Association of the Variants<i>CASP8</i>D302H and<i>CASP10</i>V410I with Breast and Ovarian Cancer Risk in<i>BRCA1</i>and<i>BRCA2</i>Mutation Carriers
Bibliographic record
Abstract
BACKGROUND: The genes caspase-8 (CASP8) and caspase-10 (CASP10) functionally cooperate and play a key role in the initiation of apoptosis. Suppression of apoptosis is one of the major mechanisms underlying the origin and progression of cancer. Previous case-control studies have indicated that the polymorphisms CASP8 D302H and CASP10 V410I are associated with a reduced risk of breast cancer in the general population. METHODS: To evaluate whether the CASP8 D302H (CASP10 V410I) polymorphisms modify breast or ovarian cancer risk in BRCA1 and BRCA2 mutation carriers, we analyzed 7,353 (7,227) subjects of white European origin provided by 19 (18) study groups that participate in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). A weighted cohort approach was used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI). RESULTS: The minor allele of CASP8 D302H was significantly associated with a reduced risk of breast cancer (per-allele HR, 0.85; 95% CI, 0.76-0.97; P(trend) = 0.011) and ovarian cancer (per-allele HR, 0.69; 95% CI, 0.53-0.89; P(trend) = 0.004) for BRCA1 but not for BRCA2 mutation carriers. The CASP10 V410I polymorphism was not associated with breast or ovarian cancer risk for BRCA1 or BRCA2 mutation carriers. CONCLUSIONS: CASP8 D302H decreases breast and ovarian cancer risk for BRCA1 mutation carriers but not for BRCA2 mutation carriers. IMPACT: The combined application of these and other recently identified genetic risk modifiers could in the future allow better individual risk calculation and could aid in the individualized counseling and decision making with respect to preventive options in BRCA1 mutation carriers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".