No Evidence of <i>BRCA1/2</i> Genomic Rearrangements in High-Risk French-Canadian Breast/Ovarian Cancer Families
Bibliographic record
Abstract
The discovery of deleterious mutations in the breast and ovarian cancer susceptibility genes, BRCA1 and BRCA2, has facilitated the identification of individuals at particularly high risk of these diseases. There is a wide variation between populations in the prevalence and related risks of various types of BRCA1/2 mutations, so estimates cannot be extrapolated to Canadians, especially not founder populations such as French- Canadians. Polymerase chain reaction (PCR)-based methods were used to detect the majority of these mutations. These approaches usually failed to detect large DNA rearrangements, which have been claimed to be involved in other populations in 5% to up to 36% of BRCA1-positive families. There is very little information about the contribution of this type of mutation in BRCA2-positive families. To investigate if our available mutation spectrum of BRCA1 and BRCA2 in high-risk French-Canadian breast/ovarian cancer families has been biased by PCR-based direct sequencing methods, we first used Southern blot analysis to test DNA samples from 61 affected/obligate carrier individuals from 58 families in which no BRCA1/2 deleterious mutation was found. Finally, 154 individuals from 135 BRCA1/2 nonconclusive families, including all those tested previously by Southern blot analysis, were tested with the new multiplex ligation probe amplification (MLPA) technique. These approaches failed to detect any rearrangement. Moreover, if the frequency of MLPA-detectable rearrangements in our cohort of 135 BRCA1/2 nonconclusive families was 2.2% or higher, we would have had a 95% or greater chance of observing at least one such rearrangement. As no rearrangements were identified, such large rearrangements must be quite rare in our 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".