Wilms' Tumor 1 Suppressor Gene Mediates Antiestrogen Resistance via Down-Regulation of Estrogen Receptor-α Expression in Breast Cancer Cells
Bibliographic record
Abstract
The antiestrogen tamoxifen has been used in the treatment of hormone-responsive breast cancer for over a decade. The loss of estrogen receptor (ER) expression is the most common mechanism for de novo antiestrogen resistance. Wilms' tumor 1 suppressor gene (WT1) is a clinically useful marker that is associated with poor prognosis in breast cancer patients; its high level expression is frequently observed in cases of breast cancer that are estrogen and progesterone receptor negative. The lack of expression of these receptors is characteristic of tumor cells that are not responsive to hormonal manipulation. To determine whether there is a linkage between WT1 expression and antiestrogen resistance in breast cancer cells, we studied the effect of WT1 on tamoxifen responsiveness in ERalpha-positive MCF-7 cells. We found that overexpression of WT1 in MCF-7 markedly abrogated tamoxifen-induced cell apoptosis and 17beta-estradiol (E(2))-mediated cell proliferation. The expressions of ERalpha and its downstream target genes were significantly repressed following overexpression of WT1, whereas the down-regulation of WT1 by WT1 shRNA could enhance ERalpha expression and the sensitivity to tamoxifen treatment in ERalpha-negative MDA468 and HCC1954 cells that express high levels of WT1. Furthermore, we have confirmed that the WT1 protein can bind to endogenous WT1 consensus sites in the proximal promoter of ERalpha and thus inhibit the transcriptional activity of the ERalpha promoter in a WT1 site sequence-specific manner. Our study clearly implicates WT1 as a mediator of antiestrogen resistance in breast cancer through down-regulation of ERalpha expression and supports the development of WT1 inhibitors as a potential means of restoring antiestrogen responsiveness in breast cancer therapy.
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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 | 0.001 |
| 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".