A Requirement for p120-catenin in the metastasis of invasive ductal breast cancer
Bibliographic record
Abstract
We have examined the effects of targeted p120 KO in a PyMT mouse model of invasive ductal (mammary) cancer (IDC). Mosaic p120 ablation had little effect on primary tumor growth but caused significant pro-metastatic alterations in the tumor microenvironment leading ultimately to a marked increase in the number and size of pulmonary metastases. Surprisingly, although early effects of p120-ablation included decreased cell-cell adhesion and increased invasiveness, cells lacking p120 were almost entirely unable to colonized distant metastatic sites in vivo. The relevance of this observation to human IDC was established by analysis of a large clinical dataset of 1126 IDCs. As reported by others, p120 downregulation in primary IDC predicted worse overall survival. However, as in the mice, distant metastases were almost invariably p120 positive, even in matched cases where the primary tumors were p120 negative. Collectively, our results demonstrate a strong positive role for p120 (and presumably E-cadherin) during metastatic colonization of distant sites. On the other hand, downregulation of p120 in the primary tumor enhanced metastatic dissemination indirectly via pro-metastatic conditioning of the tumor microenvironment.
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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".