N-Cadherin Signaling Potentiates Mammary Tumor Metastasis via Enhanced Extracellular Signal-Regulated Kinase Activation
Bibliographic record
Abstract
N-cadherin is up-regulated in aggressive breast carcinomas, but its mechanism of action in vivo remains unknown. Transgenic mice coexpressing N-cadherin and polyomavirus middle T antigen (PyVmT) in the mammary epithelium displayed increased pulmonary metastasis, with no differences in tumor onset or growth relative to control PyVmT mice. PyVmT-N-cadherin tumors contained higher levels of phosphorylated extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK) than PyVmT controls, and phosphorylated ERK staining was further increased in pulmonary metastases. Tumor cell isolates from PyVmT-N-cadherin mice exhibited enhanced ERK activation, motility, invasion, and matrix metalloproteinase-9 (MMP-9) expression relative to PyVmT controls. MAPK/ERK kinase 1 inhibition in PyVmT-N-cadherin cells reduced MMP-9 production and invasion but not motility. Furthermore, inactivation of fibroblast growth factor receptor in PyVmT-N-cadherin cells reduced motility, invasion, and ERK activation but had no effect on PyVmT cells. Thus, de novo expression of N-cadherin in mammary ducts enhances metastasis of breast tumors via enhanced ERK signaling.
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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".