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The Effect of the G (1) - S transition Checkpoint on an Age Structured Cell Cycle Model
Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the err...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886982/ https://www.ncbi.nlm.nih.gov/pubmed/24416166 http://dx.doi.org/10.1371/journal.pone.0083477 |
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author | Chaffey, Gary S. Lloyd, David J. B. Skeldon, Anne C. Kirkby, Norman F. |
author_facet | Chaffey, Gary S. Lloyd, David J. B. Skeldon, Anne C. Kirkby, Norman F. |
author_sort | Chaffey, Gary S. |
collection | PubMed |
description | Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the errors present in these estimates may effect treatment efficacy and planning. If mathematical models are to be used to make accurate, quantitative predictions concerning treatments, whose efficacy is phase dependent, knowledge of the phase distribution is crucial. In this paper it is shown that two different transition rates at the [Image: see text]-[Image: see text] checkpoint provide a good fit to a growth curve obtained experimentally. However, the different transition functions predict a different phase distribution for the population, but both lying within the bounds of experimental error. Since treatment outcome is effected by the phase distribution of the population this difference may be critical in treatment planning. Using an age-structured population balance approach the cell cycle is modelled with particular emphasis on the [Image: see text]-[Image: see text] checkpoint. By considering the probability of cells transitioning at the [Image: see text]-[Image: see text] checkpoint, different transition functions are obtained. A suitable finite difference scheme for the numerical simulation of the model is derived and shown to be stable. The model is then fitted using the different probability transition functions to experimental data and the effects of the different probability transition functions on the model's results are discussed. |
format | Online Article Text |
id | pubmed-3886982 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38869822014-01-10 The Effect of the G (1) - S transition Checkpoint on an Age Structured Cell Cycle Model Chaffey, Gary S. Lloyd, David J. B. Skeldon, Anne C. Kirkby, Norman F. PLoS One Research Article Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the errors present in these estimates may effect treatment efficacy and planning. If mathematical models are to be used to make accurate, quantitative predictions concerning treatments, whose efficacy is phase dependent, knowledge of the phase distribution is crucial. In this paper it is shown that two different transition rates at the [Image: see text]-[Image: see text] checkpoint provide a good fit to a growth curve obtained experimentally. However, the different transition functions predict a different phase distribution for the population, but both lying within the bounds of experimental error. Since treatment outcome is effected by the phase distribution of the population this difference may be critical in treatment planning. Using an age-structured population balance approach the cell cycle is modelled with particular emphasis on the [Image: see text]-[Image: see text] checkpoint. By considering the probability of cells transitioning at the [Image: see text]-[Image: see text] checkpoint, different transition functions are obtained. A suitable finite difference scheme for the numerical simulation of the model is derived and shown to be stable. The model is then fitted using the different probability transition functions to experimental data and the effects of the different probability transition functions on the model's results are discussed. Public Library of Science 2014-01-09 /pmc/articles/PMC3886982/ /pubmed/24416166 http://dx.doi.org/10.1371/journal.pone.0083477 Text en © 2014 Chaffey 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 Chaffey, Gary S. Lloyd, David J. B. Skeldon, Anne C. Kirkby, Norman F. The Effect of the G (1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title | The Effect of the G
(1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title_full | The Effect of the G
(1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title_fullStr | The Effect of the G
(1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title_full_unstemmed | The Effect of the G
(1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title_short | The Effect of the G
(1) - S transition Checkpoint on an Age Structured Cell Cycle Model |
title_sort | effect of the g
(1) - s transition checkpoint on an age structured cell cycle model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886982/ https://www.ncbi.nlm.nih.gov/pubmed/24416166 http://dx.doi.org/10.1371/journal.pone.0083477 |
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