Progesterone receptor expression during prostate cancer progression suggests a role of this receptor in stromal cell differentiation
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The progesterone receptor, like the androgen receptor, belongs to the steroid receptor superfamily. Our previous studies have reported that the PR is expressed specifically in prostate stroma. PR inhibits proliferation of, and regulates cytokine secretion by stromal cells. However, PR protein expression in cancer-associated stroma during prostate cancer progression has not been profiled. Since the phenotypes of prostate stromal cells change dynamically as tumors progress, whether the PR plays a role in regulating stromal cell differentiation needs to be investigated. METHODS: Immunohistochemistry assays measured PR protein levels on human prostate tissue microarrays containing 367 tissue cores from benign prostate, prostate tumors with different Gleason scores, tumors under various durations of castration therapy, and tumors at the castration-resistant stage. Immunoblotting assays determined whether PR regulated the expression of alpha smooth muscle actin (α-SMA), vimentin, and fibroblast specific protein (FSP) in human prostate stromal cells. RESULTS: PR protein levels decreased in cancer-associated stroma when compared with that in benign prostate stroma. This reduction in PR expression was not correlated with Gleason scores. PR protein levels were elevated by castration therapy, but reduced to pre-castration levels when tumors progressed to the castration-resistant stage. Enhanced PR expression in human prostate stromal cells increased α-SMA, but decreased vimentin and FSP protein levels ligand-independently. CONCLUSION: These results suggest that PR plays an active role in regulating stromal cell phenotypes during prostate cancer progression.
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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 it