Abstract B27: A link between small noncoding RNAs and mRNA translation elongation: The let7-eEF2K axis in pediatric tumor adaptation to nutrient deprivation
Bibliographic record
Abstract
Abstract Background: Medulloblastoma (MB) and neuroblastoma (NB) are the most common pediatric solid cancers and the leading cause of childhood cancer-related deaths. Genetic amplifications of the MYC and MYCN oncogenes are the strongest independent predictor of adverse outcomes in MB and NB, underscoring a dire need to improve therapeutic approaches. Tumors continually weather stress from acute microenvironmental changes, including limited nutrient availability. The let-7 family of small noncoding RNAs (miRNAs) inhibits tumor progression and regulates metabolism by selectively targeting and degrading mRNAs, including MYC and MYCN. Indeed, let-7 miRNAs are frequently repressed in several cancers, including in MYC-driven MB and NB. We previously reported that the mRNA translation elongation regulator eukaryotic eEF2K is a pivotal mediator of cancer cell adaptation to nutrient deprivation. Our preliminary data indicate that the eEF2K 3´ untranslated region (UTR) harbors a potential binding site for let-7 miRNAs. In addition, eEF2K mRNA and let-7 miRNA expressions negatively correlate in MB and NB. We therefore hypothesized that let-7 downregulation induces eEF2K expression, thereby supporting MYC-driven MB and NB adaptation to nutrient deprivation and tumor progression. Methods: Effects of eEF2K pharmacologic and genetic inhibition on MB and NB cell death were evaluated in vitro by flow cytometry, while cellular mRNA translation rates were studied by polysome fractionation and Click chemistry. 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 assay. Finally, NB xenograft mouse models confirmed in vitro observations. Results: Inhibition of eEF2K significantly reduces survival of MYC/MYCN-amplified NB and MB cell lines under nutrient deprivation, altering their mRNA translation rates. Let-7 miRNAs transfection decreases eEF2K mRNA and protein levels by 40-50%. Downregulation of luciferase activity by let-7 miRNAs is impaired upon mutation of the let-7 binding site on the eEF2K 3´UTR. eEF2K knockdown decreases growth twofold in MYCN-amplified NB xenografts in mice under calorie-restriction diets. Conclusions: Let-7 miRNAs degrade the eEF2K mRNA by binding to its 3´UTR, indicating that let-7 repression in MYC-driven NB and MB is partially responsible for increased eEF2K levels. Moreover, the let-7-eEF2K axis constitutes a critical mechanism for MYC-driven MB and NB 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. Citation Format: Alberto Delaidelli, Gian Luca Negri, Xue Qi Wang, Simran Sidhu, Brian Cho, Gabriel Leprivier, Volker Hovestadt, Stefan Pfister, Michael Taylor, Marcel Kool, Poul Sorensen. A link between small noncoding RNAs and mRNA translation elongation: The let7-eEF2K axis in pediatric tumor adaptation to nutrient deprivation [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B27.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".