Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets
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 direc...
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Veröffentlicht in: | Nature communications 2022-08, Vol.13 (1), p.4450-15, Article 4450 |
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Sprache: | eng |
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Zusammenfassung: | 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 present a scalable microfluidic workflow, called Combi-Seq, to screen hundreds of drug combinations in picoliter-size droplets using transcriptome changes as a readout for drug effects. We devise 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 apply Combi-Seq 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.
Current screens to assess tumour drug resistance require a large amount of material, normally not available from patients. Here the authors report CombiSeq, a scalable microfluidic workflow to screen hundreds of drug combinations in picoliter-size droplets using transcriptome changes as a readout. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-022-32197-0 |