Misregulated Wnt/β-Catenin Signaling Leads to Ovarian Granulosa Cell Tumor Development
Bibliographic record
Abstract
Misregulation of the Wnt/beta-catenin signaling pathway is a hallmark of several forms of cancer. Components of the Wnt/beta-catenin pathway are expressed in ovarian granulosa cells; nevertheless, its potential involvement in granulosa cell tumorigenesis has not been examined. To this end, human (n = 6) and equine (n = 18) granulosa cell tumors (GCT) were analyzed for beta-catenin expression by immunohistochemistry. Unlike granulosa cells of normal ovaries, most (15 of 24) GCT samples showed nuclear localization of beta-catenin, suggesting that activation of the Wnt/beta-catenin pathway plays a role in the etiology of GCT. To confirm this hypothesis, Catnb(flox(ex3)/+); Amhr2(cre/+) mice that express a dominant stable beta-catenin mutant in their granulosa cells were generated. These mice developed follicle-like structures containing disorganized, pleiomorphic granulosa by 6 weeks of age. Even in older mice, these follicle-like lesions grew no larger than the size of antral follicles and contained very few proliferating cells. Similar to corpora lutea, the lesions were highly vascularized, although they did not express the luteinization marker Cyp11a1. Catnb(flox(ex3)/+); Amhr2(cre/+) females were also found to be severely subfertile, and fewer corpora lutea were found to form in response to exogenous gonadotropin compared with control mice. In older mice, the ovarian lesions often evolved into GCT, indicating that they represent a pretumoral intermediate stage. The GCT in Catnb(flox(ex3)/+); Amhr2(cre/+) mice featured many histopathologic similarities to the human disease, and prevalence of tumor development attained 57% at 7.5 months of age. Together, these studies show a causal link between misregulated Wnt/beta-catenin signaling and GCT development and provide a novel model system for the study of GCT biology.
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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".