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Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments
The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798276/ https://www.ncbi.nlm.nih.gov/pubmed/24146610 http://dx.doi.org/10.1371/journal.pcbi.1003293 |
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author | Falcetta, Francesca Lupi, Monica Colombo, Valentina Ubezio, Paolo |
author_facet | Falcetta, Francesca Lupi, Monica Colombo, Valentina Ubezio, Paolo |
author_sort | Falcetta, Francesca |
collection | PubMed |
description | The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dose-dependence of G(1), S and G(2)M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario. |
format | Online Article Text |
id | pubmed-3798276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37982762013-10-21 Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments Falcetta, Francesca Lupi, Monica Colombo, Valentina Ubezio, Paolo PLoS Comput Biol Research Article The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dose-dependence of G(1), S and G(2)M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario. Public Library of Science 2013-10-17 /pmc/articles/PMC3798276/ /pubmed/24146610 http://dx.doi.org/10.1371/journal.pcbi.1003293 Text en © 2013 Falcetta et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Falcetta, Francesca Lupi, Monica Colombo, Valentina Ubezio, Paolo Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title | Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title_full | Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title_fullStr | Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title_full_unstemmed | Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title_short | Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments |
title_sort | dynamic rendering of the heterogeneous cell response to anticancer treatments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798276/ https://www.ncbi.nlm.nih.gov/pubmed/24146610 http://dx.doi.org/10.1371/journal.pcbi.1003293 |
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