Synergistic Action of Prolactin (PRL) and Androgen on PRL-Inducible Protein Gene Expression in Human Breast Cancer Cells: A Unique Model for Functional Cooperation between Signal Transducer and Activator of Transcription-5 and Androgen Receptor
Bibliographic record
Abstract
The signal transducer and activator of transcription 5 (Stat5) has been shown to cooperate with some nuclear receptors. However, an interaction has never been demonstrated with the androgen receptor (AR). Given that the PRL-inducible protein/gross cystic disease fluid-15 (PIP/GCDFP-15) is both a PRL-controlled and an androgen-controlled protein, we used its promoter region to investigate the potential interaction between Stat5 and androgen receptor. Dihydrotestosterone or PRL alone slightly modulated or did not modulate the luciferase activity of all reporter gene constructs. In contrast, a maximal increase was observed using the -1477+42 reporter gene construct after exposure to both dihydrotestosterone and PRL. The requirement of half-site androgen-responsive elements and two consensus Stat5-binding elements, Stat5#1 and Stat5#2, was determined by site-directed mutagenesis. Activated Stat5B binds with a higher affinity to Stat5#2 than to Stat5#1. Stat5ADelta749 and Stat5BDelta754 mutants demonstrated that the Stat5 trans-activation domain is involved in the hormonal cooperation. The cooperation depends on the PRL-induced phosphorylation on Tyr(694) in Stat5A and Tyr(699) in Stat5B, as demonstrated using the Stat5AY694F and Stat5BY699F proteins. The use of AR Q798E, C619Y, and C784Y mutants showed that trans-activation, DNA-binding, and ligand-binding domains of AR are essential. Our study thus suggests a functional cooperation between AR and Stat5.
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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".