Constitutive expression of progesterone receptor isoforms promotes the development of hormone-dependent ovarian neoplasms
Bibliographic record
Abstract
Differences in the relative abundances of the progesterone receptor (PGR) isoforms PGRA and PGRB are often observed in women with reproductive tract cancers. To assess the importance of the PGR isoform ratio in the maintenance of the reproductive tract, we generated mice that overexpress PGRA or PGRB in all PGR-positive tissues. Whereas few PGRA-overexpressing mice developed reproductive tract tumors, all PGRB-overexpressing mice developed ovarian neoplasms that were derived from ovarian luteal cells. Transcriptomic analyses of the ovarian tumors from PGRB-overexpressing mice revealed enhanced AKT signaling and a gene expression signature similar to those of human ovarian and endometrial cancers. Treating PGRB-overexpressing mice with the PGR antagonist RU486 stalled tumor growth and decreased the expression of cell cycle-associated genes, indicating that tumor growth and cell proliferation were hormone dependent in addition to being isoform dependent. Analysis of the PGRB cistrome identified binding events at genes encoding proteins that are critical regulators of mitotic phase entry. This work suggests a mechanism whereby an increase in the abundance of PGRB relative to that of PGRA drives neoplasia in vivo by stimulating cell cycling.
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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".