Lung cancer and DNA repair genes: multilevel association analysis from the International Lung Cancer Consortium
Bibliographic record
Abstract
Lung cancer (LC) is the leading cause of cancer-related death worldwide and tobacco smoking is the major associated risk factor. DNA repair is an important process, maintaining genome integrity and polymorphisms in DNA repair genes may contribute to susceptibility to LC. To explore the role of DNA repair genes in LC, we conducted a multilevel association study with 1655 single nucleotide polymorphisms (SNPs) in 211 DNA repair genes using 6911 individuals pooled from four genome-wide case-control studies. Single SNP association corroborates previous reports of association with rs3131379, located on the gene MSH5 (P = 3.57 × 10-5) and returns a similar risk estimate. The effect of this SNP is modulated by histological subtype. On the log-additive scale, the odds ratio per allele is 1.04 (0.84-1.30) for adenocarcinomas, 1.52 (1.28-1.80) for squamous cell carcinomas and 1.31 (1.09-1.57) for other histologies (heterogeneity test: P = 9.1 × 10(-)(3)). Gene-based association analysis identifies three repair genes associated with LC (P < 0.01): UBE2N, structural maintenance of chromosomes 1L2 and POLB. Two additional genes (RAD52 and POLN) are borderline significant. Pathway-based association analysis identifies five repair pathways associated with LC (P < 0.01): chromatin structure, DNA polymerases, homologous recombination, genes involved in human diseases with sensitivity to DNA-damaging agents and Rad6 pathway and ubiquitination. This first international pooled analysis of a large dataset unravels the role of specific DNA repair pathways in LC and highlights the importance of accounting for gene and pathway effects when studying LC.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".