Malfunctions of circadian clock trigger abnormal cellular processes and influence tumorigenesis. Using an in vitro and in vivo xenograft model, we show that circadian clock disruption via the downregulation of the core-clock genes BMAL1, PER2, and NR1D1 impacts the circadian phenotype of MYC, WEE1, and TP53, and affects proliferation, apoptosis, and cell migration. In particular, both our in vitro and in vivo results suggest an impairment of cell motility and a reduction in micrometastasis formation upon knockdown of NR1D1, accompanied by altered expression levels of SNAI1 and CD44. Interestingly we show that differential proliferation and reduced tumour growth in vivo may be due to the additional influence of the host-clock and/or to the 3D tumour architecture. Our results raise new questions concerning host–tumour interaction and show that core-clock genes are involved in key cancer properties, including the regulation of cell migration and invasion by NR1D1 in zebrafish xenografts.

Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient's internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals, we review the precision of predictions and the potential usage with respect to cancer treatment and discuss whether the patient’s internal time and circadian observables, may provide an additional indication for individualized treatment timing. Besides the health improvement, timing treatment may imply financial advantages, by ameliorating side effects of treatments, thus reducing costs. Summarizing the advances of recent years, this review brings together the current clinical standard for measuring biological time, the general assessment of circadian rhythmicity, the usage of rhythmic variables to predict biological time and models of circadian rhythmicity.