A circadian clock transcription model for the personalization of cancer chronotherapy

Abstract : Circadian timing of anticancer medications has improved treatment tolerability and efficacy several-fold, yet with inter-subject variability. Using three C57BL/6-based mouse strains of both sexes, we identified three chronotoxicity classes, with distinct circadian toxicity patterns of irinotecan, a topoisomerase I inhibitor active against colorectal cancer. Liver and colon circadian 24-h expression patterns of clock genes Rev-erbα and Bmal1 best discriminated these chronotoxicity classes, among 27 transcriptional 24-h time series, according to Sparse Linear Discriminant Analysis. An 8-hour phase advance was found both for Rev-erbα and Bmal1 mRNA expressions and for irinotecan chronotoxicity in clock-altered Per2m/m mice. The application of a Maximum-A-Posteriori Bayesian inference method identified a linear model based on Rev-erbα and Bmal1 circadian expressions that accurately predicted for optimal irinotecan timing. The assessment of the Rev-erbα and Bmal1 regulatory transcription loop in the molecular clock could critically improve the tolerability of chemotherapy through a mathematical model-based determination of host specific optimal timing. Major findings: The optimal circadian timing of an anticancer drug was predicted despite its variation by up to 8-h along the 24 h among six mouse categories. This prediction relied on a mathematical model using liver circadian expression of clock genes Rev-erbα and Bmal1 as input data and treatment tolerability as output parameter.
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Cancer Research, American Association for Cancer Research, 2013, 73 (24), pp.7176-7188. 〈10.1158/0008-5472.CAN-13-1528〉
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Contributeur : Myriam Baverel <>
Soumis le : jeudi 23 janvier 2014 - 09:31:57
Dernière modification le : jeudi 5 avril 2018 - 12:30:23

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X.-M. Li, Ali Mohammad-Djafari, M. Dumitru, Sandrine Dulong, Elisabeth Filipski, et al.. A circadian clock transcription model for the personalization of cancer chronotherapy. Cancer Research, American Association for Cancer Research, 2013, 73 (24), pp.7176-7188. 〈10.1158/0008-5472.CAN-13-1528〉. 〈hal-00935081〉

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