| Title |
miR-1285-3p acts as a potential tumor suppressor miRNA via downregulating JUN expression in hepatocellular carcinoma
|
|---|---|
| Published in |
Tumor Biology, September 2014
|
| DOI | 10.1007/s13277-014-2622-5 |
| Pubmed ID | |
| Authors |
Jibing Liu, Jingchen Yan, Changchun Zhou, Qinghua Ma, Qingyan Jin, Zhenbin Yang |
| Abstract |
In the world, hepatocellular carcinoma (HCC) is one of the most common and most lethal cancers. Currently, standard therapy for unresectable HCC is a local-regional therapy with transarterial chemoembolisation (TACE). In this study, we sought to assess whether plasma circulating microRNAs (miRNAs) can be used to predict the prognosis of HCC patients receiving the TACE treatment. Firstly, we systematically examined TACE therapeutic effectiveness-related circulating miRNAs through miRNA Profiling Chips. As a result, we identified 19 circulating miRNAs to be significantly differentially expressed between the TACE-response group and the TACE-nonresponse group. In the second stage, we performed quantitative analyses of these candidate miRNAs in additional HCC patients treated with TACE and validated two of the aforementioned 19 miRNAs (miR-1285-3p and miR-4741) as candidate biomarkers for predicting prognosis of TACE. Interestingly, we found that miR-1285-3p could directly repress JUN oncogene expression in HCC cells, indicating miR-1285-3p could act as a potential tumor suppressor. In conclusion, our data indicate that circulating miR-1285-3p and miR-4741 was predictive of response to TACE therapy in HCC. |
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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 24% |
| Researcher | 4 | 16% |
| Student > Doctoral Student | 2 | 8% |
| Other | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 4 | 16% |
| Unknown | 5 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 24% |
| Agricultural and Biological Sciences | 5 | 20% |
| Medicine and Dentistry | 3 | 12% |
| Environmental Science | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 6 | 24% |
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 12 May 2015.
All research outputs
#18,379,018
of 22,764,165 outputs
Outputs from Tumor Biology
#1,370
of 2,622 outputs
Outputs of similar age
#177,792
of 249,649 outputs
Outputs of similar age from Tumor Biology
#54
of 123 outputs
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