Mutation analysis of RAD51D in non-BRCA1/2 ovarian and breast cancer families
Bibliographic record
Abstract
BACKGROUND: Recent data show that mutations in RAD51D have an aetiological role in ovarian carcinoma, yet mutations do not appear to be associated with an increased risk for breast cancer. We studied ovarian and breast cancer families having at least one woman affected by ovarian carcinoma, to assess the importance of RAD51D mutations in such families. METHODS: The coding region of the RAD51D gene was analysed in 175 BRCA1/2-negative families with family histories of both ovarian and breast cancer ascertained from two Canadian and two Belgian institutions. RESULTS: We identified one previously reported deleterious mutation, p.Arg186(*) (c.556C>T), and two novel variants; missense substitution p.Cys119Arg and an intronic variant c.83-26A>G. p.Arg186(*) segregated with the disease in the family and two ovarian carcinomas available for analysis showed loss of the wild-type allele, but the novel variants are likely neutral. CONCLUSION: RAD51D should be included in genetic screening of ovarian cancer families that do not have BRCA1/BRCA2 mutations. We show that mutations are more likely to be found in families with two or more ovarian cancers, or in probands with first-degree relatives with ovarian cancer, and we feel testing should be preferentially offered to affected women from such families.
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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 | 0.001 | 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) | 0.002 | 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".