Epithelial Protein-Tyrosine Phosphatase 1B Contributes to the Induction of Mammary Tumors by HER2/Neu but Is Not Essential for Tumor Maintenance
Bibliographic record
Abstract
Protein-tyrosine phosphatase 1B (PTP1B), a well-established metabolic regulator, plays an important role in breast cancer. Using whole-body PTP1B knockout mice, recent studies have shown that PTP1B ablation delays HER2/Neu-induced mammary cancer. Whether PTP1B plays a cell-autonomous or a noncell-autonomous role in HER2/Neu-evoked tumorigenesis and whether it is involved in tumor maintenance was unknown. We generated mice expressing HER2/Neu and lacking PTP1B specifically in the mammary epithelium. We found that mammary-specific deletion of PTP1B delays the onset of HER2/Neu-evoked mammary tumors, establishing a cell autonomous role for PTP1B in such neoplasms. We also deleted PTP1B in established mouse mammary tumors or depleted PTP1B in human breast cancer cell lines grown as xenografts. PTP1B inhibition did not affect tumor growth in either model showing that neither epithelial nor stromal PTP1B is necessary for tumor maintenance. Taken together, our data show that despite the PTP1B contribution to tumor onset, it is not essential for tumor maintenance. This suggests that PTP1B inhibition could be effective in breast tumor prevention.
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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".