| Title |
Omega-3 polyunsaturated fatty acids eicosapentaenoic acid and docosahexaenoic acid enhance dexamethasone sensitivity in multiple myeloma cells by the p53/miR-34a/Bcl-2 axis
|
|---|---|
| Published in |
Biochemistry, July 2017
|
| DOI | 10.1134/s0006297917070082 |
| Pubmed ID | |
| Authors |
Xianping Dai, Mengshun Li, Feng Geng |
| Abstract |
Dexamethasone is widely used in multiple myeloma (MM) for its cytotoxic effects on lymphoid cells. However, many MM patients are resistant to dexamethasone, although some can benefit from dexamethasone treatment. In this study, we noted that ω-3 polyunsaturated fatty acids (PUFAs) enhanced the dexamethasone sensitivity of MM cells by inducing cell apoptosis. q-PCR analysis revealed that miR-34a could be significantly induced by PUFAs in U266 and primary MM cells. Transfection with miR-34a antagonist or miR-34a agomir could restore or suppress the dexamethasone sensitivity in U266 cells. Both luciferase reporter assay and Western blot showed that Bcl-2 is the direct target of miR-34a in MM cells. In addition, we observed that PUFAs induced p53 protein expression in MM cells under dexamethasone administration. Furthermore, suppressing p53 by its inhibitor, Pifithrin-α, regulated the miR-34a expression and modulated the sensitivity to dexamethasone in U266 cells. In summary, these results suggest that PUFAs enhance dexamethasone sensitivity to MM cells through the p53/miR-34a axis with a likely contribution of Bcl-2 suppression. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
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 | 5 | 25% |
| Researcher | 3 | 15% |
| Lecturer | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Professor | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 6 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Business, Management and Accounting | 2 | 10% |
| Agricultural and Biological Sciences | 2 | 10% |
| Chemistry | 2 | 10% |
| Medicine and Dentistry | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 9 | 45% |
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 26 September 2017.
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#22,764,772
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Outputs from Biochemistry
#21,450
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#286,147
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Outputs of similar age from Biochemistry
#132
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