Imagen de Portada

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

Guardado en:
Publicado en:Nature Communications vol. 15, no. 1 (2024), p. 7205
Autor principal: Ector, Carolin
Otros Autores: Schmal, Christoph, Didier, Jeff, De Landtsheer, Sébastien, Finger, Anna-Marie, Müller-Marquardt, Francesca, Schulte, Johannes H., Sauter, Thomas, Keilholz, Ulrich, Herzel, Hanspeter, Kramer, Achim, Granada, Adrián E.
Publicado:
Nature Publishing Group
Materias:
Side effects
Sensitivity analysis
Cancer therapies
Cell culture
Biological effects
Phenotypes
Medical imaging
Genetic factors
Computer applications
Biological activity
Cancer
Time of use
Data analysis
Chemotherapy
Circadian rhythms
Phenotyping
Antineoplastic drugs
Optimization
Tumor cell lines
Circadian rhythm
Software
Environmental
Acceso en línea:Citation/Abstract
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:The circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devise a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.The circadian rhythm has been linked to cancer cell sensitivity to therapy but tools to understand this further are limited. Here, by combining live-cell imaging and computational tools, the authors develop a high-throughput deep-phenotyping approach to evaluate circadian rhythms and use it to determine time-of-day drug sensitivity in cancer cell lines.
ISSN:2041-1723
DOI:10.1038/s41467-024-51611-3
Fuente:Health & Medical Collection