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A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer

  • Hesse, Janina1, 2
  • Martinelli, Julien3, 4, 5
  • Aboumanify, Ouda2, 6
  • Ballesta, Annabelle3, 4
  • Relógio, Angela1, 2, 6
  • 1 Institute for Systems Medicine, Department of Human Medicine, MSH Medical School Hamburg – University of Applied Sciences and Medical University, Hamburg 20457, Germany
  • 2 Institute for Theoretical Biology (ITB), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, and Berlin Institute of Health, Berlin 10117, Germany
  • 3 INSERM U900, Saint-Cloud, France, Institut Curie, Saint Cloud, France, Paris Saclay University, France, MINES ParisTech, CBIO - Centre for Computational Biology, PSL Research University, Paris, France
  • 4 UPR 'Chronotherapy, Cancers and Transplantation', Faculty of Medicine, Paris Saclay University, Campus CNRS, 7 rue Guy Moquet, 94800 Villejuif, France
  • 5 Lifeware Group, Inria Saclay Ile-de-France, Palaiseau 91120, France
  • 6 Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology, and Tumor Immunology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin
Published Article
Computational and Structural Biotechnology Journal
Publication Date
Sep 02, 2021
DOI: 10.1016/j.csbj.2021.08.051
PMID: 34630937
PMCID: PMC8477139
PubMed Central
  • 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.

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