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Cited by 174

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Ancient drug curcumin impedes 26S proteasome activity by direct inhibition of dual-specificity tyrosine-regulated kinase 2

Open access
Banerjee, Sourav, Ji, Chenggong, Mayfield, Joshua E., Goel, Apollina, Xiao, Junyu, Dixon, Jack E., Guo, Xing·2018·Proceedings of the National Academy of Sciences

Abstract

Significance: Curcumin is an ancient drug derived from turmeric and has been found to exhibit potent anticancer properties albeit through controversial mechanisms of action. Using a biochemical model, mouse cancer model, and cellular models, we show that curcumin is a highly potent and selective inhibitor of dual-specificity tyrosine-regulated kinase 2 (DYRK2), a positive regulator of the 26S proteasome. Curcumin perturbs 26S proteasome activity via DYRK2 inhibition in various cancer cells and in the mouse cancer model leading to impairment of cell proliferation and reduction of cancer burden in mice. This novel mechanism of action of curcumin opens up new avenues for potential preventative or therapeutic strategies in proteasome-addicted cancers like triple-negative breast cancer and multiple myeloma.

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Metadata

Authors
Banerjee, S., Ji, C., Mayfield, J. E., Goel, A., Xiao, J., Dixon, J. E., & Guo, X.
Venue
Proceedings of the National Academy of Sciences
Published
2018-07-09
Volume
115
Issue
32
Pages
8155-8160
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2861982167
Cited by
174
References
6
FWCI
6.52
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Ancient drug curcumin impedes 26S proteasome activity by direct inhibition of dual-specificity tyrosine-regulated kinase 2. https://app.cochat.ai/papers/10.1073/pnas.1806797115
The paper
Banerjee, S., Ji, C., Mayfield, J. E., Goel, A., Xiao, J., Dixon, J. E., & Guo, X. (2018). Ancient drug curcumin impedes 26S proteasome activity by direct inhibition of dual-specificity tyrosine-regulated kinase 2. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1806797115

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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.