| Title |
MicroRNA-153 acts as a prognostic marker in gastric cancer and its role in cell migration and invasion
|
|---|---|
| Published in |
OncoTargets and therapy, February 2015
|
| DOI | 10.2147/ott.s78236 |
| Pubmed ID | |
| Authors |
Zhengliang Zhang, Jiangli Sun, Zhenghai Bai, Haijun Li, Shicai He, Rui Chen, Xiangming Che |
| Abstract |
MicroRNA (miRNA)-153 (miR-153) has been considered as a novel tumor-related miRNA and is found to be significantly deregulated in human cancers. In this study, we found that the expression levels of miR-153 were obviously lower in gastric cancer tissues than those in matched adjacent nontumor tissues. Otherwise, miR-153 was expressed at significantly lower levels in aggressive tumor tissues. Clinical association analysis indicated that low expression of miR-153 was prominently correlated with poor prognostic features in gastric cancer. Furthermore, we demonstrated that the low expression of miR-153 was correlated with short 5-year survival of gastric cancer patients. Multivariate Cox regression analysis indicated that miR-153 was an independent prognostic marker in gastric cancer. Our in vitro studies showed that upregulation of miR-153 reduced cell migration and invasion in MKN-45 cells. Meanwhile, downregulation of miR-153 promoted SGC-7901 cell migration and invasion. An inverse correlation between miR-153 and SNAI1 expression was observed in gastric cancer tissues. In addition, upregulation of miR-153 reduced SNAI1 expression and subsequently suppressed epithelial-mesenchymal transition (EMT) with elevated expression of E-cadherin and reduced expression of vimentin in MKN-45 cells. Furthermore, downregulation of miR-153 increased SNAI1 expression and promoted EMT in SGC-7901 cells. In conclusion, miR-153 is an independent prognostic marker for predicting survival of gastric cancer patients and may promote gastric cancer cell migration and invasion, by inhibiting SNAI1-induced EMT. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Other | 1 | 9% |
| Student > Master | 1 | 9% |
| Student > Postgraduate | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 5 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 18% |
| Agricultural and Biological Sciences | 2 | 18% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Unknown | 6 | 55% |
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 14 February 2015.
All research outputs
#22,760,732
of 25,374,917 outputs
Outputs from OncoTargets and therapy
#2,078
of 3,016 outputs
Outputs of similar age
#309,276
of 361,176 outputs
Outputs of similar age from OncoTargets and therapy
#15
of 18 outputs
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