Identification of NUAK1/2 Regulators in the Hippo Signaling Pathway
Bibliographic record
Abstract
The Hippo signaling pathway plays a central role in regulating cell proliferation, differentiation, and tissue size. In response to various upstream regulators, the mammalian STE20‐like protein kinase 1/2 (MST1/2) and large tumor suppressor kinase 1/2 (LATS1/2) phosphorylate Yes‐associated protein (YAP) and transcriptional co‐activator with PDZ‐binding motif (TAZ) to promote their cytoplasmic retention and degradation. Unphosphorylated YAP/TAZ translocate into the nucleus and interact with several transcription factors to regulate gene expression that drives cell growth and migration. Dysregulation of the Hippo pathway causes tissue overgrowth and tumorigenesis and elevated YAP/TAZ levels or activities are positively correlated with progression of almost all solid cancers. The NUAK family kinase 1/2 (NUAK1/2) are members of the AMP‐activated protein kinase‐related kinase family. Our lab showed that NUAK2 negatively regulates the Hippo pathway by preventing LATS‐mediated YAP/TAZ phosphorylation and cytoplasmic sequestration. Moreover, this work showed that loss of NUAK2 attenuates in vivo mammary tumor growth. However, how NUAK1/2 are regulated is poorly understood. Here, we will undertake screens in cancer cell lines to identify upstream and downstream NUAK1/2 regulators and partners. Since, abrogation of NUAK expression blocks cell growth in a context‐dependent manner, my current efforts are being directed towards generating cell lines expressing inducible NUAK1/2 shRNAs. Independent clones have been selected and validated for their knockdown efficiencies and effects on YAP/TAZ downstream target gene expression. Once validated, the selected lines will be subjected to genome‐wide CRISPR screens. We hypothesize that the screens will identify components that enhance or attenuate the effect of NUAKs and will reveal any differential regulators and partners for NUAK1/2. Discovering novel cancer‐relevant NUAK regulators will enhance our understanding of the tumor promoting roles of NUAKs and provide insights into how to target these kinases for better therapeutic outcomes.
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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) | 0.001 | 0.001 |
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".