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Development of a scoring function for comparing simulated and experimental tumor spheroids
Progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), allowing cells to invade alone or collectively. Tumor sp...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10089329/ https://www.ncbi.nlm.nih.gov/pubmed/36996248 http://dx.doi.org/10.1371/journal.pcbi.1010471 |
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author | Herold, Julian Behle, Eric Rosenbauer, Jakob Ferruzzi, Jacopo Schug, Alexander |
author_facet | Herold, Julian Behle, Eric Rosenbauer, Jakob Ferruzzi, Jacopo Schug, Alexander |
author_sort | Herold, Julian |
collection | PubMed |
description | Progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), allowing cells to invade alone or collectively. Tumor spheroids cultured in collagen represent a simplified, reproducible 3D model system, which is sufficiently complex to recapitulate the evolving organization of cells and interaction with the ECM that occur during invasion. Recent experimental approaches enable high resolution imaging and quantification of the internal structure of invading tumor spheroids. Concurrently, computational modeling enables simulations of complex multicellular aggregates based on first principles. The comparison between real and simulated spheroids represents a way to fully exploit both data sources, but remains a challenge. We hypothesize that comparing any two spheroids requires first the extraction of basic features from the raw data, and second the definition of key metrics to match such features. Here, we present a novel method to compare spatial features of spheroids in 3D. To do so, we define and extract features from spheroid point cloud data, which we simulated using Cells in Silico (CiS), a high-performance framework for large-scale tissue modeling previously developed by us. We then define metrics to compare features between individual spheroids, and combine all metrics into an overall deviation score. Finally, we use our features to compare experimental data on invading spheroids in increasing collagen densities. We propose that our approach represents the basis for defining improved metrics to compare large 3D data sets. Moving forward, this approach will enable the detailed analysis of spheroids of any origin, one application of which is informing in silico spheroids based on their in vitro counterparts. This will enable both basic and applied researchers to close the loop between modeling and experiments in cancer research. |
format | Online Article Text |
id | pubmed-10089329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100893292023-04-12 Development of a scoring function for comparing simulated and experimental tumor spheroids Herold, Julian Behle, Eric Rosenbauer, Jakob Ferruzzi, Jacopo Schug, Alexander PLoS Comput Biol Research Article Progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), allowing cells to invade alone or collectively. Tumor spheroids cultured in collagen represent a simplified, reproducible 3D model system, which is sufficiently complex to recapitulate the evolving organization of cells and interaction with the ECM that occur during invasion. Recent experimental approaches enable high resolution imaging and quantification of the internal structure of invading tumor spheroids. Concurrently, computational modeling enables simulations of complex multicellular aggregates based on first principles. The comparison between real and simulated spheroids represents a way to fully exploit both data sources, but remains a challenge. We hypothesize that comparing any two spheroids requires first the extraction of basic features from the raw data, and second the definition of key metrics to match such features. Here, we present a novel method to compare spatial features of spheroids in 3D. To do so, we define and extract features from spheroid point cloud data, which we simulated using Cells in Silico (CiS), a high-performance framework for large-scale tissue modeling previously developed by us. We then define metrics to compare features between individual spheroids, and combine all metrics into an overall deviation score. Finally, we use our features to compare experimental data on invading spheroids in increasing collagen densities. We propose that our approach represents the basis for defining improved metrics to compare large 3D data sets. Moving forward, this approach will enable the detailed analysis of spheroids of any origin, one application of which is informing in silico spheroids based on their in vitro counterparts. This will enable both basic and applied researchers to close the loop between modeling and experiments in cancer research. Public Library of Science 2023-03-30 /pmc/articles/PMC10089329/ /pubmed/36996248 http://dx.doi.org/10.1371/journal.pcbi.1010471 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Herold, Julian Behle, Eric Rosenbauer, Jakob Ferruzzi, Jacopo Schug, Alexander Development of a scoring function for comparing simulated and experimental tumor spheroids |
title | Development of a scoring function for comparing simulated and experimental tumor spheroids |
title_full | Development of a scoring function for comparing simulated and experimental tumor spheroids |
title_fullStr | Development of a scoring function for comparing simulated and experimental tumor spheroids |
title_full_unstemmed | Development of a scoring function for comparing simulated and experimental tumor spheroids |
title_short | Development of a scoring function for comparing simulated and experimental tumor spheroids |
title_sort | development of a scoring function for comparing simulated and experimental tumor spheroids |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10089329/ https://www.ncbi.nlm.nih.gov/pubmed/36996248 http://dx.doi.org/10.1371/journal.pcbi.1010471 |
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