A circadian clock transcription model for the personalization of cancer chronotherapy
Menée à l'aide de modèles murins, cette étude évalue l'intérêt d'un modèle mathématique pour optimiser l'efficacité et la tolérabilité d'une chimiothérapie en fonction de son heure d'administration
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.