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PTPmu-targeted nanoparticles label invasive pediatric and adult glioblastoma
Poor prognosis for glioblastoma (GBM) is a consequence of the aggressive and infiltrative nature of gliomas where individual cells migrate away from the main tumor to distant sites, making complete surgical resection and treatment difficult. In this manuscript, we characterize an invasive pediatric...
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Published in: | Nanomedicine 2020-08, Vol.28, p.102216-102216, Article 102216 |
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Main Authors: | , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Poor prognosis for glioblastoma (GBM) is a consequence of the aggressive and infiltrative nature of gliomas where individual cells migrate away from the main tumor to distant sites, making complete surgical resection and treatment difficult. In this manuscript, we characterize an invasive pediatric glioma model and determine if nanoparticles linked to a peptide recognizing the GBM tumor biomarker PTPmu can specifically target both the main tumor and invasive cancer cells in adult and pediatric glioma models. Using both iron and lipid-based nanoparticles, we demonstrate by magnetic resonance imaging, optical imaging, histology, and iron quantification that PTPmu-targeted nanoparticles effectively label adult gliomas. Using PTPmu-targeted nanoparticles in a newly characterized orthotopic pediatric SJ-GBM2 model, we demonstrate individual tumor cell labeling both within the solid tumor margins and at invasive and dispersive sites.
Two PTPμ-targeting nanoparticles were developed to recognize tumor associated fragments of the receptor protein tyrosine phosphatase PTPμ in adult and pediatric glioma. When used as an intravenous labeling agent, the PTPμ-targeting liposomal nanoparticle (red) recognized invading pediatric glioma cells (green) that had migrated away from the main tumor mass, observable in tissue sections taken from a pediatric intracranial glioma tumor model. [Display omitted] |
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ISSN: | 1549-9634 1549-9642 |
DOI: | 10.1016/j.nano.2020.102216 |