Characterization of Pulmonary T Cell Response to Helper-Dependent Adenoviral Vectors following Intranasal Delivery
Bibliographic record
Abstract
In spite of the extensive research in the field of gene therapy, host immune responses continue to be the major barrier in translating basic research to clinical practice. Helper-dependent adenoviral (HD-Ad) vectors show great potential for pulmonary gene therapy, but the knowledge of pulmonary immune responses toward these vectors is very limited. In this study, we show that HD-Ad vectors are potent stimulators of dendritic cell (DC) maturation, thus leading to stimulation of T cell proliferation with approximately 6% of naive CD4(+) T cells from pulmonary mediastinal lymph node responding to HD-Ad-treated DCs. In contrast to the belief that HD-Ad vectors are unable to prime adaptive immune response, we show for the first time, through in vivo pulmonary studies in mice, that HD-Ad vectors can prime CD4(+) and CD8(+) T cell responses in the lung at high and substantially low doses. This indicates cross-presentation of HD-Ad-derived epitopes by DCs to prime CD8(+) T cell responses. To assess the basis of pulmonary T cell response against HD-Ad vectors, we examined the response of conventional DCs (cDCs) and plasmacytoid DCs (pDCs) in the lung. In response to HD-Ad delivery, there is induction of maturation in both cDC and pDC subsets, but it is the cDCs, not pDCs, that migrate rapidly to draining lymph nodes within the first 2 days after vector delivery to prime adaptive immune response against these vectors. These findings have implications for development of strategies to prevent adaptive immune responses against gene therapy vectors.
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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".