Synergistic Tumor Suppression by Adenovirus-Mediated Inhibitor of Growth 4 and Interleukin-24 Gene Cotransfer in Hepatocarcinoma Cells
Bibliographic record
Abstract
Inhibitor of growth 4 (ING4) is a novel member of ING tumor suppressor family and has apparent tumor-suppressive effect. Interleukin-24 (IL-24) as a unique cytokine-tumor suppressor displays ubiquitous antitumor property and tumor-specific killing activity. Multigene-based combination therapy may be an effective practice in cancer gene therapy. The therapeutic potential of a conjunction of ING4 and IL-24 for cancers is still elusive. This study evaluated the combined effect on SMMC-7721 and HepG2 human hepatocarcinoma cells by adenovirus-mediated ING4 and IL-24 coexpression (Ad-ING4-IL-24) and also elucidated its underlying molecular mechanism. It was demonstrated that Ad-ING4-IL-24 induced synergistic growth inhibition, apoptosis, invasion suppression, as well as an enhanced effect on upregulation of P21, P27, Fas, FasL, FADD, Bad, Bax, Bak, cleaved Bid, cleaved Caspase-8, -9, and -3, and cleaved PARP, downregulation of Bcl-2, Bcl-X(L), matrix metalloproteinase (MMP)-2, 9, vascular endothelial growth factor (VEGF), IL-8, CD34, and microvessel density, and cytochrome c release from mitochondria into cytosol in in vitro SMMC-7721 and HepG2 hepatocarcinoma cells and/or in vivo SMMC-7721 hepatocarcinoma subcutaneous xenografted tumors in athymic nude mice. The in vitro and in vivo synergistic antitumor activity elicited by Ad-ING4-IL-24 was closely associated with the cooperative activation of extrinsic and intrinsic apoptotic pathways and reduced proangiogenic factors' production of VEGF and IL-8, leading to synergistic inhibition of tumor angiogenesis. Thus, results indicate that cancer gene therapy combining two or more tumor suppressors such as ING4 and IL-24 may constitute a novel and effective therapeutic strategy for hepatocarcinoma and other cancers.
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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".