Associations between non-coding RNAs genetic polymorphisms with ovarian cancer risk: A systematic review and meta-analysis update with trial sequential analysis
Bibliographic record
Abstract
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). 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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.074 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".