A Mutant of Hepatitis B Virus X Protein (HBxΔ127) Promotes Cell Growth through A Positive Feedback Loop Involving 5-Lipoxygenase and Fatty Acid Synthase
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Hepatitis B virus X protein (HBx) contributes to the development of HCC, whereas HBx with COOH-terminal deletion is a frequent event in the HCC tissues. Previously, we identified a natural mutant of HBx-truncated 27 amino acids at the COOH-terminal (termed HBxDelta127), which strongly enhanced cell growth. In the present study, we focused on investigating the mechanism. Accordingly, fatty acid synthase (FAS) plays a crucial role in cancer cell survival and proliferation; thus, we examined the signaling pathways involving FAS. Our data showed that HBxDelta127 strongly increased the transcriptional activities of FAS in human hepatoma HepG2 and H7402 cells. Moreover, we found that 5-lipoxygenase (5-LOX) was responsible for the up-regulation of FAS by using MK886 (an inhibitor of 5-LOX) and 5-LOX small interfering RNA. We observed that HBxDelta127 could upregulate 5-LOX through phosphorylated extracellular signal-regulated protein kinases 1/2 and thus resulted in the increase of released leukotriene B4 (LTB4, a metabolite of 5-LOX) by ELISA. The additional LTB4 could upregulate the expression of FAS in the cells as well. Interestingly, we found that FAS was able to upregulate the expression of 5-LOX in a feedback manner by using cerulenin (an inhibitor of FAS). Collectively, HBxDelta127 promotes cell growth through a positive feedback loop involving 5-LOX and FAS, in which released LTB4 is involved in the up-regulation of FAS. Thus, our finding provides a new insight into the mechanism involving the promotion of cell growth mediated by HBxDelta127.
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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".