The <i>In Vitro</i> and <i>In Vivo</i> Antitumor Activity of Adenovirus-Mediated Interleukin-24 Expression for Laryngocarcinoma
Bibliographic record
Abstract
Interleukin-24 (IL-24)/melanoma differentiation associated gene-7 (mda-7) as a novel tumor-suppressor gene has potent antitumor activities in a broad spectrum of human cancers through the activation of various signaling pathways. However, the suppressive effect of adenovirus-mediated IL-24 (Ad-IL-24) expression on human laryngeal cancers is still elusive. In this study, we explored the therapeutic effect of Ad-IL-24 on human laryngeal cancers in vitro and in vivo in an athymic nude mouse model, using a Hep-2 human laryngocarcinoma cell line, and a WI-38 human diploid cell line served as a normal cell control. We demonstrated that Ad-IL-24 induced significant growth inhibition and apoptosis, upregulated the expression of P21, P27, and Bax, downregulated Bcl-2 expression, and activated caspase-3 in Hep-2 laryngeal tumor cells, while it exerted no direct effect on the in vitro proliferation of WI-38 normal diploid cells. Moreover, intratumoral injections of Ad-IL-24 in nude mice bearing Hep-2 tumors significantly suppressed the laryngeal xengrafted tumor growth and reduced microvessel density (MVD) and VEGF expression in tumors. This retarded tumor growth in vitro and in vivo elicited by Ad-IL-24 was closely associated with the upregulation of proliferation-related molecules P21 and P27, decrease in the ratio of anti- to proapoptotic molecules Bcl-2/Bax, followed by the activation of caspase-3, leading to apoptosis via intrinsic apoptotic pathways, and the reduced expression of proangiogenic factor VEGF involved in the inhibition of tumor angiogenesis. Thus, our results indicate that the potent, selective killing activity of Ad-IL-24 in laryngeal cancer cells, but not in normal cells, makes this vector a potential candidate for laryngeal cancer gene therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".