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Record W2099803758 · doi:10.1002/path.4001

A fatty acid‐binding protein 7/RXRβ pathway enhances survival and proliferation in triple‐negative breast cancer

2012· article· en· W2099803758 on OpenAlexaff
Rong‐Zong Liu, Kathryn Graham, Darryl Glubrecht, Raymond Lai, John R. Mackey, Roseline Godbout

Bibliographic record

VenueThe Journal of Pathology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of Alberta
FundersCancer Research Institute
KeywordsTriple-negative breast cancerBreast cancerCancer researchCancerChemistryInternal medicineBiologyOncologyMedicine

Abstract

fetched live from OpenAlex

FABP7 has been implicated in tumour cell proliferation, cell migration, and poor prognosis in patients with high-grade astrocytoma and melanoma. In this study, we examine FABP7 expression in a cohort of 176 primary breast cancers by gene profiling and tissue microarray immunostaining. We show that FABP7 is significantly up-regulated in triple-negative breast cancer. Elevated FABP7 levels are associated with poor prognosis, absence of oestrogen and progesterone hormone receptors (ER, PR) and HER2, increased cell proliferation, and high tumour grade. Depletion of FABP7 in the ER/PR-negative cell line, MDA-MB-435S, significantly reduced cell growth rate and sensitized the cells to growth inhibition by omega-3 docosahexaenoic acid (DHA). A target of DHA-bound FABP7 in the nucleus is RXRβ, a retinoid-activated nuclear receptor that functions as a transcription factor by either homodimerizing or heterodimerizing with other nuclear receptors such as PPARs. Based on our microarray data, RXRβ, like FABP7, is an adverse prognostic factor for breast cancer. We propose that the DHA-FABP7-RXRβ pathway promotes cell survival/proliferation in triple-negative breast cancer. Targeting this pathway may thus provide an alternate route for the treatment of triple-negative breast cancer.

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 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 score0.078
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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

Citations68
Published2012
Admission routes1
Has abstractyes

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