FABP7 Progenitors are a Targetable Metabolic Root in the <i>BRCA1</i> Breast
Bibliographic record
Abstract
Abstract It has been nearly 3 decades since the discovery of the BRCA1/2 genes and their link to breast cancer risk, with prophylactic mastectomy remaining the primary management option for these high-risk mutation carriers. The current paucity of interception strategies is due to undefined, targetable cancer precursor populations in the high-risk breast. Despite known cellular alterations in the BRCA1 breast, epithelial populations at the root of unwarranted cell state transitions remain unresolved. Here, we identify a root progenitor population that is dysregulated in BRCA1 carriers stemming from the metabolic role of BRCA1. This fatty-acid binding protein 7 (FABP7) expressing luminal progenitor population is spatially confined to the mammary ducts, has enhanced clonogenic capacity, and is the predicted origin of mixed basal-luminal differentiation in the BRCA1 but not BRCA2 breast. We show global H3K27 acetylation is reduced within ductal FABP7 cells in BRCA1 carriers in situ , linking to a non-canonical metabolic role of BRCA1 in regulating acetyl-CoA pools and de novo fatty acid synthesis. We demonstrate FABP7 progenitor capacity is preferentially ablated in BRCA1 carriers through inhibition of fatty acid metabolism using an FDA-approved fatty acid synthase (FASN) inhibitor. This study lays the foundation for metabolic control of breast progenitor dynamics to mitigate breast cancer risk in the BRCA1 breast.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".