Cell Growth of Ovarian Cancer Cells is Stimulated by Xenoestrogens through an Estrogen-Dependent Pathway, but Their Stimulation of Cell Growth Appears not to be Involved in the Activation of the Mitogen-Activated Protein Kinases ERK-1 and p38
Bibliographic record
Abstract
Although endocrine disrupting chemicals (EDCs) may interfere with the endocrine system(s) of our body and have estrogenicity or androgenicity, the exact mechanism(s) underlying their detrimental effects is not clearly understood. Thus, in this study, we evaluated the effects of EDCs on proliferation and regulation of transcription of estrogen receptor (ER)-positive BG-1 ovarian cancer cells, and their possible mechanisms were further examined. Treatment with bisphenol A (BPA), nonylphenol (NP), octylphenol (OP) and methoxychlor (MXC) for 24 h resulted in an increase of cell proliferation. Treatment with BPA, NP, OP and MXC increased the estrogen response element (ERE) activity. The increase of cell proliferation and activation of ERE were reversed in the presence of an estrogen receptor antagonist, ICI 182780. These results suggest that ER is involved in EDC-mediated pathway in ovarian cancer cells. Based on this, we further investigated the involvement of EDCs in activation of mitogen-activated protein kinase (MAPK) in relation to cell growth. BPA rapidly induced activation of extracellular signal-regulated kinase (ERK) 1/2 and p38 MAPK at 15 min, but the effect of BPA (10 microM) on stimulation of cell growth was not blocked by pretreatment with inhibitors of MEK (PD98059) or p38 (SB203580) in a dose-dependent manner. Taken together, EDC-induced proliferation is mediated by a genomic effect through ERs and ERE, but EDC-activated MAPK is unlikely to be involved in EDC-induced cell growth in estrogen-responsive ovarian cancer cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".