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Cited by 406

The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.

Nitric Oxide Donor-Based Cancer Therapy: Advances and Prospects

Huang, Zhangjian, Fu, Junjie, Zhang, Yihua·2017·Journal of Medicinal Chemistry

Abstract

The increasing understanding of the role of nitric oxide (NO) in cancer biology has generated significant progress in the use of NO donor-based therapy to fight cancer. These advances strongly suggest the potential adoption of NO donor-based therapy in clinical practice, and this has been supported by several clinical studies in the past decade. In this review, we first highlight several types of important NO donors, including recently developed NO donors bearing a dinitroazetidine skeleton, represented by RRx-001, with potential utility in cancer therapy. Special emphasis is then given to the combination of NO donor(s) with other therapies to achieve synergy and to the hybridization of NO donor(s) with an anticancer drug/agent/fragment to enhance the activity or specificity or to reduce toxicity. In addition, we briefly describe inducible NO synthase gene therapy and nanotechnology, which have recently entered the field of NO donor therapy.

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Metadata

Authors
Huang, Z., Fu, J., & Zhang, Y.
Venue
Journal of Medicinal Chemistry
Published
2017-05-23
Volume
60
Issue
18
Pages
7617-7635
ISSN
  • 0022-2623 (ISSN-L)
  • 1520-4804
OpenAlex
W2615885638
Cited by
406
References
135
FWCI
20.60
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nitric Oxide Donor-Based Cancer Therapy: Advances and Prospects. https://app.cochat.ai/papers/10.1021/acs.jmedchem.6b01672
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Huang, Z., Fu, J., & Zhang, Y. (2017). Nitric Oxide Donor-Based Cancer Therapy: Advances and Prospects. Journal of Medicinal Chemistry. https://doi.org/10.1021/acs.jmedchem.6b01672

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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.