Abstract LB-302: eIF4E phosphorylation is Mnk-dependent but does not require assembly of the eIF4F translation initiation complex
Bibliographic record
Abstract
Abstract In numerous experimental cancer models, overexpression of eukaryotic translation initiation factor 4E (eIF4E) can drive oncogenic transformation, enable invasiveness and facilitate metastasis. eIF4E binds the 7-methylguanosine cap structure at the 5’ terminus of cellular mRNAs, recruiting these mRNAs into the multi-protein translation complex known as eIF4F. The eIF4F complex is comprised of eIF4E, the eIF4G scaffolding protein and the ATP-dependent RNA helicase, eIF4A. In addition, accessory factors (e.g. the Mnk kinases) can interact with this complex, further refining and regulating the function of the complex and the translation of mRNAs. A wealth of literature has accumulated over the past 20 years demonstrating that enhanced eIF4E function, a common event in many human cancers and experimental cancer models, selectively and disproportionately upregulates the translation of potent growth and survival factors implicated in all aspects of malignancy- dysregulated cellular growth control (c-myc, cyclinD1), enhanced cellular survival (survivin, BCL-2, MCL-1), angiogenesis (VEGF, FGF-2), invasiveness and metastasis (MMP9, osteopontin). The oncogenic function of eIF4E is critically dependent upon the phosphorylation of eIF4E at serine 209- an event exclusively controlled by the Mnk1/2 kinases and dependent upon the binding of both eIF4E and the Mnk kinases to the eIF4G scaffolding protein. We sought to understand better the dynamics of eIF4F complex assembly and eIF4E phosphorylation. Using pharmacologic inhibitors of eIF4F assembly (rapamycin, 4EGI-1, Torin, AZD8055), we now show that eIF4E phosphorylation can be induced- independent of the assembly of the eIF4F complex. This increase in eIF4E phosphorylation was blocked by addition of the Mnk inhibitor cercosporamide, suggesting the event remains Mnk-dependent. Further supporting this notion, eIF4E phosphorylation could not be induced by any treatment in Mnk double knockout mouse embryo fibroblasts (DKO-MEFs). To delineate definitively whether eIF4E could be phosphorylated independent of the eIF4F complex, we transfected glioma cells and H293T cells with eIF4E mutants that cannot bind eIF4G (W73F, G139D and the W73F + G139D double mutants). Phosphorylation of these mutants was evident in all cells tested. In DKO-MEFs, these eIF4E mutants were also phosphorylated when co-transfected with wild-type Mnk1 or Mnk2. Importantly, these eIF4E mutants that cannot bind eIF4G could also be phosphorylated in the DKO-MEFS when co-transfected with Mnk 1 or 2 mutants that also fail to bind eIF4G. These data indicate that the eIF4E interaction with Mnk does not require binding to the eIF4G scaffolding protein and, collectively, suggest a revised model for eIF4E phosphorylation- one dependent upon the Mnk kinases but not necessarily dependent on eIF4F complex assembly. Citation Format: Chad Hall, Chad Dumstorf, Bruce Konicek, Nathaniel Robichaud, Ann McNulty, Steve Parsons, Jerry Pelltier, Nahum Sonenberg, Jeremy R. Graff. eIF4E phosphorylation is Mnk-dependent but does not require assembly of the eIF4F translation initiation complex. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-302. doi:10.1158/1538-7445.AM2014-LB-302
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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) | 0.005 | 0.004 |
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".