Dendritic Cells Recruit T Cell Exosomes via Exosomal LFA-1 Leading to Inhibition of CD8+ CTL Responses through Downregulation of Peptide/MHC Class I and Fas Ligand-Mediated Cytotoxicity
Bibliographic record
Abstract
Active T cells release bioactive exosomes (EXOs). However, its potential modulation in immune responses is elusive. In this study, we in vitro generated active OVA-specific CD8(+) T cells by cultivation of OVA-pulsed dendritic cells (DC(OVA)) with naive CD8(+) T cells derived from OVA-specific TCR transgenic OTI mice and purified EXOs from CD8(+) T cell culture supernatant by differential ultracentrifugation. We then investigated the suppressive effect of T cell EXOs on DC(OVA)-mediated CD8(+) CTL responses and antitumor immunity. We found that DC(OVA) uptake OTI T cell EXOs expressing OVA-specific TCRs and Fas ligand via peptide/MHC Ag I-TCR and CD54-LFA-1 interactions leading to downregulation of peptide/MHC Ag I expression and induction of apoptosis of DC(OVA) via Fas/Fas ligand pathway. We demonstrated that OVA-specific OTI T cell EXOs, but not lymphocytic choriomeningitis virus-specific TCR transgenic mouse CD8(+) T cell EXOs, can inhibit DC(OVA)-stimulated CD8(+) CTL responses and antitumor immunity against OVA-expressing B16 melanoma. In addition, these T cell EXOs can also inhibit DC(OVA)-mediated CD8(+) CTL-induced diabetes in transgenic rat insulin promoter-mOVA mice. Interestingly, the anti-LFA-1 Ab treatment significantly reduces T cell EXO-induced inhibition of CD8(+) CTL responses in both antitumor immunity and autoimmunity. EXOs released from T cell hybridoma RF3370 cells expressing OTI CD8(+) TCRs have a similar inhibitory effect as T cell EXOs in DC(OVA)-stimulated CTL responses and antitumor immunity. Therefore, our data indicate that Ag-specific CD8(+) T cells can modulate immune responses via T cell-released EXOs, and T cell EXOs may be useful for treatment of autoimmune diseases.
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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".