Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions

Highlights

• Rigorous control of growth rate is key to understanding response to drug combinations

• Three readily interpretable principal components (PCs) explain >90% of variance

• The 2^nd PC exposes responses to individual drugs, revealing a new effect of myriocin

• The 3^rd PC captures emergent responses and can predict antagonism with a third drug

Summary

Effective design of combination therapies requires understanding the changes in cell physiology that result from drug interactions. Here, we show that the genome-wide transcriptional response to combinations of two drugs, measured at a rigorously controlled growth rate, can predict higher-order antagonism with a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90% of the variation in cellular response can be decomposed into three principal components (PCs) that have clear biological interpretations. We demonstrate that the third PC captures emergent transcriptional programs that are dependent on both drugs and can predict antagonism with a third drug targeting the emergent pathway. We further show that emergent gene expression patterns are most pronounced at a drug ratio where the drug interaction is strongest, providing a guideline for future measurements. Our results provide a readily applicable recipe for uncovering emergent responses in other systems and for higher-order drug combinations. A record of this paper’s transparent peer review process is included in the Supplemental Information.