Metformin attenuates hepatoma cell proliferation by decreasing glycolytic flux through the HIF-1α/PFKFB3/PFK1 pathway
Bibliographic record
Abstract
AIMS: Enhanced aerobic glycolysis is an essential hallmark of malignant cancer. Blocking the glycolytic pathway has been suggested as a therapeutic strategy to impair the proliferation of tumor cells. Metformin, a widely used anti-diabetes drug, exhibits anti-tumor properties. However, the underlying molecular mechanism of its action linking glucose metabolism with the suppression of proliferation has not been fully clarified. MAIN METHODS: Stable isotope tracing technology and gas chromatography-mass spectrometry method were utilized to analyze the effect of metformin on glycolytic flux in HCC cells. Western blot and immunohistochemistry were utilized to analyze the expression of phosphofructokinase-1 (PFK1) and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) in HCC cells or xenograft tumor tissues. Lactate measurement and glucose uptake assay were used to analyze the level of lactate and glucose in the presence of frucose-2,6-diphosphate (F2,6BP) in HCC cells treated with metformin. KEY FINDINGS: We found that metformin significantly impaired hepatoma cell proliferation by inhibiting the glycolytic flux via PFK1 blockade. Interestingly, activation of PFK1 by F2,6BP reverses the inhibitory effect of metformin on hepatoma cell proliferation and glycolysis. Mechanistically, PFKFB3，a potent allosteric activator of PFK1, was markedly suppressed through inhibiting hypoxia-induced factor 1 (HIF-1α) accumulation mediated by metformin. SIGNIFICANCE: Taken together these data indicate that HIF-1α/PFKFB3/PFK1 regulatory axis is a vital determinant of glucose metabolic reprogramming in hepatocellular carcinoma, which gives new insights into the action of metformin in combatting liver cancer.
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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 | 0.000 |
| 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".