Community assessment of cancer drug combination screens identifies strategies for synergy prediction

Abstract

<p>In the last decade advances in genomics, uptake of targeted therapies, and the advent of personalized treatment has fueled a step change in cancer care. However the effectiveness of most targeted therapies is short lived, as tumors evolve and develop resistance. Combinations of drugs offer the potential to overcome resistance. The space of possible  combinations is vast, and significant advances are required to effectively find optimal treatment regimens tailored to a patient’s tumor. DREAM and AstraZeneca hosted a challenge open to the scientific community aimed at computational prediction of synergistic drug combinations and associated predictive biomarkers. We released a data set comprising ~11,500 experimentally tested drug combinations, coupled to deep molecular characterization of the respective 85 cancer cell lines. Of 150 submitted approaches, methods that incorporated prior knowledge of putative drug targets outperformed other approaches in predicting drug synergy across independent data. Genomic features of winning models revealed putative mechanisms of drug synergy for multiple drugs in combination with PI3K/AKT pathway inhibitors.</p>