Inhibition of the HER2 pathway by n-3 polyunsaturated fatty acids prevents breast cancer in fat-1 transgenic mice
Bibliographic record
Abstract
Overexpression of the tyrosine kinase receptor, ErbB2/HER2/Neu, occurs in 25-30% of invasive breast cancer (BC) with poor patient prognosis. Due to confounding factors, inconsistencies still remain regarding the protective effects of n-3 polyunsaturated fatty acids (PUFAs) on BC. We therefore evaluated whether fat-1 transgenic mice, endogenously synthesizing n-3 PUFAs from n-6 PUFAs, were protected against BC development, and we then aimed to study in vivo a mechanism potentially involved in such protection. E0771 BC cells were implanted into fat-1 and wild-type (WT) mice. After tumorigenesis examination, we analyzed the expression of proteins involved in the HER2 signaling pathway and lipidomic analyses were performed in tumor tissues and plasma. Our results showed that tumors totally disappeared by day 15 in fat-1 mice but continued to grow in WT mice. This prevention can be related in part to significant repression of the HER2/β-catenin signaling pathway and formation of significant levels of n-3 PUFA-derived bioactive mediators (particularly 15-hydroxyeicosapentaenoic acid, 17-hydroxydocosahexaenoic acid, and prostaglandin E3) in the tumors of fat-1 mice compared with WT mice. All together these data demonstrate an anti-BC effect of n-3 PUFAs through, at least in part, HER2 signaling pathway downregulation, and highlight the importance of gene-diet interactions in BC.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".