Targeting the Hippo pathway in cancers via ubiquitination dependent TEAD degradation
Bibliographic record
Abstract
Abstract The Hippo pathway is among the most frequently altered key signaling pathways in cancer. TEAD1-4 are essential transcription factors and key downstream effectors in the Hippo pathway. Here we identified RNF146 as a ubiquitin ligase (E3) that can catalyze TEAD ubiquitination and negatively regulate their function in cells. We show that this ubiquitin of TEADs is governed by their PARylation state and validated the genetic interaction between RNF146 and the Hippo pathway in cancer cell lines and the model organism Drosophila melanogaster. Furthermore, we demonstrate that pharmacologically induced ubiquitination of TEADs by heterobifunctional chemical inducers of protein degradation (CIDE) molecules can promote potent pan-TEAD degradation. These TEAD-CIDEs can effectively suppress activation of TEAD target genes in a dose-dependent manner and exhibited significant anti-proliferative effects in Hippo-dependent tumor cells, thus phenocopy the effect of genetic ablation of TEAD protein. Collectively, this study demonstrates a post-translational mechanism of TEAD protein regulation and provides a proof-of-concept demonstration that pharmacological induced TEAD ubiquitination could be an effective therapeutic strategy to target Hippo-driven cancers.
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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".