Enhanced therapeutic efficacy of adenovirus-mediated interleukin-24 gene therapy combined with ionizing radiotherapy for nasopharyngeal carcinoma
Bibliographic record
Abstract
Melanoma differentiation-associated gene-7 (mda-7)/interleukin-24 (IL-24), a unique cytokine tumor suppressor, displays ubiquitous antitumor activities and cancer-specific cytotoxicities via multiple signaling pathways. In the present study, we investigated the antitumor effect of adenovirus-mediated IL-24 (AdVIL-24) gene therapy in conjunction with ionizing radiation on CNE-2Z human nasopharyngeal carcinoma (NPC) cells in vitro and in vivo in athymic nude mice, and its potential mechanisms. We demonstrated that AdVIL-24 gene therapy plus ionizing radiotherapy induced enhanced growth inhibition, cell cycle G1 phase arrest and apoptosis in vitro in CNE-2Z human NPC cells and in vivo in CNE-2Z xenografted tumors subcutaneously implanted in athymic nude mice. Mechanistically, AdVIL-24 combined with ionizing radiation led to the substantial upregulation of P21 and P27 cyclin-dependent kinase (CDK) inhibitors, ratio of pro-apoptotic to anti-apoptotic molecules Bax/Bcl-2 and cleaved caspase‑3 as well as downregulation of cyclin E and CDK2 in vitro and in vivo in CNE-2Z human NPC cells. Furthermore, AdVIL-24 plus radiation additively reduced the tumor vessel CD34 expression and microvessel density in vivo. More importantly, AdVIL-24 potentially blocked the radiation-induced enhancement of vascular endothelial growth factor (VEGF), a pro-angiogenic factor. The enhanced antitumor activity against NPC elicited by AdVIL-24 gene therapy combined with ionizing radiotherapy was closely associated with the enhanced induction of G1 phase arrest and apoptosis via additive modulation of cell cycle regulatory molecules and activation of intrinsic apoptotic pathways, and the overlapping inhibition of tumor angiogenesis. Thus, our results suggest that AdVIL-24 gene therapy combined with ionizing radiotherapy may be a novel and effective treatment strategy for human NPC.
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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".