Recombinant Human Interleukin-24 Suppresses Gastric Carcinoma Cell Growth<i>In Vitro</i>and<i>In Vivo</i>
Bibliographic record
Abstract
Previous studies have demonstrated that interleukin-24 [IL-24; originally called melanoma differentiation associated gene-7 (mda-7)] as a novel tumor suppressor gene has tumor-suppressive activity against a broad spectrum of human cancers. However, the therapeutic effect of the recombinant human IL-24 (rhIL-24) protein purified from prokaryotic cells on gastric cancer has not been reported. In this study, we purified soluble rhIL-24 using Q-Sepharose column after the denaturing and renaturing process from the protein of Escherichia coli BL21 transfected with pET-21a(+)-hIL-24 vector and treated by isopropyl-beta-D-1-thiogalactopyranoside (IPTG) for enhanced expression of transgene rhIL-24. We demonstrated that rhIL-24 was capable of inducing in vitro apoptosis of SGC7901 gastric cancer cells and activating peripheral blood mononuclear cellsto secrete cytokines such as IL-6, TNF-alpha, and IFN-gamma. We also showed that rhIL-24 was able to inhibit formation of blood capillaries on chicken embryonic allantois and in vivo tumor angiogenesis leading to suppressing SGC7901 gastric cancer cell growth in vitro and in vivo possibly due to its downregulation of Bcl-2/Bax ratio, VEGF (vascular endothelial growth factor), and CD34. Therefore, our results indicate that rhIL-24 has potent suppressive effect on human SGC7901 gastric carcinoma cell line and warrant its further investigation for therapeutic application against gastric cancer.
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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".