Blockade of Programmed Death-1 Ligands on Dendritic Cells Enhances T Cell Activation and Cytokine Production
Bibliographic record
Abstract
Programmed death-1 ligand (PD-L)1 and PD-L2 are ligands for programmed death-1 (PD-1), a member of the CD28/CTLA4 family expressed on activated lymphoid cells. PD-1 contains an immunoreceptor tyrosine-based inhibitory motif and mice deficient in PD-1 develop autoimmune disorders suggesting a defect in peripheral tolerance. Human PD-L1 and PD-L2 are expressed on immature dendritic cells (iDC) and mature dendritic cells (mDC), IFN-gamma-treated monocytes, and follicular dendritic cells. Using mAbs, we show that blockade of PD-L2 on dendritic cells results in enhanced T cell proliferation and cytokine production, including that of IFN-gamma and IL-10, while blockade of PD-L1 results in similar, more modest, effects. Blockade of both PD-L1 and PD-L2 showed an additive effect. Both whole mAb and Fab enhanced T cell activation, showing that PD-L1 and PD-L2 function to inhibit T cell activation. Enhancement of T cell activation was most pronounced with weak APC, such as iDCs and IL-10-pretreated mDCs, and less pronounced with strong APC such as mDCs. These data are consistent with the hypothesis that iDC have a balance of stimulatory vs inhibitory molecules that favors inhibition, and indicate that PD-L1 and PD-L2 contribute to the poor stimulatory capacity of iDC. PD-L1 expression differs from PD-L2 in that PD-L1 is expressed on activated T cells, placental trophoblasts, myocardial endothelium, and cortical thymic epithelial cells. In contrast, PD-L2 is expressed on placental endothelium and medullary thymic epithelial cells. PD-L1 is also highly expressed on most carcinomas but minimally expressed on adjacent normal tissue suggesting a role in attenuating antitumor immune responses.
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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) | 0.000 | 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".