chitosan-based nanoparticles for survivin targeted sirna delivery in breast tumor therapy and preventing its metastasis

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ID: 239564
2016
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Abstract
Ping Sun,1,2 Wei Huang,1,2 Mingji Jin,1,2 Qiming Wang,1,2 Bo Fan,1,2 Lin Kang,1,2 Zhonggao Gao1,2 1State Key Laboratory of Bioactive Substance and Function of Natural Medicines, 2Department of Pharmaceutics, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China Abstract: Nanoparticle-mediated small interfering RNA (siRNA) delivery is a promising therapeutic strategy in various cancers. However, it is difficult to deliver degradative siRNA to tumor tissue, and thus a safe and efficient vector for siRNA delivery is essential for cancer therapy. In this study, poly(ethylene glycol)-modified chitosan (PEG-CS) was synthesized successfully for delivering nucleic acid drug. We deemed that PEGylated CS could improve its solubility by forming a stable siRNA loaded in nanoparticles, and enhancing transfection efficiency of siRNA-loaded CS nanoparticles in cancer cell line. The research results showed that siRNA loaded in PEGylated CS (PEG-CS/siRNA) nanoparticles with smaller particle size had superior structural stability in the physical environment compared to CS nanoparticles. The data of in vitro antitumor activity revealed that 4T1 tumor cell growth was significantly inhibited and cellular uptake of PEG-CS/siRNA nanoparticles in 4T1 cells was dramatically enhanced compared to naked siRNA groups. The results from flow cytometry and confocal laser scanning microscopy showed that PEG-CS/siRNA nanoparticles were more easily taken up than naked siRNA. Importantly, PEG-CS/siRNA nanoparticles significantly reduced the growth of xenograft tumors of 4T1 cells in vivo. It has been demonstrated that the PEG-CS is a safe and efficient vector for siRNA delivery, and it can effectively reduce tumor growth and prevent metastasis. Keywords: PEGylated chitosan, non-viral vector, siRNA delivery, breast anti-tumor therapy
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p2016internationalchitosan-based Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Sun P;Huang W;Jin M;Wang Q;Fan B;Kang L;Gao Z
Journal nonlinear analysis: real world applications
Year 2016
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