Abstract 1865: <i>ERCC2</i> polymorphisms, smoking, and risk of breast cancer
Bibliographic record
Abstract
Abstract The nucleotide excision repair (NER) pathway is important in the repair of bulky DNA lesions, including those that may be induced by cigarette smoking. Excision Repair Cross-Complementing Rodent Repair Deficiency, Complementation Group 2 (ERCC2) is an important gene in the NER pathway. Previous research suggests that polymorphisms in this gene may be associated with altered DNA repair capacity, cancer risk and treatment outcome. This study investigated whether two common single nucleotide polymorphisms (SNPs) in ERCC2 (ERCC2 Asp312Gln and ERCC2 Lys751Gln) were associated with risk of breast cancer, or modified a breast cancer risk associated with smoking. We used data previously collected from a primarily Caucasian population in northeastern Ontario Canada of 347 women diagnosed (2002-2004) with breast cancer and 775 population-based controls. The mailed study package contained a questionnaire that provided information on known breast cancer risk factors and lifetime residential and occupational history of exposure to passive and active smoking, and a buccal swab for genetic analyses. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using unconditional logistic regression, and used a refined referent group that excluded women with substantial exposure to passive smoke and who were never active smokers. Both SNPs were in Hardy-Weinburg Equilibrium (HWE) in controls. Overall, there was no significant association with either SNP and risk of breast cancer. Women who were active smokers of long duration (> 29 years), or high (>20) pack-years, were at significantly increased risk of breast cancer if they carried the G allele of ERCC2Asp312Gln, with ORs of 1.72 (95% CI 1.10-2.68) and 1.68 (95% CI 1.09-2.61) and p=0.03 and 0.007 for trend, respectively. Similar significantly increased risks were observed in women who carried the A allele of ERCC2 Lys751Gln, with ORs of 1.77 (95% CI 1.14-2.76) and 1.67 (95% CI 1.08-2.58) and p=0.02 and 0.01 for trend, respectively. In conclusion, our data suggest that polymorphisms in the NER pathway may modify a smoking-breast cancer relationship. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1865.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".