Enhanced antitumor activity by combining an adenovirus harboring ING4 with cisplatin for hepatocarcinoma cells
Bibliographic record
Abstract
The inhibitor of growth (ING) family proteins have been defined as candidate tumor suppressors. ING4 as a novel member of the ING family has potential tumor-suppressive effects. In this study, we explored the combined effect of adenovirus-mediated ING4 (Ad-ING4) gene transfer plus chemotherapy drug cisplatin (CDDP) on SMMC-7721 human hepatocarcinoma cells in vitro and in vivo, and its underlying mechanism. We demonstrated that Ad-ING4 plus CDDP induced synergistic growth inhibition, enhanced apoptosis, and had an additive effect on upregulation of Fas, Bax, Bak, cleaved Bid, cleaved caspase-8, caspase-9, caspase-3 and cleaved PARP, and on downregulation of Bcl-2 and Bcl-X(L) in SMMC-7721 hepatocarcinoma cells. Moreover, Ad-ING4 plus CDDP synergistically suppressed in vivo SMMC-7721 hepatocarcinoma subcutaneous (s.c.) xenografted tumor growth and reduced tumor vessel CD34 expression and microvessel density (MVD) in athymic nude mice. Most importantly, Ad-ING4 plus CDDP did not have overlapping toxicities in HL-7702 normal human liver cells and normal liver tissues of mice. The in vitro and in vivo enhanced antitumor effect elicited by Ad-ING4 plus CDDP was closely associated with the cooperative regulation of extrinsic and intrinsic apoptotic pathways and synergistic inhibition of tumor angiogenesis. Thus, our results indicate that Ad-ING4 plus CDDP is a potential combined treatment strategy for hepatocarcinoma.
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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".