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

Cell Rep. 2017 Sep 19;20(12):2784-2791. doi: 10.1016/j.celrep.2017.08.095.


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.

Keywords: cancer; chemotherapy; sequential; time-stagger.

MeSH terms

  • Antineoplastic Combined Chemotherapy Protocols / analysis*
  • Antineoplastic Combined Chemotherapy Protocols / pharmacology*
  • Bayes Theorem
  • Cell Count
  • Cell Line, Tumor
  • Cell Survival / drug effects
  • Dose-Response Relationship, Drug
  • Drug Screening Assays, Antitumor*
  • Drug Synergism
  • Humans
  • Reproducibility of Results
  • Time Factors