4E-BP1 Is a Tumor Suppressor Protein Reactivated by mTOR Inhibition in Head and Neck Cancer
Bibliographic record
Abstract
Abstract Aberrant activation of the PI3K–mTOR signaling pathway occurs in >80% of head and neck squamous cell carcinomas (HNSCC), and overreliance on this signaling circuit may in turn represent a cancer-specific vulnerability that can be exploited therapeutically. mTOR inhibitors (mTORi) promote tumor regression in genetically defined and chemically induced HNSCC animal models, and encouraging results have been recently reported. However, the mTOR-regulated targets contributing to the clinical response have not yet been identified. Here, we focused on EIF4E-BP1 (4E-BP1), a direct target of mTOR that serves as key effector for protein synthesis. A systematic analysis of genomic alterations in the PIK3CA–mTOR pathway in HNSCC revealed that 4E-BP1 is rarely mutated, but at least one 4E-BP1 gene copy is lost in over 35% of the patients with HNSCC, correlating with decreased 4E-BP1 protein expression. 4E-BP1 gene copy number loss correlated with poor disease-free and overall survival. Aligned with a tumor-suppressive role, 4e-bp1/2 knockout mice formed larger and more lesions in models of HNSCC carcinogenesis. mTORi treatment or conditional expression of a mutant 4E-BP1 that cannot be phosphorylated by mTOR was sufficient to disrupt the translation–initiation complex and prevent tumor growth. Furthermore, CRISPR/Cas9–targeted 4E-BP1 HNSCC cells resulted in reduced sensitivity to mTORi in vitro and in vivo. Overall, these findings indicate that in HNSCC, mTOR persistently restrains 4E-BP1 via phosphorylation and that mTORi can restore the tumor-suppressive function of 4E-BP1. Our findings also support 4E-BP1 expression and phosphorylation status as a mechanistic biomarker of mTORi sensitivity in patients with HNSCC. Significance: These findings suggest that EIF4E-BP1 acts as a tumor suppressor in HNSCC and that 4E-BP1 dephosphorylation mediates the therapeutic response to mTORi, providing a mechanistic biomarker for future precision oncology trials.
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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 | 0.000 |
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".