283 Functional profiling of CAR T cells using high-dimensional CyTOF: integrating cytokine, transcription factor and immune checkpoint marker signatures
Bibliographic record
Abstract
Background Adoptive immunotherapy using chimeric antigen receptor (CAR) T cells is a revolutionary treatment in cancer therapy. CAR T therapy has achieved remarkable success in hematological B cell malignancies. However, it has faced significant challenges in solid tumors due to various factors, such as complex tumor microenvironments, restricted trafficking, impersistent antitumor activity and toxicities. A better understanding of CAR T biology will accelerate development of CAR T therapies with improved antitumor efficacy, durability and decreased toxicities.High-parameter cytometry is a powerful tool to functionally characterize CAR T cells at multiple stages of clinical development, from product characterization during manufacturing to longitudinal evaluation of the infused product in patients. Fluorescence-based cytometry faces significant challenges with signal overlap and autofluorescence, limiting sensitivity and the number of targets detected in CAR T cells. Consequently, rare cell populations and functional readouts of CAR T cells are difficult to resolve. CyTOF™ technology overcomes these limitations with low signal spillover and absence of autofluorescence. To minimize technical variation, metal-tagged antibody cocktails and stained cell samples can be frozen for later use and acquisition, enabling a streamlined and flexible workflow in clinical research. Here, we present a 40-plus-marker CyTOF panel to simultaneously analyze phenotypic and functional protein expression in CAR T cells from in vitro co-culture with tumor cells.Methods CD19-targeted CAR T cells were expanded in vitro and co-cultured with Nalm6 cells at an E:T (effector cell: target cell) ratio of 1:3 for 2–4 days. A high-parameter CyTOF panel including 43 surface, cytoplasmic and nuclear markers was used to stain CAR T cells. The co-culture samples collected at different time points were stained using a pre-aliquoted frozen antibody cocktail following surface and intracellular (simultaneous cytoplasmic and nuclear targets) staining procedures. Stained samples were frozen and simultaneously acquired on a CyTOF XT system later.Results The cytotoxicity, activation, proliferation, differentiation and exhaustion of CAR T cells were evaluated. Comprehensive profiling revealed that CAR T cells became activated, proliferated and produced cytokines in in vitro co-culture with tumor cells and exhibited an exhaustive-like Treg phenotype at the end of a four-day co-culture. A diverse polyfunctional antitumor signature in the CD8 TEMRA cell subset was discovered during the co-culture.Conclusions Overall, we demonstrate that the high-parameter CyTOF panel enables deep functional characterization of CAR T cells by simultaneous detection of surface, cytoplasmic and nuclear markers, supporting advancing clinical development of CAR T therapies.For Research Use Only. Not for use in diagnostic procedures.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".