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Record W2038146634 · doi:10.1073/pnas.1008136107

Combined deficiency for MAP kinase-interacting kinase 1 and 2 (Mnk1 and Mnk2) delays tumor development

2010· article· en· W2038146634 on OpenAlexafffund
Takeshi Ueda, Masato Sasaki, Andrew Elia, Iok In Christine Chio, Koichi Hamada, Rikiro Fukunaga, Tak W. Mak

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
FundersCanadian Institutes of Health Research
KeywordsEIF4EKinaseCancer researchPTENBiologyPhosphorylationp38 mitogen-activated protein kinasesCarcinogenesisMitogen-activated protein kinaseMAPK/ERK pathwayKnockout mouseSerineProtein kinase ATranslation (biology)Cell biologySignal transductionPI3K/AKT/mTOR pathwayCancerBiochemistryGeneGeneticsMessenger RNA

Abstract

fetched live from OpenAlex

MAP kinase-interacting kinase 1 and 2 (Mnk1 and Mnk2) are protein-serine/threonine kinases that are activated by ERK or p38 and phosphorylate eIF4E, which is involved in cap-dependent translation initiation. However, Mnk1/2 double knockout (Mnk-DKO) mice show normal cell growth and development despite an absence of eIF4E phosphorylation. Here we show that the tumorigenesis occurring in the Lck-Pten mouse model (referred to here as tPten(-/-) mice) can be suppressed by the loss of Mnk1/2. Phosphorylation of eIF4E was greatly enhanced in lymphomas of parental tPten(-/-) mice compared with lymphoid tissues of wild-type mice, but was totally absent in lymphomas of tPten(-/-); Mnk-DKO mice. Notably, stable knockdown of Mnk1 in the human glioma cell line U87MG resulted in dramatically decreased tumor formation when these cells were injected into athymic nude mice. Our data demonstrate an oncogenic role for Mnk1/2 in tumor development, and highlight these molecules as potential anticancer drug targets that could be inactivated with minimal side effects.

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)0.001
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 score0.008
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.024
GPT teacher head0.300
Teacher spread0.277 · 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

Citations200
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPI3K/AKT/mTOR signaling in cancerFrench-language works237,207