Epidermal Growth Factor-Induced GnRH-II Synthesis Contributes to Ovarian Cancer Cell Invasion
Bibliographic record
Abstract
GnRH-II modulates ovarian cancer cells invasion and is expressed in normal ovary and ovarian epithelial cancer cells; however, the upstream regulator(s) of GnRH-II expression in these cells remains unclear. We now demonstrate that epidermal growth factor (EGF) increases GnRH-II mRNA levels in several human ovarian carcinoma cell lines and up-regulates GnRH-II promoter activity in OVCAR-3 cells in a dose-dependent manner, whereas an EGF receptor inhibitor (AG148) abolishes EGF-induced increases in GnRH-II promoter activity and GnRH-II mRNA levels. EGF increases the phosphorylation of cAMP-responsive element-binding protein (p-CREB) and its association with the coregulator, CCAAT/enhancer binding protein beta, whereas blocking the EGF-induced ERK1/2 phosphorylation with MAPK inhibitors (PD98059/U0126) markedly reduced these effects. Moreover, depletion of CREB using small interfering RNA attenuated EGF-induced GnRH-II promoter activity. Chromatin immunoprecipitation assays demonstrated that EGF induces p-CREB binding to a cAMP responsive-element within the GnRH-II promoter, likely in association with CCAAT/enhancer binding protein beta, and mutagenesis of this cAMP responsive-element prevented EGF-induced GnRH-II promoter activity in OVCAR-3 cells. Importantly, GnRH-II acts additively with EGF to promote invasion of OVCAR-3 and CaOV-3 cells, but not SKOV-3 cells that express low levels of GnRH receptor (GnRHR). Treatment with GnRHR small interfering RNA also partially inhibited the EGF-induced invasion of OVCAR-3 and CaOV-3 cells. Furthermore, EGF treatment transiently increases GnRHR levels in OVCAR-3 and CaOV-3, which likely accentuates the effects of increase GnRH-II production on cell invasion. These results provide evidence that EGF is an upstream regulator of the autocrine actions of GnRH-II on the invasive properties of ovarian cancer cells.
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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".