Estrogen Receptor β2 Negatively Regulates the Transactivation of Estrogen Receptor α in Human Breast Cancer Cells
Bibliographic record
Abstract
Estrogens, by binding to and activating two estrogen receptors (ERalpha and ERbeta), are critically involved in the development of the mammary gland and breast cancer. An isoform of ERbeta, ERbeta2 (also called ERbetacx), with an altered COOH-terminal region, is coexpressed with ERalpha in many human breast cancers. In this study, we generated a stable cell line from MCF7 breast cancer cells expressing an inducible version of ERbeta2, along with endogenous ERalpha, and examined the effects of ERbeta2 on the ERalpha protein levels and function. We showed that ERbeta2 inhibited ERalpha-mediated transactivation via estrogen response element and activator protein-1 sites of reporter constructs as well as the endogenous genes pS2 and MMP-1. Chromatin immunoprecipitation assays revealed that ERbeta2 expression caused a significant reduction in the recruitment of ERalpha to both the pS2 and MMP-1 promoters. Furthermore, ERbeta2 expression induced proteasome-dependent degradation of ERalpha. The inhibitory effects of ERbeta2 on ERalpha activity were further confirmed in HEK293 cells that lack functional endogenous ERs. We also showed that ERbeta2 can interact with ERalpha both in vitro and in mammalian cells, which is compatible with a model where ERbeta2/ERalpha heterodimers are targeted to the proteasome. Finally, in human breast cancer samples, we observed that expression of ERbeta2 significantly correlated with ERalpha-negative phenotype. Our data suggest that ERbeta2 could influence ERalpha-mediated effects relevant for breast cancer development, including hormone responsiveness.
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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 | 0.000 | 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".