Engineering a versatile lipoMSN delivery platform for the development of gene and drug therapies
By: Jing Gong
Publisher: [publisher not identified]
Published: 2020
Place of publication: [New York, N.Y.?]
Language: eng
Description: The question of delivery has become a critical part of therapeutic research and development. While nanoparticle formulations are now used in a variety of FDA-approved therapies, these focus on simple oral formulations or systemic lipid nanoparticle administration; therefore, significant research is ongoing in the development of specialized delivery systems for more complex cargos or specific targeting[1]. For therapeutics that have high potential for toxicity, like chemotherapeutics, delivery systems need to transport disproportionately into target organs and further target cells. This is more so true for therapeutics that require delivery to a specific cellular compartment to have significant efficacy, like in the case of gene editing in the nucleus or mitochondria-targeted peptides. To contribute to the development of efficient carriers for gene and drug therapy, this work aims to explore the potential of liposome-coated mesoporous silica nanoparticles and engineering methods that provide functionality to defeat barriers to efficient therapeutic development.

Recent advances in CRISPR/Cas9 technology present an attractive toolset to study genes for the development of novel therapeutics. Since traditional delivery methods for gene therapies relied heavily on viruses— requiring biosafety level clearance and eliciting immunogenicity concerns, as well as limitations in multiplex gene editing capabilities in single viral vehicles— recently, nanoparticles have become an attractive nonviral alternative for gene therapy research and development. While lipid-based nanoparticles have been at the forefront of siRNA and mRNA therapies, we looked at increasing the loading capabilitiesof a liposome by using a mesoporous silica nanoparticle (MSN) core. The MSN provides efficient electrostatic loading of the relatively large and non-uniformly charged CRISPR/Cas9 protein and guide RNA ribonucleoprotein complex (RNP) as well as more charge-dense plasmids, while a liposome coating offers the PEGylation and targeting capabilities necessary for selective uptake and in vivo application.

After demonstrating gene-editing efficiencies above 20% for both plasmid and RNP modalities of CRISPR/Cas9, we tested its application in multiplex gene editing for the study lipid metabolism pathways. To demonstrate the maintained efficiency of this system, this liposome-coated MSN (lipoMSN) platform was used to deliver a combination of RNPs targeting three genes involved in lipid metabolism in the liver. These genes, Pcsk9, Apoc3, and Angptl3, are derived from research demonstrating that populations with loss-of-function mutations in any one of these genes garner improved cardiovascular health, characterized by lowered blood cholesterol and triglycerides. The lipoMSN system demonstrated that it maintained significant gene editing, above 25% efficiency, at a specific gene target despite reduced dosage of target-specific RNP due to the combination of other target RNP. By leveraging this system to deliver various combinations of targeting RNPs in the same nanoparticle and therefore ensuring a higher probability that any given cell is edited at all targets, synergistic effects on lipid metabolism can be observed in vitro and in vivo.

These effects, such as an approximately 50% decrease in serum LDL-cholesterol 4-weeks after treatment with pcsk9 and angptl3- targeted RNPs, have not been observed in previous studies. Continued work with this lipoMSN platform is ongoing, with projects leveraging the system for multiplex gene disruption as well as endosomal delivery of peptide and chemical drugs. We are currently leveraging the comparatively low spread of lipoMSN to provide gene disruption of adra1a, adra1b, and adra1d in the discrete area of the thalamus. Further, this system is also well suited for other CRISPR/Cas9 elements, such as deactivated Cas9 (dCas9) fused to epigenetic modifiers, enhancers and repressors. To demonstrate another facet of the lipoMSN delivery platform, we adjusted the formulation for the specific delivery to endosomal compartments of nociceptive neurons. Previous work by our collaborators at the Bunnett Lab provided evidence that signaling in the endosomal compartment is partially responsible for both pain propagation and amelioration.

In order to provide highly targeted treatment to reduce the off-target effects linked with opioid-based pain treatment, we wanted to leverage the resonance of these nanoparticles in the endosomes following endocytosis and enhance the drug delivery to the endosomal compartments propagating nociceptive signaling. We did this by first integrating a targeting ligand in the form of a DADLE-peptide, to the outside of the liposomes, providing a 20-40% increase in uptake for delta-opioid receptor (DOR)-expressing cell types. Further, we used an oxidation- and pH-sensitive MSN core to provide increased drug release to the endosomal environment, which is naturally oxidizing and at a lower pH of approximately 5.2. This resulted in an increased therapeutic effect when compared to naked peptide drug in a mouse model of neurogenic pain. We are also looking at leveraging this system for other endosomal signaling pathways and applying our lipoMSN platform to cargos such as glucagon-like peptide-1 (GLP-1) receptor agonists for diabetes and US28 receptor antagonists for reduction of proliferative signaling in cancers.

Collectively, these projects provide insight on how to design delivery vehicles for specific gene and drug delivery. This lipoMSN system has the potential to be a versatile platform for the development of combinatorial gene therapeutics in liver-related disease. Further, this platform may inform research and development in the next generation of endosomally-targeted therapeutics for increased efficacy and reduced off-target or side effects.
Notes: Department: Biomedical Engineering.

Thesis advisor: Kam W. Leong.

Thesis (Ph.D.)--Columbia University, 2020.