Abstract IA10: Inhibition of the Hippo pathway by AMPK-family kinases
Bibliographic record
Abstract
Abstract Inactivation of the Hippo pathway is a common feature in numerous cancers, yet mutations in pathway components are relatively rare. To uncover novel Hippo pathway regulators, we conducted multidimensional high-throughput screens. These efforts uncovered two AMPK family kinases, MARK4 and NUAK2, as negative regulators of the Hippo pathway. MARK kinases, including MARK3 and MARK4, phosphorylate both SAV1 and MST1/2 and inhibit MST1/2-dependent activation of LATS. Moreover, we showed that DLG5 acts as a scaffold to promote MARK-mediated phosphorylation of MST. In contrast to MARKs, NUAK2 interacts with and phosphorylates LATS. Interestingly, NUAK2 is induced by YAP/TAZ in cooperation with AP-1 and this is required for robust YAP/TAZ signaling. Inhibition or loss of NUAK2 reduces the growth of cultured cancer cells and mammary tumors in mice. In human patient samples, NUAK2 expression is elevated in aggressive, high-grade bladder cancer and strongly correlates with a YAP/TAZ gene signature. Thus, we identified a positive feed-forward loop in the Hippo pathway that establishes a key role for NUAK2 in enforcing the tumor-promoting activities of YAP/TAZ. Citation Format: Liliana Attisano. Inhibition of the Hippo pathway by AMPK-family kinases [abstract]. In: Proceedings of the AACR Special Conference on the Hippo Pathway: Signaling, Cancer, and Beyond; 2019 May 8-11; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(8_Suppl):Abstract nr IA10.
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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) | 0.001 | 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 | 0.001 |
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".