A combination of genetically engineered oncolytic virus and melittin-CpG for cancer viro-chemo-immunotherapy
Bibliographic record
Abstract
BACKGROUND: Immunotherapy has emerged as an efficient therapeutic approach for cancer management. However, stimulation of host immune system against cancer cells often fails to achieve promising clinical outcomes mainly owing to the immunosuppressive characteristics of the tumor microenvironment (TME). Combination therapeutics that can trigger sustained immunogenic cell death (ICD) have provided new opportunities for cancer treatment. METHODS: In this study, we designed and applied an ICD inducer regimen, including a genetically engineered oncolytic virus (miRNA-modified coxsackieviruses B3, miR-CVB3), a pore-forming lytic peptide (melittin, found in bee venom), and a synthetic toll-like receptor 9 ligand (CpG oligodeoxynucleotides), for breast cancer and melanoma treatment. We compared the anti-tumor efficacy of miR-CVB3 and CpG-melittin (CpGMel) alone and in combination (miR-CVB3 + CpGMel) and investigated possible mechanisms involved. RESULTS: We demonstrated that miR-CVB3 + CpGMel had no major impact on viral growth, while enhancing the cellular uptake of CpGMel in vitro. We further showed that combination therapy led to significant increases in tumor cell death and release of damage-associated molecular patterns compared with individual treatment. In vivo studies in 4T1 tumor-bearing Balb/c mice revealed that both primary and distant tumors were significantly suppressed, and the survival rate was significantly prolonged after administration of miR-CVB3 + CpGMel compared with single treatment. This anti-tumor effect was accompanied by increased ICD and immune cell infiltration into the TME. Safety analysis showed no significant pathological abnormalities in Balb/c mice. Furthermore, the developed therapeutic regimen also demonstrated a great anti-tumor activity in B16F10 melanoma tumor-bearing C57BL/6 J mice. CONCLUSIONS: Overall, our findings indicate that although single treatment using miR-CVB3 or CpGMel can efficiently delay tumor growth, combining oncolytic virus-based therapy can generate even stronger anti-tumor immunity, leading to a greater reduction in tumor size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".