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Record W2769603806 · doi:10.1155/2017/6098107

The eIF4E2‐Directed Hypoxic Cap‐Dependent Translation Machinery Reveals Novel Therapeutic Potential for Cancer Treatment

2017· review· en· W2769603806 on OpenAlexafffund
Gaelan Melanson, Sara Timpano, James Uniacke

Bibliographic record

VenueOxidative Medicine and Cellular Longevity · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsUniversity of Guelph
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanadian Cancer SocietyCanadian Institutes of Health ResearchCancer Research Society
KeywordsEIF4ETranslation (biology)Cancer researchCancerMetastasisHypoxia (environmental)Cancer cellBiologyTumor microenvironmentGeneMessenger RNATumor cellsChemistryGenetics

Abstract

fetched live from OpenAlex

Hypoxia is an aspect of the tumor microenvironment that is linked to radiation and chemotherapy resistance, metastasis, and poor prognosis. The ability of hypoxic tumor cells to achieve these cancer hallmarks is, in part, due to changes in their gene expression profiles. Cancer cells have a high demand for protein synthesis, and translational control is subsequently deregulated. Various mechanisms of translation initiation are active to improve the translation efficiency of select transcripts to drive cancer progression. This review will focus on a noncanonical cap-dependent translation initiation mechanism that utilizes the eIF4E homolog eIF4E2, a hypoxia-activated cap-binding protein that is implicated in hypoxic cancer cell migration, invasion, and tumor growth in mouse xenografts. A historical perspective about eIF4E2 and its various aliases will be provided followed by an evaluation of potential therapeutic strategies. The recent successes of disabling canonical translation and eIF4E with drugs should highlight the novel therapeutic potential of targeting the homologous eIF4E2 in the treatment of hypoxic solid tumors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.102
GPT teacher head0.365
Teacher spread0.264 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations43
Published2017
Admission routes2
Has abstractyes

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