Mechanism-based approach in designing patient-specific combination therapies for nonsense mutation diseases

Premature termination codon (PTC) diseases account for ∼12% of all human disease mutations. Although there are no FDA approved treatments for increasing PTC readthrough, one readthrough inducing drug, ataluren, has conditional approval for treatment of Duchenne muscular dystrophy elsewhere. Ataluren displays low toxicity in clinical trials for treatment of PTC diseases, but its therapeutic effects are inconsistent. The messenger RNA (mRNA) sequence context of a PTC is a major determinant of PTC readthrough efficiency. We have shown that ataluren stimulates readthrough exclusively by competitively inhibiting release factor complex (RFC) catalysis of translation termination. Here, using an in vitro reconstituted system, we demonstrate that PTC identity and the immediately adjacent mRNA sequence contexts modulate RFC activity in terminating peptide elongation. Such modulation largely determines the effectiveness of ataluren in stimulating readthrough, whether added alone or in combination with either the aminoglycoside G418 or an anticodon edited aa-tRNA, which stimulate readthrough by mechanisms orthogonal to that of ataluren. Our results suggest a potential rationale for the variability of ataluren effectiveness in stimulating readthrough. We hypothesize that patients harboring a PTC mutation within a sequence context promoting strong interaction with RFC will be resistant to ataluren, but that ataluren treatment will be more effective for patient sequences conferring weaker interaction with RFC.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2025-03-07
DOI
https://doi.org/10.1093/nar/gkaf216
Citations
2
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mechanism-based approach in designing patient-specific combination therapies for nonsense mutation diseases

Barry S. Cooperman, Saleem Y. Bhat, Yale E. Goldman, John D. Lueck et al.
2 citations
Nucleic Acids Research
RNA and protein synthesis mechanisms
1.61
article

Mechanism-based approach in designing patient-specific combination therapies for nonsense mutation diseases

Barry S. Cooperman, Saleem Y. Bhat, Yale E. Goldman, John D. Lueck, Xiaonan Cui, A.A. Bhattacharya, Hong Li
article en
2 citations

Abstract

Premature termination codon (PTC) diseases account for ∼12% of all human disease mutations. Although there are no FDA approved treatments for increasing PTC readthrough, one readthrough inducing drug, ataluren, has conditional approval for treatment of Duchenne muscular dystrophy elsewhere. Ataluren displays low toxicity in clinical trials for treatment of PTC diseases, but its therapeutic effects are inconsistent. The messenger RNA (mRNA) sequence context of a PTC is a major determinant of PTC readthrough efficiency. We have shown that ataluren stimulates readthrough exclusively by competitively inhibiting release factor complex (RFC) catalysis of translation termination. Here, using an in vitro reconstituted system, we demonstrate that PTC identity and the immediately adjacent mRNA sequence contexts modulate RFC activity in terminating peptide elongation. Such modulation largely determines the effectiveness of ataluren in stimulating readthrough, whether added alone or in combination with either the aminoglycoside G418 or an anticodon edited aa-tRNA, which stimulate readthrough by mechanisms orthogonal to that of ataluren. Our results suggest a potential rationale for the variability of ataluren effectiveness in stimulating readthrough. We hypothesize that patients harboring a PTC mutation within a sequence context promoting strong interaction with RFC will be resistant to ataluren, but that ataluren treatment will be more effective for patient sequences conferring weaker interaction with RFC.

Nucleic Acids ResearchVol. 53(6)
University of Rochester (US), University of Pennsylvania (US)
Cystic Fibrosis Foundation, National Institutes of Health
Good health and well-being
Openalex Percentile: Top 18%
RNA and protein synthesis mechanisms
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.