Hepatitis B Virus X Protein Up-Regulates AKR1C1 Expression Through Nuclear Factor-Y in Human Hepatocarcinoma Cells
Bibliographic record
Abstract
BACKGROUND: The hepatitis B virus X (HBx) protein has long been recognized as an important transcriptional transactivator of several genes. Human aldo-keto reductase family 1, member C1 (AKR1C1), a member of the family of AKR1CS, is significantly increased in HBx-expressed cells. OBJECTIVES: This study aimed to investigate the possible mechanism of HBx in regulating AKR1C1 expression in HepG2.2.15 cells and the role of AKR1C1 for HBV-induced HCC. MATERIALS AND METHODS: RT-PCR was performed to detect AKR1C1 expression on mRNA level in HepG2 and HepG2.2.15 cell. The promoter activity of AKR1C1 was assayed by transient transfection and Dual-luciferase reporter assay system. The AKR1C1 promoter sequence was screened using the TFSEARCH database and the ALIBABA 2.0 software. The potential transcription factors binding sites were identified using 5' functional deletion analysis and site-directed mutagenesis. RESULTS: In this study, we found that HBx promoted AKR1C1 expression in HepG2.2.15 cells. Knockdown of HBx inhibited AKR1C1 activation. The role of HBx expression in regulating the promoter activity of human AKR1C1 gene was analyzed. The 5'functional deletion analysis identified that the region between -128 and -88 was the minimal promoter region of HBx to activate AKR1C1 gene expression. Site-directed mutagenesis studies suggested that nuclear factor-Y (NF-Y) plays an important role in this HBx-induced AKR1C1 activation. CONCLUSIONS: In HepG2.2.1.5 cell, HBx can promote AKR1C1 promoter activity and thus activates the basal transcription of AKR1C1 gene. This process is mediated by the transcription factor NF-Y. This study explored the mechanism for the regulation of HBV on AKR1C1 expression and has provided a new understanding of HBV-induced HCC.
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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) | 0.002 | 0.001 |
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".