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- W4386688306 abstract "Nanoparticles have been suggested as drug-delivery systems for chemotherapeutic drugs to allow for controlled drug release profiles and selectivity to target cancer cells. In addition, nanoparticles can be used for the in situ generation and amplification of reactive oxygen species (ROS), which have been shown to be a promising strategy for cancer treatment. Thus, a targeted nanoscale drug-delivery platform could be used to synergistically improve cancer treatment by the action of chemotherapeutic drugs and ROS generation. Herein, we propose a promising chemotherapy strategy where the drug-loaded nanoparticles generate high doses of ROS together with the loaded ROS-generating chemotherapeutic drugs, which can damage the mitochondria and activate cell death, potentiating the therapeutic outcome in cancer therapy. In the present study, we have developed a dual-targeted drug-delivery nanoassembly consisting of a mesoporous silica core loaded with the chemotherapeutic, ROS-generating drug, paclitaxel (Px), and coated with a liposome layer for controlled drug release. Two different lung cancer-targeting ligands, folic acid and peptide GE11, were used to target the overexpressed nonsmall lung cancer receptors to create the final nanoassembly (MSN@Px) L-GF. Upon endocytosis by the cancer cells, the liposome layer was degraded by the intracellular lipases, and the drug was rapidly released at a rate of 65% within the first 20 h. In vitro studies confirmed that this nanoassembly was 8-fold more effective in cancer therapy compared to the free drug Px." @default.
- W4386688306 created "2023-09-13" @default.
- W4386688306 creator A5025998875 @default.
- W4386688306 creator A5069894979 @default.
- W4386688306 creator A5075810198 @default.
- W4386688306 creator A5091815442 @default.
- W4386688306 date "2023-09-12" @default.
- W4386688306 modified "2023-10-17" @default.
- W4386688306 title "Fabrication of a Dual-Targeted Liposome-Coated Mesoporous Silica Core–Shell Nanoassembly for Targeted Cancer Therapy" @default.
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