Physiologic Levels of 2-Methoxyestradiol Interfere with Nongenomic Signaling of 17β-Estradiol in Human Breast Cancer Cells
Bibliographic record
Abstract
PURPOSE: The purpose of this investigation is to determine the effects of physiologic levels (10-50 nmol/L) of 2-methoxyestradiol (2ME) on the growth of estrogen receptor (ER)-positive breast cancer cells and provide insights into its mechanism(s) of action. EXPERIMENTAL DESIGN: Using the ERalpha-positive breast cancer cells, we studied the effects of 2ME on cell proliferation and cell signaling. Our hypothesis is that 17beta-estradiol (E(2)) and 2ME can affect shared cell signaling pathways, leading to different outcomes in cell proliferation, depending on the absence/presence of E(2). RESULTS: E(2) stimulated the growth of MCF-7 and T-47 D cells and induced Akt phosphorylation, a nongenomic signaling pathway. In the absence of E(2), 10 to 50 nmol/L of 2ME enhanced cell growth and Akt phosphorylation. However, in the presence of E(2), 2ME inhibited E(2)-induced cell growth and prevented E(2)-induced Akt phosphorylation. Confocal microscopic studies showed that 2ME inhibited subcellular distribution of ERalpha in response to E(2) in MCF-7 and T-47D cells. 2ME also down-regulated E(2)-induced increases in cyclic AMP and ornithine decarboxylase activity. In addition, treatment of MCF-7 cells with 2ME in the presence of E(2) resulted in a decrease in ERalpha level by 72 hours. Accelerated down-regulation of ERalpha may contribute to growth inhibition in the presence of E(2)/2ME combinations. In contrast, a concentration of up to 2.5 mumol/L 2ME had no effect on the growth of ER-negative SK-BR-3 cells, either in the presence or absence of E(2). CONCLUSIONS: Our results provide evidence for the nongenomic action of 2ME in ER-positive cells. In the presence of E(2), 2ME suppressed E(2)-induced cell growth, Akt signaling, and generation of cyclic AMP, whereas it acted as an estrogen in the absence of E(2). The intriguing growth-stimulatory and growth-inhibitory effects of 2ME on breast cancer cells suggests the need for its selective use in patients.
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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 | 0.000 | 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 | 0.001 |
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".