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Long noncoding RNA H19 promotes transforming growth factor-β-induced epithelial–mesenchymal transition by acting as a competing endogenous RNA of miR-370-3p in ovarian cancer cells

Overview of attention for article published in OncoTargets and therapy, January 2018
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Title
Long noncoding RNA H19 promotes transforming growth factor-β-induced epithelial–mesenchymal transition by acting as a competing endogenous RNA of miR-370-3p in ovarian cancer cells
Published in
OncoTargets and therapy, January 2018
DOI 10.2147/ott.s149908
Pubmed ID
Authors

Jing Li, YingYing Huang, XiaoJun Deng, ManLing Luo, XueFei Wang, HaiYan Hu, CiDi Liu, Mei Zhong

Abstract

Ovarian cancer is a gynecological malignant tumor with a high mortality rate among women, owing to metastatic progression and recurrence. Acquisition of invasiveness is accompanied by the loss of epithelial features and a gain of a mesenchymal phenotype, a process known as epithelial-mesenchymal transition (EMT). Transforming growth factor-β (TGF-β) has been implicated in the regulation of EMT. In the present study, we aimed to investigate the role of long noncoding RNA H19 and microRNA-370 (miR-370-3p) in TGF-β-induced EMT. Ovarian cancer cell lines SKOV-3 and OVCAR3 were incubated with different concentrations of TGF-β, and the results showed that TGF-β treatment upregulated H19 and downregulated miR-370-3p. In addition, an H19 knockdown or miR-370-3p overexpression suppressed TGF-β-induced EMT, while H19 overexpression or a miR-370-3p knockdown promoted TGF-β-induced EMT. Mechanistically, H19 could directly bind to miR-370-3p and effectively act as its competing endogenous RNA. Furthermore, we demonstrated that this activity of H19 was involved in its promotion of TGF-β-induced EMT. Thus, our results may provide novel insights into the process of TGF-β-induced EMT.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 20%
Student > Ph. D. Student 3 15%
Student > Bachelor 1 5%
Librarian 1 5%
Other 1 5%
Other 1 5%
Unknown 9 45%
Readers by discipline Count As %
Medicine and Dentistry 5 25%
Biochemistry, Genetics and Molecular Biology 2 10%
Agricultural and Biological Sciences 1 5%
Nursing and Health Professions 1 5%
Social Sciences 1 5%
Other 1 5%
Unknown 9 45%
Attention Score in Context

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 07 February 2018.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from OncoTargets and therapy
#1,597
of 3,016 outputs
Outputs of similar age
#343,505
of 449,550 outputs
Outputs of similar age from OncoTargets and therapy
#39
of 69 outputs
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So far Altmetric has tracked 3,016 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.