PEGylated enhanced cell penetrating peptide nanoparticles for lung gene therapy

The lung remains an attractive target for the gene therapy of monogenetic diseases such as cystic fibrosis (CF). Despite over 27 clinical trials, there are still very few gene therapy vectors that have shown any improvement in lung function; highlighting the need to develop formulations with improved gene transfer potency and the desirable physiochemical characteristics for efficacious therapy. Herein, we introduce a novel cell penetrating peptide (CPP)-based non-viral vector that utilises glycosaminoglycan (GAG)-binding enhanced transduction (GET) for highly efficient gene transfer. GET peptides couple directly with DNA through electrostatic interactions to form nanoparticles (NPs). In order to adapt the GET peptide for efficient in vivo delivery, we engineered PEGylated versions of the peptide and employed a strategy to form DNA NPs with different densities of PEG coatings. We were able to identify candidate formulations (PEGylation rates >= 40%) that shielded the positively charged surface of particles, maintained colloidal stability in bronchoalveolar lavage fluid (BALF) and retained gene transfer activity in human bronchial epithelial cell lines and precision cut lung slices (PCLS) in vitro. Using multiple particle tracking (MPT) technology, we demonstrated that PEG-GET complexes were able to navigate the mucus mesh and diffuse rapidly through patient CF sputum samples ex vivo. When tested in mouse lung models in vivo, PEGylated particles demonstrated superior biodistribution, improved safety profiles and efficient gene transfer of a reporter luciferase plasmid compared to non-PEGylated complexes. Furthermore, gene expression was significantly enhanced in comparison to polyethylenimine (PEI), a non-viral gene carrier that has been widely tested in pre-clinical settings. This work describes an innovative approach that combines novel GET peptides for enhanced transfection with a tuneable PEG coating for efficacious lung gene therapy.