| Title |
Serum microRNA profiling in patients with glioblastoma: a survival analysis
|
|---|---|
| Published in |
Molecular Cancer, March 2017
|
| DOI | 10.1186/s12943-017-0628-5 |
| Pubmed ID | |
| Authors |
Hua Zhao, Jie Shen, Tiffany R. Hodges, Renduo Song, Gregory N. Fuller, Amy B. Heimberger |
| Abstract |
Because circulating microRNAs (miRNAs) have drawn a great deal of attention as promising novel cancer diagnostics and prognostic biomarkers, we sought to identify serum miRNAs significantly associated with outcome in glioblastoma patients. To do this, we performed global miRNA profiling in serum samples from 106 primary glioblastoma patients. The study subjects were randomly divided into two sets: set one (n = 40) and set two (n = 66). Using a Cox regression model, 3 serum miRNAs (miR-106a-5p, miR-182, and miR-145-5p) and 5 serum miRNAs (miR-222-3p, miR-182, miR-20a-5p, miR-106a-5p, and miR-145-5p) were identified significantly associated with 2-year patient overall survival and disease-free survival (P < 0.05) in both sets and the combined set. We then created the miRNA risk scores to assess the total impact of the significant serum miRNAs on survival. The high risk scores were associated with poor patient survival (overall survival: HR = 1.92, 95% CI: 1.19, 10.23, and disease-free survival: HR = 2.03, 95%CI: 1.24, 4.28), and were independent of other clinicopathological factors. Our results suggest that serum miRNAs could serve as prognostic predictors of glioblastoma. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 19% |
| Researcher | 8 | 14% |
| Student > Ph. D. Student | 7 | 12% |
| Student > Doctoral Student | 6 | 10% |
| Student > Bachelor | 4 | 7% |
| Other | 12 | 20% |
| Unknown | 11 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 25% |
| Biochemistry, Genetics and Molecular Biology | 14 | 24% |
| Neuroscience | 4 | 7% |
| Agricultural and Biological Sciences | 4 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Other | 7 | 12% |
| Unknown | 13 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 18 March 2017.
All research outputs
#14,060,729
of 23,305,591 outputs
Outputs from Molecular Cancer
#886
of 1,757 outputs
Outputs of similar age
#166,252
of 309,046 outputs
Outputs of similar age from Molecular Cancer
#19
of 47 outputs
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