Nanoparticle amplification via photothermal unveiling of cryptic collagen binding sites
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Lo_2013-Nanoparticle amplification.pdf
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Author(s)
Lo, Justin H.
Douglass, Jacqueline
Park, Ji-Ho
Sailor, Michael J.
Ruoslahti, Erkki
Bhatia, Sangeeta N
von Maltzhan, Geoffrey
Date Issued
June 2013
Journal
Journal of Materials Chemistry B
Publisher
Royal Society of Chemistry
Citation
Lo, Justin H., Geoffrey von Maltzahn, Jacqueline Douglass, Ji-Ho Park, Michael J. Sailor, Erkki Ruoslahti, and Sangeeta N. Bhatia. “Nanoparticle amplification via photothermal unveiling of cryptic collagen binding sites.” Journal of Materials Chemistry B 1, no. 39 (2013): 5235. © Royal Society of Chemistry 2013
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Final published version
Abstract
The success of nanoparticle-based cancer therapies ultimately depends on their ability to selectively and efficiently accumulate in regions of disease. Outfitting nanoparticles to actively target tumor-specific markers has improved specificity, yet it remains a challenge to amass adequate therapy in a selective manner. To help address this challenge, we have developed a mechanism of nanoparticle amplification based on stigmergic (environment-modifying) signalling, in which a “Signalling” population of gold nanorods induces localized unveiling of cryptic collagen epitopes, which are in turn targeted by “Responding” nanoparticles bearing gelatin-binding fibronectin fragments. We demonstrate that this two-particle system results in significantly increased, selective recruitment of responding particles. Such amplification strategies have the potential to overcome limitations associated with single-particle targeting by leveraging the capacity of nanoparticles to interact with their environment to create abundant new binding motifs.
MIT Department
Whitaker College of Health Sciences and Technology
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1039/c3tb20619j
