Maximizing hepatic genome correction efficiency of prime editing three-component cargo delivered via lipid nanoparticles
Background: Bottlenecks in tripartite cargo loading of existing non-viral LNP delivery systems and in vivo editing efficiency data barriers in R&D for inherited metabolic diseases
Prime editing is a next-generation, precise genome editing modality that operates with a tripartite structure of Cas9 nickase-reverse transcriptase fusion protein (PE fusion), prime editing guide RNA (pegRNA), and nicking sgRNA, enabling the introduction of substitutions, insertions, and deletions at target genomic loci with single-nucleotide resolution. However, when this tripartite RNA cargo is simultaneously encapsulated and delivered by lipid nanoparticles (LNPs), multiple bottlenecks overlap, including imbalances in the molar ratios of individual mRNAs and guide RNAs, competitive electrostatic complex formation between ionizable lipids and cargo, and non-linear attenuation of endosomal escape efficiency, resulting in in vivo editing efficiencies that plateau in the single-digit percentage range. Existing adenine base editor (ABE)-based LNPs demonstrated 48% liver editing with a single dose in the VERVE-101 clinical trial (PCSK9 inactivation, HEART-1 Phase 1b) by Verve Therapeutics; however, this is attributable to the structural simplicity of the two-component system, and direct translation to tripartite prime editing has been thwarted by the inverse correlation barrier between cargo complexity and delivery efficiency. In particular, despite the accumulation of protein engineering advancements such as PEmax, PE4, PE5, PE6, and PE7, based on the PE2 scaffold initially presented by the David R. Liu group in 2019, no reports have demonstrated the achievement of approximately 50% in vivo liver editing, clinically relevant, using non-viral LNPs alone, without adeno-associated virus (AAV) vectors. This has structurally blocked the entry into an IND-enabling study for a non-viral, curative, single-dose strategy for monogenic liver metabolic diseases such as phenylketonuria (PKU, PAH R408W point mutation), Wilson's disease (ATP7B), and alpha-1 antitrypsin deficiency (SERPINA1), creating a data bottleneck.
Discovery: Implementation of a systematic workflow for PE-LNP cargo design optimization and demonstration of 49% editing efficiency in bulk liver tissue at the resolution of a tensor
Jiang, Liu, et al. (Nat. Nanotechnol. 2026, 10.1038/s41565-026-02200-6) established a PE-LNP optimization platform that systematically dissects the key bottlenecks that limit the LNP loading of tripartite prime editing cargo—PE fusion mRNA length (~6.3 kb), pegRNA chemical stability, nicking sgRNA molar ratio, ionizable lipid composition, and N/P ratio. This generalizable workflow models the cargo design variable space as a multidimensional tensor, and operates as an in silico-wet lab hybrid iterative loop that explores the global optimum of the interaction tensor between the three components, rather than optimizing individual variables independently. As a result, a single intravenous administration of 2 mg/kg achieved an average prime editing efficiency of 49% in the entire bulk mouse liver, a disruptive improvement over existing tripartite PE-LNP reports. Critically, off-target editing was significantly minimized compared to DNA plasmid or AAV delivery, which is attributable to the inherent transience of mRNA-based delivery, which thermodynamically suppresses the probability of off-target cleavage at the entire genome by limiting the intracellular residence time of Cas9 nickase. Transient increases in liver enzymes (ALT/AST) were observed, and further amplification of editing efficiency was observed with repeated administration, demonstrating the establishment of a therapeutic window within the linear range of the dose-response.
Fine-tuning of PAH R408W point mutation correction and establishment of a precise, layered model for reversible phenylalanine metabolic homeostasis
The researchers applied the optimized PE-LNP workflow to a phenylketonuria (PKU) mouse model to demonstrate precise correction of the pathogenic R408W (c.1222C>T) point mutation in exon 12 of the PAH (phenylalanine hydroxylase) gene. PAH R408W is the most common variant, detected in approximately 30-40% of PKU patients in the European Caucasian population, and distorts the BH4 cofactor binding pocket structure within the catalytic domain of the enzyme, virtually down-regulating the rate constant (kcat) of the rate-limiting step of the phenylalanine→tyrosine hydroxylation reaction. The in vivo PAH gene editing rate achieved after PE-LNP administration reduced plasma phenylalanine levels below the therapeutic threshold, suggesting a curative level of metabolic homeostasis restoration. This result provides a framework for precision stratification based on patient molecular phenotypes, classifying patients with R408W homozygous and compound heterozygous genotypes as candidates for PE-LNP single-dose curative therapy, and linking the dose-response correction coefficient on an individual basis according to residual PAH enzyme activity levels, creating an omics matrix-based stratification backbone. In particular, by constructing a genotype-phenotype correlation tensor with BH4-responsive mild PKU (e.g., PAH Y414C), it is possible to in silico back-calculate the cost-effectiveness threshold (ICER threshold) compared to patients managed with dietary restriction alone, which is directly linked to the reorganization of governance in precision medicine for rare metabolic diseases.
