A Systematic Study of the Impact of Estrogens and Selective Estrogen Receptor Modulators on Prostate Cancer Cell Proliferation
Bibliographic record
Abstract
The estrogen signaling pathway has been reported to modulate prostate cancer (PCa) progression through the activity of estrogen receptors α and β (ERα and ERβ). Given that selective estrogen receptor modulators (SERMs) are used to treat breast cancer, ERs have been proposed as attractive therapeutic targets in PCa. However, many inconsistencies regarding the expression of ERs and the efficacy of SERMs for PCa treatment exist, notably due to the use of ERβ antibodies lacking specificity and treatments with high SERM concentrations leading to off-target effects. To end this confusion, our objective was to study the impact of estrogenic and anti-estrogenic ligands in well-studied in vitro PCa models with appropriate controls, dosages, and ER subtype-specific antibodies. When using physiologically relevant concentrations of nine estrogenic/anti-estrogenic compounds, including five SERMs, we observed no significant modulation of PCa cell proliferation. Using RNA-seq and validated antibodies, we demonstrate that these PCa models do not express ERs. In contrast, RNA-seq from PCa samples from patients have detectable expression of ERα. Overall, our study reveals that commonly used PCa models are inappropriate to study ERs and indicate that usage of alternative models is essential to properly assess the roles of the estrogen signaling pathway in PCa.
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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".