Graft-versus-Host Disease Impairs Vaccine Responses through Decreased CD4+ and CD8+ T Cell Proliferation and Increased Perforin-Mediated CD8+ T Cell Apoptosis
Bibliographic record
Abstract
Tumor-targeted vaccines represent a strategy to enhance the graft-versus-leukemia effect after allogeneic blood and marrow transplantation (BMT). We have previously shown that graft-versus-host disease (GVHD) can negatively impact quantitative responses to vaccines. Using a minor histocompatibility Ag-mismatched BMT (B6 → B6 × C3H.SW) followed by adoptive transfer of HY-specific T cells and HY-expressing dendritic cells, we assessed whether GVHD induced by donor lymphocyte infusion (DLI) affects the persistence, proliferation, and survival of vaccine-responding, nonalloantigen reactive T cells. Both CD8(+) and CD4(+) HY-specific T cells undergo less vaccine-driven proliferation in allogeneic recipients with GVHD. Although vaccine-responding CD8(+) T cells show decreased IFN-γ and CD107a production, CD4(+) T cells exhibit increased programmed death 1 and T cell Ig mucin-like domain 3 expression. In addition, the degree of apoptosis in vaccine-responding CD8(+) T cells was higher in the presence of GVHD, but there was no difference in CD4(+) T cell apoptosis. Using Fas ligand-deficient or TRAIL-deficient DLI had no impact on apoptosis of HY-specific T cells. However, perforin-deficient alloreactive DLI induced significantly less apoptosis of vaccine-responding CD8(+) T cells and resulted in enhanced tumor protection. Thus, diminished vaccine responses during GVHD result from impaired proliferation of CD8(+) and CD4(+) T cells responding to vaccination, with an additional contribution from perforin-mediated CD8(+) T cell apoptosis. These results provide important insights toward optimizing vaccine responses after allogeneic BMT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".