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Associations between non-coding RNAs genetic polymorphisms with ovarian cancer risk: A systematic review and meta-analysis update with trial sequential analysis
被引:3
作者:
Liu, Huaying
[1
]
Sun, Lili
[2
]
Liu, Xiaoping
[3
]
Wang, Ruichai
[3
]
Luo, Qinqin
[1
]
机构:
[1] Wuhan 1 Hosp, Dept Tradit Chinese Med, Wuhan 430022, Peoples R China
[2] Wuhan Univ, Zhongnan Hosp, Dept Gynaecol Oncol, Wuhan, Peoples R China
[3] Cent Hosp Xianning, Dept Geriatr, Xianning, Peoples R China
来源:
关键词:
gene polymorphism;
meta-analysis;
non-coding RNAs;
ovarian cancer risk;
BREAST-CANCER;
LUNG-CANCER;
H19;
GENE;
SUSCEPTIBILITY;
SNP;
BINDING;
PROGNOSIS;
MODIFIERS;
RS920778;
MIR-146A;
D O I:
10.1097/MD.0000000000035257
中图分类号:
R5 [内科学];
学科分类号:
1002 ;
100201 ;
摘要:
Background: This systemic review and meta-analysis seeks to systematically analyze and summarize the association between non-coding RNA polymorphisms and ovarian cancer risk.Methods: We searched PubMed, Web of Science and CNKI for available articles on non-coding RNA polymorphisms in patients with ovarian cancer from inception to March 1, 2023. The quality of each study included in the meta-analysis was rated according to the Newcastle-Ottawa Scale. Odds ratios (ORs) with their 95% confidence intervals (95% CI) were used to assess associations. Chi-square Q-test combined with inconsistency index (I2) was used to test for heterogeneity among studies. Lastly, trial sequential analysis (TSA) software was used to verify the reliability of meta-analysis results, and in-silico miRNA expression were also performed. The meta-analysis was registered with PROSPERO (No. CRD42023422091).Methods: We searched PubMed, Web of Science and CNKI for available articles on non-coding RNA polymorphisms in patients with ovarian cancer from inception to March 1, 2023. The quality of each study included in the meta-analysis was rated according to the Newcastle-Ottawa Scale. Odds ratios (ORs) with their 95% confidence intervals (95% CI) were used to assess associations. Chi-square Q-test combined with inconsistency index (I2) was used to test for heterogeneity among studies. Lastly, trial sequential analysis (TSA) software was used to verify the reliability of meta-analysis results, and in-silico miRNA expression were also performed. The meta-analysis was registered with PROSPERO (No. CRD42023422091).Results: A total of 17 case-control studies with 18 SNPs were selected, including 2 studies with H19 rs2107425 and HOTAIR rs4759314, and 5 studies with miR-146a rs2910164 and miR-196a rs11614913. Significant associations were found between H19 rs2107425, miR-146a rs2910164, and miR-196a rs11614913 and ovarian cancer risk. Three genetic models of H19 rs2107425 (CT vs TT (heterozygote model): OR = 1.36, 95% CI = 1.22-1.52, P < .00001; CC + CT vs TT (dominant model): OR = 1.12, 95% CI = 1.02-1.24, P = .02; and CC vs CT + TT (recessive model): OR = 1.23, 95% CI = 1.16-1.31, P < .00001), 2 genetic models of miR-146a rs2910164 (allele model: OR = 1.75, 95% CI = 1.05-2.91, P = .03; and heterozygote model: OR = 0.33, 95% CI = 0.11-0.98, P = .05), 3 genetic models of miR-196a rs11614913 (allele model: OR = 0.70, 95% CI = 0.59-0.82, P < .0001; dominant model: OR = 1.62, 95% CI = 1.18-2.24, P = .0001; and recessive model: OR = 0.70, 95% CI = 0.57-0.87, P = .03) were statistically linked to ovarian cancer risk. Subgroup analysis for miR-146a rs2910164 was performed according to ethnicity. No association was found in any genetic model. The outcomes of TSA also validated the findings of this meta-analysis.Conclusion: This study summarizes that H19 rs2107425, miR-146a rs2910164, and miR-196a rs11614913 polymorphisms are significantly linked with the risk of ovarian cancer, and moreover, large-scale and well-designed studies are needed to validate our result.
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