Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing

Nat Commun. 2021 Feb 24;12(1):1277. doi: 10.1038/s41467-021-21518-4.


Therapeutic antibodies are transforming the treatment of cancer and autoimmune diseases. Today, a key challenge is finding antibodies against new targets. Phenotypic discovery promises to achieve this by enabling discovery of antibodies with therapeutic potential without specifying the molecular target a priori. Yet, deconvoluting the targets of phenotypically discovered antibodies remains a bottleneck; efficient deconvolution methods are needed for phenotypic discovery to reach its full potential. Here, we report a comprehensive investigation of a target deconvolution approach based on pooled CRISPR/Cas9. Applying this approach within three real-world phenotypic discovery programs, we rapidly deconvolute the targets of 38 of 39 test antibodies (97%), a success rate far higher than with existing approaches. Moreover, the approach scales well, requires much less work, and robustly identifies antibodies against the major histocompatibility complex. Our data establish CRISPR/Cas9 as a highly efficient target deconvolution approach, with immediate implications for the development of antibody-based drugs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antibodies / metabolism
  • CRISPR-Cas Systems / genetics
  • Cell Line, Tumor
  • Cell Survival / genetics
  • Cell Survival / physiology
  • Clustered Regularly Interspaced Short Palindromic Repeats / genetics
  • Gene Editing*
  • Humans


  • Antibodies