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Flow cytometry is a proven technology, able to deliver exceptionally detailed and quantitative information in a wide variety of applications and is an integral part of CAR T-cell and cell-based therapies research. Detecting and measuring different cell types such as T cells has long been an important application of flow cytometry and this is an important reason why it is so useful in CAR T-cell therapy development.
CAR T-cell therapy is a groundbreaking therapy that uses the body’s immune system to attack disease-causing cells. So far it has predominantly been used to treat lymphoma and leukemia, and works by engineering a patient’s own T cells to make them express an artificial protein on their surface that acts in a similar way to an antibody. Called a Chimeric Antigen Receptor (CAR), this new receptor recognizes and binds to proteins, or antigens, on the surface of cancer cells. They may then kill them directly or flag them for attack by other parts of the immune system.
Recent advances in technology, in the form of high-throughput screening, mean that the speed at which flow cytometry analysis can be performed has greatly increased. This offers even greater utility to CAR T-cell therapy development. We examine some examples of how flow cytometry and in particular the ZE5 Cell Analyzer, is being used to empower the development of CAR T-cell therapies.
Optimization of a CAR T-Cell Workflow
Optimizing the success of your transfection technique is an important preliminary step in validating a CAR T-cell workflow. We set out to test the effectiveness of electroporation for CAR transfection by developing an optimized workflow for generating anti-CD19 CAR T cells by mRNA electroporation. In this example, the antigen that the CAR has been designed to bind to is CD19, a marker expressed by B cells. Here we will examine some of the flow cytometry experiments that were crucial to this study.
Figure 1 demonstrates the effect of increasing mRNA dose on successful transfection resulting in protein level expression of a GFP (Fig. 1A) and CD19 CAR (Fig. 1B) construct. GFP can be detected directly whereas CD19 CAR expression was detected using FITC labeled recombinant CD19. Results show an RNA dose-dependent increase in transgene expression.
Fig. 1: Optimization of mRNA electroporation in Jurkat T cells
mRNA dose-response experiment showing GFP expression measured as fluorescence intensity following electroporation A. Anti-CD19 CAR expression measured as a function of fluorescence intensity following binding of FITC labeled recombinant CD19 B. Expression was assayed 6 hr (Blue) and 24 hr (Orange) after electroporation. We see that in all cases increasing RNA dose has a positive effect on transfection success. In the case of anti-CD19 CAR a significantly higher transfection rate is seen at the 6 hr time point.
Binding to the Target Molecule
One of the critical properties of a CAR is that it is able to bind to the molecule or antigen that it has been designed to target. Figure 2 shows the proportion of total T cells (Fig. 2A) and CD8+ T cells (Fig. 2B) transfected with a CAR designed to target CD19 and detected using an anti-CAR FITC labeled antibody or FITC labeled recombinant CD19 with and without electroporation. The results show a comparable number of total and CD8 positive T cells stained using both methods. This confirms CAR expression at the cell surface and efficient binding of CAR to the CD19 antigen.
Total T Cells
CD8+ T Cells
Fig. 2: Anti-CD19 CAR expression in total and CD8+ primary T cells
CAR expression measured as a proportion of total and CD8+ T cells, detected using FITC labeled anti-CD19 CAR specific antibodies or FITC labeled recombinant CD19 with and without electroporation. This shows that the anti-CD19 construct is expressed on the cell surface of approximately 70% of cells and that it also successfully binds to the target antigen in 70% of cells.
Transfection can reduce cell viability. To assess the effect of electroporation on the viability of primary T cells, The ZE5 Cell Analyzer was used to measure the proportion of viable cells highlighted by non-uptake of the DNA dye 7-aminoactinomycin D (7-AAD) (Fig. 3). Mock electroporation had a negligible impact on viability whereas transfection with either a GFP of CAR construct resulted in an expected reduction in T-cell viability.
