Genetic variants and haplotype analyses of the <i>ZBRK1/ZNF350</i> gene in high‐risk non BRCA1/2 French Canadian breast and ovarian cancer families
Bibliographic record
Abstract
Our current understanding of breast cancer susceptibility involves mutations in the 2 major genes BRCA1 and BRCA2, found in about 25% of high-risk families, as well as few other low penetrance genes such as ATM and CHEK2. Approximately two-thirds of the multiple cases families remain to be explained by mutations in still unknown genes. In a candidate gene approach to identify new genes potentially involved in breast cancer susceptibility, we analyzed genomic variants in the ZBRK1 gene, a co-repressor implicated in BRCA1-mediated repression of GADD45. Direct sequencing of ZBRK1 entire coding region in affected breast cancer individuals from 97 high-risk French Canadian breast/ovarian cancer families and 94 healthy controls led to the identification of 18 genomic variants. Haplotype analyses, using PHASE, COCAPHASE and HaploStats programs, put in evidence 3 specific haplotypes which could potentially modulate breast cancer risk, and among which 2 that are associated with a potential protective effect (p = 0.01135 and p = 0.00268), while another haplotype is over-represented in the case group (p = 0.00143). Further analyses of these haplotypes indicated that a strong component of the observed difference between both groups emerge from the first 5 variants (out of 12 used for haplotype determination). The present study also permitted to determine a set of tagging SNPs that could be useful for subsequent analyses in large scale association studies. Additional studies in large cohorts and other populations will however be needed to further evaluate if common and/or rare ZBRK1 sequence variants and haplotypes could be associated with a modest/intermediate breast cancer risk.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".