17β-Estradiol sensitizes ovarian surface epithelium to transformation by suppressing Disabled-2 expression
Bibliographic record
Abstract
Estrogen replacement therapy increases the risk of human ovarian cancer and exogenous estradiol accelerates the onset of ovarian cancer in mouse models. This study uses primary cultures of mouse ovarian surface epithelium (OSE) to demonstrate that one possible mechanism by which estrogen accelerates the initiation of ovarian cancer is by up-regulation of microRNA-378 via the ESR1 pathway to result in the down-regulation of a tumour suppressor called Disabled-2 (Dab2). Estrogen suppression of Dab2 was reproducible in vivo and across many cell types including mouse oviductal epithelium and primary cultures of human ovarian cancer cells. Suppression of Dab2 resulted in increased proliferation, loss of contact inhibition, morphological dysplasia, and resistance to oncogene-induced senescence - all factors that can sensitize OSE to transformation. Given that DAB2 is highly expressed in healthy human OSE and is absent in the majority of ovarian tumours, this study has taken the first steps to provide a mechanistic explanation for how estrogen therapy may play a role in the initiation of ovarian cancer.
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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".