JNK activation is a mediator of arsenic trioxide-induced apoptosis in acute promyelocytic leukemia cells
Bibliographic record
Abstract
Arsenic trioxide induces c-jun N-terminal kinase (JNK) activation and apoptosis in acute promyelocytic leukemia (APL), where it has major clinical activity, but whether JNK is necessary to induce apoptosis is unknown. To clarify this necessity, we established 2 arsenic trioxide (As(2)O(3))-resistant subclones of the APL cell line, NB4. Both resistant lines showed little activation of JNK1 following treatment with As(2)O(3), even at doses sufficient to elicit robust activation in NB4 cells. One mechanism of resistance in these cells is up-regulated glutathione (GSH) content, and GSH depletion by l-buthionine-[S,R]-sulfoximine (BSO) restores JNK activation and As(2)O(3) sensitivity. This correlation between JNK activation and apoptosis led us to test whether inhibition of JNK would protect cells from As(2)O(3)-induced apoptosis. SEK1(-/-) mouse embryo fibroblasts (MEFs) showed diminished JNK activation following As(2)O(3) treatment and were protected from As(2)O(3)-induced but not doxorubicin-induced apoptosis. Furthermore, treatment of arsenic trioxide-sensitive APL cells with the JNK inhibitor, dicumarol, significantly increased growth and survival in response to As(2)O(3) but did not protect cells from doxorubicin. Together, these data support an essential role for JNK signaling in the induction of growth inhibition and apoptosis by As(2)O(3) and suggest that activating JNK may provide a therapeutic advantage in the treatment of cancers that do not respond to arsenic alone.
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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) | 0.002 | 0.001 |
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".