ENGINEERING OF MULTIFUNCTIONAL NANOPARTICLES FOR PRECISION THERANOSTICS OF GLIOBLASTOMA
Glioblastoma is one of the most aggressive and invasive types of cancer. Unfortunately, due to the overlapping nature of side-effects with other types of neurological diseases and the difficulty to identify them with diagnostic measures, it is not discovered until stage four. At this point, patients have limited options for care and ultimately end up in palliative care not long after diagnosis. The blood-brain barrier (BBB) has proved to be a difficult boundary for current modern medicines as it prevents adequate accumulation within the brain. As gliomas often form in inoperable parts of the brain, conventional FDA-approved therapies prove to be ineffective. Within the past ten years, targeting strategies using RGD peptides have proven effective at transporting drugs, contrast agents, or nanoparticle delivery vehicles across the barrier, but suffer from off-targeting effects due to expression of the peptide-recognizing integrins on the surface of healthy cells. Extracellular vesicles, particularly exosomes, have shown promising specific targeting effects of cells from which the vesicles originate. They have also shown a remarkable ability to pass through the BBB innately. The focus of this project was the development of a glioblastoma derived-exosome coated Prussian Blue nanoparticle (Exo:PB) that could easily accumulate within glioblastoma tissues and provide enhanced diagnostics as well as localized therapy. Prussian Blue nanoparticles are FDA-approved for scavenging heavy metals present within the body after extreme radiation exposure. Based on their exceptional application to photothermal therapy and ability to be used for photoacoustic imaging and MRI, they are an ideal candidate for glioblastoma theranostics. By investigating the distribution and accumulation patterns of these newly developed Exo:PB nanoparticles within preclinical mouse models, earlier diagnosis and treatment intervention can be achieved for glioblastoma.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Hill, Meghan Lorene
- Thesis Advisors
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Kim, Taeho
- Committee Members
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Gilad, Assaf
Kanada, Masamitsu
Huang, Xuefei
- Date Published
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2024
- Subjects
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Engineering
- Program of Study
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Biomedical Engineering - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- 207 pages
- Permalink
- https://doi.org/doi:10.25335/68ay-bh92