CELF1 is an EIF4E binding protein that promotes translation of epithelial-mesenchymal transition effector mRNAs
Bibliographic record
Abstract
Abstract Mounting evidence is revealing a granularity within gene regulation that occurs at the level of mRNA translation. Within mammalian cells, canonical cap-dependent mRNA translation is dependent upon the interaction between the m 7 G cap-binding protein eukaryotic initiation factor 4E (eIF4E) and the scaffolding protein eukaryotic initiation factor 4G (eIF4G), the latter of which facilitates pre-translation initiation complex assembly, mRNA circularization, and ultimately ribosomal scanning. In breast epithelial cells, we previously demonstrated that the CELF1 RNA-binding protein promotes the translation of epithelial to mesenchymal transition (EMT) effector mRNAs containing GU-rich elements (GREs) within their 3’ untranslated regions (UTRs). Here we show that within this context, CELF1 directly binds to both the eIF4E cap-binding protein and Poly(A) binding protein (PABP), promoting translation of GRE-containing mRNAs in mesenchymal cells. Disruption of this CELF1/eIF4E interaction inhibits both EMT induction and experimental metastasis. Our findings illustrate a novel way in which non-canonical mechanisms of translation initiation underlie transitional cellular states within the context of development or human disease.
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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) | 0.003 | 0.001 |
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".