Ribosomal read through as an alternative therapy for patients with hemophilia with nonsense mutations

Drug-induced ribosomal read through can rescue nonsense mutations by inserting a replacement amino acid at the premature termination codon. Hemophilia A (HA) is well suited for this therapy as even modest increases in cofactor activity can substantially improve severe bleeding symptoms. Identifying highly efficient, low-toxicity read through compounds and pinpointing responsive mutations are critical steps in advancing this therapy.

To compare the effects of different read through compounds and identify nonsense mutations in F8 that respond to read through treatments.

We used a cell-based model stably expressing B-domain-deleted factor (F)VIII-Gaussia luciferase fusion proteins to evaluate the efficacy of 2,6-diaminopurine (DAP), ELX-02, and G418. Rescue of nonsense mutants was assessed by measuring secreted luciferase activity, as well as FVIII activity and antigen levels. Immunoprecipitation-immunoblotting was used to detect intracellular and secreted FVIII. DAP efficacy was further investigated in vivo using a mouse model expressing nonsense mutant human FVIII delivered via hydrodynamic tail vein injection.

We tested 26 nonsense mutations, including the most prevalent ones in hemophilia A. All 3 compounds induced varying levels of read through, but DAP showed higher efficacy than ELX-02 and G418 in most mutants. Immunoblotting confirmed the presence of intact fusion proteins in cell lysates and media after DAP and G418 treatments. Nonsense suppression was also confirmed in full-length FVIII. Rescue efficacy was determined by read through efficiency and the effects of replacement amino acids on FVIII secretion and activity. Finally, DAP treatment rescued the p.R355X mutant of human full-length FVIII expressed in mice, yielding detectable levels of antigen in plasma.

Ribosomal read through therapy offers a promising small-molecule treatment option for managing bleeding symptoms in patients with hemophilia A based on individual mutation profiles.