Deubiquitinase OTUD5 Modulates mTOR Signaling Pathways to Promote Bladder Cancer Progression
Bibliographic record
Abstract
Abstract BackgroundThe mammalian target of Rapamycin (mTOR) pathway serves as a crucial regulator of various biological processes such as cell growth and cancer progression. In bladder cancer, recent discoveries showing the cancer-promoting role of mTOR complex 1 have attracted wide attention. However, the regulation of mTOR signaling in bladder cancer is complicated and the underlying mechanism remains elusive. Here, we report that the deubiquitinating enzyme, ovarian tumor domain-containing protein 5 (OTUD5), can activate the mTOR signaling pathway, promote cancer progression, and show its oncogenic potential in bladder cancer.MethodsThe expression of OTUD5 in bladder cancer was analyzed using bladder cancer tissue microarrays and Western blotting analysis. Meanwhile, to demonstrate the role of OTUD5-RNF186-Sestrin2-mTOR axis in bladder cancer, we have adopted a series of biochemical and molecular biological methods to verify in vivo and in vitro. The methods used included quantitative real time PCR assay; western blot assay; Immunofluorescence staining assay; MTT assay; colony formation assay; Co-immunoprecipitation assay; In vivo ubiquitination assay; Immunohistochemical assay and Bladder Cancer xenograft animal model.ResultsIn our study, we found that OTUD5 deubiquitinated a RING-type E3 ligase, RNF186, and stabilized its function. In addition, the stabilization of RNF186 further led to the degradation of Sestrin2, which is an inhibitor of mTOR signaling pathway. ConclusionTogether, we first proved that OTUD5 can promote bladder cancer progression through the OTUD5-RNF186-Sestrin2-mTOR axis and provided novel insights into the diagnosis and treatment of bladder cancer.
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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) | 0.002 | 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".