Preparation of siRNA–PLGA/Fabʹ–PLGA mixed micellar system with target cell-specific recognition

Author:

Hazekawa Mai,Nishinakagawa Takuya,Mori Takeshi,Yoshida Miyako,Uchida Takahiro,Ishibashi Daisuke

Abstract

AbstractSmall interfering RNAs (siRNAs) are susceptible to nucleases and degrade quickly in vivo. Moreover, siRNAs demonstrate poor cellular uptake and cannot cross the cell membrane because of its polyanionic characteristics. To overcome these challenges, an intelligent gene delivery system that protects siRNAs from nucleases and facilitates siRNA cellular uptake is required. We previously reported the potential of siRNA-poly(d,l-lactic-co-glycolic acid; PLGA) micelles as an effective siRNA delivery tool in a murine peritoneal dissemination model by local injection. However, there was no effective formulation for siRNA delivery to target cells via intravenous injection. This study aimed to prepare siRNA–PLGA/Fabʹ–PLGA mixed micelles for siRNA delivery to target floating cells and evaluate its formulation in vitro. As the target siRNA protein in CEMx174, CyclinB1 levels were significantly reduced when siRNA–PLGA/Fabʹ–PLGA mixed micelles were added to cells compared with siRNA–PLGA micelles. siRNA–PLGA/Fabʹ–PLGA mixed micelles have high cell permeability and high target cell accumulation by endocytosis because flow cytometry detected labeling micelles in target cells. This study supports siRNA–PLGA/Fabʹ–PLGA mixed micelles as an effective siRNA delivery tool. This formulation can be administered systemically in dosage form against target cells, including cancer metastasis or blood cancer.

Funder

JSPS KAKENHI

Fukuoka Foundation for Sound Health Cancer Research Fund

Found from the Central Research Institute of Fukuoka University

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3