Expression of xCT and activity of system xc− are regulated by NRF2 in human breast cancer cells in response to oxidative stress
Bibliographic record
Abstract
Cancer cells adapt to high levels of oxidative stress in order to survive and proliferate by activating key transcription factors. One such master regulator, the redox sensitive transcription factor NF E2 Related Factor 2 (NRF2), controls the expression of cellular defense genes including those encoding intracellular redox-balancing proteins involved in glutathione (GSH) synthesis. Under basal conditions, Kelch-like ECH-associated protein 1 (KEAP1) targets NRF2 for ubiquitination. In response to oxidative stress, NRF2 dissociates from KEAP1, entering the nucleus and binding to the antioxidant response element (ARE) in the promoter of its target genes. Elevated reactive oxygen species (ROS) production may deplete GSH levels within cancer cells. System xc(-), an antiporter that exports glutamate while importing cystine to be converted into cysteine for GSH synthesis, is upregulated in cancer cells in response to oxidative stress. Here, we provided evidence that the expression of xCT, the light chain subunit of system xc(-), is regulated by NRF2 in representative human breast cancer cells. Hydrogen peroxide (H2O2) treatment increased nuclear translocation of NRF2, also increasing levels of xCT mRNA and protein and extracellular glutamate release. Overexpression of NRF2 up-regulated the activity of the xCT promoter, which contains a proximal ARE. In contrast, overexpression of KEAP1 repressed promoter activity and decreased xCT protein levels, while siRNA knockdown of KEAP1 up-regulated xCT protein levels and transporter activity. These results demonstrate the importance of the KEAP1/NRF2 pathway in balancing oxidative stress in breast cancer cells through system xc(-). We have previously shown that xCT is upregulated in various cancer cell lines under oxidative stress. In the current investigation, we focused on MCF-7 cells as a model for mechanistic studies.
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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 | 0.000 |
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".