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Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions

Kyuho Han1, Edwin E Jeng1,2, Gaelen T Hess1

  • 1Department of Genetics, Stanford University, Stanford, California, USA.

Nature Biotechnology
|March 21, 2017
PubMed

Insights

A new CRISPR-based double knockout system efficiently screens cancer drug combinations. This approach identified synergistic drug pairs, including BCL2L1 and MCL1, effective against resistant leukemia cells.

Area of Science:

  • Genomics
  • Cancer Biology
  • Drug Discovery

Background:

  • Drug resistance in cancer necessitates novel combination therapies.
  • Screening all potential drug combinations is computationally and experimentally challenging.
  • CRISPR-based genetic screening offers a powerful approach to identify functional genetic interactions.

Purpose of the Study:

  • To develop and validate a CRISPR-based double knockout (CDKO) system for efficient high-throughput screening of combinatorial genetic interactions.
  • To construct a large-scale human genetic interaction (GI) map.
  • To identify synthetic lethal drug target pairs and synergistic drug combinations for cancer therapy.

Main Methods:

  • Development of a CRISPR-based double knockout (CDKO) system with efficient paired single guide RNA (sgRNA) library cloning and sequencing.
  • Application of CDKO to generate a human GI map in K562 leukemia cells, targeting 21,321 gene pairs.
  • Utilizing a robust statistical scoring method to calculate genetic interactions (GIs) from CRISPR-deleted gene pairs.
  • Validation of the CDKO system using known modifiers of ricin toxicity.

Main Results:

  • Generated a comprehensive human GI map of 490,000 double-sgRNAs.
  • Identified synthetic lethal drug target pairs exhibiting synergistic killing upon drug treatment.
  • Discovered the BCL2L1 and MCL1 drug combination, demonstrating efficacy in imatinib-resistant leukemia cells.
  • Validated novel and known genetic interactions.

Conclusions:

  • The CDKO system provides an effective high-throughput strategy for screening synergistic drug combinations.
  • This CRISPR-based tool enables the dissection of functional genetic interaction networks.
  • The identified synthetic lethal interactions offer potential therapeutic strategies for drug-resistant cancers.

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