EMBR-20. ELONGATION CONTROL OF MRNA TRANSLATION DRIVES GROUP 3 MEDULLOBLASTOMA
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is the most common pediatric intracranial tumor and leading cause of childhood related cancer deaths. Group 3 affiliation and genetic amplifications of the MYC oncogene are predictors of adverse outcome in MB, underscoring a dire need for novel and more effective therapeutic approaches. The let-7 family of small non-coding RNAs (miRNAs) is known to inhibit tumor progression and regulate metabolism by targeting and degrading several cellular mRNAs, including MYC. Indeed, let-7 miRNAs are frequently repressed in several cancer types, including in MYC-driven MB. We previously reported that the mRNA translation elongation regulator eukaryotic Elongation Factor-2 Kinase (eEF2K) is a pivotal mediator of cancer cell adaptation to nutrient deprivation. In the current work, we identified a potential binding site for let-7 miRNAs on the eEF2K 3’ untranslated region (UTR). In addition, eEF2K mRNA and let-7 miRNA expressions negatively correlate in MB, suggesting a potential regulation of the former by the latter. Let-7 miRNAs transfection decreases eEF2K mRNA and protein levels (by ~40–50%). Down-regulation of luciferase activity by let-7 miRNAs is impaired upon mutation of the let-7 binding site on the eEF2K 3’UTR. Inhibition of eEF2K significantly reduces survival of MYC-amplified MB cell lines under nutrient deprivation, altering their mRNA translation rates. Knockout of eEF2K increases survival of MYC-amplified MB xenografts when mice are kept under calorie restricted diets. We conclude that let-7 miRNAs degrade the eEF2K mRNA by binding to its 3’UTR, indicating that let-7 repression in MYC-driven MB is partially responsible for increased eEF2K levels. Moreover, the let-7-eEF2K axis constitutes a critical mechanism for MYC-driven MB adaptation to acute metabolic stress, representing a promising therapeutic target. Future therapeutic studies will aim to combine eEF2K inhibition with caloric restriction mimetic drugs, as eEF2K activity appears critical under metabolic stress conditions.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".