BRCA1 Promoter Hypermethylation in Malignant Breast Tumors and in the Histologically Normal Adjacent Tissues to the Tumors: Exploring Its Potential as a Biomarker and Its Clinical Significance in a Translational Approach
Bibliographic record
Abstract
The hypermethylation status of the promoter region of the breast cancer 1 (BRCA1), a well-known tumor suppressor gene, has been extensively investigated in the last two decades as a potential biomarker for breast cancer. In this retrospective study, we investigated the prevalence of BRCA1 promoter methylation in 84 human breast tissues, and we correlated this epigenetic silencing with the clinical and histopathological parameters of breast cancer. We used methylation-specific PCR (MSP) to analyze BRCA1 promoter hypermethylation in 48 malignant breast tumors (MBTs), 15 normal adjacent tissues (NATs), and 21 benign breast lesions (BBLs). The results showed that BRCA1 promoter hypermethylation was higher in MBTs (20/48; 41.67%) and NATs (7/15; 46.67%) compared to BBLs (4/21; 19.05%). The high percentage of BRCA1 hypermethylation in the histologically normal adjacent tissues to the tumors (NATs) suggests the involvement of this epigenetic silencing as a potential biomarker of the early genomic instability in NATs surrounding the tumors. The detection of BRCA1 promoter hypermethylation in BBLs reinforces this suggestion, knowing that a non-negligible rate of benign breast lesions was reported to evolve into cancer. Moreover, our results indicated that the BRCA1 promoter hypermethylated group of MBTs exhibited higher rates of aggressive features, as indicated by the SBR III grade (14/19; 73.68%), elevated Ki67 levels (13/16; 81.25%), and Her2 receptor overexpression (5/20; 25%). Finally, we observed a concordance (60%) in BRCA1 promoter hypermethylation status between malignant breast tumors and their paired histologically normal adjacent tissues. This study highlights the role of BRCA1 promoter hypermethylation as a potential useful biomarker of aggressiveness in MBTs and as an early marker of genomic instability in both histological NATs and BBLs.
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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 | 0.001 | 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".