Prognostic significance of <i>SOCS1</i> and <i>SOCS3</i> tumor suppressors in hepatocellular carcinoma and its correlation to key oncogenic signaling pathways
Bibliographic record
Abstract
Abstract Suppressor of cytokine signaling (SOCS) proteins SOCS1 and SOCS3 are considered tumor suppressors in liver hepatocellular carcinoma (LIHC). To gain insight into the underlying molecular mechanisms, the expression of SOCS1/ SOCS3 was evaluated in The Cancer Genome Atlas LIHC dataset along with key oncogenic signaling pathway genes. SOCS1 expression was not significantly reduced in HCC yet higher expression predicted favorable prognosis, whereas SOCS3 lacked predictive potential despite lower expression. Only a small proportion of the cell cycle, receptor tyrosine kinase, growth factor and RAS-RAF-MEK-MAPK signaling genes negatively correlated with SOCS1 or SOCS3 , of which even fewer showed elevated expression in HCC and predicted survival. However, many PI3K-AKT-MTOR pathway genes showed mutual exclusivity with SOCS1 / SOCS3 and displayed independent predictive ability. Among genes that negatively correlated with SOCS1 / SOCS3, CDK2, MLST8, AURKA, MAP3K4 and RPTOR showed corresponding modulations in the livers of mice lacking Socs1 or Socs3 during liver regeneration and in experimental HCC, and in Hepa1-6 murine HCC cells overexpressing SOCS1/SOCS3. However, Cox proportional hazards model identified CXCL8, DAB2 and PIK3R1 as highly predictive in combination with SOCS1 or SOCS3 . These data suggest that developing prognostic biomarkers and precision treatment strategies based on SOCS1/SOCS3 expression need careful testing in different patient cohorts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".