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A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer
Scheduling anticancer drug administration over 24 h may critically impact treatment success in a patient-specific manner. Here, we address personalization of treatment timing using a novel mathematical model of irinotecan cellular pharmacokinetics and –dynamics linked to a representation of the core...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477139/ https://www.ncbi.nlm.nih.gov/pubmed/34630937 http://dx.doi.org/10.1016/j.csbj.2021.08.051 |
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author | Hesse, Janina Martinelli, Julien Aboumanify, Ouda Ballesta, Annabelle Relógio, Angela |
author_facet | Hesse, Janina Martinelli, Julien Aboumanify, Ouda Ballesta, Annabelle Relógio, Angela |
author_sort | Hesse, Janina |
collection | PubMed |
description | Scheduling anticancer drug administration over 24 h may critically impact treatment success in a patient-specific manner. Here, we address personalization of treatment timing using a novel mathematical model of irinotecan cellular pharmacokinetics and –dynamics linked to a representation of the core clock and predict treatment toxicity in a colorectal cancer (CRC) cellular model. The mathematical model is fitted to three different scenarios: mouse liver, where the drug metabolism mainly occurs, and two human colorectal cancer cell lines representing an in vitro experimental system for human colorectal cancer progression. Our model successfully recapitulates quantitative circadian datasets of mRNA and protein expression together with timing-dependent irinotecan cytotoxicity data. The model also discriminates time-dependent toxicity between the different cells, suggesting that treatment can be optimized according to their cellular clock. Our results show that the time-dependent degradation of the protein mediating irinotecan activation, as well as an oscillation in the death rate may play an important role in the circadian variations of drug toxicity. In the future, this model can be used to support personalized treatment scheduling by predicting optimal drug timing based on the patient’s gene expression profile. |
format | Online Article Text |
id | pubmed-8477139 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-84771392021-10-07 A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer Hesse, Janina Martinelli, Julien Aboumanify, Ouda Ballesta, Annabelle Relógio, Angela Comput Struct Biotechnol J Research Article Scheduling anticancer drug administration over 24 h may critically impact treatment success in a patient-specific manner. Here, we address personalization of treatment timing using a novel mathematical model of irinotecan cellular pharmacokinetics and –dynamics linked to a representation of the core clock and predict treatment toxicity in a colorectal cancer (CRC) cellular model. The mathematical model is fitted to three different scenarios: mouse liver, where the drug metabolism mainly occurs, and two human colorectal cancer cell lines representing an in vitro experimental system for human colorectal cancer progression. Our model successfully recapitulates quantitative circadian datasets of mRNA and protein expression together with timing-dependent irinotecan cytotoxicity data. The model also discriminates time-dependent toxicity between the different cells, suggesting that treatment can be optimized according to their cellular clock. Our results show that the time-dependent degradation of the protein mediating irinotecan activation, as well as an oscillation in the death rate may play an important role in the circadian variations of drug toxicity. In the future, this model can be used to support personalized treatment scheduling by predicting optimal drug timing based on the patient’s gene expression profile. Research Network of Computational and Structural Biotechnology 2021-09-02 /pmc/articles/PMC8477139/ /pubmed/34630937 http://dx.doi.org/10.1016/j.csbj.2021.08.051 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Hesse, Janina Martinelli, Julien Aboumanify, Ouda Ballesta, Annabelle Relógio, Angela A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title | A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title_full | A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title_fullStr | A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title_full_unstemmed | A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title_short | A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
title_sort | mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477139/ https://www.ncbi.nlm.nih.gov/pubmed/34630937 http://dx.doi.org/10.1016/j.csbj.2021.08.051 |
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