Dual Drug Backboned Shattering Polymeric Theranostic Nanomedicine for Synergistic Eradication of Patient-Derived Lung Cancer
Autor: | Jianxun Ding, Xing-Jie Liang, Yubin Huang, Zigui Wang, Haihua Xiao, Hejian Xiong, Xuesi Chen, Dongfang Zhou, Yuwei Cong, Chan Li |
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Rok vydání: | 2017 |
Předmět: |
Drug
Materials science Lung Neoplasms Theranostic Nanomedicine Polymers media_common.quotation_subject Antineoplastic Agents 02 engineering and technology 010402 general chemistry 01 natural sciences Drug Delivery Systems In vivo medicine Humans General Materials Science Lung cancer media_common Cisplatin Mechanical Engineering Cancer 021001 nanoscience & nanotechnology medicine.disease 0104 chemical sciences Nanomedicine Mechanics of Materials Drug delivery Cancer research Nanoparticles 0210 nano-technology medicine.drug |
Zdroj: | Advanced materials (Deerfield Beach, Fla.). 30(11) |
ISSN: | 1521-4095 |
Popis: | Most of the current nanoparticle-based therapeutics worldwide failing in clinical trials face three major challenges: (i) lack of an optimum drug delivery platform with precise composition, (ii) lack of a method of directly monitoring the fate of a specific drug rather than using any other labelling molecules as a compromise, and (iii) lack of reliable cancer models with high fidelity for drug screen and evaluation. Here, starting from a PP2A inhibitor demethylcantharidin (DMC) and cisplatin, the design of a dual sensitive dual drug backboned shattering polymer (DDBSP) with exact composition at a fixed DMC/Pt ratio for precise nanomedicine is shown. DDBSP self-assembled nanoparticle (DD-NP) can be triggered intracellularly to break down in a chain-shattering manner to release the dual drugs payload. Moreover, DD-NP with extremely high Pt heavy metal content in the polymer chain can directly track the drug itself via Pt-based drug-mediated computer tomography and ICP-MS both in vitro and in vivo. Finally, DD-NP is used to eradicate the tumor burden on a high-fidelity patient-derived lung cancer model for the first time. |
Databáze: | OpenAIRE |
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