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Record W2767379037 · doi:10.1093/neuonc/nox168.808

PDTM-46. TARGETING METABOLIC ADAPTATION IN MYC DRIVEN PEDIATRIC NEURONAL TUMORS

2017· article· en· W2767379037 on OpenAlexaff
Alberto Delaidelli, Gian Luca Negri, Asad Jan, Brandon Jansonius, Jonathan Lim, Gabriel Leprivier, Marcel Kool, Stefan M. Pfister, Marc Remke, Michael D. Taylor, John M. Maris, Poul H. Sorensen

Bibliographic record

VenueNeuro-Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsHospital for Sick ChildrenUniversity of British Columbia
Fundersnot available
KeywordsGene knockdownCancer researchNeuroblastomaN-MycBiologyPediatric cancerSynthetic lethalityCell cultureCancerGeneGeneticsMutant

Abstract

fetched live from OpenAlex

MYC family proteins are implicated in many human cancers, but their therapeutic targeting has proven challenging. MYCN and c-MYC amplification in childhood neuroblastoma (NB) and medulloblastoma (MB) are associated with aggressive disease and high mortality. Novel and effective therapeutic strategies are therefore urgently needed for these tumors. MYC-driven oncogenic transformation impairs cell survival under nutrient deprivation (ND), a characteristic stress condition within the tumor microenvironment. We recently identified eukaryotic Elongation Factor 2 Kinase (eEF2K) as a pivotal mediator of the adaptive response of tumor cells to ND. We therefore hypothesized that eEF2K facilitates the adaptation of MYCN/MYC amplified NB/MB to ND, and that inhibiting this pathway can impair tumor progression. To test our hypothesis, we first analyzed publicly available genomic databases and tissue microarrays for eEF2K expression in NB and MB, and for links between eEF2K, MYCN/MYC, and clinical outcome. Effects of eEF2K inhibition were evaluated on survival of MYCN/MYC amplified versus non-amplified NB/MB cell lines under ND. Finally, NB xenograft mouse models were used to confirm in vitro observations. Our results indicate that high eEF2K expression and activity are strongly predictive of poor outcome in NB and MB (p<0.001), and correlate significantly with MYCN/MYC amplification (p<0.001). Inhibition of eEF2K significantly decreases survival of MYCN/MYC amplified NB/MB cell lines in vitro under ND. Knockdown of eEF2K under caloric restriction determines a twofold growth decrease of MYCN amplified NB xenografts. eEF2K represents a critical mediator for the adaptive response of MYCN/MYC amplified NB and MB to acute metabolic stress, and is therefore a promising therapeutic target. Future therapeutic studies will aim to combine eEF2K pharmacological inhibition with caloric restriction mimetics such as metformin or glycolysis inhibitors, as eEF2K activity appears to be critical under metabolic stress conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.036
GPT teacher head0.339
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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