CBMT-05. ROLE OF THE let7-eEF2K AXIS IN MYC-DRIVEN MEDULLOBLASTOMA ADAPTATION TO NUTRIENT DEPRIVATION
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: MYC amplification in medulloblastoma (MB) determines highly aggressive disease, underscoring an urgent need for novel therapies. Let-7 microRNAs (miRNAs) inhibit tumor progression and regulate metabolism by degrading several mRNAs, including MYC. Let-7 miRNAs are frequently repressed in cancer, including MYC-driven MB. We previously reported that eukaryotic Elongation Factor-2 Kinase (eEF2K) is a pivotal regulator of MYC-driven tumor adaptation to nutrient deprivation (ND). Our data indicate that the eEF2K 3’ untranslated region (UTR) harbors a potential binding site for let-7. In addition, eEF2K mRNA and let-7 miRNA expression negatively correlates in MB, suggesting regulation of the former by the latter. We therefore hypothesized that let-7 down-regulation induces eEF2K expression in MB, thereby supporting MYC-driven MB adaptation to ND and tumor progression. Immunohistochemistry for eEF2K substrate (p-eEF2) was performed on MB tissue microarrays to link results with MYC expression and clinical outcome. Effects of eEF2K pharmacological inhibition on MB cell survival were evaluated in vitro by MTT assays. The ability of let-7 to degrade eEF2K mRNA was assessed by let-7 miRNAs transfection into MB cells, followed by RT-PCR and Western Blotting for eEF2K. Binding of let-7 to the eEF2K 3’UTR was validated by luciferase reporter assays. High eEF2K activity is linked to MYC over-expression and reduced survival in MB (p<0.05). Pharmacological inhibition of eEF2K significantly reduces survival of MYC-amplified MB cell lines under ND. Transfection let-7 miRNAs decreases eEF2K mRNA and protein levels (by ~40–50%) in MB cells. Down-regulation of luciferase activity by let-7 miRNAs is impaired upon mutation of the let-7 binding site on the eEF2K 3’UTR. Let-7 miRNAs degrade eEF2K mRNA, indicating that let-7 repression in MYC-driven MB is partially responsible for eEF2K increased levels and activity. Moreover, the let-7-eEF2K axis represents a critical mechanism for MYC-driven MB adaptation to ND, constituting a promising therapeutic target.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".