Promoter Methylation of E-Cadherin, p16, and RAR-β<sub>2</sub>Genes in Breast Tumors and Dietary Intake of Nutrients Important in One-Carbon Metabolism
Bibliographic record
Abstract
Aberrant DNA methylation plays a critical role in carcinogenesis, and the availability of dietary factors involved in 1-carbon metabolism may contribute to aberrant DNA methylation. We investigated the association of intake of folate, vitamins B(2), B(6), B(12), and methionine with promoter methylation of E-cadherin, p16, and RAR-β(2) genes in archived tumor tissues from incident, primary breast cancer cases in a population-based case-control study. Real-time methylation-specific PCR was performed on 803 paraffin-embedded samples; usual dietary intake was queried from a food frequency questionnaire. Unconditional logistic regression was used to derive adjusted odds ratios and 95% confidence intervals for likelihood of promoter methylation for high compared to low intake of those 1-carbon nutrients. Overall, in case-case comparisons, dietary intakes of folate, vitamins B(2), B(6), B(12), and methionine were not associated with likelihood of promoter methylation of E- cadherin, p16, and RAR-β(2) for all cases combined or within strata defined by menopausal status and estrogen receptor status in this study. This finding, however, does not exclude the possibility that intake of such nutrients might have the ability to modulate promoter methylation in normal or premalignant (dysplastic) breast tissue.
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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 | 0.000 | 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".