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Issue 48, 2017, Issue in Progress
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Paclitaxel-loaded pluronic F127/P123 silica nanocapsules with surface conjugated rhTRAIL for targeted cancer therapy

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Abstract

A novel anticancer drug PFPSNT, paclitaxel (PTX)-loaded polymeric F127/P123 silica nanocapsules conjugated with TRAIL (tumor necrosis factor (TNF)-related apoptosis-inducing ligand), was designed and synthesized. Transmission electron microscopy (TEM), dynamic light scattering (DLS), UV-vis absorption and particle size analysis revealed that the synthesized PFPSNT was a spherical particle with a size of 24 nm and excellent colloidal stability. Drug loading efficiency (DL%) and encapsulation ratio (ER%) were 0.39% and 26.5%, and its cumulative release profile was linear. In vitro study showed that PFPSNT had marked cytotoxic and apoptotic activities towards HepG2 (liver cancer cell line) and CaSki (cervical cell line) cells with the IC50 values of 921.07 ng mL−1 and 236.24 ng mL−1, respectively. The antitumor efficacy of PFPSNT was evaluated by using a HepG2-xenografted BALB/c nu/nu mice model. In vivo study showed PFPSNT markedly inhibited HepG2 hepatocellular carcinoma, and its antitumor efficacy was more superior than those of TRAIL, PTX or PTX/F127/P123 silica nanocapsules. Our studies provided a novel strategy to synthesize anticancer nanodrugs with mutiple functions, and demonstrated that PFPSNT was a very effective anticancer drug. This novel nanodrug should be a promising drug for targeted cancer therapy to treat complex cancers.

Graphical abstract: Paclitaxel-loaded pluronic F127/P123 silica nanocapsules with surface conjugated rhTRAIL for targeted cancer therapy

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Publication details

The article was received on 21 Apr 2017, accepted on 05 Jun 2017 and first published on 12 Jun 2017


Article type: Paper
DOI: 10.1039/C7RA04503D
Citation: RSC Adv., 2017,7, 30250-30261
  • Open access: Creative Commons BY-NC license
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    Paclitaxel-loaded pluronic F127/P123 silica nanocapsules with surface conjugated rhTRAIL for targeted cancer therapy

    X. Liu, Y. Li, J. He, T. Zhao, C. Chen, H. Gu and X. Wang, RSC Adv., 2017, 7, 30250
    DOI: 10.1039/C7RA04503D

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