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Cited by 600

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

Glucose Oxidase‐Instructed Multimodal Synergistic Cancer Therapy

Fu, Lian‐Hua, Qi, Chao, Hu, Yan‐Ru, Lin, Jing, Huang, Peng·2019·Advanced Materials

Abstract

Over the past 3 years, glucose oxidase (GOx) has aroused great research interest in the context of cancer treatment due to its inherent biocompatibility and biodegradability, and its unique catalytic properties against β‐d‐glucose. GOx can effectively catalyze the oxidation of glucose into gluconic acid and hydrogen peroxide. This process depletes oxygen levels, resulting in elevated acidity, hypoxia, and oxidative stress in the tumor microenvironment. All of these changes can be readily harnessed to develop a multimodal synergistic cancer therapy by combining GOx with other therapeutic approaches. Herein, the representative studies of GOx‐instructed multimodal synergistic cancer therapy are introduced, and their synergistic mechanisms are discussed systematically. The current challenges and future prospects to advance the development of GOx‐based nanomedicines in this cutting‐edge research area are highlighted.

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Crossref · 10.1002/adma.201808325

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Metadata

Authors
Fu, L., Qi, C., Hu, Y., Lin, J., & Huang, P.
Venue
Advanced Materials
Publisher
Wiley
Published
2019-03-25
Volume
31
Issue
21
Pages
e1808325-e1808325
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2924970449
Cited by
600
References
60
FWCI
25.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Glucose Oxidase‐Instructed Multimodal Synergistic Cancer Therapy. https://app.cochat.ai/papers/10.1002/adma.201808325
The paper
Fu, L., Qi, C., Hu, Y., Lin, J., & Huang, P. (2019). Glucose Oxidase‐Instructed Multimodal Synergistic Cancer Therapy. Advanced Materials. https://doi.org/10.1002/adma.201808325

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.