A single-nucleotide polymorphism in the RAD51 gene modifies breast cancer risk in BRCA2 carriers, but not in BRCA1 carriers or noncarriers
Bibliographic record
Abstract
Variation in the penetrance estimates for BRCA1 and BRCA2 mutation carriers suggests that other genetic polymorphisms may modify the cancer risk in carriers. The RAD51 gene, which participates in homologous recombination double-strand breaks (DSB) repair in the same pathway as the BRCA1 and BRCA2 gene products, is a candidate for such an effect. A single-nucleotide polymorphism (SNP), RAD51-135g-->c, in the 5' untranslated region of the gene has been found to elevate breast cancer (BC) risk among BRCA2 carriers. We genotyped 309 BRCA1/2 mutation carriers, of which 280 were of Ashkenazi origin, 166 noncarrier BC patients and 152 women unaffected with BC (a control group), for the RAD51-135g-->c SNP. Risk analyses were conducted using COX proportional hazard models for the BRCA1/2 carriers and simple logistic regression analysis for the noncarrier case-control population. BRCA2 carriers were also studied using logistic regression and Kaplan-Meier survival analyses. The estimated BC hazard ratio (HR) for RAD51-135c carriers adjusted for origin (Ashkenazi vs non-Ashkenazi) was 1.28 (95% CI 0.85-1.90, P=0.23) for BRCA1/2 carriers, and 2.09 (95% CI 1.04-4.18, P=0.04) when the analysis was restricted to BRCA2 carriers. The median BC age was younger in BCRA2-RAD51-135c carriers (45 (95% CI 36-54) vs 52 years (95% CI 48-56), P=0.05). In a logistic regression analysis, the odds ratio (OR) was 5.49 (95% CI 0.5-58.8, P=0.163). In noncarrier BC cases, carrying RAD51-135c was not associated with BC risk (0.97; 95% CI 0.47-2.00). These results indicate significantly elevated risk for BC in carriers of BRCA2 mutations who also carry a RAD51-135c allele. In BRCA1 carriers and noncarriers, no effect for this SNP was found.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".