The Epidermal Growth Factor Receptor Mediates Tumor Necrosis Factor-α-induced Activation of the ERK/GEF-H1/RhoA Pathway in Tubular Epithelium
Bibliographic record
Abstract
Tumor necrosis factor (TNF)-α induces cytoskeleton and intercellular junction remodeling in tubular epithelial cells; the underlying mechanisms, however, are incompletely explored. We have previously shown that ERK-mediated stimulation of the RhoA GDP/GTP exchange factor GEF-H1/Lfc is critical for TNF-α-induced RhoA stimulation. Here we investigated the upstream mechanisms of ERK/GEF-H1 activation. Surprisingly, TNF-α-induced ERK and RhoA stimulation in tubular cells were prevented by epidermal growth factor receptor (EGFR) inhibition or silencing. TNF-α also enhanced phosphorylation of the EGFR. EGF treatment mimicked the effects of TNF-α, as it elicited potent, ERK-dependent GEF-H1 and RhoA activation. Moreover, EGF-induced RhoA activation was prevented by GEF-H1 silencing, indicating that GEF-H1 is a key downstream effector of the EGFR. The TNF-α-elicited EGFR, ERK, and RhoA stimulation were mediated by the TNF-α convertase enzyme (TACE) that can release EGFR ligands. Further, EGFR transactivation also required the tyrosine kinase Src, as Src inhibition prevented TNF-α-induced activation of the EGFR/ERK/GEF-H1/RhoA pathway. Importantly, a bromodeoxyuridine (BrdU) incorporation assay and electric cell substrate impedance-sensing (ECIS) measurements revealed that TNF-α stimulated cell growth in an EGFR-dependent manner. In contrast, TNF-α-induced NFκB activation was not prevented by EGFR or Src inhibition, suggesting that TNF-α exerts both EGFR-dependent and -independent effects. In summary, in the present study we show that the TNF-α-induced activation of the ERK/GEF-H1/RhoA pathway in tubular cells is mediated through Src- and TACE-dependent EGFR activation. Such a mechanism could couple inflammatory and proliferative stimuli and, thus, may play a key role in the regulation of wound healing and fibrogenesis.
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How this classification was reachedexpand
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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".