Abstract
Anti-cancer therapies often exhibit only short-term effects. Tumors typically develop drug resistance causing relapses that might be tackled with drug combinations. Identification of the right combination is challenging and would benefit from high-content, high-throughput combinatorial screens directly on patient biopsies. However, such screens require a large amount of material, normally not available from patients. To address these challenges, we developed a scalable microfluidic workflow to screen hundreds of drug combinations in picoliter-size droplets using transcriptome changes as a readout for drug effects. We devised a deterministic combinatorial DNA barcoding approach to encode treatment conditions, enabling the gene expression-based readout of drug effects in a highly multiplexed fashion. We applied our method to screen the effect of 420 drug combinations on the transcriptome of K562 cells using only ∼250 single cell droplets per condition, to successfully predict synergistic and antagonistic drug pairs, as well as their pathway activities.
Competing Interest Statement
L.M., R.U. and C.A.M. are inventors on patent applications covering parts of the technology described here. J.S-R has received funding from GSK and Sanofi and consultant fees from Travere Therapeutics. B.S. received consultant fees from Turbine Ltd.
