Targeting CD38 in Antibody-Mediated Rejection
Bibliographic record
Abstract
Antibody-mediated rejection (AMR) remains a major challenge in clinical transplantation. Current therapies have yielded inconsistent outcomes, highlighting the need for innovative approaches. CD38, a multifunctional glycoprotein, is highly expressed on plasma cells and natural killer (NK) cells, potentially offering a dual mechanism of action that could intervene in the pathophysiologic course of AMR: depleting alloantibody-producing plasma cells and NK cells. This review focuses on recent results from CD38-targeted therapies, with felzartamab emerging as a promising option. Previous case reports and series suggested that off-label daratumumab treatment could effectively reverse AMR. Felzartamab has now demonstrated safety and efficacy in a phase 2 trial for late AMR. Reductions in microvascular inflammation, downregulation of rejection-associated transcripts, and decreases in donor-derived cell-free DNA paralleled a substantial decrease in NK cell counts. However, felzartamab did not significantly affect donor-specific antibodies, which may reflect its distinct mechanism of action, primarily involving antibody-dependent cellular cytotoxicity and phagocytosis. The effects on rejection activity may have a rapid onset, but are transient. The potential benefits of prolonged therapy are currently being investigated in a recently launched phase III trial. Future studies may expand the applications of CD38 targeting to early AMR or broader indications, such as DSA-negative microvascular inflammation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".