S1P Stimulates Proliferation by Upregulating CTGF Expression through S1PR2-Mediated YAP Activation
Bibliographic record
Abstract
Abstract Dysregulation of the Hippo pathway in the liver results in overgrowth and eventually tumorigenesis. To date, several upstream mechanisms have been identified that affect the Hippo pathway, which ultimately regulate YAP, the major downstream effector of the pathway. However, upstream regulators of the Hippo pathway in the liver remain poorly defined. Sphingosine-1-phosphate (S1P) is a bioactive sphingolipid metabolite that has been shown to stimulate hepatocellular carcinoma (HCC) cell proliferation, but whether the Hippo pathway is involved in S1P-stimulated HCC cell proliferation remains to be determined. Here it is demonstrated that S1P activates YAP and that the S1P receptor 2 (S1PR2/S1P2) mediates S1P-induced YAP activation in both human and mouse HCC cells. S1P promotes YAP-mediated upregulation of cysteine-rich protein 61 and connective tissue growth factor (CTGF), and stimulates HCC cell proliferation. By using siRNA-mediated knockdown approaches, only CTGF was required for S1P-stimulated cell proliferation. Of note, S1P activates YAP in a MST1/2-independent manner suggesting that the canonical Hippo kinase is not required for S1P-mediated proliferation in liver. The upregulation of CTGF and S1P2 were also observed in liver-specific YAP overexpression transgenic mouse hepatocytes. Moreover, YAP regulated liver differentiation–dependent gene expression by influencing the chromatin binding of HNF4α based on ChIP-seq analysis. Finally, results using gain- and loss-of-function approaches demonstrate that HNF4α negatively regulated S1P-induced CTGF expression. Implications: These findings reveal a role for S1P in stimulating HCC cell proliferation by upregulating CTGF expression through S1P2-mediated YAP activation. Mol Cancer Res; 16(10); 1543–55. ©2018 AACR.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".