Abstract
Recently, various nanoparticle systems have been developed for tumor-targeted delivery of imaging agents or drugs. However, large amount of them still have insufficient tumor accumulation and this limits their further clinical applications. Moreover, the in vivo characteristics of nanoparticles have been largely unknown, because there are few proper technologies to achieve the direct and non-invasive characterization of nanoparticles in live animals. In this paper, we determined the key factors of nanoparticles for in vivo tumor-targeting using our glycol chitosan nanoparticles (CNPs) which have proved their tumor-targeting ability in many previous papers. For this study, CNPs were labeled with near-infrared fluorescence (NIRF) dye, Cy5.5 for in vivo analysis by non-invasive optical imaging techniques. With these Cy5.5-CNPs, the factors such as in vitro/in vivo stability, deformability, and rapid uptake into target tumor cells and their effects on in vivo tumor-targeting were evaluated in various tumor-bearing mice models. In flank tumor models, Cy5.5-CNPs were selectively localized in tumor tissue than other organs, and the real-time intravascular tracking of CNPs proved the enhanced permeation and retention (EPR) effect of nanoparticles in tumor vasculature. Importantly, tumor-targeting CNPs showed an excellent tumor-specificity in brain tumors, liver tumors, and metastasis tumor models, indicating their great potential in both cancer imaging and therapy.
Original language | English |
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Pages (from-to) | 5252-5261 |
Number of pages | 10 |
Journal | Biomaterials |
Volume | 32 |
Issue number | 22 |
DOIs | |
State | Published - Aug 2011 |
Bibliographical note
Funding Information:This work was financially supported by National R&D Program for Cancer Control of Ministry for Health and Welfare from Republic of Korea ( 1020260 ), Fusion Technology Project ( 2009-0081876 ) of MEST, and the Intramural Research Program (Theragnosis) of KIST.
Keywords
- Brain cancer
- Liver cancer
- Metastasis
- Nanoparticle
- Tumor-targeting