Absence of CCND1 gene amplification in breast tumours of BRCA1 mutation carriers
Bibliographic record
Abstract
BACKGROUND/AIMS: It was recently reported that significantly fewer breast tumours of BRCA1 mutation carriers overexpressed cyclin D1 and HER2 protein than tumours of age matched breast cancer cases unselected for family history. This study aimed to examine the genetic basis of this reduction by determining the frequency of tumours within this cohort showing DNA amplification of these genes. METHODS: Paraffin wax embedded sections of breast tumours from BRCA1 mutation carriers and age, grade, histological type, and tumour size matched non-familial controls that had previously been stained for cyclin D1 and HER2 protein overexpression were analysed for CCND1 and HER2 gene amplification using fluorescence in situ hybridisation. RESULTS: CCND1 amplification was detected in none of the 30 tumours of the BRCA1 mutation carriers and in 19 of 74 tumours of the matched controls. Of those samples previously determined to overexpress the HER2 protein, HER2 amplification was detected in one of three tumours from BRCA1 mutation carriers and in 13 of 17 tumours of the age matched non-familial cases. CONCLUSION: None of the tumours of BRCA1 mutation carriers showed CCND1 amplification and only one tumour showed HER2 amplification. In contrast, a large proportion of cyclin D1 and HER2 overexpression in tumours of non-familial breast cancer cases could be accounted for by amplification of these genes. These data suggest that breast tumorigenesis in BRCA1 mutation carriers occurs by a molecular mechanism distinct from that of age matched non-familial cases.
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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 | 0.001 | 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) | 0.002 | 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".