The aberrant upregulation of exon 10-inclusive SREK1 through SRSF10 acts as an oncogenic driver in human hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Deregulation of alternative splicing is implicated as a relevant source of molecular heterogeneity in cancer. However, the targets and intrinsic mechanisms of splicing in hepatocarcinogenesis are largely unknown. Here, we report a functional impact of a Splicing Regulatory Glutamine/Lysine-Rich Protein 1 (SREK1) variant and its regulator, Serine/arginine-rich splicing factor 10 (SRSF10). HCC patients with poor prognosis express higher levels of exon 10-inclusive SREK1 (SREK1 L ). SREK1 L can sustain BLOC1S5-TXNDC5 (B-T) expression, a targeted gene of nonsense-mediated mRNA decay through inhibiting exon-exon junction complex binding with B-T to exert its oncogenic role. B-T plays its competing endogenous RNA role by inhibiting miR-30c-5p and miR-30e-5p, and further promoting the expression of downstream oncogenic targets SRSF10 and TXNDC5. Interestingly, SRSF10 can act as a splicing regulator for SREK1 L to promote hepatocarcinogenesis via the formation of a SRSF10-associated complex. In summary, we demonstrate a SRSF10/SREK1 L /B-T signalling loop to accelerate the hepatocarcinogenesis.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".