Polymorphisms of the centrosomal gene (<i>FGFR1OP</i>) and lung cancer risk: a meta-analysis of 14 463 cases and 44 188 controls
Bibliographic record
Abstract
Centrosome abnormalities are often observed in premalignant lesions and in situ tumors and have been associated with aneuploidy and tumor development. We investigated the associations of 9354 single-nucleotide polymorphisms (SNPs) in 106 centrosomal genes with lung cancer risk by first using the summary data from six published genome-wide association studies (GWASs) of the Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16 838 controls) and then conducted in silico replication in two additional independent lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26,380 controls). A total of 44 significant SNPs with false discovery rate (FDR) ≤ 0.05 were mapped to one novel gene FGFR1OP and two previously reported genes (TUBB and BRCA2). After combined the results from TRICL with those from Harvard and deCODE, the most significant association (P combined = 8.032 × 10(-6)) was with rs151606 within FGFR1OP. The rs151606 T>G was associated with an increased risk of lung cancer [odds ratio (OR) = 1.10, 95% confidence interval (95% CI) = 1.05-1.14]. Another significant tagSNP rs12212247 T>C (P combined = 9.589 × 10(-6)) was associated with a decreased risk of lung cancer (OR = 0.93, 95% CI = 0.90-0.96). Further in silico functional analyzes revealed that rs151606 might affect transcriptional regulation and result in decreased FGFR1OP expression (P trend = 0.022). The findings shed some new light on the role of centrosome abnormalities in the susceptibility to lung carcinogenesis.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".