期刊
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
卷 142, 期 3, 页码 1636-1644出版社
AMER CHEMICAL SOC
DOI: 10.1021/jacs.9b13586
关键词
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资金
- National Key Research and Development Program of China [2016YFA0203600]
- National Natural Science Foundation of China [31822019, 51703195, 91859116]
- One Belt and One Road International Cooperation Project from Key Research and Development Program of Zhejiang Province [2019C04024]
- Zhejiang Provincial Natural Science Foundation of China [LGF19C100002]
- Fundamental Research Funds for the Central Universities [2019XZZX004-15, 2018QNA7020]
- Zhejiang Pharmaceutical Association [2019ZYY12]
Recent advances in nanomedicine have facilitated the development of potent nanomaterials with intrinsic enzyme-like activities (nanozymes) for cancer therapy. However, it remains a great challenge to fabricate smart nanozymes that precisely perform enzymatic activity in tumor microenvironment without inducing off-target toxicity to surrounding normal tissues. Herein, we report on designed fabrication of biodegradation-medicated enzymatic activity-tunable molybdenum oxide nanourchins (MoO3-x NUs), which selectively perform therapeutic activity in tumor microenvironment via cascade catalytic reactions, while keeping normal tissues unharmed due to their responsive biodegradation in physiological environment. Specifically, the MoO3-x NUs first induce catalase (CAT)-like reactivity to decompose hydrogen peroxide (H2O2) in tumor microenvironment, producing a considerable amount of O-2 for subsequent oxidase (OXD)-like reactivity of MoO3-x NUs; a substantial cytotoxic superoxide radical (center dot O-2(-)) is thus generated for tumor cell apoptosis. Interestingly, once exposed to neutral blood or normal tissues, MoO3-x NUs rapidly lose the enzymatic activity via pH-responsive biodegradation and are excreted in urine, thus ultimately ensuring safety. The current study demonstrates a proof of concept of biodegradation-medicated in vivo catalytic activity-tunable nanozymes for tumor-specific cascade catalytic therapy with minimal off-target toxicity.
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