A Chemo-enzymatically Linked Bispecific Antibody Retargets T Cells to a Sialylated Epitope on CD43 in Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Acute myeloid leukemia (AML) is a high-risk disease with a poor prognosis, particularly in elderly patients. Because current AML treatment relies primarily on untargeted therapies with severe side effects that limit patient eligibility, identification of novel therapeutic AML targets is highly desired. We recently described AT1413, an antibody produced by donor B cells of a patient with AML cured after allogeneic hematopoietic stem cell transplantation. AT1413 binds CD43s, a unique sialylated epitope on CD43, which is weakly expressed on normal myeloid cells and overexpressed on AML cells. Because of its selectivity for AML cells, we considered CD43s as a target for a bispecific T-cell–engaging antibody (bTCE) and generated a bTCE by coupling AT1413 to two T-cell–targeting fragments using chemo-enzymatic linkage. In vitro, AT1413 bTCE efficiently induced T-cell–mediated cytotoxicity toward different AML cell lines and patient-derived AML blasts, whereas endothelial cells with low binding capacity for AT1413 remained unaffected. In the presence of AML cells, AT1413 bTCE induced upregulation of T-cell activation markers, cytokine release, and T-cell proliferation. AT1413 bTCE was also effective in vivo. Mice either coinjected with human peripheral blood mononuclear cells or engrafted with human hematopoietic stem cells [human immune system (HIS) mice] were inoculated with an AML cell line or patient-derived primary AML blasts. AT1413 bTCE treatment strongly inhibited tumor growth and, in HIS mice, had minimal effects on normal human hematopoietic cells. Taken together, our results indicate that CD43s is a promising target for T-cell–engaging antibodies and that AT1413 holds therapeutic potential in a bTCE-format. Significance: These findings offer preclinical evidence for the therapeutic potential of a bTCE antibody that targets a sialylated epitope on CD43 in AML.
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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".