Divergent Roles of PAX2 in the Etiology and Progression of Ovarian Cancer
Bibliographic record
Abstract
PAX2 is an essential transcription factor for development. Aberrant PAX2 expression in adult tissues is associated with carcinogenesis and experimental evidence shows that PAX2 generally exhibits oncogenic properties. Although PAX2 is not expressed in normal ovaries, it is highly expressed in low malignant potential and low-grade epithelial ovarian tumors, suggesting that PAX2 induction in ovarian surface epithelium (OSE) may contribute to transformation. Herein, we provide evidence that expression of PAX2 in normal murine OSE cells (mOSE) enhances their proliferation and survival and, with loss of p53, induces tumorigenicity. PAX2 expression in murine ovarian cancer cells enhanced or inhibited tumorigenicity, depending on the model system. In RM cells (mOSE transformed by K-RAS and c-MYC), PAX2 expression inhibited p53 and induced pERK1/2 and COX2, resulting in enhanced angiogenesis and decreased apoptosis of tumors arising from these cells. However, in a murine model of high-grade serous ovarian cancer (STOSE), PAX2 expression improved animal survival by reducing proliferation and metastasis, which correlated with increased Htra1 and decreased COX2. Thus, PAX2 may not be a classical oncogene or tumor suppressor but instead can act in either role by differential regulation of COX2 and/or HTRA1.
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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 | 0.001 | 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".