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

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.

Abhishek Niroula

DDLS Fellow

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

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