Fig. 3: Viability analysis of primary human T cells transfected with anti-CD19 CAR
Cells were assayed 6 hr after electroporation (or mock-electroporation), viable cells were identified by the exclusion of 7-AAD. Percentages shown in each panel refer to the percentage of viable cells. This shows that electroporation alone has no effect on cell viability. Electroporation with mRNA causes a 4% to 11% drop in viability.
Assessing Potency and Quality
The ZE5 Cell Analyzer continues to deliver outstanding performance in supporting CAR T-cell research in the wider research community. Here we examine some examples of how the ZE5 Cell Analyzer is being used to deliver cutting-edge research in high-quality journals, focusing on assays that measure the potency and quality of CAR T-cell therapeutic products. For more examples of the top-quality and high-impact cell and gene therapy publications see our cell and gene therapy publication list.
Depleting a Target Population
The successful depletion of a particular cell type is often one of the primary goals of CAR T-cell therapies. Many CAR T-cell therapies target B or T cell lymphomas however, Kansal et al. demonstrate that the utility of CAR T-cell therapy can also be extended to other diseases that are caused by the action of a particular cell type. B cells are predominantly responsible for driving disease in lupus. Being able to assess the proportion of disease-causing cells is paramount to understanding the efficacy of CAR T-cell therapy and can be done quickly and effectively using flow cytometry. In this case, the authors showed near total B-cell aplasia throughout the course of the experiments more than 1 year from the administration of transduced T cells.
Tumor Infiltration by CAR T Cells
In order to have a therapeutic effect, CAR T-cell therapies must be able to physically come into contact with the tumor cells. One challenge of using CAR T cells in solid tumors is the relatively inaccessible nature of the tumors to immune cells. Mishra et al. used flow cytometry to assess the infiltration of a CAR T-cell into solid tumors by introducing CAR T cells into a mouse tumor model then dissociating the cells of the tumor and measuring the proportion of T cells identified by the expression of CD3. The results show greater tumor infiltration by CAR T cells compared to control T cells, which provides evidence for the mode of action and can help strengthen efficacy claims.
Assessing the Quality of the Therapeutic Product
CAR T cells can be a mixture of CD8 and CD4 positive cells but in order to gain approval for use in a therapeutic setting, manufacturers of cell based products must monitor the composition and potency of the therapeutic product. O’Neal et al provide one simple example of how this can be achieved using flow cytometry. In their study into CS1 (SLAMF7) CAR T-cell targeting in myeloma, they were concerned that since CS1 is expressed by CD8+ T cells that they were likely to see some degree of self-killing or fratricide, their studies showed a slight reduction in the relative proportion of CD8+ T-cells (~9%) although this drop did not result in loss of efficacy. They also demonstrated again using flow cytometry that CS1 deletion prevented fratricide and resulted in stabilization of the CD8+ T-cell component but did not alter efficacy. These experiments validated the approach of CS1 targeting despite the slight deleterious effect on the proportion CD8+ T cells.
Studying T-Cell Exhaustion
One of the challenges of successful CAR T-cell therapy strategies is the tumor microenvironment. Impaired antigen presentation, high concentrations of inhibitory cytokines, and immunosurveillance evasion mechanisms within the tumor all contribute to immunosuppression. Here we demonstrated how the multiparameter capability of the ZE5 Cell Analyzer can be used to monitor T cell exhaustion in an in vitro model of chronic T-cell activation by incubation of peripheral blood mononuclear cells with a CD3/CD28 bead.
Expression of Markers of Exhaustion
Programmed cell death protein 1 (PD-1) expression is one well accepted indicator of T-cell exhaustion, others include cytotoxic T lymphocyte antigen-4 (CTLA-4) lymphocyte activation gene 3 protein (LAG-3) and T-cell immunoglobulin and mucin-domain containing-3 (TIM-3). In Figure 4 we see a comprehensive determination of the expression of these exhaustion markers with and without the presence of PD-1 inhibitor Nivolumab.
