The Role of Hepatocyte Nuclear Factor-3α (Forkhead Box A1) and Androgen Receptor in Transcriptional Regulation of Prostatic Genes
Bibliographic record
Abstract
Androgens and mesenchymal factors are essential extracellular signals for the development as well as the functional activity of the prostate epithelium. Little is known of the intraepithelial determinants that are involved in prostatic differentiation. Here we found that hepatocyte nuclear factor-3 alpha (HNF-3 alpha), an endoderm developmental factor, is essential for androgen receptor (AR)-mediated prostatic gene activation. Two HNF-3 cis-regulatory elements were identified in the rat probasin (PB) gene promoter, each immediately adjacent to an androgen response element. Remarkably, similar organization of HNF-3 and AR binding sites was observed in the prostate-specific antigen (PSA) gene core enhancer, suggesting a common functional mechanism. Mutations that disrupt these HNF-3 motifs significantly abolished the maximal androgen induction of PB and PSA activities. Overexpressing a mutant HNF-3 alpha deleted in the C-terminal region inhibited the androgen-induced promoter activity in LNCaP cells where endogenous HNF-3 alpha is expressed. Chromatin immunoprecipitation revealed in vivo that the occupancy of HNF-3 alpha on PSA enhancer can occur in an androgen-depleted condition, and before the recruitment of ligand-bound AR. A physical interaction of HNF-3 alpha and AR was detected through immunoprecipitation and confirmed by glutathione-S-transferase pull-down. This interaction is directly mediated through the DNA-binding domain/hinge region of AR and the forkhead domain of HNF-3 alpha. In addition, strong HNF-3 alpha expression, but not HNF-3 beta or HNF-3 gamma, is detected in both human and mouse prostatic epithelial cells where markers (PSA and PB) of differentiation are expressed. Taken together, these data support a model in which regulatory cues from the cell lineage and the extracellular environment coordinately establish the prostatic differentiated response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".