BCMA Extracellular Domain Functional Hotspots and Resistance to Variable Anti-BCMA T Cell Engagers in Multiple Myeloma
Bibliographic record
Abstract
Several T cell engagers (TCE) targeting B cell maturation antigen (BCMA) are currently approved or in clinical development for the treatment of multiple myeloma (MM). These TCEs have varying epitope specificity, valency, avidity, and geometry. Despite high and deep initial responses, resistance invariably occurs. Antigenic drifting represents a common escape mechanism through either biallelic deletion of TNFRSF17, or more commonly monoallelic deletion coupled with BCMA extracellular domain (ECD) mutations. These ECD mutations however do not result in universal resistance, but rather confer differential sensitivities to distinct anti-BCMA TCEs. Defining “functional hotspots” in BCMA ECD will provide a valuable tool for the rational selection of anti-BCMA TCEs. We conducted an alanine scanning mutagenesis screen in order to define BCMA ECD residues required for anti-BCMA TCE binding. Excluding the initial methionine and four native alanine residues within 54-amino-acid BCMA ECD, we mutated the remaining 49 amino acids to alanine generating a library of lentiviral particles for each BCMA variant. K562 cells stably transduced to express wild type (wt) or mutant BCMA (50 clones) were screened for surface BCMA expression by flow cytometry, as well as teclistamab, elranatamab, and alnuctamab binding and cytotoxicity in cocultures with peripheral blood mononuclear cells. BCMA mutants had varying surface expressions by polyclonal anti-BCMA flow antibody detection. Notably the following alanine substitutions, M4A, Y13A, D15A, L18A, I22A, C24A, L26A, R27A, and C37A resulted in significant downregulation of membrane BCMA expression compared to wtBCMA K562 and OPM2 MM cells. TCE binding studies were conducted by incubating wt or mutant BCMA clones with teclistamab, elranatamab, or alnuctamab (10 and 68 nM), followed by secondary antibody staining with anti-IgG4, anti-IgG2, or anti-IgG1, respectively. Critical BCMA ECD residues that abrogated the binding of all 3 tested TCEs included D15A, L17A, and C24A. Notably, C24 is involved in mediating one of the three disulfide bonds that maintain the integrity of BCMA ECD tertiary structure (Uniprot Q02223 TNR17_HUMAN), while D15 and L17 are conserved residues across species (Granja et al. PLOS ONE 2017). Binding of the bivalent alnuctamab was generally less perturbed by ECD mutations with the exception of the following 5 residues Y13A, D15A, L17A, L18A, and C24A. Teclistamab and elranatamab binding were mostly, but not uniformly, hindered by alanine substitutions clustered between D15-C37. Of interest, mutations C21A, S30A, P33A, and T36A preferentially impacted teclistamab but not elranatamab binding, while L26A only impacted elranatamab binding. Y13A and L18A selectively abrogated alnuctamab binding. Consistent with their binding profiles, BCMA ECD mutants revealed differential sensitivities to tested anti-BCMA TCEs. As such, D15A, L17A, and C24A abrogated all 3 TCE binding and cytotoxicity. In contrast, mutants with differential binding such as Y13A and L18A demonstrated selective resistance to alnuctamab, while C21A demonstrated relative resistance to teclistamab but not to elranatamab or alnuctamab. Other mutants such as R27A and C37A were selectively sensitive to alnuctamab. Whole genome sequencing (WGS) of MM cells in patients progressing on anti-BCMA TCE identified BCMA mutants that corroborated the current BCMA screen. In particular, functional hotspots D15E/ S30del and R27P were also identified in teclistamab or elranatamab refractory patients, respectively. Analysis of BCMA mutational status by WGS in patients progressing on anti-BCMA TCE (n=30) is ongoing and will be updated at the meeting. In summary, we herein established a dictionary of BCMA functional hotspots and characterized their differential impact on anti-BCMA TCE binding and cytotoxicity. These results will not only support the rational design of future anti-BCMA agents but also guide the clinical sequencing of anti-BCMA therapies.
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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 | 0.000 |
| 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".