FGD5 Regulates VEGF Receptor-2 Coupling to PI3 Kinase and Receptor Recycling
Bibliographic record
Abstract
OBJECTIVE: VEGF (vascular endothelial growth factor-A) signaling to the endothelial cell (EC) through VEGFR2 (VEGF receptor-2) is the principal cue driving new blood vessel formation. FGD5 (faciogenital dysplasia-5)-a Rho-family guanine nucleotide exchange factor-is selectively expressed in EC. Deficiency of FGD5 is embryonically lethal in mice and perturbs angiogenesis and VEGF signal transduction. However, the mechanism of FGD5 regulation of VEGF signaling is poorly understood. APPROACH AND RESULTS: Angiogenic sprouting and EC cytoskeletal remodeling were evaluated in a 3-dimensional in vitro model. We examined the subcellular localization of FGD5 and VEGFR2 in EC by immunofluorescent staining and studied the association by immunoprecipitation. FGD5 deficiency reduced the number of angiogenic sprouts and tip cell filopodia by ≈80% and ≈70%, respectively. These defects were accompanied by downregulation of the expression of tip cell-specific markers. FGD5 inactivation led to a decrease in EC migration and early protrusion (lamellipodia) formation. In resting and VEGF-stimulated EC, FGD5 forms a complex with VEGFR2 and was enriched at the leading edge of the cell and among endosomes. FGD5 loss reduced mTORC2 (mammalian target of rapamycin complex-2)/Akt-dependent cortactin activation downstream of VEGFR2 but did not alter VEGFR2 plasma membrane expression, Y1175 phosphorylation, or endocytosis. However, FGD5 loss decreased endosomal VEGFR2 coupling to phosphoinositide-3 kinase and diverted VEGFR2 to lysosomal degradation. CONCLUSIONS: FGD5 regulates VEGFR2 retention in recycling endosomes and coupling to PI3 (phosphoinositide-3) kinase/mTORC2-dependent cytoskeletal remodeling.
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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".