Trolox selectively enhances arsenic-mediated oxidative stress and apoptosis in APL and other malignant cell lines
Bibliographic record
Abstract
Although arsenic trioxide (As(2)O(3)) is an effective therapy in acute promyelocytic leukemia (APL), its use in other malignancies is limited by the toxicity of concentrations required to induce apoptosis in non-APL tumor cells. We looked for agents that would synergize with As(2)O(3) to induce apoptosis in malignant cells, but not in normal cells. We found that trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid), a widely known antioxidant, enhances As(2)O(3)-mediated apoptosis in APL, myeloma, and breast cancer cells. Treatment with As(2)O(3) and trolox increased intracellular oxidative stress, as evidenced by heme oxygenase-1 (HO-1) protein levels, c-Jun terminal kinase (JNK) activation, and protein and lipid oxidation. The synergistic effects of trolox may be specific to As(2)O(3), as trolox does not add to toxicity induced by other chemotherapeutic drugs. We explored the mechanism of this synergy using electron paramagnetic resonance and observed the formation of trolox radicals when trolox was combined with As(2)O(3), but not with doxorubicin. Importantly, trolox protected nonmalignant cells from As(2)O(3)-mediated cytotoxicity. Our data provide the first evidence that trolox may extend the therapeutic spectrum of As(2)O(3). Furthermore, the combination of As(2)O(3) and trolox shows potential specificity for tumor cells, suggesting it may not increase the toxicity associated with As(2)O(3) monotherapy in vivo.
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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".