The spectrum of mutations predisposing to familial breast cancer in Poland
Bibliographic record
Abstract
To optimize genetic testing, it is necessary to establish the spectrum of breast cancer-predisposing mutations in particular ethnic groups. We studied 1,018 women with a strong family history for breast cancer (families with hereditary breast cancer; HBC) from genetically homogenous population of Poland, which is populated by ethnic Slavs, for mutations in 14 cancer susceptibility genes. Additionally, we compared the frequency of candidate pathogenic variants in breast cancer cases and controls. Germline mutations were detected in 512 of 1,018 probands with breast cancer (50.3%), including BRCA1/2 mutations detected in 420 families and non-BRCA mutations seen in 92 families. Thirteen BRCA1/2 founder mutations represented 84% of all BRCA1/2-positive cases. Seven founder mutations of CHEK2, PALB2, NBN and RECQL represented 73% of all non-BRCA-positive cases. Odds ratios for hereditary breast cancer were 87.6 for BRCA1, 15.4 for PALB2, 7.2 for CHEK2, 2.8 for NBN and 15.8 for RECQL. Odds ratios for XRCC2, BLM and BARD1 were below 1.3. In summary, we found that 20 founder mutations in six genes (BRCA1/2, CHEK2, PALB2, NBN and RECQL) are responsible for 82% of Polish hereditary breast cancer families. A simple test for these 20 mutations will facilitate genetic testing for breast cancer susceptibility in Poland. It may also facilitate genetic testing for breast cancer susceptibility in other Slavic populations and women of Slavic descent worldwide.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".