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

Jenny Mattsson, Ludvig Ekdahl, Fredrik Junghus, Ram Ajore, Eva Erlandsson, Abhishek Niroula, Maroulio Pertesi, Björn Frendéus, Ingrid Teige and Björn Nilsson ()
Additional contact information
Jenny Mattsson: Hematology and Transfusion Medicine
Ludvig Ekdahl: Hematology and Transfusion Medicine
Fredrik Junghus: Hematology and Transfusion Medicine
Ram Ajore: Hematology and Transfusion Medicine
Eva Erlandsson: Hematology and Transfusion Medicine
Abhishek Niroula: Hematology and Transfusion Medicine
Maroulio Pertesi: Hematology and Transfusion Medicine
Björn Frendéus: BioInvent International AB
Ingrid Teige: BioInvent International AB
Björn Nilsson: Hematology and Transfusion Medicine

Nature Communications, 2021, vol. 12, issue 1, 1-8

Abstract: Abstract 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.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-021-21518-4 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21518-4

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-21518-4

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().