Suppression of CUGBP1 inhibits growth of hepatocellular carcinoma cells
Bibliographic record
Abstract
PURPOSE: The multifunctional RNA-binding protein, CUGBP1, regulates splicing, stability and translation of mRNAs. Previous studies have shown that CUGBP1 is expressed at high levels in the liver, although its role in hepatocellular carcinoma is unknown. Our aim was to determine if CUGBP1 could regulate hepatocellular carcinoma growth. METHODS: Expression levels of CUGBP1 were analyzed in 70 hepatic carcinoma and 20 normal hepatic tissue samples by immunohistochemistry (IHC). Using lentivirus-mediated short hairpin RNA (shRNA), CUGBP1 expression in human hepatocellular carcinoma HepG2 cells was knocked-down. The effect of CUGBP1 on hepatic cancer cell growth was investigated. RESULTS: CUGBP1 was expressed in 85.7% hepatocellular carcinoma specimens compared with 50% in normal liver specimens. CUGBP1 silencing remarkably decreased the proliferation of HepG2 cells, as determined by MTT assay. Flow cytometry analysis showed that knock-down of CUGBP1 led to G0/G1 phase cell cycle arrest, accompanied by sub-G1 accumulation. Moreover, depletion of CUGBP1 resulted in downregulation of cyclin B1 and upregulation of cyclin D1. CONCLUSION: These results suggest that CUGBP1 is essential for the growth of hepatocellular carcinoma cells. Knockdown of CUGBP1 might be a potential therapeutic approach for human hepatocellular carcinoma.
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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".