Integrative metabolomic characterisation identifies altered portal vein serum metabolome contributing to human hepatocellular carcinoma
Bibliographic record
Abstract
OBJECTIVE: Altered metabolites are important for the tumourigenicity of hepatocellular carcinoma (HCC). We performed integrative metabolomics analysis of the metabolites changes in portal venous blood and in comparison with the metabolites changes in liver tissues and stool samples of HCC patients and healthy liver donors. DESIGN: Serum (portal and central vein), liver tissue (HCC tumour and adjacent non-tumour, normal liver) and stool samples were collected from 102 subjects (52 HCC patients and 50 healthy controls) in the discovery cohort; and 100 subjects (50 HCC patients and 50 healthy controls) in an independent validation cohort. Untargeted metabolomic profiling was performed using high-performance liquid chromatography-mass spectrometry. The function of candidate metabolites was validated in hepatocyte cell lines. RESULTS: Detailed metabolomic evaluation showed distinct clusters of metabolites in serum, liver tissue and stool samples from patients with HCC and control individuals (p<0.001). HCC patients had significantly higher levels of portal vein serum and HCC tissue metabolites of DL-3-phenyllactic acid, L-tryptophan, glycocholic acid and 1-methylnicotinamide than healthy controls, which were associated with impaired liver function and poor survival. On the other hand, HCC patients had lower levels of linoleic acid and phenol in portal vein and stool samples than healthy controls. Linoleic acid and phenol significantly inhibited HCC proliferation, inferring their anti-HCC function as protective metabolites. CONCLUSIONS: The integrative metabolome analysis of serum, tissue and stool metabolites revealed unreported metabolic alterations in HCC patients. In portal vein, we identified elevated and depleted metabolites signifying that they might play a role in HCC development.
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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) | 0.001 | 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) | 0.001 | 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 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".