Prospects: Establishment of a standard for programmable non-viral genome medicine and launch of a next-generation IND digital governance system
This PE-LNP platform represents a declarative turning point that completely resets the governance of R&D for inherited liver diseases from the existing static, post-symptomatic treatment system—dietary restriction, enzyme supplementation (Sapropterin/Kuvan, BioMarin), Pegvaliase (Palynziq)—to a forward-looking, AI-powered, multidimensional tensor-based programmable genome editing infrastructure. In the current landscape where Prime Medicine (PRME-901, AAV-PE-based chronic liver disease pipeline, 2025 IND submission) and Beam Therapeutics (BEAM-302, alpha-1 antitrypsin deficiency ABE-LNP, Phase 1/2 ongoing) are competing on the viral and non-viral delivery axes, the 49% PE-LNP efficiency reported by the Liu group breaks the threshold of clinical feasibility for non-viral prime editing, meeting the technical prerequisites for expansion of global multinational pharmaceutical pipelines. A computational moat is established by linking the genetic gradient correction coefficient of the pegRNA spacer length, PBS length, and RTT sequence combination to the LNP formulation variables in real time during high-throughput screening, thereby zeroing out the batch-to-batch editing efficiency variation within the cGMP acceptable range. Furthermore, the integration with a liquid biopsy-based companion diagnostic (CDx) panel that replaces liver biopsies will function as a master asset that disruptively shortens the FDA/EMA IND review and approval timeline for editing efficiency biomarkers, establishing a backbone infrastructure that directly links the commercial viability of non-viral genome medicine to GMP-grade manufacturing scale-up.
Prime editing is a versatile clinical genome editing method that enables precise substitutions, small insertions and deletions at specified locations in the genomes of living systems including human cells. Although non-viral lipid nanoparticle (LNP) delivery of RNA in vivo has become a preferred method for gene editing in animals and patients, its application to complex, three-component prime editing systems has yielded low editing efficiencies. Here we developed a systematic prime editing LNP (PE-LNP) optimization platform that addresses key bottlenecks in cargo design that limit editing efficiency. This generalizable workflow yielded PE-LNPs that can achieve 49% average in vivo prime editing in the bulk mouse liver with a single dose of 2 mg kg
This study's non-viral PE-LNP tripartite optimization platform goes beyond theoretical exploration of genome editing mechanisms and directly translates into a real-world global finished drug supply chain and a next-generation precision personalized gene therapy business line.
First, in the clinical setting, the rate of PAH enzyme activity deficiency in PKU patients is immediately scanned by a pegRNA sequence optimization algorithm, eliminating the temporal noise gap from newborn screening positivity to irreversible neurotoxic accumulation and maintaining a safe threshold of plasma phenylalanine below 360 μmol/L.
At the same time, by linking the PAH variant omics matrix compiled in ClinVar, gnomAD, and PharmGKB, confounding variables of BH4 responsiveness can be virtually simulated during clinical trial design, and a companion diagnostic (CDx) panel interface is realized that links the effective intracellular docking concentration of PE fusion protein to mRNA translation efficiency in real time.
Furthermore, when multinational companies conduct large-scale, next-generation, liver-targeted genome therapy clinical trials, linking the LNP ionizable lipid molar ratio, N/P ratio, and pegRNA chemical modification as correction coefficients will zero out the coefficient of variation in batch-to-batch editing efficiency and maximize the probability of obtaining clinical trial protocol and cGMP commercial approval from global regulatory agencies, creating a backbone infrastructure.