Abstract B08: eIF4E3 forms a novel cap-binding complex for mRNA translation initiation.
Bibliographic record
Abstract
Abstract Dysregulation of mRNA translation can alter the cellular phenotype leading to cancer initiation, maintenance, progression, invasion or metastasis. Cap-dependent translation is the primary mechanism of mRNA translation in eukaryotic cells. The conventional cap-binding complex, eIF4F consists of three components including eIF4A, eIF4G and eIF4E1. eIF4E1 binds the 7-methyl-guanosine-cap (cap) structure in the mRNA and functions to bridge mRNA to the ribosome. eIF4E3 is another member of the eIF4E family that has been recently shown to bind cap using biophysical approach. We explored the biological function of eIF4E3 in a diffuse large B-cell lymphoma model. We found that in the absence or lack of eIF4E1 phosphorylation, eIF4E3 expression is enhanced, and this increases the cap-binding ability of eIF4E3. We find that eIF4E3 also physically associates with the components of the cap-binding complex eIF4A and eIF4G, essentially forming a novel cap-binding complex. We interrogated the functional capacity of the eIF4E3-mediated translation by analyzing the translatome and transcriptome of eIF4E3 expressing cells. eIF4E3 and eIF4E1 mutually regulate a high fraction of total mRNA transcripts, while exclusively modulating translation of select messages. Interestingly, we identified selective motif enrichments in the 5'UTR that may facilitate transcript selection by eIF4E1 or eIF4E3. Together, we have identified a novel cap-binding complex consisting of eIF4A, eIF4G and eIF4E3, which can initiate mRNA translation of select messages. Citation Format: Ari L. Landon, Parameswary A Muniandy, Simone Houng, Amol Shetty, Kevin Becker, Katherine Borden, Ronald B. Gartenhaus. eIF4E3 forms a novel cap-binding complex for mRNA translation initiation. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr B08.
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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 | 0.001 | 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".