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The future of gene-targeted therapy for hereditary tyrosinemia type 1 as a lead indication among the inborn errors of metabolism.
Introduction: Inborn errors of metabolism (IEMs) often result from single-gene mutations and collectively cause liver dysfunction in neonates leading to chronic liver and systemic disease. Current treatments for many IEMs are limited to maintenance therapies that may still require orthotropic liver transplantation. Gene therapies offer a potentially superior approach by correcting or replacing defective genes with functional isoforms; however, they face unique challenges from complexities presented by individual diseases and their diverse etiology, presentation, and pathophysiology. Furthermore, immune responses, off-target gene disruption, and tumorigenesis are major concerns that need to be addressed before clinical application of gene therapy.
Areas covered: The current treatments for IEMs are reviewed as well as the advances in, and barriers to, gene therapy for IEMs. Attention is then given to ex vivo and in vivo gene therapy approaches for hereditary tyrosinemia type 1 (HT1). Of all IEMs, HT1 is particularly amenable to gene therapy because of a selective growth advantage conferred to corrected cells, thereby lowering the initial transduction threshold for phenotypic relevance.
Expert opinion: It is proposed that not only is HT1 a safe indication for gene therapy, its unique characteristics position it to be an ideal IEM to develop for clinical investigation.
Areas covered: The current treatments for IEMs are reviewed as well as the advances in, and barriers to, gene therapy for IEMs. Attention is then given to ex vivo and in vivo gene therapy approaches for hereditary tyrosinemia type 1 (HT1). Of all IEMs, HT1 is particularly amenable to gene therapy because of a selective growth advantage conferred to corrected cells, thereby lowering the initial transduction threshold for phenotypic relevance.
Expert opinion: It is proposed that not only is HT1 a safe indication for gene therapy, its unique characteristics position it to be an ideal IEM to develop for clinical investigation.
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