Clinical Impact of CTLA-4 Single-Nucleotide Polymorphism in DLBCL Patients Treated with CAR-T Cell Therapy
Bibliographic record
Abstract
FMC63-CAR T cell therapy targeting CD19 protein on malignant B-cells is effective in patients with relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL), with complete response rates of 43–54%. Common germline variants of the immune-checkpoint regulator CTLA-4 may elicit different responses to CAR-T cell therapy. The CTLA4 gene single-nucleotide polymorphism rs231775 coding threonine or alanine at amino acid position 17 of the CTLA-4 protein was prevalent in 55% of the studied DLBCL patients. In a retrospective comparative analysis of clinical outcome, there were significant differences in CTLA4 A17hom vs. T17Ahet and T17hom carriers with four-year progression-free survival at 77%, 59%, and 30% (p = 0.019), four-year overall survival was 79%, 41%, and 33% (p = 0.049), the relapse rates were 20%, 37%, and 56% (p = 0.025), and the death rates 20%, 54%, and 52% (p = 0.049). Conclusions: CTLA4 rs231775 polymorphism may impact the treatment outcome in FMC63-anti-CD19 CAR-T cell therapy, with an association of the CTLA4 minor allele A17 to favorable treatment outcome.
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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 | 0.001 |
| 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".