Time-of-day effects of cancer drugs revealed by high-throughput deep phenotyping

This research introduces a high-throughput approach integrating live-imaging and data analysis to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. It identifies optimal treatment windows and responsive cell types and drug combinations, and uses computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. The versatile approach is adaptable to various biological models, leveraging circadian rhythms to optimize anti-cancer drug treatments.

Carolin Ector, Christoph Schmal, Jeff Didier, Sébastien De Landtsheer, Anna-Marie Finger, Francesca Müller-Marquardt, Johannes H. Schulte, Thomas Sauter, Ulrich Keilholz, Hanspeter Herzel, Achim Kramer, Adrián E. Granada