ACGTU LAB
Precision Strategies for Enhanced Nucleic Acid Therapy
RESEARCH
Research Overview: precision strategies for enhanced nucleic acid therapy
Gene therapy has the potential to cure a monogenic disease by correction of a malfunctioning gene through replacement or silencing. However, accurate and precise delivery of nucleic acids remains a significant challenge to the clinical translation of genetic medicine for inaccessible organs. Genetic therapeutics must overcome multiple biological barriers from systemic circulation (if administered systemically) down to tissue, cellular and molecular levels to reach the intracellular target. Off-target accumulation carries a risk of prolonged damage due to detrimental genetic modification. Our laboratory will utilize various formulation design and optimization strategies to address the shortcomings of gene delivery.
Focus Area 1: modularizing organ / tissue / cell targeting functionalities
Adeno-associated viruses adhered to the surface of their carrier, red blood cells, to the target organ
Most of current targeting strategies in drug delivery utilize singular modality, which often fails to overcome multiple biological barriers present and yields low level of on-target rate. Alternatively, various functions can be conferred in modular fashion by engineering each of the modular components individually to address a specific delivery challenge. We will exploit three modular composite platforms: 1) non-covalent serial attachment of functional moieties to nanoparticles via an intermediary metal-phenolic-network chemistry, 2) tailored microneedles for precise local delivery of nanoparticles, and 3) biomimetic microparticles as carriers of nanoparticles. Delivery efficiency across various tissue-specific barriers will be explored, such as internal limiting membrane, cornea, or sclera (ocular), blood brain barrier (brain), mucosa (lungs), and stratum corneum (skin).
Focus Area 2: building personalized prediction model for gene delivery vectors
Current gene delivery vehicles for cancer are designed and evaluated against generalized cancer types. However, one of the major reasons behind the disconnect between pre-clinical in vivo data and clinical trial results is the variability in disease pathology and biology between patients. The outcome of non-viral gene therapy can be greatly enhanced by optimizing delivery vectors for individual patient. A patient’s tumor biopsy offers a unique opportunity to not only extract biological and histopathological information from the tumor cells and tissues but also to directly screen potential therapeutics. We aim to create a patient-specific prediction model for the efficiency of a library of gene delivery vectors through machine-learning based computational optimization modeling with data generated through material characterization, high-throughput transfection screening, and next generation sequencing of individual diseased tissue samples.
Real time quantitative PCR-based high-throughput in vivo screening method for non-viral vectors using plasmid DNA as the barcode for each vector. Efficiency of delivering DNA to specific organs by polymeric vectors of differential structure was investigated.