4.8 Article

Development of drug loaded nanoparticles for tumor targeting. Part 1: synthesis, characterization, and biological evaluation in 2D cell cultures

Journal

NANOSCALE
Volume 5, Issue 9, Pages 3895-3903

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c3nr33777d

Keywords

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Funding

  1. NIH [R01CA149451]
  2. NSF CAREER award

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Nanoparticles (NPs) are being extensively studied as carriers for drug delivery, but they often have limited penetration inside tumors. We envision that by targeting an endocytic receptor on the cell surface, the uptake of NPs can be significantly enhanced through receptor mediated endocytosis. In addition, if the receptor is recycled to the cell surface, the NP cargo can be transported out of the cells, which is then taken up by neighboring cells thus enhancing solid tumor penetration. To validate our hypothesis, in the first of two articles, we report the synthesis of doxorubicin (DOX)-loaded, hyaluronan (HA) coated silica nanoparticles (SNPs) containing a highly fluorescent core to target CD44, a receptor expressed on the cancer cell surface. HA was conjugated onto amine-functionalized SNPs prepared through an oil-water microemulsion method. The immobilization of the cytotoxic drug DOX was achieved through an acid sensitive hydrazone linkage. The NPs were fully characterized by transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential measurements, thermogravimetric analysis (TGA), UV-vis absorbance, and nuclear magnetic resonance (NMR). Initial biological evaluation experiments demonstrated that compared to ligand-free SNPs, the uptake of HA-SNPs by the CD44-expressing SKOV-3 ovarian cancer cells was significantly enhanced when evaluated in the 2D monolayer cell culture. Mechanistic studies suggested that cellular uptake of HA-SNPs was mainly through CD44 mediated endocytosis. HA-SNPs with immobilized DOX were endocytosed efficiently by the SKOV-3 cells as well. The enhanced tumor penetration and drug delivery properties of HA-SNPs will be evaluated in 3D tumor models in the subsequent paper.

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