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Record W1574588412 · doi:10.1002/bies.201400085

How does oncogene transformation render tumor cells hypersensitive to nutrient deprivation?

2014· article· en· W1574588412 on OpenAlexafffund
Gabriel Leprivier, Poul H. Sorensen

Bibliographic record

VenueBioEssays · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of British Columbia
FundersCanadian Cancer Society Research InstituteConquer Cancer Foundation
KeywordsCell biologyReprogrammingBiologyOncogeneRegulatorMechanism (biology)Cancer researchCellCell cycleBiochemistryGene

Abstract

fetched live from OpenAlex

Oncogene activation leads to cellular transformation by deregulation of biological processes such as proliferation and metabolism. Paradoxically, this can also sensitize cells to nutrient deprivation, potentially representing an Achilles' heel in early stage tumors. The mechanisms underlying this phenotype include loss of energetic and redox homeostasis as a result of metabolic reprogramming, favoring synthesis of macromolecules. Moreover, an emerging mechanism involving the deregulation of mRNA translation elongation through inhibition of eukaryotic elongation factor 2 kinase (eEF2K) is presented. The potential consequences of eEF2K deregulation leading to cell death under nutrient depletion are discussed. Finally, the relevance of eEF2K as a master regulator of the response to nutrient deprivation in vivo, and its potential exploitation for therapeutic targeting of cancers, are elaborated. Overall, a better understanding of the adaptive mechanisms allowing tumors to circumvent oncogene-induced hypersensitivity to nutrient deprivation is a promising avenue for uncovering novel therapeutic targets in cancers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.425
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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 teacher head, 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

Citations9
Published2014
Admission routes2
Has abstractyes

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