| Title |
LncRNA NEAT1 contributes to paclitaxel resistance of ovarian cancer cells by regulating ZEB1 expression via miR-194
|
|---|---|
| Published in |
OncoTargets and therapy, November 2017
|
| DOI | 10.2147/ott.s147586 |
| Pubmed ID | |
| Authors |
Jihong An, Weiling Lv, Yongzhou Zhang |
| Abstract |
Chemoresistance is one of the major obstacles for cancer therapy in the clinic. Nuclear paraspeckle assembly transcript 1 (NEAT1) has been reported as an oncogene in most malignancies such as lung cancer, esophageal cancer, and gastric cancer. This study is designed to investigate the function of NEAT1 in paclitaxel (PTX) resistance of ovarian cancer and its potential molecular mechanism. The expressions of NEAT1 and miR-194 in ovarian cancer tissues and cells were estimated by quantitative real-time polymerase chain reaction (qRT-PCR). MTT, flow cytometry, and Western blot assays were used to assess the effect of NEAT1 on PTX resistance in PTX-resistant ovarian cancer cells. Luciferase reporter assay was applied to examine the association between NEAT1, zinc finger E-box-binding homeobox 1 (ZEB1) and miR-194. Xenograft tumor model was established to confirm the biological role of NEAT1 in PTX resistance of ovarian cancer in vivo. NEAT1 was upregulated, and miR-194 was downregulated in PTX-resistant ovarian cancer tissues and cells. Functionally, NEAT1 knockdown enhanced cell sensitivity to PTX via promoting PTX-induced apoptosis in vitro. NEAT1 was identified as a molecular sponge of miR-194 to upregulate ZEB1 expression. Mechanistically, NEAT1-knockdown-induced PTX sensitivity was mediated by miR-194/ZEB1 axis. Moreover, NEAT1 knockdown improved PTX sensitivity of ovarian cancer in vivo. NEAT1 contributed to PTX resistance of ovarian cancer cells at least partly through upregulating ZEB1 expression by sponging miR-194, elucidating a novel regulatory pathway of chemoresistance in PTX-resistant ovarian cancer cells and providing a possible long noncoding RNA (lncRNA)-targeted therapy for ovarian cancer. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 21% |
| Student > Ph. D. Student | 5 | 13% |
| Student > Bachelor | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Postgraduate | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 11 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 17 | 45% |
| Medicine and Dentistry | 4 | 11% |
| Agricultural and Biological Sciences | 2 | 5% |
| Nursing and Health Professions | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 11 | 29% |
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 29 November 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from OncoTargets and therapy
#1,447
of 3,016 outputs
Outputs of similar age
#248,688
of 340,752 outputs
Outputs of similar age from OncoTargets and therapy
#41
of 73 outputs
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