The Early Induction of PDL1 On Monocytes by Ivig Suppresses T Cell Activation in Allogeneic Mixed Lymphocyte Reactions
Bibliographic record
Abstract
Abstract Abstract 4111 Background: Recognition of histocompatibility determinants by allogeneic T cells together with the engagement of co-stimulatory molecules with their ligands expressed on accessory cells (B7:CD28, CD40:CD40L) is essential for the induction of T cell-mediated allograft rejection. In contrast, the PD1:PDL1 negative co-stimulatory pathway plays a critical role in the induction and maintenance of peripheral transplantation tolerance. Despite the use of potent immunosuppressive therapy for the blockade of co-stimulatory pathways, allograft rejection and drug toxicity remain an important problem in transplanted patients. IVIg was first used as a prophylactic agent in these immunocompromised patients to prevent infections, but several studies have suggested that IVIg also improved the rate of graft survival in patients with high risk for rejection. The mechanisms responsible for this anti-inflammatory effect are unclear and remain to be determined. We recently showed, using the allogeneic mixed lymphocyte reaction (MLR) as an in vitro model of allograft rejection and GvHD, that IVIg strongly inhibited T cell activation. In the present study, we sought to determine the mechanisms underlying this inhibition. Methods: For allogeneic MLR, human peripheral blood mononuclear cells (PBMC) from 2 different individuals were mixed together with or without 2 mg/ml of IVIg and incubated for 4 days prior to determination of IL-2 secretion by ELISA as a measure of T cell activation. The expression of TCR, CD3, CD28 and PD1 on T cells and HLA-DR, CD80, CD86 and PDL1 on monocytes was evaluated by flow cytometry. Results: IVIg strongly inhibited IL-2 secretion (>90%; P<0.001) as previously reported. To explain the inhibition of T cell activation in the presence of IVIg, we postulated that the expression of molecules involved in antigen presentation and in different co-stimulatory pathways was modulated by IVIg. We thus evaluated the effect of IVIg on the cell surface expression of various molecules implicated in T cell activation or tolerance, 24 hours after the onset of the MLR. Our results showed no modulation of TCR, CD3, CD28 and PD1 expression on T cells. Similarly, IVIg did not affect the expression of CD86 on monocytes. In contrast, the expression of CD80 was significantly decreased (>30%; P<0.01) on these cells after IVIg treatment. In addition, a strong increase in PDL1 expression (>70%; P<0.05) on monocytes was observed in MLRs done in the presence of IVIg. Finally, the expression of HLA-DR was increased by >60% (P<0.01) and that of CD14 was decreased by >50% (P<0.01) in the presence of IVIg, which is characteristic of the emergence of an anti-inflammatory monocyte population. Conclusion: Altogether, our results suggest that IVIg induces its immunosuppressive effects in allogeneic MLRs by modulating the expression of co-stimulatory molecules on monocytes and by inducing an anti-inflammatory monocyte population. This study contributes to a better understanding of the mechanisms by which IVIg may induce peripheral tolerance and improve graft survival in transplanted patients. Disclosures: No relevant conflicts of interest to declare.
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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".