Cystic fibrosis (CF) is a severe monogenic disease characterized by debilitating lung dysfunction caused by loss-of-function mutations in the CFTR gene. While CRISPR-based gene editing holds promise for correcting these mutations and potentially curing CF, efficient delivery of gene editors to the lung epithelium through the mucosal barrier remains a major challenge. In this study, we developed a lung-optimized gene editing strategy using lipid nanoparticles (LNPs) and evaluated it in increasingly complex, biomimetic human-based and patient-derived models. Systematic optimization of helper lipids, genetic cargo, guide RNA modifications, and gene editor ratios, alongside analysis of innate immune responses, achieved ∼50 % editing efficiency in the model gene HPRT in two-dimensional models. Editing efficiency significantly dropped to ∼5 % in biomimetic three-dimensional CF bronchial epithelial tissue models following topical LNP application. Pretreatment with the approved mucolytic agent dornase alpha increased editing efficiency to ∼12.7 %. Finally, in CF patient-derived cells harboring the CFTRmutation, our optimized LNP formulation achieved ∼12 % correction on gene level, offering a potential treatment avenue for this yet untreatable mutation. Taken together, this study demonstrates that optimizing the genetic cargo as well as the delivery vehicle is key when striving for clinically applicable treatment approaches. It further provides insights into gene editing rates in human-based normal and CF patient-derived bronchial tissue models which express all relevant biological barriers and, thus, can pave the way for topically applicable treatment options for patients with CF and other genetic lung diseases. R1162X
