Grb2 and Shc Adapter Proteins Play Distinct Roles in Neu (ErbB-2)-Induced Mammary Tumorigenesis: Implications for Human Breast Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Amplification of the Neu (ErbB-2 or HER-2) receptor tyrosine kinase occurs in 20 to 30% of human mammary carcinomas, correlating with a poor clinical prognosis. We have previously demonstrated that four (Y1144 Y1201, Y1227 and Y1253) of the five known Neu autophosphorylation sites can independently mediate transforming signals. The transforming potential of two of these mutants correlates with their capacity to recruit Grb2 directly to Y1144 (YB) or indirectly through Shc to Y1227 (YD). Here, we demonstrate that these transformation-competent neu mutants activate extracellular signal-regulated kinases and stimulate Ets-2-dependent transcription. Although the transforming potential of three of these mutants (YB, YD, and YE) was susceptible to inhibition by Rap1A, a genetic antagonist of Ras, the transforming potential of YC was resistant to inhibition by Rap1A. To further address the significance of these ErbB-2-coupled signaling molecules in induction of mammary cancers, transgenic mice expressing mutant Neu receptors lacking the known autophosphorylation sites (NYPD) or those coupled directly to either Grb2 (YB) or Shc (YD) adapter molecules were derived. In contrast to the NYPD strains, which developed focal mammary tumors after a long latency period with low penetrance, all female mice derived from YB and YD strains rapidly developed mammary tumors. Although female mice from several independent YB or YD lines developed mammary tumors, the YB strains developed lung metastases at substantially higher rates than the YD strains. These observations argue that Grb2 and Shc play important and distinct roles in ErbB-2/Neu-induced mammary tumorigenesis and metastasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it