A tumor-suppressive function for Notch3 in the parous mammary gland
Bibliographic record
Abstract
Notch3 promotes mammary luminal cell specification and forced Notch3 activation can induce mammary tumor formation. However, recent studies suggest a tumor-suppressive role for Notch3. Here, we report on Notch3 expression and functional analysis in the mouse mammary gland. Notch3 is expressed in the luminal compartment throughout mammary gland development, but switches to basal cells with initiation of post-lactational involution. Deletion of Notch3 caused a decrease of Notch activation in luminal cells and diminished luminal progenitors at puberty, as well as reduced alveolar progenitors during pregnancy. Parous Notch3-/- mammary glands developed hyperplasia with accumulation of CD24hiCD49flo cells, some of which progressed to invasive tumors with luminal features. Notch3 deletion abolished Notch activation in basal cells during involution, accompanied by altered apoptosis and reduced brown adipocytes, leading to expansion of parity-identified mammary epithelial cells (PI-MECs). Interestingly, the postpartum microenvironment is required for the stem cell activity of Notch3-/- PI-MECs. Finally, high expression of NOTCH3 is associated with prolonged survival in patients with luminal breast cancer. These results highlight an unexpected tumor-suppressive function for Notch3 in the parous mammary gland through restriction of PI-MEC expansion.
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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".