Uncoupling of PI3K from ErbB3 Impairs Mammary Gland Development but Does Not Impact on ErbB2-Induced Mammary Tumorigenesis
Bibliographic record
Abstract
The formation of ErbB2/ErbB3 heterodimers plays a critical role in ErbB2-mediated signaling in both normal mammary development and mammary tumor progression. Through 7 phosphoinositide 3-kinase (PI3K) phosphotyrosine-binding sites, ErbB3 is able to recruit PI3K and initiate the PI3K/AKT signaling pathway. To directly explore the importance of the ErbB3/PI3K pathway in mammary development and tumorigenesis, we generated a mouse model that carries a mutant ErbB3 allele lacking the seven known PI3K-binding sites (ErbB3(Δ85)). Mice homozygous for the ErbB3(Δ85) allele exhibited an initial early growth defect and a dramatic impairment of mammary epithelial outgrowth. Although homozygous adult mice eventually recovered from the growth defect, their mammary glands continued to manifest the mammary outgrowth and lactation defects throughout their adult life. Interestingly, despite the presence of a profound mammary gland defect, all of the female ErbB3Δ85 mice developed metastatic ErbB2-induced mammary tumors secondary to mammary epithelial expression of an activated ErbB2 oncogene capable of compensatory PI3K signaling from both EGF receptor and ErbB2. Our findings therefore indicate that, although ErbB3-associated PI3K activity is critical for mammary development, it is dispensable for ErbB2-induced mammary tumor progression.
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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) | 0.002 | 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".