The delivery challenge: fulfilling the promise of therapeutic genome editing.


Journal

Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648

Informations de publication

Date de publication:
07 2020
Historique:
received: 02 11 2018
accepted: 19 05 2020
pubmed: 1 7 2020
medline: 8 10 2020
entrez: 1 7 2020
Statut: ppublish

Résumé

Genome editing has the potential to treat an extensive range of incurable monogenic and complex diseases. In particular, advances in sequence-specific nuclease technologies have dramatically accelerated the development of therapeutic genome editing strategies that are based on either the knockout of disease-causing genes or the repair of endogenous mutated genes. These technologies are progressing into human clinical trials. However, challenges remain before the therapeutic potential of genome editing can be fully realized. Delivery technologies that have serendipitously been developed over the past couple decades in the protein and nucleic acid delivery fields have been crucial to genome editing success to date, including adeno-associated viral and lentiviral vectors for gene therapy and lipid nanoparticle and other non-viral vectors for nucleic acid and protein delivery. However, the efficiency and tissue targeting capabilities of these vehicles must be further improved. In addition, the genome editing enzymes themselves need to be optimized, and challenges regarding their editing efficiency, specificity and immunogenicity must be addressed. Emerging protein engineering and synthetic chemistry approaches can offer solutions and enable the development of safe and efficacious clinical genome editing.

Identifiants

pubmed: 32601435
doi: 10.1038/s41587-020-0565-5
pii: 10.1038/s41587-020-0565-5
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

845-855

Subventions

Organisme : NINDS NIH HHS
ID : UG3 NS115599
Pays : United States

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Auteurs

Joost van Haasteren (J)

California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA.

Jie Li (J)

Department of Bioengineering, University of California, Berkeley, CA, USA.
Innovative Genomics Institute (IGI), University of California, Berkeley, CA, USA.

Olivia J Scheideler (OJ)

Department of Bioengineering, University of California, Berkeley, CA, USA.

Niren Murthy (N)

California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA. nmurthy@berkeley.edu.
Department of Bioengineering, University of California, Berkeley, CA, USA. nmurthy@berkeley.edu.
Innovative Genomics Institute (IGI), University of California, Berkeley, CA, USA. nmurthy@berkeley.edu.

David V Schaffer (DV)

California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA. schaffer@berkeley.edu.
Department of Bioengineering, University of California, Berkeley, CA, USA. schaffer@berkeley.edu.
Innovative Genomics Institute (IGI), University of California, Berkeley, CA, USA. schaffer@berkeley.edu.
Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA, USA. schaffer@berkeley.edu.
Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA. schaffer@berkeley.edu.
Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA. schaffer@berkeley.edu.

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