Association of Breast Cancer DNA Methylation Profiles with Hormone Receptor Status and Response to Tamoxifen
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We have generated DNA methylation profiles of 148 human breast tumors and found significant differences in hormone receptor (HR) status between clusters of DNA methylation profiles. Of 35 DNA methylation markers analyzed, the ESR1 gene, encoding estrogen receptor alpha, proved to be the best predictor of progesterone receptor status, whereas methylation of the PGR gene, encoding progesterone receptor, was the best predictor of estrogen receptor status. ESR1 methylation outperformed HR status as a predictor of clinical response in patients treated with the antiestrogen tamoxifen, whereas promoter methylation of the CYP1B1 gene, encoding a tamoxifen- and estradiol-metabolizing cytochrome p450, predicted response differentially in tamoxifen-treated and nontamoxifen-treated patients. High levels of promoter methylation of the ARHI gene, encoding a RAS-related small G-protein, were strongly predictive of good survival in patients who had not received tamoxifen therapy. Our results reveal an as yet unrecognized degree of interaction between DNA methylation and HR biology in breast cancer cells and suggest potentially clinically useful novel DNA methylation predictors of response to hormonal and non-hormonal breast cancer therapy.
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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 it