Expression of Phosphatidylethanolamine N-Methyltransferase in Human Hepatocellular Carcinomas
Bibliographic record
Abstract
OBJECTIVE: Hepatic phosphatidylethanolamine is converted into phosphatidylcholine by the enzyme phosphatidylethanolamine N-methyltransferase (PEMT) when the dietary choline supply is inadequate. Our previous reports implicated PEMT in the regulation of hepatocyte growth and transformation. In the present study, we analyzed PEMT activity, PEMPT gene status and its mRNA expression in 29 human hepatocellular carcinomas (HCC). METHODS: The status of the PEMPT gene and PEMT2 mRNA expression were evaluated with Southern and Northern blotting, respectively, in HCC and the noninvolved liver. PEMT activity was assessed by biochemical assay. Cell proliferation markers were defined by immunohistochemical or histoautoradiographic methods. RESULTS: PEMT activity was lower in HCC than in the noninvolved liver and it was negligible in 62% of the tumors. No deletions or mutations of the PEMPT gene were found and PEMT2 mRNA expression was absent or reduced in HCC compared with peritumoral liver tissue. PEMT2 mRNA expression was inversely related to tumor proliferation and to histologic grade. Patients whose HCC did not express PEMT2 mRNA showed poorer outcomes for cancer-related survival than those with PEMT2-positive HCC. CONCLUSIONS: The present findings suggest that (1). clones lacking PEMT2 expression may have been selected during liver tumorigenesis and progression, and (2). PEMT2 expression seems to be associated with clinical progression.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".