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Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy
The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed “cyclotherapy”. Quantitative approaches that describe these dysregula...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435348/ https://www.ncbi.nlm.nih.gov/pubmed/28467408 http://dx.doi.org/10.1371/journal.pcbi.1005529 |
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author | Jackson, Robert C. Di Veroli, Giovanni Y. Koh, Siang-Boon Goldlust, Ian Richards, Frances M. Jodrell, Duncan I. |
author_facet | Jackson, Robert C. Di Veroli, Giovanni Y. Koh, Siang-Boon Goldlust, Ian Richards, Frances M. Jodrell, Duncan I. |
author_sort | Jackson, Robert C. |
collection | PubMed |
description | The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed “cyclotherapy”. Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs. |
format | Online Article Text |
id | pubmed-5435348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54353482017-05-27 Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy Jackson, Robert C. Di Veroli, Giovanni Y. Koh, Siang-Boon Goldlust, Ian Richards, Frances M. Jodrell, Duncan I. PLoS Comput Biol Research Article The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed “cyclotherapy”. Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs. Public Library of Science 2017-05-03 /pmc/articles/PMC5435348/ /pubmed/28467408 http://dx.doi.org/10.1371/journal.pcbi.1005529 Text en © 2017 Jackson 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Jackson, Robert C. Di Veroli, Giovanni Y. Koh, Siang-Boon Goldlust, Ian Richards, Frances M. Jodrell, Duncan I. Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title | Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title_full | Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title_fullStr | Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title_full_unstemmed | Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title_short | Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy |
title_sort | modelling of the cancer cell cycle as a tool for rational drug development: a systems pharmacology approach to cyclotherapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435348/ https://www.ncbi.nlm.nih.gov/pubmed/28467408 http://dx.doi.org/10.1371/journal.pcbi.1005529 |
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