A Coiled‐Coil Domain Containing 50 Splice Variant Is Modulated by Serine/Arginine‐Rich Splicing Factor 3 and Promotes Hepatocellular Carcinoma in Mice by the Ras Signaling Pathway
Bibliographic record
Abstract
Deregulation of alternative splicing contributes to the malignant progression of cancer. Little is known about the significant alternative splicing events in hepatocellular carcinoma (HCC). High-throughput sequencing revealed that coiled-coil domain containing 50 (CCDC50) pre-mRNA is aberrantly spliced in 50% of our HCC cases. A BaseScope assay was performed to examine the expression of CCDC50S (a truncated oncogenic splice variant) in HCC tissues. Compared with benign liver tumors and several other types of solid tumors, CCDC50S mRNA was up-regulated in HCC, with a diagnostic potential (sensitivity, 0.711; specificity, 0.793). High expression of CCDC50S mRNA in HCC was significantly correlated with poor tumor differentiation, advanced tumor node metastasis (TNM) stage, and unfavorable prognosis. Overexpression of CCDC50S exerted tumorigenic activities that promoted HCC growth and metastasis by activation of Ras/forkhead box protein O4 (Foxo4) signaling. Either suppression of mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) phosphorylation or overexpression of Foxo4 markedly attenuated CCDC50S-mediated phenotypes. Furthermore, serine- and arginine-rich splicing factor 3 (SRSF3) directly bound to CCDC50S mRNA to maintain its stability in the cytoplasm. The cytosolic retention of SRSF3 was mediated by the interaction of hepatitis B virus-encoded X protein (HBx) and 14-3-3β. Ectopic HBx expression induced expression of cytosolic SRSF3 and CCDC50S. Conclusion: Our study provided compelling evidence that up-regulation of CCDC50S was modulated by HBx/SRSF3/14-3-3β complex and enhanced oncogenic progression of HCC through the Ras/Foxo4 signaling pathway. These data suggest that CCDC50S may serve as a diagnostic and prognostic biomarker and probably a promising therapeutic target in HCC.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".