MétaCan
Menu
← Back to cohort
Record W1647140950

Metformin mediated AMPK activation inhibits translation initiation in breast cancer cells

2007· article· en· W1647140950 on OpenAlexaff
Ryan J.O. Dowling, Mahvash Zakikhani, Nahum Sonenberg, Michaël Pollak

Bibliographic record

VenueCancer Research · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcGill University
Fundersnot available
KeywordsMetforminAMPKPI3K/AKT/mTOR pathwayP70-S6 Kinase 1Protein kinase AAMP-activated protein kinasemTORC1EndocrinologyCell growthCancer researchInternal medicineChemistryKinaseSignal transductionBiologyCell biologyMedicineBiochemistryInsulin
DOInot available

Abstract

fetched live from OpenAlex

4470 The antidiabetic drug metformin lowers blood glucose by decreasing hepatic gluconeogenesis and stimulating glucose uptake in muscle. Some of the beneficial effects of metformin have been linked to the activation of the AMP activated protein kinase (AMPK) in muscle, adipose tissue, and liver, but effects of metformin on normal or transformed epithelial cells have not been well characterized. Upon activation, AMPK phosphorylates a number of effector proteins leading to the activation of ATP generating pathways, and the inhibition of ATP consuming pathways, such as protein synthesis. AMPK mediates its effects on protein synthesis through inhibition of the serine/threonine kinase, mTOR (mammalian target of rapamycin). mTOR is a major regulator of mRNA translation, and its effects on protein synthesis are mediated by two of its direct targets: the eIF4E binding proteins (4E-BPs) and the S6 protein kinase (S6K1), which are involved in regulating mRNA translation initiation. Inappropriate activation of mTOR can lead to increased cell growth, proliferation and neoplasia. Therefore, the inhibition of mTOR is being explored as a potential anti-cancer therapy. Recently we demonstrated ( Cancer Research 66:10269, 2006) that metformin inhibited the growth of breast cancer cells through the activation of AMPK. To extend this, we studied the effects of metformin on protein synthesis. Cells were treated with increasing doses of metformin for 24 hours and overall cellular translation was assessed by incorporation of 35 S methionine. In the breast cancer cell line MCF-7, metformin treatment led to a 30% decrease in protein synthesis. More specifically, the effect of metformin on cap-dependent translation was examined using a bicistronic reporter assay. Under these conditions, metformin caused a dose dependent decrease in cap-dependent translation, with a maximal inhibition of 40% at a dose of 20 mM. Polysome profile analysis also indicated an inhibition of translation initiation as metformin treatment of MCF-7 cells led to a decrease in heavy polysomes and a concomitant increase in the amount of 80S monosomes. The effects of metformin on translation were specifically mediated by AMPK, as treatment of cells with the AMPK inhibitor Compound C reversed the inhibition of protein synthesis. Furthermore, MDAMB-231 cells, which lack the AMPK regulator LKB1, were unaffected by metformin treatment. The effect of metformin on cellular translation was associated with mTOR inhibition and a decrease in the phosphorylation of ribosomal protein S6, and 4E-BP1. These results demonstrate that metformin-mediated AMPK activation leads to an inhibition of mTOR and a reduction in translation initiation, thus providing a mechanism for direct inhibition of cancer cell growth, separate from any growth inhibition that may relate to metformin-induced reduction of insulin levels in vivo .

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.058
GPT teacher head0.383
Teacher spread0.326 · 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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicMetabolism, Diabetes, and Cancer→French-language works237,207→