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Cited by 284

The DOI matches its Crossref record; 148 of the 148 references it cites were found in a registry or an index.

Strategies for enhancing cancer chemodynamic therapy performance

Open access
Jana, Deblin, Zhao, Yanli·2022·Exploration

Abstract

Chemodynamic therapy (CDT) has emerged to be a frontrunner amongst reactive oxygen species‐based cancer treatment modalities. CDT utilizes endogenous H 2 O 2 in tumor microenvironment (TME) to produce cytotoxic hydroxyl radicals (•OH) via Fenton or Fenton‐like reactions. While possessing advantages such as tumor specificity, no need of external stimuli, and low side effects, practical applications of CDT are still impeded owing to the heterogeneity, complexity, and reductive environment of TME. Over the past couple of years, strategies to enhance CDT for efficient tumor regression are in rapid development in synergy with the growth of nanomedicine. In this review, we initially outline the fundamental understanding of Fenton and Fenton‐like reactions and their relationship with CDT. Subsequently, the development in the design of nanosystems for CDT is highlighted in a general manner. Furthermore, recent advancement of the strategies to augment Fenton reactions in TME for enhanced CDT is discussed in detail. Finally, perspectives toward the future development of CDT for better therapeutic outcome are presented. This review is expected to draw attention for collaborative research on CDT in the best interest of its future clinical applications.

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Crossref · 10.1002/exp.20210238

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Metadata

Authors
Jana, D., & Zhao, Y.
Venue
Exploration
Publisher
Wiley
Published
2022-03-07
Volume
2
Issue
2
Pages
20210238-20210238
ISSN
2766-2098 (ISSN-L)
OpenAlex
W4221012755
Cited by
284
References
148
FWCI
16.19
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Strategies for enhancing cancer chemodynamic therapy performance. https://app.cochat.ai/papers/10.1002/exp.20210238
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Jana, D., & Zhao, Y. (2022). Strategies for enhancing cancer chemodynamic therapy performance. Exploration. https://doi.org/10.1002/exp.20210238

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

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