Tisagenlecleucel immunogenicity in relapsed/refractory acute lymphoblastic leukemia and diffuse large B-cell lymphoma
Bibliographic record
Abstract
Tisagenlecleucel is indicated for pediatric and young adult patients with relapsed/refractory (r/r) B-cell acute lymphoblastic leukemia (B-ALL) and adult patients with r/r diffuse large B-cell lymphoma (DLBCL). The tisagenlecleucel chimeric antigen receptor (CAR) contains a murine single-chain variable fragment domain; we examined the effects of humoral and cellular immune responses to tisagenlecleucel on clinical outcomes using 2 validated assays. Data were pooled from the ELIANA (registered at www.clinicaltrials.gov as #NCT02435849) and ENSIGN (#NCT02228096) trials in r/r B-ALL (N = 143) and the JULIET trial (#NCT02445248) in r/r DLBCL (N = 115). Humoral responses were determined by flow cytometric measurement of anti-murine CAR19 (mCAR19) antibodies in serum. Cellular responses were determined using T-cell production of interferon-γ in response to 2 different pools of mCAR19 peptides. Pretreatment anti-mCAR19 antibodies were detected in 81% of patients with r/r B-ALL and 94% of patients with r/r DLBCL. Posttreatment anti-mCAR19 antibodies were higher than patient-specific baseline in 42% of r/r B-ALL and 9% of r/r DLBCL patients. Pretreatment and posttreatment anti-mCAR19 antibodies did not affect tisagenlecleucel cellular kinetics, including maximum concentration and persistence (r2 < 0.05), clinical response (day-28 response, duration of response, and event-free survival), and safety. T-cell responses were consistent over time, with net responses <1% at baseline and posttreatment time points in a majority of patients and no effect on transgene expansion or persistence or outcomes. Presence of baseline and/or posttreatment anti-mCAR19 antibodies or T-cell responses did not alter the activity of tisagenlecleucel in patients with r/r B-ALL or r/r DLBCL.
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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) | 0.000 | 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".