Binding of inhibitory checkpoints to CD18 in <i>cis</i> hinders anti-cancer immune responses
Bibliographic record
Abstract
Abstract SIRPα is an inhibitory receptor on macrophages that limits phagocytosis and anti-tumor activity of macrophages by “ trans ” interacting with CD47 on tumor cells. Herein, we found that a large component of SIRPα’s inhibitory function occurred independently of CD47-binding and phosphatase signaling. This function resulted from a direct interaction between SIRPα and CD18 (β2 integrin) in “ cis ” at the surface of macrophages, involving SIRPα amino acids distinct from those implicated in the SIRPα-CD47 interaction. The cis interaction prevented activation of CD18, which is necessary for phagocytosis. Combined blockade of SIRPα-CD18 and SIRPα-CD47 was essential for maximizing phagocytosis and suppression of tumor growth in vivo . Similar cis interactions between CD18 and other inhibitory checkpoints, including PD-1, were also observed. Thus, in addition to mediating effects when engaged by ligands in trans , inhibitory checkpoints suppress immune cell activation through a mechanism targeting CD18 in cis . This dual mode of action should be considered when developing blockers of inhibitory checkpoints for immunotherapy. One-Sentence Summary In addition to being engaged in “ trans ” by ligands on tumor cells, inhibitory receptors, such as SIRPα and PD-1, hinder anti-cancer immune responses by “ cis ” interacting with β2 integrin CD18.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.018 | 0.007 |
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".