Abstract B047: Transcriptional signatures associated with persisting CD19 CAR-T cells in children with leukemia
Bibliographic record
Abstract
Abstract Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. One of the most critical determinants of achieving a durable response is the persistence of CAR T-cells. Here, we systematically analysed CD19 CAR T cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). We performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We first found that late, long-lived CAR T cells developed a CD4/CD8 double-negative (DN) phenotype characterised by GZMK+ exhausted-like memory state. Our key finding was that the most recurrent and strongest markers of long-lived CAR-T cells generated a persisting CAR T signature that was delineated by the expression of bona fide immune-related genes, such as TIGIT and GPR183, as well as genes with unknown or emerging roles in immune biology. This signature emerged across clonotypes and subsets of T-cells, indicating that CAR T-cells converge transcriptionally when a durable clinical response is achieved. Remarkably, we also detected this persistence signature in recipients of a different CD19 CAR T-cell product that maintained decade long remissions in two adult patients with chronic lymphocytic leukaemia. Examination of single T-cell transcriptomes from a wide range of healthy and diseased tissues across children and adults indicated that the persistence signature is rarely encountered in other settings. Accordingly, we found a persistence signature that appears to be independent of infusion product, patient age, and leukaemia type. These findings raise the possibility that a universal transcriptional signature of clinically effective, persistent CD19 CAR T cells exist. It may provide a basis for the identification of biomarkers of persistence and guide refinement of manufacturing methods. Citation Format: Nathaniel D. Anderson, Jack Birch, Theo Accogli, Ignacio Criado, Eleonora Khabirova, Conor Parks, Yvette Wood, Matthew D. Young, Tarryn Porter, Rachel Richardson, Sarah J. Albon, Bilyana Popova, Andre Lopes, Robert Wynn, Rachael Hough, Satyen H. Gohil, Martin Pule, Persis J. Amrolia, Sam Behjati, Sara Ghorashian. Transcriptional signatures associated with persisting CD19 CAR-T cells in children with leukemia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B047.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".