Estrogen receptor alpha pathway is involved in leptin-induced ovarian cancer cell growth
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Bibliographic record
Abstract
Previously, we demonstrated that leptin, a pleiotropic hormone produced by adipocytes, stimulates the growth of BG-1 ovarian cancer cells via the extracellular signal-regulated kinase signaling pathway. In this study, we further investigated the involvement of estrogen receptor (ER) pathway in the mechanism of leptin-induced ovarian cancer cell growth. Treatment with leptin (100 ng/ml) resulted in a significant increase in the cell growth of ERα-transfected OVCAR-3 and A2780 cells, whereas no significant difference was observed in ERβ-transfected cells. Downregulation of ERα using small interfering RNA completely reversed leptin-induced growth of BG-1 cells. Treatment with leptin resulted in ER transcriptional activation, i.e. nuclear localization of ER and increased expression of pS2, an estrogen-dependent gene. Luciferase reporter assay revealed that treatment of BG-1 cells with leptin (100 ng/ml) stimulated the expression of the reporter gene in the absence of estradiol (E2). To examine an involvement of Janus kinase 2/signal transducers and activators of transcription 3 (STAT-3) and phosphatidyl-inositol 3-kinase (PI3K)/Akt in leptin-induced pathway, we demonstrated that leptin increased phosphorylation of STAT-3 and Akt in BG-1 cells in a time- and dose-dependent manner. On the other hand, leptin-induced cell growth and ER transactivation were effectively blocked by specific STAT-3 inhibitor AG490 and, to a lesser extent, by PI3K inhibition. Further study with coimmunoprecipitation assay revealed that stimulation with leptin induced STAT-3 binding to ERα. Taken together, these results indicate that the stimulation of ovarian cancer cell growth by leptin involves, at least in part, ER transcriptional activation via the STAT-3 signaling pathways.
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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) | 0.001 | 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 it