Antibodies Against Macrophage CD44 Protect Platelets from FcγR-Mediated Phagocytosis: A Potential Mechanism for CD44 Antibody Amelioration of Murine Immune Thrombocytopenia
Bibliographic record
Abstract
Abstract CD44 is a transmembrane protein that is widely expressed on leukocytes and other cell types. CD44 is the major receptor for hyaluronan, and CD44-hyaluronan binding plays an important role in regulating immune cell migration, inflammation, and wound repair. Interestingly, targeting CD44 with monoclonal antibodies (anti-CD44) has demonstrated therapeutic efficacy in numerous murine autoimmune disease models including passive antibody-mediated immune thrombocytopenia (ITP), where it is effective at a three log-fold-lower dose compared to intravenous immunoglobulin (IVIg). However, the anti-inflammatory mechanisms behind anti-CD44 remain largely unsolved. In passive antibody-mediated ITP, anti-platelet antibody is administered to induce thrombocytopenia by FcγR-dependent and independent mechanisms, and macrophage depletion as well as FcγR blocking antibodies protect platelets from FcγR-dependent removal. The efficacy of anti-CD44 in this model suggest to us that anti-CD44 may be interfering with platelet removal by phagocytes. Here we show that anti-CD44 inhibits macrophage FcγR-mediated phagocytosis and protects platelets from macrophage uptake in vitro. Anti-CD44 inhibited RAW 264.7 macrophage phagocytosis of antibody-opsonized platelets in a dose-dependent manner, up to near complete (>90%) inhibition as compared to isotype controls. Multiple anti-CD44 clones tested were capable of inhibiting macrophage uptake of platelets opsonized with different anti-platelet antibodies. The binding of antibody-opsonized platelets to anti-CD44-treated macrophages was not blocked, suggesting that inhibition of phagocytosis occurs at a post-FcγR binding step. Because CD44 can regulate actin polymerization by recruiting the Rho-family GTPase-activating proteins Tiam1 and Vav2, we asked whether anti-CD44 may be interfering with actin polymerization required for platelet uptake. Live-cell microscopy of RAW 264.7 macrophages transfected with LifeAct (plasmid encoding a fluorescent non-cytotoxic actin binding protein) revealed that anti-CD44 did not affect actin dynamics and filopodia formation in the absence of antibody-opsonized platelets. However, anti-CD44-treated macrophages failed to initiate phagocytic cup formation upon antibody-opsonized-platelet binding, suggesting that inhibition is upstream of actin polymerization initiated by FcγRs. Finally, the ability of anti-CD44 to inhibit platelet uptake also showed complete concordance with a blocking antibody against FcγRIIb/III, implicating that anti-CD44 may be mediating inhibition of the FcγRIII pathway. In conclusion, our data suggests that antibodies against CD44 protect platelets from macrophage phagocytosis in vitro by inhibition of FcγRs, and that inhibition occurs at a step post-binding but before phagocytic cup formation. New therapies for ITP are needed to replace current donor-derived therapeutics and irreversible splenectomy. This research helps to shed light on how anti-CD44 functions to normalize platelet counts in murine passive ITP, and may pave the way for future novel therapeutics to replace IVIg in the treatment of ITP. Disclosures Lazarus: CSL pharmaceuticals: Research Funding; St.Michael's Hosp/The Canadian Blood Services: Other: Patents on monoclonal antibodies as IVIg and anti-D replacements; Rigel pharmaceuticals: Research Funding; Momenta pharmaceuticals: Honoraria.
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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 | 0.001 | 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".