Optimizing Angiopep-2 Density on Polymeric Nanoparticles for Enhanced Blood-Brain Barrier Penetration and Glioblastoma Targeting: Insights from In Vitro and In Vivo Experiments

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Abstract

The blood-brain barrier (BBB) poses a formidable challenge to efficient drug delivery into the brain. One promising approach involves leveraging receptor-mediated transcytosis facilitated by Angiopep-2 peptide (Ang-2)-conjugated nanoparticles. However, the precise impact of Ang-2 density on BBB penetration remains poorly understood. In this study, we developed a versatile polymeric nanoparticle system with tuneable Ang-2 surface density and systemically examined its influence on BBB penetration through various in vitro assays and an in vivo study. Our findings revealed a nuanced relationship between Ang-2 surface density and BBB penetration across the different experimental setups. In 2D cell culture, we observed a positive correlation between Ang-2 surface density and cellular association in hCMEC/D3 cells, characterized by a distinctive inflection point. Conversely, in the Transwell model, higher Ang-2 density correlated negatively with BBB penetration, whereas the BBB-GBM-on-a-chip showed the opposite trend. These disparities may arise from differences in avidity under static versus dynamic conditions, potentially modulating nanoparticle interactions due to fluidic forces. In vivo studies revealed that higher Ang-2 densities facilitated nanoparticle transport across the BBB, consistent with the findings of the BBB-GBM-on-a-chip model. Furthermore, loading doxorubicin into nanoparticles with optimal Ang-2 density resulted in controlled pH-responsive release and enhanced anticancer effect against U87 GBM cells in both 2D cell cultures and a 3D BBB-GBM-on-a-chip model. These results underscore the critical importance of optimizing Ang-2 surface density for efficient BBB penetration and emphasize the utility of dynamic models in preclinical in vitro assessment of novel nanoparticle formulations for targeted delivery to the brain.

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last seen: 2026-05-19T01:45:01.086888+00:00