CD8 T Cells Target Antigen Cross-Presented by Bone Marrow Derived Cells to Induce Bystander Rejection of Grafts Lacking the Cognate Peptide-MHC
Bibliographic record
Abstract
CD8 T cells play a key role in cancer immunotherapy and allograft rejection. However, it is not clear how they kill cells and tissues that do not have the agonist peptide-major histocompatibility complex (MHC) on their surface, as in the settings of MHC class I deficient tumors and indirect rejection of MHC-mismatched transplants. CD8 T cells might respond to agonist antigen cross-presented on hematopoietic cells, leading to a "bystander" rejection. Alternatively, they may recognize agonist antigen cross-presented on recipient endothelial cells and kill the tissue's vital blood supply. The latter mechanism predicts that all non-vascularized grafts, grafts dependent on in-growth of recipient blood vessels, will be susceptible to CD8 T cell mediated indirect rejection. In contrast, we show here that non-vascularized transplants, bearing the same agonist antigen, are not universally susceptible to this rejection pathway. Non-vascularized skin, but not islet or heart tissue transplants were indirectly rejected by CD8 T cells. Furthermore, CD8 T cells were able to indirectly reject skin grafts when recipient MHC class I expression was restricted to bone marrow derived cells but not when it was restricted to radioresistant cells (e.g. endothelial cells). These findings argue against a major role for endothelial cell cross-presentation in killing of tissue that does not present the agonist peptide-MHC class I. Instead, the data suggests that cross-presentation by recipient hematopoietic cells underlies the CD8 T cell mediated killing of tissue that is unable to directly present the target peptide-MHC class I.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".