Belantamab mafodotin does not induce B-cell maturation antigen loss or systemic immune dysfunction in multiple myeloma
Bibliographic record
Abstract
Various drug classes target B-cell maturation antigen (BCMA) including chimeric antigen receptor T-cell (CAR T) therapies, bispecific antibodies (bsAb), and antibody-drug conjugates (ADC). Outcomes with CAR T and bsAb therapies in multiple myeloma (MM) have been affected by T-cell exhaustion, and abrogated expression/mutation of the BCMA target has been observed with anti-BCMA therapies. Optimal anti-BCMA sequencing strategies are needed to improve long-term clinical outcomes. We used data from multiple clinical studies of the ADC belantamab mafodotin (as monotherapy and combination regimens) to explore its impact on BCMA levels and binding (using electrochemiluminescence methodology) and T-cell/ natural killer (NK) cell fitness (including cell counts, expression of functional markers), to determine whether belantamab mafodotin could be sequenced ahead of other BCMA-targeting therapies for MM. Levels of free soluble BCMA (sBCMA), measured at the best-confirmed response (BCR) and at progression, dropped at BCR but returned to near baseline at time of disease progression. There was no apparent impact on the binding epitope of BCMA, as indicated by the retention of belantamab mafodotin binding to sBCMA. No significant changes in cell counts or expression of T-cell exhaustion markers (PD-1, TIGIT, TIM-3 [except NK cells], or CTLA-4) and co-stimulatory markers (ICOS [except CD4+ T cells], OX40, 4-1BB) were observed at relevant time points (up to 4 or 21+ months depending on the marker). No negative impact was observed on expression of proliferation (Ki67) and antitumor activity (granzyme B, CD107a) markers. Pending confirmatory studies, our results indicate potential for utilizing belantamab mafodotin ahead of other anti-BCMA therapies in MM.
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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) | 0.001 | 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) | 0.000 | 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".