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Peptide-Functionalized Layer-by-Layer Nanoparticles Demonstrate Improved Blood Brain Barrier Permeability for Glioblastoma Treatment

Author(s)
Ganesh, Priya
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Advisor
Hammond, Paula
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In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/
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Abstract
The greatest obstacle in the treatment of glioblastomas is the blood-brain barrier (BBB), the endothelial cells that line the vessels of the brain and are stitched together into a barrier by tight junction complexes. One approach to overcoming this barrier is encapsulating drugs in nanoparticles whose surfaces are engineered (usually, with the addition of ligands) to promote binding to various receptors of the BBB, thus triggering transcytosis and allowing the nanoparticle and its drug contents to cross the BBB. Previous research has shown that electrostatic absorption (as opposed to covalent functionalization) is a quick and effective method for attaching cationic, tumor-penetrating peptides to anionic nanoparticles synthesized through an iterative layer-by-layer (LbL) approach. Here, I demonstrate that LbL nanoparticles functionalized with Angiopep-2, a BBB-penetrating peptide, can penetrate the BBB to deliver their contents to the brain. Peptide-functionalized particles were screened in an in vitro transwell model of the blood-brain barrier, and particularly promising candidates were screened in a mouse model through intravital imaging, leading to a conclusion that the combination of a poly-L-aspartate outer layer and Angiopep-2 leads to significant improvement in nanoparticle uptake in the brain. Future work will include in vivo experiments with peptide-functionalized LbL nanoparticles with a hyaluronic acid (HA) outer layer, as HA particles have been shown to have in vivo transport properties not reflected in in vitro transport experiments.
Date issued
2023-06
URI
https://hdl.handle.net/1721.1/154039
Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Publisher
Massachusetts Institute of Technology

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