Oxidative stress contributes to the tamoxifen-induced killing of breast cancer cells: implications for tamoxifen therapy and resistance
Bibliographic record
Abstract
Tamoxifen is the accepted therapy for patients with estrogen receptor-α (ERα)-positive breast cancer. However, clinical resistance to tamoxifen, as demonstrated by recurrence or progression on therapy, is frequent and precedes death from metastases. To improve breast cancer treatment it is vital to understand the mechanisms that result in tamoxifen resistance. This study shows that concentrations of tamoxifen and its metabolites, which accumulate in tumors of patients, killed both ERα-positive and ERα-negative breast cancer cells. This depended on oxidative damage and anti-oxidants rescued the cancer cells from tamoxifen-induced apoptosis. Breast cancer cells responded to tamoxifen-induced oxidation by increasing Nrf2 expression and subsequent activation of the anti-oxidant response element (ARE). This increased the transcription of anti-oxidant genes and multidrug resistance transporters. As a result, breast cancer cells are able to destroy or export toxic oxidation products leading to increased survival from tamoxifen-induced oxidative damage. These responses in cancer cells also occur in breast tumors of tamoxifen-treated mice. Additionally, high levels of expression of Nrf2, ABCC1, ABCC3 plus NAD(P)H dehydrogenase quinone-1 in breast tumors of patients at the time of diagnosis were prognostic of poor survival after tamoxifen therapy. Therefore, overcoming tamoxifen-induced activation of the ARE could increase the efficacy of tamoxifen in treating breast cancer.
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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".