| Title |
Nigericin inhibits epithelial ovarian cancer metastasis by suppressing the cell cycle and epithelial−mesenchymal transition
|
|---|---|
| Published in |
Biochemistry, August 2017
|
| DOI | 10.1134/s0006297917080089 |
| Pubmed ID | |
| Authors |
Wen Wang, Yan Zhao, Shujuan Yao, Xiujuan Cui, Wenying Pan, Wenqian Huang, Jiangang Gao, Taotao Dong, Shiqian Zhang |
| Abstract |
Epithelial ovarian cancer (EOC) has the highest mortality among various types of gynecological malignancies. Most patients die of metastasis and recurrence due to cisplatin resistance. Thus, it is urgent to develop novel therapies to cure this disease. CCK-8 assay showed that nigericin exhibited strong cytotoxicity on A2780 and SKOV3 cell lines. Flow cytometry indicated that nigericin could induce cell cycle arrest at G0/G1 phase and promote cell apoptosis. Boyden chamber assay revealed that nigericin could inhibit migration and invasion in a dose-dependent manner by suppressing epithelial-mesenchymal transition (EMT) in EOC cells. These effects were mediated, at least partly, by the Wnt/β-catenin signaling pathway. Our results demonstrated that nigericin could inhibit EMT during cell invasion and metastasis through the canonical Wnt/β-catenin signaling pathway. Nigericin may prove to be a novel therapeutic strategy that is effective in patients with metastatic EOC. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 20% |
| Lecturer > Senior Lecturer | 1 | 10% |
| Lecturer | 1 | 10% |
| Student > Bachelor | 1 | 10% |
| Student > Ph. D. Student | 1 | 10% |
| Other | 1 | 10% |
| Unknown | 3 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 30% |
| Nursing and Health Professions | 2 | 20% |
| Agricultural and Biological Sciences | 1 | 10% |
| Engineering | 1 | 10% |
| Unknown | 3 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 September 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from Biochemistry
#20,694
of 22,290 outputs
Outputs of similar age
#253,265
of 326,939 outputs
Outputs of similar age from Biochemistry
#131
of 161 outputs
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