Papers

Peer-reviewed
Sep, 2007

Development of bionanocapsules targeting brain tumors

JOURNAL OF CONTROLLED RELEASE
  • Yumi Tsutsui
  • ,
  • Kazuhito Tomizawa
  • ,
  • Mana Nagita
  • ,
  • Hiroyuki Michiue
  • ,
  • Tei-ichi Nishiki
  • ,
  • Iori Ohmori
  • ,
  • Masaharu Seno
  • ,
  • Hideki Matsui

Volume
122
Number
2
First page
159
Last page
164
Language
English
Publishing type
Research paper (scientific journal)
DOI
10.1016/j.jconrel.2007.06.019
Publisher
ELSEVIER

Bionanocapsules (BNCs) are hollow nanoparticles that are composed of L protein (the hepatitis B virus surface antigen) and show specific affinity for human hepatocytes. The pre-S1 peptide displayed on the surface of BNCs is the specific ligand for binding to the receptor on human hepatocytes. Therefore, BNCs are not delivered to other tissues, such as the brain. The aim of the present study was to develop a novel drug delivery system (DIDS) targeting brain tumors using BNCs that selectively targeted brain tumors. Epidermal growth factor receptor (EGFR), especially a constitutively active genomic sequence deletion variant of EGFR (EGFRvIII), is overexpressed in human glioblastoma. In the present study, we replaced the pre-S1 peptide with the antibody affinity motif of protein A and made hybrid BNCs conjugated with anti-human EGFR antibody recognizing EGFRvIII. The hybrid BNCs were efficiently delivered to glioma cells but not normal glial cells. Moreover, we confirmed the specific delivery of the hybrid BNCs to brain tumors in an in vivo brain tumor model. These results suggest that this new approach using BNCs is a promising system for brain tumor-targeted drug delivery. (C) 2007 Elsevier B.V. All rights reserved.

Link information
DOI
https://doi.org/10.1016/j.jconrel.2007.06.019
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000250068700005&DestApp=WOS_CPL
ID information
  • DOI : 10.1016/j.jconrel.2007.06.019
  • ISSN : 0168-3659
  • eISSN : 1873-4995
  • Web of Science ID : WOS:000250068700005

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