Econazole induces p53-dependent apoptosis and decreases metastasis ability in gastric cancer cells

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Title
Econazole induces p53-dependent apoptosis and decreases metastasis ability in gastric cancer cells
Author(s)
Eun Kyoung Choi; Eun Jung Park; T T Phan; Hae Dong Kim; K L Hoe; Dong Uk Kim
Bibliographic Citation
Biomolecules & Therapeutics, vol. 28, no. 4, pp. 370-379
Publication Year
2020
Abstract
Econazole, a potent broad-spectrum antifungal agent and a Ca2+ channel antagonist, induces cytotoxicity in leukemia cells and is used for the treatment of skin infections. However, little is known about its cytotoxic effects on solid tumor cells. Here, we investigated the molecular mechanism underlying econazole-induced toxicity in vitro and evaluated its regulatory effect on the metastasis of gastric cancer cells. Using the gastric cancer cell lines AGS and SNU1 expressing wild-type p53 we demonstrated that econazole could significantly reduce cell viability and colony-forming (tumorigenesis) ability. Econazole induced G0/G1 phase arrest, promoted apoptosis, and effectively blocked proliferation- and survival-related signal transduction pathways in gastric cancer cells. In addition, econazole inhibited the secretion of matrix metalloproteinase- 2 (MMP-2) and MMP-9, which degrade the extracellular matrix and basement membrane. Econazole also effectively inhibited the metastasis of gastric cancer cells, as confirmed from cell invasion and wound healing assays. The protein level of p53 was significantly elevated after econazole treatment of AGS and SNU1 cells. However, apoptosis was blocked in econazole-treated cells exposed to a p53-specific small-interfering RNA to eliminate p53 expression. These results provide evidence that econazole could be repurposed to induce gastric cancer cell death and inhibit cancer invasion.
Keyword
ApoptosisEconazoleGastric cancerInvasionMigrationp53
ISSN
1976-9148
Publisher
Korea Soc-Assoc-Inst
Full Text Link
http://dx.doi.org/10.4062/biomolther.2019.201
Type
Article
Appears in Collections:
Division of A.I. & Biomedical Research > Digital Biotech Innovation Center > 1. Journal Articles
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