The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Layer-by-Layer Nanoparticles for Systemic Codelivery of an Anticancer Drug and siRNA for Potential Triple-Negative Breast Cancer Treatment
Open accessAbstract
A single nanoparticle platform has been developed through the modular and controlled layer-by-layer process to codeliver siRNA that knocks down a drug-resistance pathway in tumor cells and a chemotherapy drug to challenge a highly aggressive form of triple-negative breast cancer. Layer-by-layer films were formed on nanoparticles by alternately depositing siRNA and poly-l-arginine; a single bilayer on the nanoparticle surface could effectively load up to 3500 siRNA molecules, and the resulting LbL nanoparticles exhibit an extended serum half-life of 28 h. In animal models, one dose via intravenous administration significantly reduced the target gene expression in the tumors by almost 80%. By generating the siRNA-loaded film atop a doxorubicin-loaded liposome, we identified an effective combination therapy with siRNA targeting multidrug resistance protein 1, which significantly enhanced doxorubicin efficacy by 4 fold in vitro and led to up to an 8-fold decrease in tumor volume compared to the control treatments with no observed toxicity. The results indicate that the use of layer-by-layer films to modify a simple liposomal doxorubicin delivery construct with a synergistic siRNA can lead to significant tumor reduction in the cancers that are otherwise nonresponsive to treatment with Doxil or other common chemotherapy drugs. This approach provides a potential strategy to treat aggressive and resistant cancers, and a modular platform for a broad range of controlled multidrug therapies customizable to the cancer type in a singular nanoparticle delivery system.
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Cites
Knocking down barriers: advances in siRNA delivery
Whitehead, K. A., Langer, R., & Anderson, D. G. (2009) · Nature Reviews Drug Discovery · doi:10.1038/nrd2742 · Cited by 3,115
Transvascular delivery of small interfering RNA to the central nervous system
Kumar, P., Wu, H., McBride, J. L., Jung, K.-E., Hee Kim, M., Davidson, B. L., Kyung Lee, S., Shankar, P., & Manjunath, N. (2007) · Nature · doi:10.1038/nature05901 · Cited by 1,246
Triple-negative breast cancer: epidemiological considerations and recommendations
Boyle, P. (2012) · Annals of Oncology · doi:10.1093/annonc/mds187 · Cited by 593
Layer-by-Layer Nanoparticles with a pH-Sheddable Layer for in Vivo Targeting of Tumor Hypoxia
Poon, Z., Chang, D., Zhao, X., & Hammond, P. T. (2011) · ACS Nano · doi:10.1021/nn200876f · Cited by 343
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Mitchell, M. J., Jain, R. K., & Langer, R. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2017.83 · Cited by 273
Dreaden, E. C., Morton, S. W., Shopsowitz, K. E., Choi, J.-H., Deng, Z. J., Cho, N.-J., & Hammond, P. T. (2014) · ACS Nano · doi:10.1021/nn502861t · Cited by 179
Self-citationHanssen, K. M., Haber, M., & Fletcher, J. I. (2021) · Drug Resistance Updates · doi:10.1016/j.drup.2021.100795 · Cited by 102
Babu, A., Wang, Q., Muralidharan, R., Shanker, M., Munshi, A., & Ramesh, R. (2014) · Molecular Pharmaceutics · doi:10.1021/mp500259e · Cited by 94
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Li, J., Li, Z., Li, M., Zhang, H., & Xie, Z. (2015) · Journal of Applied Polymer Science · doi:10.1002/app.41440 · Cited by 16
Metadata
- Authors
- Deng, Z. J., Morton, S. W., Ben-Akiva, E., Dreaden, E. C., Shopsowitz, K. E., & Hammond, P. T.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-10-21
- Volume
- 7
- Issue
- 11
- Pages
- 9571-9584
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2150375936
- Cited by
- 516
- References
- 4
- FWCI
- 19.23
- Type
- journal article
- Language
- en
- Open access
- green
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