CD19 and FcγRIIb co-engagement inhibits processes essential to T cell–dependent B-cell responses
Bibliographic record
Abstract
Obexelimab is an investigational, bifunctional humanized monoclonal antibody that inhibits B-lineage cells by binding CD19 via its Fab region and simultaneously co-engaging the inhibitory receptor FcγRIIb through a modified Fc region. Interactions between B cells and T cells specific for the same Ag are essential for the development of germinal center (GC) B-cell responses and high-affinity antibodies. Mutant mice expressing human FcγRIIb and a mouse obexelimab surrogate (mObx) were used to determine if mObx inhibits these critical interactions between cognate B cells and T cells. In ex vivo experiments, mObx blocked B-cell receptor (BCR)-mediated uptake of Ag-coated beads by splenic follicular (Fo) and marginal zone (MZ) B cells and peritoneal cavity (PerC) B1 cells. Similarly, obexelimab treatment of human B cells significantly reduced BCR-mediated bead uptake ex vivo. mObx-treatment inhibited Ag presentation by splenic B cells to co-cultured T cells, as T-cell proliferation and expression of activation markers CD25 and CD44 were significantly reduced when mObx, but not control anti-CD19 antibody, was added to the co-culture. Finally, prophylactic treatment of mice with mObx effectively blocked the activation of human FcγRIIb-expressing B cells and the development of an Ag-specific GC response in vivo. Treatment after GC onset resulted in dissolution of the GC. Collectively, these data demonstrate that CD19/FcγRIIb co-engagement effectively suppresses processes essential to support T cell-dependent B-cell responses, which is consistent with the proposed mechanism of action of obexelimab.
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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".