Durable preservation of antiviral antibodies after CD19-directed chimeric antigen receptor T-cell immunotherapy
Bibliographic record
Abstract
The long-term effects of CD19-targeted chimeric antigen receptor-modified T-cell immunotherapy (CD19-CARTx) for B-cell malignancies on humoral immunity are unclear. We examined antiviral humoral immunity in 39 adults with B-cell malignancies who achieved durable complete remission without additional therapy for >6 months after CD19-CARTx. Despite CD19+ B-cell aplasia in all patients, the incidence of viral infections occurring >90 days post-CD19-CARTx was low (0.91 infections per person-year). Because long-lived plasma cells are CD19- and should not be direct targets of CD19-targeted chimeric antigen receptor T cells, we tested the hypothesis that humoral immunity was preserved after CD19-CARTx based on linear mixed-effects models of changes in serum total immunoglobulin G (IgG) concentration, measles IgG concentration, and the number of viruses or viral epitopes to which serum IgG was directed (the "antivirome") using the novel VirScan assay. Samples were tested pre-CD19-CARTx and ∼1, 6, and 12 months post-CD19-CARTx. Although total IgG concentration was lower post-CD19-CARTx (mean change, -17.5%), measles IgG concentration was similar (mean change, 1.2%). Only 1 participant lost measles seroprotection post-CD19-CARTx but had undergone allogeneic hematopoietic cell transplantation before CD19-CARTx. The antivirome was also preserved, with mean absolute losses of 0.3 viruses and 6 viral epitopes detected between pre- and post-CD19-CARTx samples. Most participants gained IgG to ≥2 epitopes for ≥2 viruses, suggesting that humoral immunity to some viruses may be maintained or recover after successful CD19-CARTx. These findings may differ in children. Studies of immunoglobulin replacement and vaccination after CARTx are warranted.
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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 | 0.001 | 0.001 |
| 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 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".