Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing.
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Mattsson J, Ekdahl L, Junghus F, Ajore R, Erlandsson E, Niroula A, Pertesi M, Frendéus B, Teige I, Nilsson B
Nat Commun 12 (1) 1277 [2021-02-24; online 2021-02-24]
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.
PubMed 33627649
DOI 10.1038/s41467-021-21518-4
Crossref 10.1038/s41467-021-21518-4
pmc: PMC7904777
pii: 10.1038/s41467-021-21518-4