Role of PELP1/MNAR Signaling in Ovarian Tumorigenesis
Bibliographic record
Abstract
Emerging evidence suggests that nuclear receptor (NR) coregulators have potential to act as master genes and their deregulation can promote oncogenesis. Proline-, glutamic acid-, and leucine-rich protein-1 (PELP1/MNAR) is a novel NR coregulator. Its expression is deregulated in hormone-driven cancers. However, the role of PELP1/MNAR in ovarian cancer progression remains unknown. Analysis of serial analysis of gene expression data suggested deregulation of PELP1/MNAR expression in ovarian tumors. Western analysis of PELP1/MNAR in normal and serous ovarian tumor tissues showed 3- to 4-fold higher PELP1/MNAR expression in serous tumors compared with normal ovarian tissues. To examine the significance of PELP1/MNAR in ovarian cancer progression, we have generated model cells that overexpress PELP1/MNAR and ovarian cancer cells in which PELP1/MNAR expression is down-regulated by stable expression of PELP1/MNAR-specific shRNA. Down-regulation of PELP1/MNAR in cancerous ovarian model cells (OVCAR3) resulted in reduced proliferation, affected the magnitude of c-Src and protein kinase B (AKT) signaling, and reduced tumorigenic potential of ovarian cancer cells in a nude mouse model. PELP1/MNAR overexpression in nontumorigenic immortalized surface epithelial cells (IOSE cells) promoted constitutive activation of c-Src and AKT signaling pathways and promoted anchorage-independent growth. Immunohistochemical studies using human ovarian cancer tissue arrays (n = 123) showed that PELP1/MNAR is 2- to 3-fold overexpressed in 60% of ovarian tumors, and PELP1/MNAR deregulation occurs in all different types of ovarian cancer. Collectively, these results suggest that PELP1/MNAR signaling plays a role in ovarian cancer cell proliferation and survival, and that its expression is deregulated in ovarian carcinomas.
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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".