ERβ Sensitizes Breast Cancer Cells to Retinoic Acid: Evidence of Transcriptional Crosstalk
Bibliographic record
Abstract
Abstract The ability of retinoids to inhibit breast cancer cell growth correlates with estrogen receptor (ER) α status, as shown by the antiproliferative effects of retinoids in ERα-positive breast cancer cells and their use as chemopreventive agents in premenopausal women. The discovery of ERβ, also present in breast cancer cells, has added a new level of complexity to this malignancy. To determine the retinoid response in ERβ-expressing breast cancer cells, we used retroviral transduction of ERβ in ER-negative MDA-MB-231 cells. Western blot and immunofluorescence confirmed expression and nuclear localization of ERβ, whereas functionality was shown using an estrogen response element–containing reporter. A significant retinoic acid (RA)–mediated growth inhibition was observed in the transduced ERβ-positive cells as shown by proliferation assays. Addition of estradiol, tamoxifen, or ICI 182,780 had no effect on cell growth and did not alter RA sensitivity. We observed that retinoids altered ERβ-mediated transcriptional activity from an estrogen response element, which was confirmed by decreased expression of the pS2 gene, and from an activator protein response element. Conversely, the expression of ERβ altered RA receptor (RAR) β expression, resulting in greater induction of RARβ gene expression on RA treatment, without altered expression of RARα. Our data provide evidence of transcriptional crosstalk between ERβ and RAR in ERβ-positive breast cancer cells that are growth inhibited by RA.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".