Mammary epithelial cells have lineage-restricted metabolic identities
Bibliographic record
Abstract
ABSTRACT Cancer metabolism adapts the metabolic network of its tissue-of-origin. However, breast cancer is not a disease of a singular origin. Multiple epithelial populations serve as the culprit cell-of-origin for specific breast cancer subtypes, yet knowledge surrounding the metabolic network of normal mammary epithelial cells is limited. Here, we show that mammary populations have cell type-specific metabolic programs. Primary human breast cell proteomes of basal, luminal progenitor, and mature luminal populations revealed their unique enrichment of metabolic proteins. Luminal progenitors had higher abundance of electron transport chain subunits and capacity for oxidative phosphorylation, whereas basal cells were more glycolytic. Targeting oxidative phosphorylation and glycolysis with inhibitors exposed distinct metabolic vulnerabilities of the mammary lineages. Computational analysis indicated that breast cancer subtypes retain metabolic features of their putative cell-of-origin. Lineage-restricted metabolic identities of normal mammary cells partly explain breast cancer metabolic heterogeneity and rationalize targeting subtype-specific metabolic vulnerabilities to advance breast cancer therapy.
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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 | 0.001 | 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".