Abstract 6333: A high-parameter mass cytometry panel for the functional characterization of CAR T cells
Bibliographic record
Abstract
Abstract High-parameter flow cytometry provides a powerful tool for in-depth analysis of CAR T cell therapy, from characterizing CAR T cell populations to understanding their interactions within the tumor microenvironment. This information is crucial for advancing CAR T cell therapies and improving their effectiveness in treating cancer. To address the need for deep immunoprofiling at all stages of CAR T cell therapy, we created a robust and comprehensive mass cytometry panel of antibodies against 44 cell surface and intracellular markers. This assay allows for comprehensive characterization of CAR T cell features including surface marker expression, activation state, cytokine production, and differentiation status. These data will provide researchers with a better understanding of the phenotype of the CAR T cells used in therapy and can guide optimization efforts to enhance expansion, persistence, and self-renewal. For example, newer-generation CAR T cells (T cells redirected for antigen-unrestricted cytokine-initiated killing, or TRUCKs) that are engineered to produce cytokines such as IL-2 to enhance their own survival can be evaluated in vitro to select CAR constructs with the most potent anti-tumor activity. The lyophilized and validated 30-marker Maxpar® Direct™ Immune Profiling Assay™ enables comprehensive characterization of immune cell populations in both whole blood and PBMC. The 7-marker Maxpar Direct T Cell Expansion Panel 3 (OX40, TIGIT, CD69, PD-1, Tim-3, ICOS, and 4-1BB) and the Maxpar Direct Basic Activation Expansion Panel (CD107a, IL-2, TNFα, IFNγ, perforin, and granzyme B) are add-on modules that can further characterize CAR T cell exhaustion, degranulation, cytokine production, and cytotoxicity against target cells. We also compared CAR T detection options for sensitivity and specificity using a CD19 CAR-transduced cell line spiked into healthy donor PBMC. Indirect staining with Miltenyi Biotec biotinylated CD19 CAR Detection Reagent followed by anti-biotin- or streptavidin-conjugated metal tags was compared against a directly conjugated or biotinylated anti-G4S linker antibody. We included sample multiplexing using 6 metal-tagged CD45 antibodies to address the need to minimize batch effects, crucial to multi-site and longitudinal studies. Samples were acquired on a CyTOF® XT™ instrument, and preliminary data analysis was performed using Maxpar Pathsetter™ for automated enumeration of immune cells. By combining the lyophilized single-tube Maxpar Immune Profiling Assay and Expansion Panels with specific detection of CAR T cells, this assay enables researchers to analyze multiple key parameters simultaneously at the single-cell level at all stages of CAR T therapy development. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Deeqa Mahamed, Geneve Awong, Thiru Selvanatham. A high-parameter mass cytometry panel for the functional characterization of CAR T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6333.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".