The Oncogene eIF4E: Using Biochemical Insights to Target Cancer
Bibliographic record
Abstract
The eukaryotic translation initiation factor eIF4E is overexpressed in many human malignancies where it is typically a harbinger of poor prognosis. eIF4E is positioned as a nexus in post-transcriptional gene expression. To carry out these functions, eIF4E needs to bind the m(7)G cap moiety on mRNAs. It plays critical roles in mRNA translation, mRNA export, and most likely in mRNA stability as well. Through these activities, eIF4E coordinately modulates the expression of many transcripts involved in proliferation and survival. eIF4E function is controlled by interactions with protein cofactors in concert with many signaling pathways, including Ras, Mnk, Erk, MAPK, PI3K, mTOR, and Akt. This review describes the eIF4E activity and provides several examples of cellular control mechanisms. Further, we describe some therapeutic strategies in preclinical and clinical development.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".