Susceptibility loci of <i>CNOT6</i> in the general mRNA degradation pathway and lung cancer risk—A re‐analysis of eight GWASs
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Bibliographic record
Abstract
PURPOSE: mRNA degradation is an important regulatory step for controlling gene expression and cell functions. Genetic abnormalities involved in mRNA degradation genes were found to be associated with cancer risks. Therefore, we systematically investigated the roles of genetic variants in the general mRNA degradation pathway in lung cancer risk. EXPERIMENTAL DESIGN: Meta-analyses were conducted using summary data from six lung cancer genome-wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung and additional two GWASs from Harvard University and deCODE in the International Lung Cancer Consortium. Expression quantitative trait loci analysis (eQTL) was used for in silico functional validation of the identified significant susceptibility loci. RESULTS: This pathway-based analysis included 6816 single nucleotide polymorphisms (SNP) in 68 genes in 14 463 lung cancer cases and 44 188 controls. In the single-locus analysis, we found that 20 SNPs were associated with lung cancer risk with a false discovery rate threshold of <0.05. Among the 11 newly identified SNPs in CNOT6, which were in high linkage disequilibrium, the rs2453176 with a RegulomDB score "1f" was chosen as the tagSNP for further analysis. We found that the rs2453176 T allele was significantly associated with lung cancer risk (odds ratio = 1.11, 95% confidence interval = 1.04-1.18) in the eight GWASs. In the eQTL analysis, we found that levels of CNOT6 mRNA expression were significantly correlated with the rs2453176 T allele, which provided additional biological basis for the observed positive association. CONCLUSION: The CNOT6 rs2453176 SNP may be a new functional susceptible locus for lung cancer risk. © 2016 Wiley Periodicals, Inc.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it