Genistein versus ICI 182, 780: An ally or enemy in metastatic progression of prostate cancer
Bibliographic record
Abstract
BACKGROUND: Androgen signalling through the androgen receptor (AR) plays a critical role in prostate cancer (PCa) initiation and progression. Estrogen in synergy with androgen is essential for cell growth of the normal and malignant prostate. However, the exact role that estrogen and the estrogen receptor play in prostate carcinogenesis remains unclear. We have previously demonstrated the metastasis-promoting effect of an estrogen receptor beta (ERβ) agonist (genistein) in a patient-derived PCa xenograft model mimicking localized and metastatic disease. METHODS: To test the hypothesis that the tumor-promoting activity of genistein was due to its estrogenic properties, we treated the xenograft-bearing mice with genistein and an anti-estrogen compound (ICI 182, 780) and compared the differential gene expression using microarrays. RESULTS: Using a second xenograft model which was derived from another patient, we showed that genistein promoted disease progression in vivo and ICI 182, 780 inhibited metastatic spread. The microarray analysis revealed that the metallothionein (MT) gene family was differentially expressed in tumors treated by these compounds. Using qRT-PCR, the differences in expression levels were validated in the metastatic and non-metastatic LTL313 PCa xenograft tumor lines, both of which were originally derived from the same PCa patient. CONCLUSIONS: Together our data provide evidence that genistein stimulates and ICI 182, 780 inhibits metastatic progression, suggesting that these effects may be mediated by ERβ signalling.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".