Potent immunotherapy against well‐established thymoma using adoptively transferred transgene <i>IL‐6</i>‐engineered dendritic cell‐stimulated CD8<sup>+</sup> T‐cells with prolonged survival and enhanced cytotoxicity
Bibliographic record
Abstract
BACKGROUND: Adoptive transfer of CD8(+) T-cells specific for tumor-antigens is an attractive strategy for anti-tumor therapy. In the present study, the subsets TA and TB were used to represent the population of CD8(+) T cells generated by culturing the respective cells with irradiated dendritic cells (DCs) pulsed with ovalbumin (OVA) protein and transfected with adenoviral vector constructs as described. METHODS: Naïve OVA specific CD8(+) T cells were isolated from the spleen of OVA-specific T-cell receptor transgenic OTI mice. The subsets TA and TB were then generated by in vitro activating the population of CD8(+) T cells with OVA-pulsed DCs transfected with IL-6-expressing adenoviral vector (AdVIL-6 ) or the control vector (AdVNull ). To assess their in vivo immunotherapeutic effects, TA - or TB -cells were intravenously transferred into C57BL/6 mice bearing EG7 thymoma (6-8 mm in diameter). RESULTS: TA -cells displayed a higher level of expression of CD62 l, IL-7R, FasL, perforin and CCR6, and also exhibited more potent in vitro cytotoxicity to OVA-expressing EG7 thymoma cells via perforin- and Fas/FasL-mediated apoptosis than TB -cells. CD8(+) T-cell survival was kinetically analyzed in C57BL/6 mice transferred with TA - or TB -cells by flow cytometry. We found that the adoptively transferred TA -cells had prolonged survival and enhanced T-cell memory development compared to TB -cells. In addition, TA -, but not TB -cells were able to eradicate well-established EG7 thymomas in all eight tumor-bearing mice. CONCLUSIONS: Our data suggest that AdVIL-6 -transfected DC-stimulated CD8(+) T cells with potent cytotoxicity and survival advantage may serve as an effective adoptive CD8(+) T-cell immunotherapy strategy for anti-tumor treatment.
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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) | 0.001 | 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".