Identification of PTPN12 Phosphatase as a Novel Negative Regulator of Hippo Pathway Effectors YAP/TAZ in Breast Cancer
Bibliographic record
Abstract
The Hippo pathway plays crucial roles in governing various biological processes during tumorigenesis and metastasis. Within this pathway, upstream signaling stimuli activate a core kinase cascade, involving MST1/2 and LATS1/2, which subsequently phosphorylates and inhibits the transcriptional co-activators YAP and its paralog TAZ. This inhibition modulates the transcriptional regulation of downstream target genes, impacting cell proliferation, migration, and death. Despite the acknowledged significance of protein kinases in the Hippo pathway, the regulatory influence of protein phosphatases remains largely unexplored. In this study, we conducted the first gain-of-functional screen for protein tyrosine phosphatases (PTPs) regulating the Hippo pathway. Utilizing a LATS kinase biosensor (LATS-BS), a YAP/TAZ activity reporter (STBS-Luc), and a comprehensive PTP library, we identified numerous novel PTPs that play regulatory roles in the Hippo pathway. Subsequent experiments validated PTPN12, a master regulator of oncogenic receptor tyrosine kinases (RTKs), as a previously unrecognized negative regulator of the Hippo pathway effectors, oncogenic YAP/TAZ, influencing breast cancer cell proliferation and migration. In summary, our findings offer valuable insights into the roles of PTPs in the Hippo signaling pathway, significantly contributing to our understanding of breast cancer bi-ology and potential therapeutic strategies.
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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".