Zerumbone inhibits epithelial-mesenchymal transition and cancer stem cells properties by inhibiting the β-catenin pathway through miR-200c.
Fatemeh Karimi DermaniRazieh AminiMassoud SaidijamMona PourjafarSahar SakiRezvan NajafiPublished in: Journal of cellular physiology (2018)
Colorectal cancer (CRC) is one of the most lethal and rampant human malignancies in the world. Zerumbone, a sesquiterpene isolated from subtropical ginger, has been found to exhibit an antitumor effect in various cancer types. However, the effect of Zerumbone on the biological properties of CRC, including epithelial-mesenchymal transition (EMT) and cancer stem cells (CSCs) has not been fully elucidated. Here, we investigated the inhibitory action of Zerumbone on the EMT process, CSC markers, and the β-catenin signaling pathway in the presence or absence of miR-200c. The effect of Zerumbone on HCT-116 and SW-48 cells viability was examined by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay. The effects of Zerumbone on EMT-related genes, CSCs markers, cell migration, invasion, sphere-forming, and β-catenin signaling pathway were explored. To evaluate the role of miR-200c in anticancer effects by Zerumbone, miR-200c was downregulated by LNA-anti-miR-200c. Zerumbone significantly inhibited cell viability, migration, invasion, and sphere-forming potential in HCT-116 and SW-48 cell lines. Zerumbone significantly suppressed the EMT and CSC properties as well as downregulated the β-catenin. Silencing of miR200c reduced the inhibitory effects of Zerumbone on EMT and CSCs in CRC cells. These data indicated that Zerumbone may be a promising candidate for reducing the risk of CRC progression by suppressing the β-catenin pathway via miR-200c.
Keyphrases
- epithelial mesenchymal transition
- cell proliferation
- long non coding rna
- cancer stem cells
- long noncoding rna
- cell migration
- transforming growth factor
- signaling pathway
- cell cycle arrest
- induced apoptosis
- pi k akt
- high throughput
- cell death
- young adults
- big data
- deep learning
- human health
- oxidative stress
- data analysis
- induced pluripotent stem cells