Improved tumor-targeting drug delivery and therapeutic efficacy by cationic liposome modified with truncated bFGF peptide

Journal of Controlled Release(2010)

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摘要
Fibroblast growth factor receptors (FGFRs), overexpressed on the surface of a variety of tumor cells and on tumor neovasculature in situ, are potential targets for tumor- and vascular-targeting therapy. This study aimed to develop a FGFR-mediated drug delivery system to target chemotherapeutic agents to FGFR-overexpressed tumor cells and tumor neovasculature endothelial cells in vitro and in vivo. Here we designed a truncated human basic fibroblast growth factor peptide (tbFGF), which was attached to the surface of cationic liposomal doxorubicin (LPs-DOX) and paclitaxel (LPs-PTX) via electrostatic force. Then we characterized the tbFGF-modified liposome (tbFGF-LPs) and examined internalization of doxorubicin in tumor cells (TRAMP-C1, B16) and HUVEC cells in vitro. In vivo, we evaluated the biodistribution and antitumor efficacy of tbFGF-LPs-DOX and tbFGF-LPs-PTX in C57BL/6J mice bearing TRAMP-C1 prostate carcinoma and B16 melanoma, respectively. The tbFGF-LPs-DOX significantly improved the uptake of doxorubicin in TRAMP-C1, B16 and HUVEC cells, respectively. Biodistribution study in B16 tumor-bearing mice showed that tbFGF-LPs-PTX achieved 7.1-fold (72.827±7.321mgh/L vs 10.292±0.775mgh/L, mean±SD, P<0.01) accumulation of paclitaxel in tumor tissue than those of free paclitaxel. More importantly, treatment of tumor-bearing mice with tbFGF-LPs-DOX and tbFGF-LPs-PTX showed the significant inhibition in tumor growth and improvement in survival rate as compared with mice treated with free and liposomal drugs in TRAMP-C1 and B16 tumor models, respectively. Furthermore, repeated intravenous administration of tbFGF-LPs-DOX/PTX did not induce anti-bFGF antibodies. These results suggested that this FGFR-mediated drug delivery system may provide a new treatment strategy for tumors which overexpress FGFRs.
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关键词
FGF receptors,Drug delivery system,Tumor-targeting,Vascular-targeting
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