| Title |
Genetic association between HER2 and ESR2 polymorphisms and ovarian cancer: a meta-analysis
|
|---|---|
| Published in |
OncoTargets and therapy, March 2018
|
| DOI | 10.2147/ott.s149428 |
| Pubmed ID | |
| Authors |
Liang Tang, Jianming Li, Meihua Bao, Ju Xiang, Yiwei Chen, Yan Wang |
| Abstract |
The estrogen receptor (ER) and the human epidermal growth factor receptor 2 (HER2) each play an important role in female cancers. This study aimed to investigate the genetic association between three common single nucleotide polymorphisms (SNPs) and the risk of ovarian cancer. The SNPs investigated in this study were ESR2 rs1271572 and rs3020450 and HER2 rs1801200. In this study, databases were electronically searched in a meta-analysis. Databases used were PubMed, Embase, China National Knowledge Infrastructure (CNKI), Wanfang and Cochrane library. Case-control studies on the association between ESR2 and HER2 polymorphisms were selected according to inclusion and exclusion standard. Articles were evaluated for quality, and data were extracted. A total of 13 articles with 5,461 cases and 7,603 controls were included in this meta-analysis. The recessive model of ESR2 rs1271572 was shown to be significantly associated with the risk of ovarian cancer (p= 0.008, odds ratio [OR] [95% confidence interval {CI}] = 1.13 [1.03, 1.24]), and this significant association still existed in a subgroup analysis stratified by ethnicity (Asian:p= 0.04, OR [95% CI] = 1.92 [1.04, 3.56]; Caucasian:p= 0.02, OR [95% CI] = 1.12 [1.02, 1.23]). In addition, the distribution of the dominant model of ESR2 rs3020450 was significantly different in the total group (p= 0.02, OR [95% CI] = 0.71 [0.53, 0.95]) and the Caucasian subgroup (p= 0.02, OR [95% CI] = 0.67 [0.48, 0.94]). Furthermore, no significant association between allelic, dominant, codominant and recessive models of HER2 rs1801200 (V655I) and ovarian cancer was found (p> 0.05). The recessive model of ESR2 rs1271572 and the dominant model of ESR2 rs3020450 might be susceptible factors for ovarian cancer. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 23% |
| Researcher | 3 | 23% |
| Student > Ph. D. Student | 1 | 8% |
| Unspecified | 1 | 8% |
| Lecturer | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 31% |
| Engineering | 2 | 15% |
| Economics, Econometrics and Finance | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Unspecified | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 4 | 31% |
Attention Score in Context
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Outputs from OncoTargets and therapy
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