Germline BRCA1/2 Variants in Polish Patients with Family History of Breast and Ovarian Cancer: Prevalence, CNV Detection, and Identification of a Novel Loss-of-Function Mutation
Bibliographic record
Abstract
Background/Objectives: Pathogenic and likely pathogenic variants in the BRCA1 and BRCA2 genes are associated with a significantly increased risk of breast and/or ovarian cancer. We investigated genetic variants in a cohort of 450 unaffected individuals with a family history of breast and/or ovarian cancer, involving at least one first-degree relative. Methods: Next-generation sequencing (NGS) was used to analyze the coding regions of these two genes, with copy number variation (CNV) analysis. Results: A total of 16 unique to our cohort variants classified as pathogenic or likely pathogenic were identified in 22 patients, including one novel loss-of-function variant in BRCA1 gene. Furthermore, we identified a deletion of exon 21 in the BRCA1 gene in two patients. Conclusions: These results emphasize the difficulties involved in molecular diagnostics and indicate the need for further research into new predictive models for patients with hereditary breast and ovarian cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.002 | 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".