| Title |
Hepatoma-derived growth factor predicts unfavorable prognosis of epithelial ovarian cancer
|
|---|---|
| Published in |
OncoTargets and therapy, August 2015
|
| DOI | 10.2147/ott.s85660 |
| Pubmed ID | |
| Authors |
Xue-jun Liu, Wen-lian Liu, Fang-mei Yang, Xiao-qing Yang, Xiao-fei Lu |
| Abstract |
To evaluate the expression and clinical significance of hepatoma-derived growth factor (HDGF) in epithelial ovarian cancer (EOC). Recent studies have demonstrated that HDGF overexpression correlates to the progression and poor prognosis in several kinds of cancers. However, the clinical significance and prognostic value of HDGF in EOC have not been investigated. Expression of HDGF was visualized by immunohistology and then the cohort was divided into higher- and lower-expression groups. The correlation between HDGF and clinicopathologic factors was analyzed by χ (2) test. The prognostic value of HDGF was assessed by univariate analysis with Kaplan-Meier method, and by multivariate analysis with Cox-regression model. With experiments in vitro, HDGF expression in ovarian cancer cell lines was detected by immunoblotting. Higher HDGF expression rate was 52.76% in EOC. HDGF expression was significantly associated with lymphatic metastasis (P=0.006). Higher HDGF expression was closely correlated to poorer 5-year overall survival rate with univariate analysis (P=0.003), and was identified as an independent prognostic factor with multivariate analysis (P=0.007). With experiments in vitro, HDGF was proved to exist in all ovarian cancer cell lines with different expression levels. HDGF expression correlates to unfavorable prognosis and can be considered as an independent prognostic factor, indicating that HDGF may be a promising potential molecular drug target. |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 50% |
| Professor > Associate Professor | 1 | 25% |
| Unknown | 1 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 50% |
| Immunology and Microbiology | 1 | 25% |
| Unknown | 1 | 25% |
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 21 August 2015.
All research outputs
#15,344,095
of 22,824,164 outputs
Outputs from OncoTargets and therapy
#1,026
of 2,933 outputs
Outputs of similar age
#154,510
of 264,261 outputs
Outputs of similar age from OncoTargets and therapy
#37
of 96 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,933 research outputs from this source. They receive a mean Attention Score of 2.6. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,261 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.