Enhanced Protective Immunity Derived from Dendritic Cells with Phagocytosis of CD40 Ligand Transgene-engineered Apoptotic Tumor Cells via Increased Dendritic Cell Maturation
Bibliographic record
Abstract
AIMS AND BACKGROUND: Dendritic cells (DCs) play a pivotal role in regulating CD8+ cytotoxic T-lymphocyte (CTL) responses. Currently, DC vaccines have been used in experimental animal models and clinical trials for evaluation of antitumor immunity. However, their efficacy is limited, warranting the improvement of DC-based cancer vaccines. CD40 ligand (CD40L) stimulates DC activation and maturation via CD40-CD40L interaction. We demonstrated that DCs that had phagocytized apoptotic tumor cells induced antitumor immunity. METHODS: We generated CD40L-expressing (EG7-CD40L) and the control (EG7-Null) EG7 tumor cells by transfection of EG7 tumor cells with CD40L-expressing adenoviral vector AdVCD40L and the control vector AdV(pLpA), respectively. We also generated DC vaccines (DC-EG7/CD40L and the control DC-EG7/Null) using DCs with phagocytosis of irradiated EG7-CD40L and EG7-Null tumor cells, and assessed their phenotype and immunogenicity by flow cytometry and animal studies in C57BL/6 mice. RESULTS: We demonstrate that an irradiation of 9000-rad induced Annexin V-expressing cell apoptosis in most (~75%) tumor cells, and provide evidence for phagocytosis of apoptotic tumor cells by flow cytometry and confocal microscopy. The DC-EG7/CD40L cells showed higher expression of DC maturation markers (Ia(b), CD40, CD80, and CD86) and peptide/major histocompatibility complex I than the control DC-EG7/Null cells. In addition, DC-EG7/CD40L vaccine stimulates more efficient (0.97%) tumor-specific CTL responses than DC-EG7/Null cells (0.31%). Furthermore, 80% (4/5) of mice immunized with DC-EG7/CD40L vaccine become tumor-free after EG7 tumor cell challenge, whereas DC-EG7/Null vaccine only delays immunized mouse death. CONCLUSIONS: Dendritic cells that have phagocytized CD40L-expressing apoptotic tumor cells appear to offer new strategies in DC cancer vaccines.
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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 | 0.001 |
| 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".