Ajuba inhibits hepatocellular carcinoma cell growth via targeting of β-catenin and YAP signaling and is regulated by E3 ligase Hakai through neddylation
Bibliographic record
Abstract
BACKGROUND: Aberrant activation of β-catenin and Yes-associated protein (YAP) signaling pathways has been associated with hepatocellular carcinoma (HCC) progression. The LIM domain protein Ajuba regulates β-catenin and YAP signaling and is implicated in tumorigenesis. However, roles and mechanism of Ajuba expression in HCC cells remain unclear. The E3 ligase Hakai has been shown to interact with other Ajuba family members and whether Hakai interacts and regulates Ajuba is unknown. METHODS: HCC cell lines stably depleted of Ajuba or Hakai were established using lentiviruses expressing shRNAs against Ajuba or Hakai. The effects of Ajuba on HCC cells were determined by a number of cell-based analyses including anchorage-independent growth, three dimension cultures and trans-well invasion assay. In vivo tumor growth was determined in a xenograft model and Ajuba expression in tumor sections was examined by immunohistochemistry. Co-immunoprecipitation, confocal microscopy and immunoblot assay were used to examine the expression and interaction between Ajuba and Hakai. RESULTS: Depletion of Ajuba in HCC cells significantly enhanced anchorage-independent growth, invasion, the formation of spheroids and tumor growth in a xenograft model, suggesting a tumor suppressor function for Ajuba in HCC. Mechanistically, Ajuba depletion triggered E-cadherin loss and β-catenin translocation with increased Cyclin D1 levels. In addition, depletion of Ajuba upregulated the levels of YAP and its target gene CYR61. Furthermore, siRNA-mediated knockdown of either β-catenin or YAP attenuated the pro-tumor effects by Ajuba depletion on HCC cells. Notably, Ajuba stability in HCC cells was regulated by Hakai, an E3 ligase for E-cadherin. Hakai interacted with Ajuba via its HYB domain and induced Ajuba neddylation, which was antagonized by the neddylation inhibitor, MLN4924, but not MG132. We further show that overexpression of Hakai in HCC cells markedly increased anchorage-independent growth, spheroid-formation ability and tumor growth in xenografts whereas Hakai depletion resulted in these opposite effects, indicating an oncogenic role for Hakai in HCC. Hakai also induced β-catenin translocation with increased levels of Cyclin D1. CONCLUSIONS: Our data suggest a role for Ajuba and Hakai in HCC, and uncover the mechanism underlying the regulation of Ajuba stability.
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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".