Redox-modulating agents target NOX2-dependent IKKε oncogenic kinase expression and proliferation in human breast cancer cell lines
Bibliographic record
Abstract
Oxidative stress is considered a causative factor in carcinogenesis, but also in the development of resistance to current chemotherapies. The appropriate usage of redox-modulating compounds is limited by the lack of knowledge of their impact on specific molecular pathways. Increased levels of the IKKε kinase, as a result of gene amplification or aberrant expression, are observed in a substantial number of breast carcinomas. IKKε not only plays a key role in cell transformation and invasiveness, but also in the development of resistance to tamoxifen. Here, we studied the effect of in vitro treatment with the redox-modulating triphenylmethane dyes, Gentian Violet and Brilliant Green, and nitroxide Tempol on IKKε expression and cell proliferation in the human breast cancer epithelial cell lines exhibiting amplification of IKKε, MCF-7 and ZR75.1. We show that Gentian Violet, Brilliant Green and Tempol significantly decrease intracellular superoxide anion levels and inhibit IKKε expression and cell viability. Treatment with Gentian Violet and Brilliant Green was associated with a reduced cyclin D1 expression and activation of caspase 3 and/or 7. Tempol decreased cyclin D1 expression in both cell lines, while activation of caspase 7 was only observed in MCF-7 cells. Silencing of the superoxide-generating NOX2 NADPH oxidase expressed in breast cancer cells resulted in the significant reduction of IKKε expression. Taken together, our results suggest that redox-modulating compounds targeting NOX2 could present a particular therapeutic interest in combination therapy against breast carcinomas exhibiting IKKε amplification.
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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 | 0.001 |
| 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 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".