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Strategies for In Vivo Screening and Mitigation of Hepatotoxicity Associated with Antisense Drugs

Antisense oligonucleotide (ASO) gapmers downregulate gene expression by inducing enzyme-dependent degradation of targeted RNA and represent a promising therapeutic platform for addressing previously undruggable genes. Unfortunately, their therapeutic application, particularly that of the more potent...

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Detalles Bibliográficos
Autores principales: Kamola, Piotr J., Maratou, Klio, Wilson, Paul A., Rush, Kay, Mullaney, Tanya, McKevitt, Tom, Evans, Paula, Ridings, Jim, Chowdhury, Probash, Roulois, Aude, Fairchild, Ann, McCawley, Sean, Cartwright, Karen, Gooderham, Nigel J., Gant, Timothy W., Moores, Kitty, Hughes, Stephen A., Edbrooke, Mark R., Clark, Kenneth, Parry, Joel D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537172/
https://www.ncbi.nlm.nih.gov/pubmed/28918038
http://dx.doi.org/10.1016/j.omtn.2017.07.003
Descripción
Sumario:Antisense oligonucleotide (ASO) gapmers downregulate gene expression by inducing enzyme-dependent degradation of targeted RNA and represent a promising therapeutic platform for addressing previously undruggable genes. Unfortunately, their therapeutic application, particularly that of the more potent chemistries (e.g., locked-nucleic-acid-containing gapmers), has been hampered by their frequent hepatoxicity, which could be driven by hybridization-mediated interactions. An early de-risking of this liability is a crucial component of developing safe, ASO-based drugs. To rank ASOs based on their effect on the liver, we have developed an acute screen in the mouse that can be applied early in the drug development cycle. A single-dose (3-day) screen with streamlined endpoints (i.e., plasma transaminase levels and liver weights) was observed to be predictive of ASO hepatotoxicity ranking established based on a repeat-dose (15 day) study. Furthermore, to study the underlying mechanisms of liver toxicity, we applied transcriptome profiling and pathway analyses and show that adverse in vivo liver phenotypes correlate with the number of potent, hybridization-mediated off-target effects (OTEs). We propose that a combination of in silico OTE predictions, streamlined in vivo hepatotoxicity screening, and a transcriptome-wide selectivity screen is a valid approach to identifying and progressing safer compounds.