Phosphorylation of eIF4E Confers Resistance to Cellular Stress and DNA-Damaging Agents through an Interaction with 4E-T: A Rationale for Novel Therapeutic Approaches
Bibliographic record
Abstract
Phosphorylation of the eukaryotic translation initiation factor eIF4E is associated with malignant progression and poor cancer prognosis. Accordingly, here we have analyzed the association between eIF4E phosphorylation and cellular resistance to oxidative stress, starvation, and DNA-damaging agents in vitro. Using immortalized and cancer cell lines, retroviral expression of a phosphomimetic (S209D) form of eIF4E, but not phospho-dead (S209A) eIF4E or GFP control, significantly increased cellular resistance to stress induced by DNA-damaging agents (cisplatin), starvation (glucose+glutamine withdrawal), and oxidative stress (arsenite). De novo accumulation of eIF4E-containing cytoplasmic bodies colocalizing with the eIF4E-binding protein 4E-T was observed after expression of phosphomimetic S209D, but not S209A or wild-type eIF4E. Increased resistance to cellular stress induced by eIF4E-S209D was lost upon knockdown of endogenous 4E-T or use of an eIF4E-W73A-S209D mutant unable to bind 4E-T. Cancer cells treated with the Mnk1/2 inhibitor CGP57380 to prevent eIF4E phosphorylation and mouse embryonic fibroblasts derived from Mnk1/2 knockout mice were also more sensitive to arsenite and cisplatin treatment. Polysome analysis revealed an 80S peak 2 hours after arsenite treatment in cells overexpressing phosphomimetic eIF4E, indicating translational stalling. Nonetheless, a selective increase was observed in the synthesis of some proteins (cyclin D1, HuR, and Mcl-1). We conclude that phosphorylation of eIF4E confers resistance to various cell stressors and that a direct interaction or regulation of 4E-T by eIF4E is required. Further delineation of this process may identify novel therapeutic avenues for cancer treatment, and these results support the use of modern Mnk1/2 inhibitors in conjunction with standard therapy.
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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) | 0.001 | 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) | 0.001 | 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".