NF-κB p65 Overexpression Promotes Bladder Cancer Cell Migration via FBW7-Mediated Degradation of RhoGDIα Protein
Bibliographic record
Abstract
BACKGROUND: Since invasive bladder cancer (BC) is one of the most lethal urological malignant tumors worldwide, understanding the molecular mechanisms that trigger the migration, invasion, and metastasis of BC has great significance in reducing the mortality of this disease. Although RelA/p65, a member of the NF-kappa B transcription factor family, has been reported to be upregulated in human BCs, its regulation of BC motility and mechanisms have not been explored yet. METHODS: NF-κBp65 expression was evaluated in N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN)-induced high invasive BCs by immunohistochemistry staining and in human BC cell lines demonstrated by Western Blot. The effects of NF-κBp65 knockdown on BC cell migration and invasion, as well as its regulated RhoGDIα and FBW7, were also evaluated in T24T cells by using loss- and gain-function approaches. Moreover, the interaction of FBW7 with RhoGDIα was determined with immunoprecipitation assay, while critical role of ubiquitination of RhoGDIα by FBW7 was also demonstrated in the studies. RESULTS: p65 protein was remarkably upregulated in the BBN-induced high invasive BCs and in human BC cell lines. We also observed that p65 overexpression promoted BC cell migration by inhibiting RhoGDIα expression. The regulatory effect of p65 on RhoGDIα expression is mediated by its upregulation of FBW7, which specifically interacted with RhoGDIα and promoted RhoGDIα ubiquitination and degradation. Mechanistic studies revealed that p65 stabilizing the E3 ligase FBW7 protein was mediated by its attenuating pten mRNA transcription. CONCLUSIONS: We demonstrate that p65 overexpression inhibits pten mRNA transcription, which stabilizes the protein expression of ubiquitin E3 ligase FBW7, in turn increasing the ubiquitination and degradation of RhoGDIα protein and finally promoting human BC migration. The novel identification of p65/PTEN/FBW7/RhoGDIα axis provides a significant insight into understanding the nature of BC migration, further offering a new theoretical support for cancer therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".