985 PSGL-1 is a novel inhibitor of tumor cell phagocytosis by macrophages
Bibliographic record
Abstract
<h3>Background</h3> In recent years, macrophages have emerged as an essential component of the antitumor immune response. Indeed, macrophages are able to ‘phagocytose’, i.e., to ingest and kill tumor cells. The cellular and molecular mechanisms that regulate this process have been increasingly investigated.<sup>1</sup> Our group and others have demonstrated the implication of specific ligand-receptor pathways involved in the regulation of phagocytosis.<sup>2–4</sup> Building on these findings, we aim at identifying additional regulators of phagocytosis which could constitute novel targets for immunotherapy. <h3>Methods</h3> <h3>Mice</h3> Wild-type (WT) mice were generated in the C57Bl/6J background. Sele, Sell, Selp (triple selectin) KO mice were acquired from The Jackson Laboratory (Bar Harbor, Maine, USA). <h3>Cells</h3> Bone marrow-derived macrophages (BMDM) and PSGL-1-deficient target cells were generated as previously described.<sup>3</sup> <h3>Microscopy-based phagocytosis assay</h3> This assay was performed as previously described.<sup>3</sup> Briefly, BMDMs were coincubated with fluorescently labelled target cells at a ratio of 1:4 (macrophages: target cells). After 2 hours, the cells were washed and imaged with an inverted microscope (Carl Zeiss Axiovert S100 TV). The percentage of phagocytosis was calculated as the number of macrophages containing labelled target cells versus the total number of macrophages. All experiments were repeated at least three times. Statistical analyses were performed on the initial raw values. <h3>Results</h3> We have recently identified a molecule at the surface of tumor cells of lymphoid and myeloid lineages, named PSGL-1 (P-selectin glycoprotein ligand 1), that prevents the elimination of these cancer cells by macrophages. PSGL-1 has primarily been described as a ligand for the selectin family of adhesion proteins<sup>5</sup> Our results demonstrate that PSGL-1 expression at the surface of tumor cells inhibits phagocytosis and efficient elimination of these cells by macrophages. Indeed, a deficiency in PSGL-1 on these tumor cells increases their phagocytosis (figure 1). Furthermore, we found that this inhibitory effect was independent of selectins, as macrophages lacking all three selectins (Triple Selectin KO) showed no defect in phagocytosis (figure 2). <h3>Conclusions</h3> Our results demonstrate a previously unsuspected role of PSGL-1. We observed that loss of PSGL-1 on murine tumor cells (L1210) and human multiple myeloma (RPMI-8226, OPM-2) promotes phagocytosis of these tumor cells. Results not shown here further suggest a novel mechanism of action for PSGL-1 as an anti-phagocytic ligand which likely interacts with an as of yet unknown receptor. For future work, we aim to provide convincing evidence that this pathway could represent a new target for anti-cancer immunotherapy. <h3>References</h3> Freeman SA, S Grinstein, Phagocytosis: receptors, signal integration, and the cytoskeleton.<i> Immunol Rev</i>, 2014;<b>262</b>(1):193–215. Chen J, <i>et al.</i><i> SLAMF7 is critical for phagocytosis of haematopoietic tumour cells via Mac-1 integrin.</i><i> Nature</i>, 2017;<b>544</b>(7651):493–497. Tang Z, <i>et al.</i><i> Inflammatory macrophages exploit unconventional pro-phagocytic integrins for phagocytosis and anti-tumor immunity.</i><i> Cell Rep</i>, 2021;<b>37</b>(11):110111. Barkal AA, <i>et al.</i><i> Engagement of MHC class I by the inhibitory receptor LILRB1 suppresses macrophages and is a target of cancer immunotherapy.</i><i> Nat Immunol</i>, 2018;<b>19</b>(1):76–84. Borsig L. Selectins in cancer immunity.<i> Glycobiology</i>, 2018;<b>28</b>(9):648–655.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".