Functional analysis of miR-101-3p and Rap1b involved in hepatitis B virus-related hepatocellular carcinoma pathogenesis
Bibliographic record
Abstract
MicroRNA-101(miR-101) has been shown to be down-regulated in hepatocellular carcinoma (HCC). The hepatitis B virus (HBV) is a major risk factor in the development and progression of HCC. However, the correlation between HBV and miR-101 has not yet been fully elucidated. In this study, we reported that HBV could repress miR-101-3p by inhibiting its promoter activity and identified the potential effects of miR-101-3p on some important biological properties of HCC cells by targeting Rap1b. Dual-luciferase reporter assays showed that HBV down-regulated miR-101-3p by inhibiting its promoter activity. Down-regulation of miR-101-3p promoted cell proliferation, migration, and reduced apoptosis, and resulted in up-regulation of Rap1b, while overexpression of miR-101-3p inhibited these processes. Moreover, overexpression of Rap1b was able to reverse the suppressed cell proliferation and migration mediated by miR-101-3p. Our data showed that HBV down-regulated miR-101-3p expression by inhibiting its promoter activity, which resulted in up-regulation of Rap1b, and down-regulation of miR-101-3p or up-regulation of Rap1b promoted proliferation and migration of HCC cells. This provides a new understanding of the mechanism of HBV-related HCC pathogenesis and the potential application of miR-101-3p in cancer therapy.
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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) | 0.000 | 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) | 0.000 | 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".