Identification and Functional Analysis of Phosphorylated Tyrosine Residues within EphA2 Receptor Tyrosine Kinase
Bibliographic record
Abstract
EphA2 is a member of the Eph family of receptor tyrosine kinases. EphA2 mediates cell-cell communication and plays critical roles in a number of physiological and pathologic responses. We have previously shown that EphA2 is a key regulator of tumor angiogenesis and that tyrosine phosphorylation regulates EphA2 signaling. To understand the role of EphA2 phosphorylation, we have mapped phosphorylated tyrosines within the intracellular region of EphA2 by a combination of mass spectrometry analysis and phosphopeptide mapping using two-dimensional chromatography in conjunction with site-directed mutagenesis. The function of these phosphorylated tyrosine residues was assessed by mutational analysis using EphA2-null endothelial cells reconstituted with EphA2 tyrosine-to-phenylalanine or tyrosine-to-glutamic acid substitution mutants. Phosphorylated Tyr(587) and Tyr(593) bind to Vav2 and Vav3 guanine nucleotide exchange factors, whereas Tyr(P)(734) binds to the p85 regulatory subunit of phosphatidylinositol 3-kinase. Mutations that uncouple EphA2 with Vav guanine nucleotide exchange factors or p85 are defective in Rac1 activation and cell migration. Finally, EphA2 mutations in the juxtamembrane region (Y587F, Y593F, Y587E/Y593E), kinase domain (Y734F), or SAM domain (Y929F) inhibited ephrin-A1-induced vascular assembly. In addition, EphA2-null endothelial cells reconstituted with these mutants were unable to incorporate into tumor vasculature, suggesting a critical role of these phosphorylation tyrosine residues in transducing EphA2 signaling in vascular endothelial cells during tumor angiogenesis.
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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".