Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines
Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in...
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description | Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function. |
doi_str_mv | 10.1371/journal.pcbi.1006273 |
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We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1006273</identifier><identifier>PMID: 30849070</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Alginates ; Alginic acid ; Animals ; Biology ; Biology and Life Sciences ; Biomechanics ; Biotechnology ; Calibration ; Cancer ; Cell cycle ; Cell growth ; Cell Line, Tumor ; Cell Shape - physiology ; Colon ; Compressibility ; Computational Biology ; Computer simulation ; Dextran ; Experiments ; Growth conditions ; Growth kinetics ; Homeostasis ; Humans ; Kinetics ; Life Sciences ; Mathematical models ; Mathematical Physics ; Mathematics ; Mechanical properties ; Mechanotransduction, Cellular - physiology ; Mice ; Models, Biological ; Molecular weight ; Osmosis ; Parameters ; Physical Sciences ; Physics ; Populations ; Research and Analysis Methods ; Resolution cell ; Software ; Spheroids ; Spheroids, Cellular - physiology ; Stress ; Supervision ; Tumor Cells, Cultured - physiology ; Volumetric strain</subject><ispartof>PLoS computational biology, 2019-03, Vol.15 (3), p.e1006273-e1006273</ispartof><rights>2019 Van Liedekerke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>2019 Van Liedekerke et al 2019 Van Liedekerke et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4053-10528ee19a0af467cd11c5fb52b877308eee1bf942db1ecd34489d3f0d36384e3</citedby><cites>FETCH-LOGICAL-c4053-10528ee19a0af467cd11c5fb52b877308eee1bf942db1ecd34489d3f0d36384e3</cites><orcidid>0000-0002-9314-6281 ; 0000-0002-9995-5987 ; 0000-0003-4615-9431 ; 0000-0002-1986-3493</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538187/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538187/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23864,27922,27923,53789,53791,79370,79371</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30849070$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-02371813$$DView record in HAL$$Hfree_for_read</backlink></links><search><contributor>Komarova, Natalia L.</contributor><creatorcontrib>Van Liedekerke, Paul</creatorcontrib><creatorcontrib>Neitsch, Johannes</creatorcontrib><creatorcontrib>Johann, Tim</creatorcontrib><creatorcontrib>Alessandri, Kevin</creatorcontrib><creatorcontrib>Nassoy, Pierre</creatorcontrib><creatorcontrib>Drasdo, Dirk</creatorcontrib><title>Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><description>Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function.</description><subject>Alginates</subject><subject>Alginic acid</subject><subject>Animals</subject><subject>Biology</subject><subject>Biology and Life Sciences</subject><subject>Biomechanics</subject><subject>Biotechnology</subject><subject>Calibration</subject><subject>Cancer</subject><subject>Cell cycle</subject><subject>Cell growth</subject><subject>Cell Line, Tumor</subject><subject>Cell Shape - physiology</subject><subject>Colon</subject><subject>Compressibility</subject><subject>Computational Biology</subject><subject>Computer simulation</subject><subject>Dextran</subject><subject>Experiments</subject><subject>Growth conditions</subject><subject>Growth kinetics</subject><subject>Homeostasis</subject><subject>Humans</subject><subject>Kinetics</subject><subject>Life Sciences</subject><subject>Mathematical models</subject><subject>Mathematical Physics</subject><subject>Mathematics</subject><subject>Mechanical properties</subject><subject>Mechanotransduction, Cellular - 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physiology</topic><topic>Colon</topic><topic>Compressibility</topic><topic>Computational Biology</topic><topic>Computer simulation</topic><topic>Dextran</topic><topic>Experiments</topic><topic>Growth conditions</topic><topic>Growth kinetics</topic><topic>Homeostasis</topic><topic>Humans</topic><topic>Kinetics</topic><topic>Life Sciences</topic><topic>Mathematical models</topic><topic>Mathematical Physics</topic><topic>Mathematics</topic><topic>Mechanical properties</topic><topic>Mechanotransduction, Cellular - physiology</topic><topic>Mice</topic><topic>Models, Biological</topic><topic>Molecular weight</topic><topic>Osmosis</topic><topic>Parameters</topic><topic>Physical Sciences</topic><topic>Physics</topic><topic>Populations</topic><topic>Research and Analysis Methods</topic><topic>Resolution cell</topic><topic>Software</topic><topic>Spheroids</topic><topic>Spheroids, Cellular - physiology</topic><topic>Stress</topic><topic>Supervision</topic><topic>Tumor Cells, Cultured - physiology</topic><topic>Volumetric strain</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Van Liedekerke, Paul</creatorcontrib><creatorcontrib>Neitsch, Johannes</creatorcontrib><creatorcontrib>Johann, Tim</creatorcontrib><creatorcontrib>Alessandri, Kevin</creatorcontrib><creatorcontrib>Nassoy, Pierre</creatorcontrib><creatorcontrib>Drasdo, Dirk</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Van Liedekerke, Paul</au><au>Neitsch, Johannes</au><au>Johann, Tim</au><au>Alessandri, Kevin</au><au>Nassoy, Pierre</au><au>Drasdo, Dirk</au><au>Komarova, Natalia L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2019-03</date><risdate>2019</risdate><volume>15</volume><issue>3</issue><spage>e1006273</spage><epage>e1006273</epage><pages>e1006273-e1006273</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30849070</pmid><doi>10.1371/journal.pcbi.1006273</doi><orcidid>https://orcid.org/0000-0002-9314-6281</orcidid><orcidid>https://orcid.org/0000-0002-9995-5987</orcidid><orcidid>https://orcid.org/0000-0003-4615-9431</orcidid><orcidid>https://orcid.org/0000-0002-1986-3493</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alginates Alginic acid Animals Biology Biology and Life Sciences Biomechanics Biotechnology Calibration Cancer Cell cycle Cell growth Cell Line, Tumor Cell Shape - physiology Colon Compressibility Computational Biology Computer simulation Dextran Experiments Growth conditions Growth kinetics Homeostasis Humans Kinetics Life Sciences Mathematical models Mathematical Physics Mathematics Mechanical properties Mechanotransduction, Cellular - physiology Mice Models, Biological Molecular weight Osmosis Parameters Physical Sciences Physics Populations Research and Analysis Methods Resolution cell Software Spheroids Spheroids, Cellular - physiology Stress Supervision Tumor Cells, Cultured - physiology Volumetric strain |
title | Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines |
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