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A triple-synergistic strategy for combinational photo/radiotherapy and multi-modality imaging based on hyaluronic acid-hybridized polyaniline-coated WS2 nanodots

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Abstract

In this study, we report a strategy for integrating hyaluronic acid (HA), polyaniline (PANI), WS2 nanodots (WS2), and chlorin e6 (Ce6) into a single nanoplatform (HA-WS2@PANI/Ce6) for fluorescence, photoacoustic, and computed tomography multi-modality imaging-guided trimodal photothermal/radiation/photodynamic combination therapy of tumors. The WS2 nanodot core is used as the radiosensitizer with the PANI shell as the hyperthermal agent and the photosensitizer reservoir. HA and Ce6 were adsorbed on the outer shell for tumor targeting and photodynamic therapy, respectively. The in vivo trimodal imaging uncovered that HA-WS2@PANI/Ce6 nanoparticles showed enhanced tumor uptake and diagnosis effects after intravenous injection. More importantly, in the in vitro and in vivo experiments, the nanoparticles exhibited an evident near-infrared induced photothermal effect, which remarkably improved the radiation and photodynamic therapy efficiency by accelerating the blood flow and subsequently increasing oxygen supply in the tumor. The nanohybrids were found to be safe to cells in vitro and organs in vivo. Taken together, our current work demonstrates a nanoplatform for multimodal imaging guided targeted triple-therapy, which reveals a potential strategy for tumor treatment.

Graphical abstract: A triple-synergistic strategy for combinational photo/radiotherapy and multi-modality imaging based on hyaluronic acid-hybridized polyaniline-coated WS2 nanodots

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Publication details

The article was received on 27 Nov 2016, accepted on 23 Mar 2017 and first published on 28 Mar 2017


Article type: Paper
DOI: 10.1039/C6NR09219E
Citation: Nanoscale, 2017, Advance Article
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    A triple-synergistic strategy for combinational photo/radiotherapy and multi-modality imaging based on hyaluronic acid-hybridized polyaniline-coated WS2 nanodots

    J. Wang, X. Pang, X. Tan, Y. Song, L. Liu, Q. You, Q. Sun, F. Tan and N. Li, Nanoscale, 2017, Advance Article , DOI: 10.1039/C6NR09219E

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