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Abstract P4-03-02: Establishing a Relationship between Breast Cancer, Prolactin and Altered Fat Metabolism

2010· article· en· W2320231577 on OpenAlexaffabout
Katja Linher, Gurmit Singh

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEndocrinologyInternal medicineAMPKLipogenesisBreast cancerFatty acid synthaseCarnitineBiologyCancerLipid metabolismProtein kinase AMedicineKinaseBiochemistry

Abstract

fetched live from OpenAlex

Abstract Despite decades of research, breast cancer remains one of the most common cancers world-wide. Mammary carcinoma has been associated with a high-fat diet, and its rate in overweight post-menopausal women is up to 50% higher than in normal-weight women. The current study examined breast cancer as a metabolic disease in the context of altered fat catabolism, with a focus on examining the effects of prolactin (PRL) on the adenosine 5'-monophosphate-activated protein kinase (AMPK) energy sensing pathway that culminates with carnitine palmitoyl transferase 1 (CPT1), an enzyme that shuttles long-chain fatty acids into the mitochondrial matrix for beta oxidation. When a cell has high energy demands or is stressed, AMPK activation leads to either increased glucose uptake or the phosphorylation of acetyl-CoA carboxylase (ACC), resulting in a reduction in malonyl-CoA levels that lift an allosteric inhibition on CPT1, in turn leading to an increase in CPT1 enzyme activity. Conversely, increased malonyl-CoA levels, together with increased fatty acid synthase activity, favor lipogenesis. PRL has been shown to affect fat metabolism in adipocytes by altering malonyl-CoA levels, and we therefore examined whether CPT1 expression was altered in breast cancer cells in response to treatment with recombinant human PRL. The metabolic effects of this hormone, which is normally produced in breast tissue and has been epidemiologically linked with breast cancer, were investigated in a normal human breast epithelial cell line (184B5) and in breast cancer cells. PRL up-regulated CPT1 expression at both the mRNA and protein levels in cancer cells, but not in 184B5 cells. Of note, compared to MCF-7 or MDA-MB-231 cells, T47D cells expressed the highest levels of CPT1. The 85 kDa PRL receptor isoform was also highly expressed in this cell line compared to 184B5 or MCF-7 cells. Furthermore, PRL dose-dependently increased CPT1 enzyme activity in T47D cells, also inducing the phosphorylation of both the AMPKα catalytic subunit at threonine 172 and ACC. In T47D cells treated with AMPKα siRNA, transient knock-down of the catalytic AMPK subunit correlated with a similar knock-down in CPT1 mRNA levels. CPT1 levels in the knock-down cells could not be restored by treatment with PRL, suggesting that the PRL-mediated effect requires activation of the AMPK pathway. We also demonstrated that treatment with PRL leads to the phosphorylation of TAK1 and LKB1, two kinases that are known to activate AMPKα. It is known that PRL contributes to breast cancer by inducing cell proliferation, survival, motility, and angiogenesis. Our work proposes a novel role for this hormone in mammary carcinogenesis through its effect on fat metabolism via the induction of the AMPK pathway. Elucidating how breast cancer cells differentially produce and utilize energy compared to normal breast epithelial cells may lead to the development of new therapies for the treatment or improved management of this complex disease. (Research supported by Canadian Institutes of Health Research.) Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P4-03-02.

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)0.001
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.062
GPT teacher head0.382
Teacher spread0.319 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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