Structural details of monoclonal antibody m971 recognition of the membrane-proximal domain of CD22
Bibliographic record
Abstract
Cluster of differentiation-22 (CD22) belongs to the sialic acid–binding immunoglobulin (Ig)-like lectin family of receptors that is expressed on the surface of B cells. It has been classified as an inhibitory coreceptor for the B-cell receptor because of its function in establishing a baseline level of B-cell inhibition. The restricted expression of CD22 on B cells and its inhibitory function make it an attractive target for B-cell depletion in cases of B-cell malignancies. Genetically modified T cells with chimeric antigen receptors (CARs) derived from the m971 antibody have shown promise when used as an immunotherapeutic agent against B-cell acute lymphoblastic leukemia. A key aspect of the efficacy of this CAR-T was its ability to target a membrane-proximal epitope on the CD22 extracellular domain; however, the molecular details of m971 recognition of CD22 have thus far remained elusive. Here, we report the crystal structure of the m971 fragment antigen-binding in complex with the two most membrane-proximal Ig-like domains of CD22 (CD22 d6–d7 ). The m971 epitope on CD22 resides at the most proximal Ig domain (d7) to the membrane, and the antibody paratope contains electrostatic surfaces compatible with interactions with phospholipid head groups. Together, our data identify molecular details underlying the successful transformation of an antibody epitope on CD22 into an effective CAR immunotherapeutic target.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".