A fatty acid‐binding protein 7/RXRβ pathway enhances survival and proliferation in triple‐negative breast cancer
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".