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Tuning Nanoparticle Interactions with Ovarian Cancer through Layer-by-Layer Modification of Surface Chemistry
Name
nihms-1552577.pdf
Description
Accepted version
Size
3.16 MB
Format
Adobe PDF
Checksum (MD5)
41b474d8bb140d6293871e5f38d7b1d6
Author(s)
Correa, Santiago
Boehnke, Natalie
Barberio, Antonio E
Deiss-Yehiely, Elad
Shi, Aria
Oberlton, Benjamin
Smith, Sean G
Zervantonakis, Ioannis
Dreaden, Erik C
Hammond, Paula T
Date Issued
2020
Journal
ACS Nano
Publisher
American Chemical Society (ACS)
Citation
Correa, Santiago, Boehnke, Natalie, Barberio, Antonio E, Deiss-Yehiely, Elad, Shi, Aria et al. 2020. "Tuning Nanoparticle Interactions with Ovarian Cancer through Layer-by-Layer Modification of Surface Chemistry." ACS Nano, 14 (2).
Version
Author's final manuscript
Abstract
© 2020 American Chemical Society. Nanoparticle surface chemistry is a fundamental engineering parameter that governs tumor-targeting activity. Electrostatic assembly generates controlled polyelectrolyte complexes through the process of adsorption and charge overcompensation utilizing synthetic polyions and natural biomacromolecules; it can yield films with distinctive hydration, charge, and presentation of functional groups. Here, we used electrostatic layer-by-layer (LbL) assembly to screen 10 different surface chemistries for their ability to preferentially target human ovarian cancer in vitro. Our screen identified that poly-l-aspartate, poly-l-glutamate, and hyaluronate-coated LbL nanoparticles have striking specificity for ovarian cancer, while sulfated poly(β-cyclodextrin) nanoparticles target noncancerous stromal cells. We validated top candidates for tumor-homing ability with a murine model of metastatic disease and with patient-derived ovarian cancer spheroids. Nanoparticle surface chemistry also influenced subcellular trafficking, indicating strategies to target the cell membrane, caveolae, and perinuclear vesicles. Our results confirm LbL is a powerful tool to systematically engineer nanoparticles and achieve specific targeting.
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Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1021/ACSNANO.9B09213
