Significant proportion of breast and/or ovarian cancer families of French Canadian descent harbor 1 of 5 <i>BRCA1</i> and <i>BRCA2</i> mutations
Bibliographic record
Abstract
In 1998, we reported that a significant proportion of breast and/or ovarian cancer families of French Canadian descent harbor specific germline mutations in BRCA1 or BRCA2 attributed to common founders. Here we report the frequency of previously described mutations (n = 7) and 13 mutations identified in French Canadian families since 1998, in a new group of families (n = 88). Four of the previously described mutations, 4446C>T, 2953delGTAinsC, 8765delAG and 6085C>T, account for 72% and 69% of mutation-positive families in previously (n = 81) and recently ascertained groups, respectively. Only 2 of 13 recently identified mutations were found in more than 1 family: 3875delGTCT (n = 2) and 3398delAAAAG (n = 4). The 2 groups (ascertained pre- and post-gene discovery) did not differ significantly when distribution of mutations based on cancer syndrome phenotype and age of diagnosis or number of breast cancer cases were compared. Five common mutations accounted for a significant proportion (84%) of all mutation-positive families. The age of diagnosis of female breast cancer in mutation-negative families was significantly higher than that of the mutation-positive families (p<0.0001). The total number of cases of cancer per family was significantly lower in mutation-negative than mutation-positive families (p<0.001). Our results define a new mutation panel for screening BRCA1/2 mutations and the phenotype of mutation-positive families harboring the common mutations in the French Canadian population.
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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) | 0.003 | 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".