Deletion of STAT5 prevents HER2/Neu/ErbB2-induced mammary tumor development.
Bibliographic record
Abstract
Abstract Abstract #3045 HER2 (ErbB2/Neu in rodents) is overexpressed in a number of breast cancers and it activates several intracellular signaling pathways by recruiting adaptor proteins. Among them, Shc or Gab2 signaling mediates ErbB2/Neu-induced mammary tumor progression. HER2 activates the transcription factors STAT5A/B but their contribution to the etiology of breast cancer remains to be elucidated. STAT5 mediates signals from a wide variety of cytokine receptors, including the EGFR and ErbB4. Further, constitutive activation of STAT5 has been observed in human breast cancer, leukemia and many solid tumors. To address whether STAT5 mediates HER2/ErbB2/Neu-induced breast cancer progression, both Stat5 genes were deleted specifically in ErbB2/Neu oncogene (known as HER2 in human)-expressing mammary epithelial cells in mice. Briefly, transgenic mice carrying floxed Stat5 alleles (Stat5fl/fl mice) were mated with transgenic MMTV/NIC mice expressing both activated Neu/ErbB2 and Cre recombinase from the same bicistronic transcript due to the presence of an internal ribosome entry site (IRES) between the two cDNA sequences (NIC) under the control of mouse mammary tumor virus (MMTV) long terminal repeat. Whole mount staining of mammary tissue of MMTV/NIC mice demonstrated that mammary glands of control virgin NIC mice (MMTV/NIC;Stat5+/+) exhibited hyperplastic lesions at 5 months of age, while no lesions were detected in NIC mice that lacked STAT5 (MMTV/NIC;Stat5fl/fl). Histological analysis revealed the absence of hyperplastic or neoplastic lesions in MMTV/NIC;Stat5fl/fl mammary glands. These results indicate that inactivation of Stat5 results in the absence of hyperplasias in spite of overexpression of ErbB2/Neu in mammary epithelium and suggest that activation of STAT5 contributes to the development of HER2-induced breast cancer. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 3045.
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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 | 0.001 | 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) | 0.004 | 0.001 |
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".