PD-1 endocytosis unleashes the cytolytic potential of check-point blockade in tumor immunity
Bibliographic record
Abstract
Summary PD-1 immune checkpoint blockade (ICB) is now a promising first-line treatment for many cancers. While the steric blockade of PD-1 binding to its ligand plays a role, the role of internalisation in promoting the efficacy of ICB has not been explored. In this study, we show that PD-1 internalisation also contributes by unlocking the full cytolytic potential of ICB in cancer immunotherapy. We found that anti-mouse and human PD-1 downregulate a subset of PD-1 surface receptors on T-cells with high-density surface PD-1 leaving T-cells with intermediate expression resistant to further internalisation. Down regulation was seen on both CD4 and CD8 cells but was maximally effective on CD8 effector cells. In human T-cells, nivolumab outperformed pembrolizumab in terms of rate and efficacy. We also found that PD-1 internalisation depended on bivalent antibody (Ab)-induced crosslinking, while monovalent Ab sterically blocked PD-1 without inducing endocytosis. Immunologically, while both monovalent and bivalent Ab limited B16-PD-L1 tumor growth, bivalent Ab was significantly more effective. In molecular terms, while both antibodies increased granzyme B (GZMB) expression in CD8+ cytolytic T-cells, the induction of the second key cytolytic pore-forming mediator, perforin, was dependent on the blockade and internalisation mediated by bilavent anti-PD-1. Our findings unveil a novel mechanism in checkpoint blockade where steric blockade combined with the removal of PD-1 from the cell surface by endocytosis can complement and optimize therapy. The targeting of PD-1 internalisation holds promise for enhancing anti-tumor immunity and improving PD-1 checkpoint blockade therapy. Graphical Abstract In brief Ben Saad et al define the mechanism of PD-1 inhibitory endocytosis and show that the removal of surface PD-1 by endocytosis plays a role in complementing and optimizing checkpoint blockade. Targeting PD-1 internalisation holds promise for enhancing anti-tumor immunity and improving the efficacy of PD-1 checkpoint blockade therapy.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".