Development of a B-cell maturation antigen-specific T-cell antigen coupler receptor for multiple myeloma
Bibliographic record
Abstract
BACKGROUND AIMS: T cells engineered with synthetic receptors have delivered powerful therapeutic results for patients with relapsed/refractory hematologic malignancies. The authors have recently described the T-cell antigen coupler (TAC) receptor, which co-opts the endogenous T-cell receptor (TCR) and activates engineered T cells in an HLA-independent manner. Here the authors describe the evolution of a next-generation TAC receptor with a focus on developing a TAC-engineered T cell for multiple myeloma. METHODS: To optimize the TAC scaffold, the authors employed a bona fide antigen-binding domain derived from the B-cell maturation antigen-specific monoclonal antibody C11D5.3, which has been used successfully in the clinic. The authors first tested humanized versions of the UCHT1 domain, which is used by the TAC to co-opt the TCR. The authors further discovered that the signal peptide affected surface expression of the TAC receptor. Higher density of the TAC receptor enhanced target binding in vitro, which translated into higher levels of Lck at the immunological synapse and stronger proliferation when only receptor-ligand interactions were present. RESULTS: The authors observed that the humanized UCHT1 improved surface expression and in vivo efficacy. Using TAC T cells derived from both healthy donors and multiple myeloma patients, the authors determined that despite the influence of receptor density on early activation events and effector function, receptor density did not impact late effector functions in vitro, nor did the receptor density affect in vivo efficacy. CONCLUSIONS: The modifications to the TAC scaffold described herein represent an important step in the evolution of this technology, which tolerates a range of expression levels without impacting therapeutic efficacy.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".