Mammary epithelial-specific disruption of c-Src impairs cell cycle progression and tumorigenesis
Bibliographic record
Abstract
The tyrosine kinase c-Src is activated in a large proportion of breast cancers, in which it is thought to play a key role in promoting the malignant phenotype. c-Src activity is also elevated in transgenic mouse models of breast cancer, including the widely used polyomavirus middle-T antigen (PyVmT) model, which provides an opportunity to study the importance of c-Src in mammary tumorigenesis. However, germline c-Src deletion in mammary epithelial and stromal compartments complicates the interpretation of in vivo tumorigenesis studies as a result of severe defects in mammary gland development. We have therefore engineered a mouse strain in which deletion of c-Src can be targeted to the mammary epithelium. We demonstrate that mammary epithelial disruption of c-Src impairs proliferation and tumor progression driven by PyVmT in vivo. Whereas related kinases substitute for c-Src in PyVmT signaling, c-Src ablation impairs cell cycle progression with decreased cyclin expression and elevated expression of cyclin-dependent kinase inhibitors. Our data indicate that c-Src has essential and unique functions in proliferation and tumor progression in this mouse model that may also be important in certain contexts in some human breast cancers.
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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) | 0.001 | 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".