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-017-0461-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-54502272017-06-01 Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data Delgado-SanMartin, J. A. Hare, J. I. Davies, E. J. Yates, J. W. T. BMC Med Inform Decis Mak Research Article BACKGROUND: The tumour stroma -or tumour microenvironment- is an important constituent of solid cancers and it is thought to be one of the main obstacles to quantitative translation of drug activity between the preclinical and clinical phases of drug development. The tumour-stroma relationship has been described as being both pro- and antitumour in multiple studies. However, the causality of this complex biological relationship between the tumour and stroma has not yet been explored in a quantitative manner in complex tumour morphologies. METHODS: To understand how these stromal and microenvironmental factors contribute to tumour physiology and how oxygen distributes within them, we have developed a lattice-based multiscalar cellular automaton model. This model uses principles of cytokine and oxygen diffusion as well as cell motility and plasticity to describe tumour-stroma landscapes. Furthermore, to calibrate the model, we propose an innovative modelling platform to extract model parameters from multiple in-vitro assays. This platform provides a novel way to extract meta-data that can be used to complement in-vivo studies and can be further applied in other contexts. RESULTS: Here we show the necessity of the tumour-stroma opposing relationship for the model simulations to successfully describe the in-vivo stromal patterns of the human lung cancer cell lines Calu3 and Calu6, as models of clinical and preclinical tumour-stromal topologies. This is especially relevant to drugs that target the tumour microenvironment, such as antiangiogenics, compounds targeting the hedgehog pathway or immune checkpoint inhibitors, and is potentially a key platform to understand the mechanistic drivers for these drugs. CONCLUSION: The tumour-stroma automaton model presented here enables the interpretation of complex in-vitro data and uses it to parametrise a model for in-vivo tumour-stromal relationships. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-017-0461-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-30 /pmc/articles/PMC5450227/ /pubmed/28558757 http://dx.doi.org/10.1186/s12911-017-0461-1 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Delgado-SanMartin, J. A.
Hare, J. I.
Davies, E. J.
Yates, J. W. T.
Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title_full Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title_fullStr Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title_full_unstemmed Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title_short Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
title_sort multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450227/
https://www.ncbi.nlm.nih.gov/pubmed/28558757
http://dx.doi.org/10.1186/s12911-017-0461-1
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