The Shc adaptor protein is critical for VEGF induction by Met/HGF and ErbB2 receptors and for early onset of tumor angiogenesis
Bibliographic record
Abstract
The etiology and progression of a variety of human malignancies are linked to the deregulation of receptor tyrosine kinases (RTKs). To define the role of RTK-dependent signals in various oncogenic processes, we have previously engineered RTK oncoproteins that recruit either the Shc or Grb2 adaptor proteins. Although these RTK oncoproteins transform cells with similar efficiencies, fibroblasts expressing the Shc-binding RTK oncoproteins induced tumors with short latency (approximately 7 days), whereas cells expressing the Grb2-binding RTK oncoproteins induced tumors with delayed latency (approximately 24 days). The early onset of tumor formation correlated with the ability of cells expressing the Shc-binding RTK oncoproteins to produce vascular endothelial growth factor (VEGF) in culture and an angiogenic response in vivo. Consistent with this, treatment with a VEGF inhibitor, VEGF-Trap, blocked the in vivo angiogenic and tumorigenic properties of these cells. The importance of Shc recruitment to RTKs for the induction of VEGF was further demonstrated by using mutants of the Neu/ErbB2 RTK, where the Shc, but not Grb2, binding mutant induced VEGF. Moreover, the use of fibroblasts derived from ShcA-deficient mouse embryos, demonstrated that Shc was essential for the induction of VEGF by the Met/hepatocyte growth factor RTK oncoprotein and by serum-derived growth factors. Together, our findings identify Shc as a critical angiogenic switch for VEGF production downstream from the Met and ErbB2 RTKs.
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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 | 0.000 |
| 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".