Monoacylglycerol Lipase: A Novel Potential Therapeutic Target and Prognostic Indicator for Hepatocellular Carcinoma
Bibliographic record
Abstract
Monoacylglycerol lipase (MAGL) is a key enzyme in lipid metabolism that is demonstrated to be involved in tumor progression through both energy supply of fatty acid (FA) oxidation and enhancing cancer cell malignance. The aim of this study was to investigate whether MAGL could be a potential therapeutic target and prognostic indicator for hepatocellular carcinoma (HCC). To evaluate the relationship between MAGL levels and clinical characteristics, a tissue microarray (TMA) of 353 human HCC samples was performed. MAGL levels in HCC samples were closely linked to the degree of malignancy and patient prognosis. RNA interference, specific pharmacological inhibitor JZL-184 and gene knock-in of MAGL were utilized to investigate the effects of MAGL on HCC cell proliferation, apoptosis, and invasion. MAGL played important roles in both proliferation and invasion of HCC cells through mechanisms that involved prostaglandin E2 (PGE2) and lysophosphatidic acid (LPA). JZL-184 administration significantly inhibited tumor growth in mice. Furthermore, we confirmed that promoter methylation of large tumor suppressor kinase 1 (LATS1) resulted in dysfunction of the Hippo signal pathway, which induced overexpression of MAGL in HCC. These results indicate that MAGL could be a potentially novel therapeutic target and prognostic indicator for HCC.
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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 | 0.001 | 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) | 0.000 | 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".