Amplification of the <i>neu/erbB-2</i> oncogene in a mouse model of mammary tumorigenesis
Bibliographic record
Abstract
The neu (c-erbB-2, Her-2) protooncogene is amplified and overexpressed in 20-30% of human breast cancers. Although transgenic mouse models have illustrated the role of Neu in the induction of mammary tumors, Neu expression in these models is driven by a strong viral promoter of questionable relevance to the human disease. To ascertain whether expression of activated Neu under the control of the endogenous promoter in the mammary gland could induce mammary tumors we have generated mice that conditionally express activated Neu under the transcriptional control of the intact endogenous Neu promoter. Expression of oncogenic neu in the mammary gland resulted in accelerated lobulo-alveolar development and formation of focal mammary tumors after a long latency period. However, expression of activated Neu under the normal transcriptional control of the endogenous promoter was not sufficient for the initiation of mammary carcinogenesis. Strikingly, all mammary tumors bear amplified copies (2-22 copies) of the activated neu allele relative to the wild-type allele and express highly elevated levels of neu transcript and protein. Thus, like human erbB-2-positive breast tumors, mammary tumorigenesis in this mouse model requires the amplification and commensurate elevated expression of the neu gene.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".