Proteomic Analysis of the E3 Ubiquitin-Ligase Hakai Highlights a Role in Plasticity of the Cytoskeleton Dynamics and in the Proteasome System
Bibliographic record
Abstract
Carcinoma, the most common type of cancer, arises from epithelial cells. The transition from adenoma to carcinoma is associated with the loss of E-cadherin and, in consequence, the disruption of cell-cell contacts. E-cadherin is a tumor suppressor, and it is down-regulated during epithelial-to-mesenchymal transition (EMT); indeed, its loss is a predictor of poor prognosis. Hakai is an E3 ubiquitin-ligase protein that mediates E-cadherin ubiquitination, endocytosis and finally degradation, leading the alterations of cell-cell contacts. Although E-cadherin is the most established substrate for Hakai activity, other regulated molecular targets for Hakai may be involved in cancer cell plasticity during tumor progression. In this work we employed an iTRAQ approach to explore novel molecular pathways involved in Hakai-driven EMT during tumor progression. Our results show that Hakai may have an important influence on cytoskeleton-related proteins, extracellular exosome-associated proteins, RNA-related proteins and proteins involved in metabolism. Moreover, a profound decreased expression in several proteasome subunits during Hakai-driven EMT was highlighted. Since proteasome inhibitors are becoming increasingly used in cancer treatment, our findings suggest that the E3 ubiquitin-ligase, such as Hakai, may be a better target than proteasome for using novel specific inhibitors in tumor subtypes that follow EMT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".