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Viral Vectors, Animal Models, and Cellular Targets for Gene Therapy of Cystic Fibrosis Lung Disease
Author(s) -
Yinghua Tang,
Ziying Yan,
John F. Engelhardt
Publication year - 2020
Publication title -
human gene therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.633
H-Index - 149
eISSN - 1557-7422
pISSN - 1043-0342
DOI - 10.1089/hum.2020.013
Subject(s) - genetic enhancement , cystic fibrosis , disease , lung , biology , transduction (biophysics) , immunology , gene delivery , viral vector , medicine , gene , pathology , genetics , recombinant dna , biochemistry
After more than two decades since clinical trials tested the first use of recombinant adeno-associated virus (rAAV) to treat cystic fibrosis (CF) lung disease, gene therapy for this disorder has undergone a tremendous resurgence. Fueling this enthusiasm has been an enhanced understanding of rAAV transduction biology and cellular processes that limit transduction of airway epithelia, the development of new rAAV serotypes and other vector systems with high-level tropism for airway epithelial cells, an improved understanding of CF lung pathogenesis and the cellular targets for gene therapy, and the development of new animal models that reproduce the human CF disease phenotype. These advances have created a preclinical path for both assessing the efficacy of gene therapies in the CF lung and interrogating the target cell types in the lung required for complementation of the CF disease state. Lessons learned from early gene therapy attempts with rAAV in the CF lung have guided thinking for the testing of next-generation vector systems. Although unknown questions still remain regarding the cellular targets in the lung that are required or sufficient to complement CF lung disease, the field is now well positioned to tackle these challenges. This review will highlight the role that next-generation CF animal models are playing in the preclinical development of gene therapies for CF lung disease and the knowledge gaps in disease pathophysiology that these models are attempting to fill.

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