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MS3-3: Energy Metabolism in Breast Cancer: Translational Science Insights Relevant to Effects of Diet, Exercise, and Metformin on Risk and Prognosis.

2011· article· en· W2320971620 on OpenAlexaff
Michaël Pollak

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMetforminBreast cancerInsulinMedicineInternal medicineEndocrinologyCancerCarcinogenesisHormoneDiabetes mellitusOncologyCancer research

Abstract

fetched live from OpenAlex

Abstract Energy metabolism is relevant to breast cancer at both the cellular and whole organism levels. Whole organism energy balance determines body mass, which has been associated with variations in both breast cancer risk and prognosis. Experimentally, breast carcinogenesis is facilitated by excess caloric intake and inhibited by caloric restriction. The simplistic notion that excess food intake provides additional energy to breast epithelial cells at risk for transformation or to breast cancers, leading to aggressive behavior, is not supported by experimental data. Rather, variations in energy balance have important influences on the hormonal and cytokine environment of the patient, and these influence carcinogenesis and tumor behaviour. Experimental models provide evidence that one such mediating hormone is insulin. Most breast cancers have insulin receptors. When mice with breast cancer are experimentally manipulated to have insulin deficiency (type I) diabetes, tumor growth rate is slowed (despite hyperglycemia). Conversley, when mice are provided with a “junk food” diet, insulin levels rise, tumor insulin receptor activation increases, and tumors grow more quickly. However, when breast cancers evolve to have activating muations in signalling networks downstream of insulin receptors, they become more aggressive and unresponsive to variations in energy intake and insulin no longer influences their behavior. There is retrospective pharmacoepidemiologic evidence for a substantial ( ∼50%) reduction in breast cancer risk in type II (hyperinsulinemic) diabetic patients prescribed metformin. This has contributed to current interest in the hypothesis that metformin has uses in cancer prevention or treatment. Metformin acts to reduce cellular ATP production by inhibiting mitochondrial respiratory complex I. This results in activation of AMPK. In liver, this results in reduced gluconeogenesis, which reduces the hyperglycemia and hyperinsulinemia of type II diabetes. This systemic effect may reduce proliferation of the subset of neoplasms that are growth stimulated by insulin, but does not operate in the absence of baseline hyperinsulinemia. Other mechanisms of metformin action involve direct effects on at-risk or transformed cells. These mechanisms require adequate levels of the drug in the relevant cells, but metformin doses used in diabetes treatment may not achieve optimum concentrations in cancers, particularly those that lack the active transport molecules responsible for cellular metformin uptake. Overall, laboratory studies suggest that any benefits of metformin will not be homogeneous among a population of at-risk women in a prevention context, nor among breast cancer patients in a treatment context. The validation of candidate predictive biomarkers for metformin benefit, together with more detailed pharmokinetic data, may allow for optimized clinical trial design. Further research is also required to clarify if metformin should best be evaluated as a single agent or in combinations. Thus, metformin and derivatives can be regarded as lead compounds for optimization, and this line of research may lead to novel metabolic approaches to breat cancer prevention and treatment. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr MS3-3.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.311
Teacher spread0.288 · 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 designObservational
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

Citations1
Published2011
Admission routes1
Has abstractyes

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