A RhoA–YAP–c-Myc signaling axis promotes the development of polycystic kidney disease
Bibliographic record
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder caused by mutations in PKD1 or PKD2 and affects one in 500–1000 humans. Limited treatment is currently available for ADPKD. Here we identify the Hippo signaling effector YAP and its transcriptional target, c-Myc, as promoters of cystic kidney pathogenesis. While transgenic overexpression of YAP promotes proliferation and tubule dilation in mouse kidneys, loss of YAP/TAZ or c-Myc suppresses cystogenesis in a mouse ADPKD model resulting from Pkd1 deficiency. Through a comprehensive kinase inhibitor screen based on a novel three-dimensional (3D) culture of Pkd1 mutant mouse kidney cells, we identified a signaling pathway involving the RhoGEF (guanine nucleotide exchange factor) LARG, the small GTPase RhoA, and the RhoA effector Rho-associated kinase (ROCK) as a critical signaling module between PKD1 and YAP. Further corroborating its physiological importance, inhibition of RhoA signaling suppresses cystogenesis in 3D culture of Pkd1 mutant kidney cells as well as Pkd1 mutant mouse kidneys in vivo. Taken together, our findings implicate the RhoA–YAP–c-Myc signaling axis as a critical mediator and potential drug target in ADPKD.
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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".