Genetic susceptibility to breast cancer in French-Canadians: Role of carcinogen-metabolizing enzymes and gene-environment interactions
Bibliographic record
Abstract
Breast cancer is the most frequent malignancy among women. Since genetic factors such as BRCA1 and BRCA2 as well as reproductive history constitute only 30% of the cause, environmental exposure may play a significant role in the development of breast cancer. Likewise, the relevant enzymes involved in the biotransformation of xenobiotics (from tobacco smoke, diet or other environmental sources) might play a role in breast carcinogenesis. Since individuals with modified ability to metabolize these carcinogens could have a different risk for breast cancer, we investigated the role of cytochromes P-450 (CYP1A1, CYP2D6), glutathione-S-transferases (GSTM1, GSTT1, GSTP1) and N-acetyltransferases (NAT1, NAT2) gene variants in breast carcinogenesis. A case-control study was conducted on 149 women with breast carcinoma and 207 healthy controls, both of French-Canadian origin. The CYP1A1*4 allele was found to be a significant risk determinant of breast carcinoma (OR = 3.3, 95% CI 1.1-9.7), particularly among post-menopausal women (OR = 4.0, 95% CI 1.2-13.8). The frequency of NAT2 rapid acetylators was increased among smokers (OR = 2.6, 95% CI 0.8-8.2), while the NAT1*10 allele conferred a 4-fold increase in risk among women who consumed well-done meat (OR = 4.4, 95% CI 1.0-18.9). These data suggest that CYP1A1*4, NAT1 and NAT2 variants are involved in the susceptibility to breast carcinoma by modifying the impact of exogenous and/or endogenous exposures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".