Prostate Stromal Cells Express the Progesterone Receptor to Control Cancer Cell Mobility
Bibliographic record
Abstract
BACKGROUND: Reciprocal interactions between epithelium and stroma play vital roles for prostate cancer development and progression. Enhanced secretions of cytokines and growth factors by cancer associated fibroblasts in prostate tumors create a favorable microenvironment for cancer cells to grow and metastasize. Our previous work showed that the progesterone receptor (PR) was expressed specifically in prostate stromal fibroblasts and smooth muscle cells. However, the expression levels of PR and its impact to tumor microenvironment in prostate tumors are poorly understood. METHODS: Immunohistochemistry assays are applied to human prostate tissue biopsies. Cell migration, invasion and proliferation assays are performed using human prostate cells. Real-time PCR and ELISA are applied to measure gene expression at molecular levels. RESULTS: Immunohistochemistry assays showed that PR protein levels were decreased in cancer associated stroma when compared with paired normal prostate stroma. Using in vitro prostate stromal cell models, we showed that conditioned media collected from PR positive stromal cells inhibited prostate cancer cell migration and invasion, but had minor suppressive impacts on cancer cell proliferation. PR suppressed the secretion of stromal derived factor-1 (SDF-1) and interlukin-6 (IL-6) by stromal cells independent to PR ligands. Blocking PR expression by siRNA or supplementation of exogenous SDF-1 or IL-6 to conditioned media from PR positive stromal cells counteracted the inhibitory effects of PR to cancer cell migration and invasion. CONCLUSIONS: Decreased expression of the PR in cancer associated stroma may contribute to the elevated SDF-1 and IL-6 levels in prostate tumors and enhance prostate tumor progression.
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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) | 0.001 | 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 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".