Adenovirus-Mediated Il-24 Expression Suppresses Hepatocellular Carcinoma Growth via Induction of Cell Apoptosis and Cycling Arrest and Reduction of Angiogenesis
Bibliographic record
Abstract
Previous studies have shown that interleukin (IL)-24 as a novel tumor suppressor gene has tumor-suppressor activity in a broad spectrum of human cancer cells both in vitro and in vivo. In this study, we explored the potential effect of adenovirus-mediated IL-24 gene therapy on human hepatocellular carcinoma (HCC) by using a HCC cell line, SMMC-7721. We constructed a recombinant adenovirus, AdVGFP/IL-24 expressing the marker green fluorescent protein (GFP) and the tumor-suppressor gene, IL-24. We demonstrated that AdVGFP/IL-24 treatment of SMMC-7721 cells in vitro significantly induced HCC cell cytotoxicity and apoptosis, and altered HCC cell cycling with an S-phase reduction and G2/M phase arrest, compared with AdVGFP, without IL-24 expresssion (p < 0.05). Furthermore, we also showed that the treatment of SMMC-7721 tumors by an intratumoral injection of AdVGFP/IL-24 significantly suppressed in vivo HCC growth in athymic nude mice, compared with AdVGFP treatment (p < 0.05). In addition, we also elucidated the molecular mechanism responsible for AdVGFP/IL-24-associated tumor suppression. These include: (1) upregulation of p53-independent apoptosis-associated caspase-3 and (2) downregulation of angiogenesis-associated vascular endothelial growth factor and CD34. Therefore, this study will provide a framework for future clinical applications of AdVGFP/IL-24 in HCC gene therapy.
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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".