Polymorphisms XRCC1-<i>R399Q</i> and XRCC3-<i>T241M</i> and the Risk of Breast Cancer at the Ontario Site of the Breast Cancer Family Registry
Bibliographic record
Abstract
This study investigates the role of two nonsynonymous single nucleotide polymorphisms in DNA repair genes, X-ray repair cross-complementing group 1 (XRCC1)-R399Q and X-ray repair cross-complementing group 3 (XRCC3)-T241M, in breast cancer. Incident cases of invasive breast cancer in Caucasian women [n = 402, mean age = 45.7 (SD = 6.2) years] and female Caucasian controls [n = 402, mean age = 45.2 (6.5) years] frequency matched on 5-year age intervals were identified from the Ontario Familial Breast Cancer Registry. No evidence for a main effect of the XRCC1-R399Q genotype on breast cancer risk was observed. Estimates of risk for a family history (FH) of breast cancer compared with no FH differed by XRCC1-R399Q genotype (P value for interaction = 0.001). Homozygote XRCC1-399 R/R individuals and FH+ were at a 2.92-fold [95% confidence interval (95% CI) = 1.47-5.79] increased risk of disease compared with FH- individuals; the estimate of risk increased for R/Q heterozygotes with FH+ [odds ratio (OR) = 3.85, 95% CI = 1.94-7.65] but not for Q/Q homozygotes with FH+ (OR = 0.54, 95% CI = 0.20-1.47) compared with homozygous R/R and FH- individuals. A marginal positive association for XRCC3-241 M/M compared with T/T genotype was found (OR = 1.44, 95% CI = 0.94-2.19), but the heterozygous T/M was not associated with an increase in risk (OR = 0.96, 95% CI = 0.71-1.32). There was also some evidence for a combined effect of body mass index and XRCC3-T241M on estimates of risk. Our results suggest that these polymorphisms may influence breast cancer risk by modifying the effect of risk factors such as FH. There is a need for further study into the role of these polymorphisms as effect modifiers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".