Dynamic Rearrangement of Cell States Detected by Systematic Screening of Sequential Anticancer Treatments

Simon Koplev, James Longden, Jesper Ferkinghoff-Borg, Mathias Blicher Bjerregård, Thomas R. Cox, Janine T. Erler, Jesper T. Pedersen, Franziska Voellmy, Morten Otto Alexander Sommer, Rune Linding

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Abstract

Signaling networks are nonlinear and complex, involving a large ensemble of dynamic interaction states that fluctuate in space and time. However, therapeutic strategies, such as combination chemotherapy, rarely consider the timing of drug perturbations. If we are to advance drug discovery for complex diseases, it will be essential to develop methods capable of identifying dynamic cellular responses to clinically relevant perturbations. Here, we present a Bayesian dose-response framework and the screening of an oncological drug matrix, comprising 10,000 drug combinations in melanoma and pancreatic cancer cell lines, from which we predict sequentially effective drug combinations. Approximately 23% of the tested combinations showed high-confidence sequential effects (either synergistic or antagonistic), demonstrating that cellular perturbations of many drug combinations have temporal aspects, which are currently both underutilized and poorly understood.
Original languageEnglish
JournalCell Reports
Volume20
Issue number12
Pages (from-to)2784-2791
ISSN2211-1247
DOIs
Publication statusPublished - 2017

Cite this

Koplev, S., Longden, J., Ferkinghoff-Borg, J., Blicher Bjerregård, M., Cox, T. R., Erler, J. T., Pedersen, J. T., Voellmy, F., Sommer, M. O. A., & Linding, R. (2017). Dynamic Rearrangement of Cell States Detected by Systematic Screening of Sequential Anticancer Treatments. Cell Reports, 20(12), 2784-2791. https://doi.org/10.1016/j.celrep.2017.08.095