Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing
(2021) In Nature Communications 12. p.1-8- 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... (More)
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.
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- author
- Mattsson, Jenny LU ; Ekdahl, Ludvig LU ; Junghus, Fredrik LU ; Ajore, Ram LU ; Erlandsson, Eva LU ; Niroula, Abhishek LU ; Pertesi, Maroulio LU ; Frendéus, Björn LU ; Teige, Ingrid LU and Nilsson, Björn LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Antibodies/metabolism, CRISPR-Cas Systems/genetics, Cell Line, Tumor, Cell Survival/genetics, Clustered Regularly Interspaced Short Palindromic Repeats/genetics, Gene Editing, Humans
- in
- Nature Communications
- volume
- 12
- article number
- 1277
- pages
- 1 - 8
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85101554959
- pmid:33627649
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-021-21518-4
- language
- English
- LU publication?
- yes
- id
- 857305dd-d0f4-4cf3-a288-1dd7d31cea2b
- date added to LUP
- 2022-10-04 15:06:32
- date last changed
- 2024-09-06 03:57:27
@article{857305dd-d0f4-4cf3-a288-1dd7d31cea2b, abstract = {{<p>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.</p>}}, author = {{Mattsson, Jenny and Ekdahl, Ludvig and Junghus, Fredrik and Ajore, Ram and Erlandsson, Eva and Niroula, Abhishek and Pertesi, Maroulio and Frendéus, Björn and Teige, Ingrid and Nilsson, Björn}}, issn = {{2041-1723}}, keywords = {{Antibodies/metabolism; CRISPR-Cas Systems/genetics; Cell Line, Tumor; Cell Survival/genetics; Clustered Regularly Interspaced Short Palindromic Repeats/genetics; Gene Editing; Humans}}, language = {{eng}}, pages = {{1--8}}, publisher = {{Nature Publishing Group}}, series = {{Nature Communications}}, title = {{Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing}}, url = {{http://dx.doi.org/10.1038/s41467-021-21518-4}}, doi = {{10.1038/s41467-021-21518-4}}, volume = {{12}}, year = {{2021}}, }