Arsenic trioxide decreases AKT protein in a caspase-dependent manner
Bibliographic record
Abstract
Arsenic trioxide (As2O3) is used clinically to treat acute promyelocytic leukemia but is less successful in other malignancies. To identify targets for potential combination therapies, we have begun to characterize signaling pathways leading to As2O3-induced cytotoxicity. Previously, we described the requirement for a reactive oxygen species-mediated, SEK1/c-Jun NH2-terminal kinase (JNK) pathway to induce apoptosis. AKT inhibits several steps in this pathway; therefore, we postulated that As2O3 might decrease its activity. Indeed, As2O3 decreases not only AKT activity but also total AKT protein, and sensitivity to As2O3 correlates with the degree of AKT protein decrease. Decreased AKT expression further correlates with JNK activation and the release of AKT from the JNK-interacting protein 1 scaffold protein known to assemble the mitogen-activated protein kinase cascade. We found that As2O3 regulates AKT protein stability without significant effects on its transcription or translation. We show that As2O3 decreases AKT protein via caspase-mediated degradation, abrogated by caspase-6, caspase-8, caspase-9, and caspase-3 inhibitors but not proteosome inhibitors. Furthermore, As2O3 enhances the ability of a heat shock protein 90 inhibitor to decrease AKT expression and increase growth inhibition. This suggests that As2O3 may be useful in combination therapies that target AKT pathways or in tumors that have constitutively active AKT expression.
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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) | 0.002 | 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".