Constitutional CHEK2 mutations are associated with a decreased risk of lung and laryngeal cancers
Bibliographic record
Abstract
Mutations in the CHEK2 gene have been associated with increased risks of breast, prostate and colon cancer. In contrast, a previous report suggests that individuals with the I157T missense variant of the CHEK2 gene might be at decreased risk of lung cancer and upper aero-digestive cancers. To confirm this hypothesis, we genotyped 895 cases of lung cancer, 430 cases of laryngeal cancer and 6391 controls from Poland for four founder alleles in the CHEK2 gene, each of which has been associated with an increased risk of cancer at several sites. The presence of a CHEK2 mutation was protective against both lung cancer [odds ratio (OR) = 0.3; 95% confidence interval (CI) 0.2-0.5; P = 3 x 10(-8)] and laryngeal cancer (OR = 0.6; 95% CI 0.3-0.99; P = 0.05). The basis of the protective effect is unknown, but may relate to the reduced viability of lung cancer cells with a CHEK2 mutation. Lung cancers frequently possess other defects in genes in the DNA damage response pathway (e.g. p53 mutations) and have a high level of genotoxic DNA damage induced by tobacco smoke. We speculate that lung cancer cells with impaired CHEK2 function undergo increased rates of cell death.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".