Overexpression of the C-terminal PG-M/versican domain impairs growth of tumor cells by intervening in the interaction between epidermal growth factor receptor and β1-integrin
Bibliographic record
Abstract
Versican is highly expressed in many types of tumors. In a previous study, we found that a G3 mutant [G3DeltaEGF; a versican G3 domain lacking two epidermal growth factor (EGF)-like motifs] exerted a dominant-negative effect on versican secretion and binding. Here, we report that astrocytoma U87 cells expressing the versican G3 mutant lost the hallmark of cell transformation and tumorigenesis in vitro and in vivo. U87 cells expressing G3DeltaEGF had enhanced cell adhesion and spreading, but lost the tumor characteristic of anchorage-independent growth. When U87 cells were deprived of serum, FAK was quickly dephosphorylated, integrin/EGF-receptor (EGFR) complexes dissociated and the cells retained an appropriate level of EGFR phosphorylation. These cells quickly detached, migrated, rounded, reorganized and survived. However, after serum withdrawal from G3DeltaEGF-transfected U87 cells, sustained FAK phosphorylation and integrin-EGFR association were observed, but a greatly reduced EGFR phosphorylation. These cells remained spread and continued to grow before undergoing massive apoptosis. The addition of EGF promoted U87 cell rounding but had little effect on G3DeltaEGF-transfected cells owing to reduced EGFR phosphorylation. Our study sheds light on the question of how the matrix molecule versican modulates tumorigenesis by affecting integrin and EGFR signals.
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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".