2026-04-17T15:56:23Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/688712025-12-12T03:11:27Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Toledano, Ignasi author Supek, Fran author Lehner, Ben author 2024-12-02T07:17:13Z 2024-12-02T07:17:13Z 2024 Premature termination codons (PTCs) cause ~10-20% of inherited diseases and are a major mechanism of tumor suppressor gene inactivation in cancer. A general strategy to alleviate the effects of PTCs would be to promote translational readthrough. Nonsense suppression by small molecules has proven effective in diverse disease models, but translation into the clinic is hampered by ineffective readthrough of many PTCs. Here we directly tackle the challenge of defining drug efficacy by quantifying the readthrough of ~5,800 human pathogenic stop codons by eight drugs. We find that different drugs promote the readthrough of complementary subsets of PTCs defined by local sequence context. This allows us to build interpretable models that accurately predict drug-induced readthrough genome-wide, and we validate these models by quantifying endogenous stop codon readthrough. Accurate readthrough quantification and prediction will empower clinical trial design and the development of personalized nonsense suppression therapies. Work in the Supek laboratory was supported by an ERC StG ‘HYPER-INSIGHT’ (757700) and ERC CoG ‘STRUCTOMATIC’ (101088342), Horizon2020 project ‘DECIDER’ (965193), Horizon Europe project ‘LUCIA’ (101096473), Spanish government project ‘REPAIRSCAPE’, CaixaResearch project ‘POTENT-IMMUNO’ (HR22-00402), an ICREA professorship to F.S., the SGR funding from the Catalan government and a Novo Nordisk Fonden starting package. Work in the Lehner laboratory was funded by European Research Council (ERC) Advanced (grant 883742) and Consolidator (grant 616434), the Spanish Ministry of Science and Innovation (BFU2017-89488-P, EMBL Partnership, Severo Ochoa Center of Excellence), the Bettencourt Schueller Foundation, the AXA Research Fund, Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR, 2017 SGR 1322) and the CERCA Program/Generalitat de Catalunya. The authors would like to thank the four members E. Ramírez, A. Bote, E. Julià and Ò. Fornàs of the Flow Cytometry CRG Core Unit for their support and time, together with G. Palou (IRB) for his help in retrieving the transcript sequences from the Ensembl database and all members of the Supek and Lehner laboratories for helpful discussions and suggestions. Genetics research Genomics Clinical trial design Genome-scale quantification and prediction of pathogenic stop codon readthrough by small molecules