17β‐estradiol upregulates GREB1 and accelerates ovarian tumor progression <i>in vivo</i>
Bibliographic record
Abstract
Exogenous 17β-estradiol (E2) accelerates the progression of ovarian cancer in the transgenic tgCAG-LS-TAg mouse model of the disease. We hypothesized that E2 has direct effects on ovarian cancer cells and this study was designed to determine the molecular mechanisms by which E2 accelerates ovarian tumor progression. Mouse ovarian cancer ascites (MAS) cell lines were derived from tgCAG-LS-TAg mice. Following intraperitoneal engraftment of two MAS cell lines, MASC1 and MASE2, into SCID mice, exogenous E2 significantly decreased the survival time and increased the tumor burden. Microarray analysis performed on MASE2-derived tumors treated with E2 or placebo showed that E2 treatment caused the upregulation of 197 genes and the downregulation of 55 genes. The expression of gene regulated by estrogen in breast cancer 1 (Greb1) was upregulated in mouse tumors treated with E2 and was overexpressed in human ovarian cancers relative to human ovarian surface epithelium, suggesting a role for GREB1 in human ovarian tumor progression. RNA interference-mediated knockdown of GREB1 in MASE2 cells decreased their proliferation rate in vitro and increased survival time in mice engrafted with the cells. These results emphasize the importance of E2 in ovarian tumor progression and identify Greb1 as a novel gene target for therapeutic intervention.
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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".