<scp>PRR11</scp> Promotes Bladder Cancer Growth and Metastasis by Facilitating <scp>G1</scp>/S Progression and Epithelial‐Mesenchymal Transition
Bibliographic record
Abstract
BACKGROUND: Although Proline-rich Protein 11 (PRR11) abnormalities are closely associated with carcinogenesis, the precise mechanism of bladder cancer remains unclear. Here, we sought to elucidate the molecular mechanisms of PRR11 in bladder cancer. METHODS: We performed differential expression analysis of PRR11 from the TCGA and GEO databases, followed by validation with clinical samples. Survival analysis was employed to assess the correlation between PRR11 and patient prognosis. The effects of PRR11 on bladder cancer cells were examined through both in vitro and in vivo experiments. Additionally, Gene Set Enrichment Analysis (GSEA) was used to predict the downstream pathways associated with PRR11, which were further validated through subsequent experiments. RESULTS: PRR11 is upregulated in bladder cancer and could lead to poor prognosis. In vitro, PRR11 promoted tumor cell proliferation; in vivo, it promoted subcutaneous tumor growth. PRR11 knockdown inhibited its oncogenic function. On the molecular level, PRR11 promotes tumor metastasis by inducing Epithelial-mesenchymal Transition (EMT). GSEA suggests that PRR11 is strongly linked to the cell cycle, and silencing of PRR11 can achieve anti-tumor effects by inhibiting CCNE and blocking the G1/S phase transition. CONCLUSIONS: Our study demonstrates that silencing PRR11 can arrest the malignant progression of bladder cancer by inhibiting EMT and blocking the G1/S transition. Targeting PRR11 may provide new insights for targeting cell cycle therapy.
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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 | 0.000 | 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) | 0.000 | 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".