Towards a tRNA-based therapy for nonsense mutations: developing engineered suppressor tRNAs to combat genetic diseases

Abstract

Recent advancements in genomic technologies have significantly enhanced the accessibility and accuracy of the detection of genetic diseases, leading to precise diagnoses of various human disorders and their underlying causes. Accounting for approximately 11% of all genetic diseases, nonsense mutations present a critical challenge as they introduce premature termination codons (PTCs) that disrupt protein synthesis and result in truncated, non-functional proteins. These mutations are associated with diverse genetic disorders, including cystic fibrosis and cancer. To date, diseases resulting from nonsense mutations are still untreatable, as none of the strategies targeting these mutations have successfully completed clinical trials, highlighting the urgent need for innovative therapeutic options. This thesis provides a comprehensive framework and pioneers an innovative pharmaceutical approach to address nonsense mutations using engineered suppressor transfer RNAs (sup-tRNAs), combining molecular precision with therapeutic versatility. Sup-tRNAs are engineered to decode the PTCs and incorporate the correct amino acids, restoring the synthesis of full-length, functional proteins. To maximize their clinical potential, in Chapter 1 of this thesis we introduce a systematic optimization framework based on previous knowledge from our group. Through lipid nanoparticle (LNP)-mediated delivery, sup-tRNAs successfully restored CFTR mutants in cystic fibrosis models, achieving clinically relevant thresholds with favorable safety profiles. Another key insight of this thesis lies in uncovering the sequence context dependency of sup-tRNA readthrough efficiency. In Chapter 2, we analyze the translational dynamics upstream of PTCs and reveal that abrupt changes in ribosome velocity associate with ribosomal collisions that ultimately have an impact on the suppression efficiency of sup-tRNAs. We employed Ribo-seq analysis to model these translational landscapes, enabling the precise prediction of sup-tRNA performance at pathogenic PTCs. This personalized approach paves the way for tailoring therapies to individual genetic contexts, addressing the variability in treatment response. To demonstrate the therapeutic potential of sup-tRNAs beyond inherited disorders, we sought to evaluate the ability of sup-tRNAs to correct nonsense mutations in TP53, the most commonly mutated gene in human cancers. In Chapter 3, we demonstrate that sup-tRNAs can restore functional p53 expression and activity in various cellular models, outperforming traditional small-molecule approaches in both efficacy and specificity. By targeting this critical genomic regulator, sup-tRNAs proved to be an efficient strategy to restore one of the most pervasive drivers of cancer tumors. Looking toward a broader application of sup-tRNA, in Chapter 4 we pioneer a strategy to address several diseases by using a unique effective treatment called ‘sup-tRNA cocktails’. The sup-tRNA cocktails were strategically designed and customized to precisely target various PTCs by combining multiple sup-tRNAs. By focusing on shared molecular signatures, such as specific PTCs and associated amino acids, this strategy exemplifies a scalable, cost-effective solution for diverse genetic disorders, expanding therapeutic reach while streamlining regulatory approval. By integrating fundamental molecular insights with innovative therapeutic designs, this thesis establishes sup-tRNAs as a versatile and precise tool for treating nonsense mutations. It bridges the gap between personalized medicine and scalable therapies, offering a transformative framework for addressing genetic disorders with unprecedented specificity, efficacy, and safety.