Analysis of <i>PALB2</i> / <i>FANCN</i> -associated breast cancer families
Bibliographic record
Abstract
No more than approximately 30% of hereditary breast cancer has been accounted for by mutations in known genes. Most of these genes, such as BRCA1, BRCA2, TP53, CHEK2, ATM, and FANCJ/BRIP1, function in DNA repair, raising the possibility that germ line mutations in other genes that contribute to this process also predispose to breast cancer. Given its close relationship with BRCA2, PALB2 was sequenced in affected probands from 68 BRCA1/BRCA2-negative breast cancer families of Ashkenazi Jewish, French Canadian, or mixed ethnic descent. The average BRCAPRO score was 0.58. A truncating mutation (229delT) was identified in one family with a strong history of breast cancer (seven breast cancers in three female mutation carriers). This mutation and its associated breast cancers were characterized with another recently reported but unstudied mutation (2521delA) that is also associated with a strong family history of breast cancer. There was no loss of heterozygosity in tumors with either mutation. Moreover, comparative genomic hybridization analysis showed major similarities to that of BRCA2 tumors but with some notable differences, especially loss of 18q, a change that was previously unknown in BRCA2 tumors and less common in sporadic breast cancer. This study supports recent observations that PALB2 mutations are present, albeit not frequently, in breast cancer families. The apparently high penetrance noted in this study suggests that at least some PALB2 mutations are associated with a substantially increased risk for the disease.
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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) | 0.001 | 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".