E3 ubiquitin-ligase Hakai induces LRP4 degradation and regulates Wnt/β-catenin signalling in colorectal cancer cells
Bibliographic record
Abstract
Abstract The epithelial-mesenchymal transition (EMT) is closely linked to the acquisition of cancer stem cell (CSC) properties, which contribute to treatment resistance and metastasis. This study investigates the role of the E3 ubiquitin-ligase Hakai, the first identified post-translational regulator of E-cadherin stability, in promoting CSC traits in colorectal cancer (CRC). To examine Hakai’s involvement in CSC regulation, we used an inducible shRNA in a HT29 cells. Under conditions that promote CSC characteristics, we silenced Hakai and evaluated tumoursphere formation and CSC marker expression. Proteomic and bioinformatic analyses were performed to identify Hakai-regulated proteins in tumoursphere cultures. Additionally, Western blot, RT-qPCR, co-immunoprecipitation, immunofluorescence and TOPFlash assays were employed to study CSC-related protein regulation in response to Hakai expression. Furthermore, we assessed the impact of Hakin-1, the pharmacological inhibitor specifically targeting Hakai’s HYB domain responsible for its E3 ubiquitin-ligase activity, on tumoursphere properties. Hakai silencing significantly reduced tumoursphere size and number accompanied by decreased expression of CSC markers and Wnt target genes. CSC-related proteins regulated by Hakai were identified, including LRP4, a negative regulator of Wnt/β-catenin pathway. Hakai interacts with LRP4, promoting its ubiquitination and degradation. Moreover, Hakai overexpression induces hyperactivation of Wnt/β-catenin sand disrupts LRP4’s inhibitory effect. Treatment with Hakin-1 effectively inhibited self-renewal and promoted differentiation within tumourspheres. These findings suggest that Hakai promotes CSCs properties by hyperactivation of the Wnt/β-catenin pathway via LRP4-mediated modulation. Additionally, Hakin-1 emerges as a promising therapeutic agent targeting CSCs by enhancing differentiation and attenuating Wnt/β-catenin activity, highlighting Hakai as a potential target for improving CSC treatment.
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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".