Fig. 4: Determination of exhaustion marker expression
Dot plots highlighting differential expression of PD-1 following CD3/CD28 activation. In naïve, central memory, and effector memory CD4+ and CD8+ T cells A. Differential expression of PD-1 (blue), TIM-3 (red), LAG-3 (green), and CTLA-4 (Purple) with and without Nivolumab in total CD4+ and CD8+ T cells B. Exhaustion marker expression is increased in CD4 and CD8+ T cells as a result of bead stimulation. In the case of PD-1, LAG-3 and CTLA4, expression peaks at day 4 and drops at day 14, but in the case of TIM-3 high expression is maintained at day 14.
Expanded Phenotypic Analysis of Marker Expression
One of the key benefits of flow cytometry is its ability to deliver highly multi-parametric data. In Figure 5 we see how this can be used to enhance the granularity of an experiment here we see a segmentation of the above data based on T-cell phenotype specifically into cytotoxic and T-helper phenotypes and further subphenotyping into Naïve, central memory, effector memory, and terminally differentiated effector memory cells.
Fig. 5: PD-1 and TIM-3 expression in T cell subsets
Expression of A, PD-1 and B, TIM-3 in CD4+ and CD8+ T cells stimulated with CD3/CD28 beads, sub divided into memory subsets in the presence and absence of Nivolumab at 0, 4, and 13 days following stimulation. Bead stimulation drives a large increase in PD-1 and TIM-3 expression in the central memory subset in both CD4 and CD8+ cells at day 4 although this effect is largely lost by day 13. Stimulation has a negative effect on TIM-3 expression in Naïve CD4 and CD8 + T cells and this effect is maintained at day 13. Nivolumab has no effect on PD-1 or TIM-3 expression.
Intracellular Cytokine Expression
As a final demonstration of the utility of flow cytometry and the ZE5 Cell Analyzer in particular for understanding T-cell responses, we measured the accumulation of intracellular cytokines. In Figure 6 we see cytokine expression following chronic stimulation with and without the presence of Nivolumab in cytotoxic and T-helper subsets divided into naïve, central memory, effector memory, and terminally differentiated effector memory cells.
Fig. 6: Cytokine expression in T cell subsets
Expression of IL-2 (red), TNF (green), and IFN-γ (purple) in CD4+ and CD8+ memory subsets following stimulation with CD3/CD28 beads in the presence or absence of nivolumab at 0, 4, and 13 days following stimulation. Stimulation results in a decrease in all cytokine expression from naïve cells and an increase in cytokine expression in central memory cells. Nivolumab has no clear effect on cytokine expression.
All the above examples feature data collected with the ZE5 Cell Analyzer but represent only a fraction of the potential uses of flow cytometry in the field of CAR T-cell therapy development. The ZE5 Cell Analyzer has a host of benefits that make it the ideal choice for cell and gene therapy research:
- Perform complex immunophenotyping assays with up to 5 lasers and 27 colors
- Speed up your workflow with fast sample acquisition and plate handling
- Flexibility to handle any workflow with a wide range of sample input types
- Superior reliability – clog resistant, reliable, and robust – meaning that you can walk away with confidence
Further Learning and Resources
For more information on the ZE5 Cell Analyzer, how the experiments were performed to create this data or how this flow cytometer is being used in the wider research community please visit the links below.
View the full details and specifications of this market-leading flow cytometer.
Learn about high throughput screening, what it is, and how flow cytometry is becoming an essential technology in this field.
Learn how SpyTag technology can facilitate and enhance CAR T-cell therapy development.
Part of the cell therapy knowledgebase, we take a more in depth look into CAR T-cell characterization.
Learn more about the most efficient, non-viral gene delivery method for introducing DNA, RNA, mRNA, RNPs, proteins, and other molecules into a wide variety of cells.
Due to the small size of exosomes, there are limited methods available to detect and study them. Learn why flow cytometry is ideal.
Antibodies and Reagents
Suitable antibodies and reagents are critical components for CAR T-cell therapy development. Bio-Rad is dedicated to providing cutting edge reagents for all flow cytometry applications, and has recently launched an exclusive range of StarBright Dyes to allow you to build superior panels. Bio-Rad also has an extensive range of high-quality antibodies and reagents validated for flow cytometry, to help you conduct successful experiments.