title: Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs.
abstract: Quantitative prediction of cellular responses to drugs and drug combinations is a challenging and valuable topic in pharmaceutical research. In the past decade, microarray technology has become a routine tool for monitoring genome-wide expression changes and has been widely adopted for exploring drug response in the pharmaceutical field. However, how to predict the synergistic effect of drug combinations using microarray data is a challenging task. In this article, we report a simple prediction framework based on the genome-wide and quantitative profiling of cellular responses to individual drugs. By exploring the differential expression profiles, our correlation-based strategy can reveal the synergistic effects of drug combinations. The comparison with gold-standard experimental results demonstrates the strengths and weaknesses in relation to prediction based only on cellular response to individual drugs. Specifically, the prediction strategy may work for a drug combination whose individual drugs show related transcriptomic mechanisms but not for others.
authors.affiliation: National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
authors.forename: J
authors.initials: J
authors.lastname: Zhao
authors.affiliation: National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
authors.forename: X-S
authors.initials: XS
authors.lastname: Zhang
authors.affiliation: National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
authors.forename: S
authors.initials: S
authors.lastname: Zhang