Targeting TAZ and YAP as a New Therapeutic Approach to Diabetic Nephropathy
Bibliographic record
Abstract
Introduction Fibrosis is a major contributor to chronic kidney disease (CKD), for which no effective clinical treatment exists. The primary source of fibrosis is the activation of fibroblasts to the myofibroblast state. Fibroblast-myofibroblast transition requires transforming growth factor-β (TGF-β) and its canonical Smad signaling pathway. Purpose Recent findings suggest that mechanical stimuli affect fibroblast behavior. Nuclear localization of YAP/TAZ, closely associated mechanosensitive transcriptional co-factors, are regulated by substrate stiffness. As YAP/TAZ are Smad nuclear retention factors promoting TGF- β signaling, we hypothesized that YAP/TAZ inhibition could attenuate stiffness-mediated, TGF- β induced pro-fibrotic responses. Methods Immunostaining and immunoblotting were used to analyze localization and activity of YAP/TAZ and Smad levels, respectively. Results YAP/TAZ are in an active nuclear location in fibroblasts grown on stiff, fibrotic-like substrates (100kPa). In fibroblasts grown on soft substrates (2kPa), YAP/TAZ are primarily in an inactive cytosolic position. Cells grown on soft surfaces demonstrated strongly attenuated nuclear Smad 2/3 translocation and Smad-3 dependent transcription upon TGF-β stimulation, indicating impaired pro-fibrotic signaling. Verteporfin, a clinically approved drug with YAP inhibitory properties, was used to test the role of YAP/TAZ in reduced TGF-β signaling. Verteporfin reduced TGF-β-induced nuclear Smad2/3 accumulation and Smad3-mediated transcription in fibroblasts grown on stiff surfaces. In vivo, Verteporfin significantly reduces markers of renal fibrosis. Conclusions Soft, healthy kidney-like substrates inhibit, while stiff fibrotic-like substrates promote, pro-fibrotic TGF-β Smad signalling. Verteporfin inactivates the YAP/TAZ fibroblast mechanosensor, reduces stiffness-augmented fibroblast responses to TGF-β through blockade of Smad signalling, and may be a novel anti-fibrotic agent for CKD.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".