Phosphorylation of the translation initiation factor eIF2α at serine 51 determines the cell fate decisions of Akt in response to oxidative stress
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Bibliographic record
Abstract
Phosphorylation of the α subunit of the translation initiation factor eIF2 at serine 51 (eIF2αP) is a master regulator of cell adaptation to various forms of stress with implications in antitumor treatments with chemotherapeutic drugs. Herein, we demonstrate that genetic loss of the eIF2α kinases PERK and GCN2 or impaired eIF2αP by genetic means renders immortalized mouse fibroblasts as well as human tumor cells increasingly susceptible to death by oxidative stress. We also show that eIF2αP facilitates Akt activation in cells subjected to oxidative insults. However, whereas Akt activation has a pro-survival role in eIF2αP-proficient cells, the lesser amount of activated Akt in eIF2αP-deficient cells promotes death. At the molecular level, we demonstrate that eIF2αP acts through an ATF4-independent mechanism to control Akt activity via the regulation of mTORC1. Specifically, eIF2αP downregulates mTORC1 activity, which in turn relieves the feedback inhibition of PI3K resulting in the upregulation of the mTORC2-Akt arm. Inhibition of mTORC1 by rapamycin restores Akt activity in eIF2αP-deficient cells but renders them highly susceptible to Akt-mediated death by oxidative stress. Our data demonstrate that eIF2αP acts as a molecular switch that dictates either cell survival or death by activated Akt in response to oxidative stress. Hence, we propose that inactivation of eIF2αP may be a suitable approach to unleash the killing power of Akt in tumor cells treated with pro-oxidant drugs.
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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 it