Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

Abstract	Drug sensitivity and resistance are conventionally quantified by IC50 or Emax values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC50 and Emax on division rate creates artefactual correlations between genotype and drug sensitivity, while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative small molecule drug-response metrics that are insensitive to division number. These are based on estimation of the magnitude of drug-induced growth rate inhibition (GR) using endpoint or time-course assays. We show that GR50 and GRmax are superior to conventional metrics for assessing the effects of small molecule drugs in dividing cells. Moreover, adopting GR metrics requires only modest changes in experimental protocols. We expect GR metrics to improve the study of cell signaling and growth using small molecules and biologics and to facilitate the discovery of drug-response biomarkers and the identification of drugs effective against specific patient-derived tumor cells.
Authors	Marc Hafner, Mario Niepel, Mirra Chung, Peter K Sorger
Journal	Nature methods (Nat Methods) Vol. 13 Issue 6 Pg. 521-7 (06 2016) ISSN: 1548-7105 [Electronic] United States
PMID	27135972 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural)
Chemical References	Antineoplastic Agents Biological Products Small Molecule Libraries
Topics	Antineoplastic Agents (pharmacology) Biological Products (pharmacology) Cell Count Cell Culture Techniques Cell Line, Tumor Cell Proliferation (drug effects) Computer Simulation Dose-Response Relationship, Drug Drug Discovery (methods) Drug Resistance, Neoplasm High-Throughput Screening Assays Humans Inhibitory Concentration 50 Models, Theoretical Small Molecule Libraries (pharmacology)

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