Scientists from the University of Luxembourg and Granada Lab – Charité Comprehensive Cancer Center have demonstrated that specific treatment timings can significantly enhance tumor cell death and reduce side effects.
Circadian rhythms, the internal biological cycles that regulate essential processes such as wakefulness and sleep, are crucial for maintaining overall health. Disruptions in these rhythms can have profound impacts on health, contributing to various diseases. Aligning medical treatments with a patient’s circadian clock can significantly enhance the effectiveness of therapies. Despite the known benefits, the clinical application of circadian-based treatments has been limited by the lack of efficient strategies to determine the optimal timing for specific drugs.
Addressing this critical gap, an interdisciplinary international team of researchers has developed a pioneering high-throughput method to analyse how cancer cells respond to drugs at different times of the day. By employing multiple-live reporter systems to monitor circadian rhythms and implementing cutting-edge time-of-day treatment protocols, the team has created a versatile framework.
“At the University of Luxembourg, we contributed to this interesting project by performing thorough statistical analysis of the multiple-live reporter systems data, and by applying various machine learning-based algorithms to expose time-of-day and drug-specific sensitivity of various cancer cell lines”, mentions the research team composed of Jeff Didier, doctoral student, Sébastien De Landtsheer, postdoctoral researcher and Thomas Sauter, Professor within the Department of Life Sciences and Medicine.
The implications of this research are profound. By pinpointing the most responsive cell types and drug combinations, the study paves the way for more personalised and precise cancer therapies. This breakthrough underscores the importance of timing in cancer treatments and holds the potential to transform clinical practices.
Publication: “Time-of-day effects of cancer drugs revealed by high-throughput deep phenotyping“, Nature Communications, August 2024