TGF-β-driven downregulation of the transcription factor TCF7L2 affects Wnt/β-catenin signaling in PDGFRα+ fibroblasts
Bibliographic record
Abstract
ABSTRACT Mesenchymal stromal cells (MSCs) are multipotent progenitors essential for organogenesis, tissue homeostasis, regeneration and scar formation. Tissue injury upregulates transforming growth factor β (TGF-β) signaling, which modulates myofibroblast fate, extracellular matrix remodeling and fibrosis. However, the molecular determinants of MSC differentiation and survival remain poorly understood. During canonical Wnt signaling, T-cell factor/lymphoid enhancer factor (TCF/LEF) transcription factors regulate development and stemness, but the mechanisms by which injury-induced cues modulate their expression remain underexplored. Here, we studied the cell type-specific gene expression of TCF/LEF transcription factors and, more specifically, we investigated whether damage-induced TGF-β signaling impairs the expression and function of TCF7L2 (also known as TCF4), using several models of MSCs, including skeletal muscle fibro-adipogenic progenitors. We show that TCF/LEFs are differentially expressed and that TGF-β reduces the expression of TCF7L2 in MSCs but not in myoblasts. We also found that the ubiquitin–proteasome system regulates TCF7L2 proteostasis and participates in TGF-β-mediated TCF7L2 protein downregulation. Finally, we show that TGF-β requires histone deacetylase activity to repress the expression of TCF7L2. Thus, our work reports a novel interplay between TGF-β and canonical Wnt signaling cascades in PDGFRα+ fibroblasts and suggests that this mechanism could be targeted in tissue repair and regeneration.
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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 | 0.000 | 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) | 0.000 | 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".