In vivo endothelial siRNA delivery using polymeric nanoparticles with low molecular weight
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Anderson_In vivo endothelial.pdf
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Author(s)
Dahlman, James E.
Jhunjhunwala, Siddharth
Shaw, Taylor E.
Xing, Yiping
Sahay, Gaurav
Bader, Andrew
Yin, Hao
Dong, Yizhou
Jiang, Shan
Seedorf, Danielle
Date Issued
May 2014
Journal
Nature Nanotechnology
Publisher
Nature Publishing Group
Citation
Dahlman, James E., Carmen Barnes, Omar F. Khan, Aude Thiriot, Siddharth Jhunjunwala, Taylor E. Shaw, Yiping Xing, et al. “In Vivo Endothelial siRNA Delivery Using Polymeric Nanoparticles with Low Molecular Weight.” Nature Nanotechnology 9, no. 8 (May 11, 2014): 648–655.
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Author's final manuscript
Abstract
Dysfunctional endothelium contributes to more diseases than any other tissue in the body. Small interfering RNAs (siRNAs) can help in the study and treatment of endothelial cells in vivo by durably silencing multiple genes simultaneously, but efficient siRNA delivery has so far remained challenging. Here, we show that polymeric nanoparticles made of low-molecular-weight polyamines and lipids can deliver siRNA to endothelial cells with high efficiency, thereby facilitating the simultaneous silencing of multiple endothelial genes in vivo. Unlike lipid or lipid-like nanoparticles, this formulation does not significantly reduce gene expression in hepatocytes or immune cells even at the dosage necessary for endothelial gene silencing. These nanoparticles mediate the most durable non-liver silencing reported so far and facilitate the delivery of siRNAs that modify endothelial function in mouse models of vascular permeability, emphysema, primary tumour growth and metastasis.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1038/nnano.2014.84
