Fatty Acid Synthase Is a Key Enabler for Endocrine Resistance in Heregulin-Overexpressing Luminal B-Like Breast Cancer
Bibliographic record
Abstract
HER2 transactivation by the HER3 ligand heregulin (HRG) promotes an endocrine-resistant phenotype in the estrogen receptor-positive (ER+) luminal-B subtype of breast cancer. The underlying biological mechanisms that link them are, however, incompletely understood. Here, we evaluated the putative role of the lipogenic enzyme fatty acid synthase (FASN) as a major cause of HRG-driven endocrine resistance in ER+/HER2-negative breast cancer cells. MCF-7 cells engineered to stably overexpress HRG (MCF-7/HRG), an in vitro model of tamoxifen/fulvestrant-resistant luminal B-like breast cancer, showed a pronounced up-regulation of FASN gene/FASN protein expression. Autocrine HRG up-regulated FASN expression via HER2 transactivation and downstream activation of PI-3K/AKT and MAPK-ERK1/2 signaling pathways. The HRG-driven FASN-overexpressing phenotype was fully prevented in MCF-7 cells expressing a structural deletion mutant of HRG that is sequestered in a cellular compartment and lacks the ability to promote endocrine-resistance in an autocrine manner. Pharmacological inhibition of FASN activity blocked the estradiol-independent and tamoxifen/fulvestrant-refractory ability of MCF-7/HRG cells to anchorage-independently grow in soft-agar. In vivo treatment with a FASN inhibitor restored the anti-tumor activity of tamoxifen and fulvestrant against fast-growing, hormone-resistant MCF-7/HRG xenograft tumors in mice. Overall, these findings implicate FASN as a key enabler for endocrine resistance in HRG+/HER2- breast cancer and highlight the therapeutic potential of FASN inhibitors for the treatment of endocrine therapy-resistant luminal-B 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".