A Deeper Dive into the Tumor-Infiltrating T Cell Immunophenotype – Introducing the New MI-Expanded CompT™ Multi-Color Flow Cytometry Panel
Flow cytometry using large antibody panels has the advantage of examining a greater number of cell subsets. This capability is particularly important when a comprehensive data set is required, but limited tumor material is available for analysis. Moreover, panels with a large number of antibodies can also be used to enable deep immunophenotypic insight into a few subsets, or an even deeper analysis into a single subset. In this Tech Spotlight, we demonstrate the latter capability by presenting data generated using the new MI-Expanded CompT™ panel, a 16-color panel that takes flow analysis of T cell activation and differentiation to a level above any other panel in the MI Bioresearch service portfolio.
The MI-Expanded CompT™ panel builds upon the MI-CompT™ panel, our most popular standard panel to examine CD4+ and CD8+ T cells. This improved panel adds effector and memory T cell markers, plus four additional markers for analysis of T cell activation and exhaustion. Table 1 describes the components of the Expanded MI-CompT™ panel, and using untreated murine MC38 colon adenocarcinomas, Figure 1 illustrates its gating and analysis strategy.
Table 1: MI-Expanded CompT™ Panel Antibodies and Description of Their Utility
|CD45||Pan immune cell marker|
|CD3||Pan-T cell marker|
|CD4||CD4+ T cell marker|
|CD8||CD8+ T cell marker|
|FoxP3||Regulatory T cell marker|
|CD25||Regulatory T cell marker/IL-2 receptor|
|CD62L||Naïve T cell/Memory marker|
|CD69||T cell activation marker|
|PD-1||T cell activation/Exhaustion marker|
|LAG-3||T cell activation/Exhaustion marker|
|TIM-3||T cell exhaustion marker|
|ICOS||T cell activation marker|
|Granzyme B||Anti-tumor cytotoxicity marker|
|Viability Dye||Dead cell exclusion|
|The MI-Expanded CompT™ can be customized to include NK/NKT cell markers (CD49b/CD335) to enable granzyme B and activation marker expression in these subsets.|
MI-Expanded CompT™ Panel Gating Strategy
As with all MI Bioresearch T cell panels, analysis begins with dead cell exclusion and subsequent CD45+ immune cell delineation to gate on CD3+ T cells (not shown). Figure 1A displays the downstream endpoints of CD4+ and CD8+ T cell analysis that are shared between the MI-CompT™ and MI-Expanded CompT™ panels. These include CD69 and PD-1, which become upregulated upon T cell activation. Their expression has been correlated with the exhausted T cell phenotype. Another shared endpoint is CD8+ T cell proliferation, provided by using Ki-67 expression as a surrogate marker. Finally, CD4+ T cells are examined to quantify helper T cells and regulatory T cells (Tregs). Figure 1B and 1C illustrate the added endpoints used to expand upon the MI-CompT™ panel, which are further described below.
Effector/Memory T Cell Analysis
Analysis of effector and memory CD8+ T cell differentiation is shown in Figure 1B. Conversion of T cells to a memory phenotype is important for the development of lasting immunological response to rechallenge in the context of both infection and cancer pathogenesis. CD44 and CD62L analysis enables the delineation of T cells into four differentiation states. These include naïve or inactivated T cells, activated effector T cells (Teff), effector memory (Tem) and central memory (Tcm) subsets. Tem and Tcm subsets can circulate but have tendencies to reside in non-lymphoid and lymphoid tissues, respectively. Recent reports have demonstrated that both of these subsets have distinct roles in the anti-tumor response. A third resident memory (Trm) population has more recently been described as playing an important role in controlling tumor growth in a variety of models and can be delineated using CD103, among other markers. The MI-Expanded CompT™ panel can be customized to include analysis of Trm cells.
T Cell Activation, Exhaustion, and Granzyme B Analysis
The MI-Expanded CompT™ panel includes ICOS, LAG-3, TIM-3, and granzyme B analysis, which are four intensively investigated biomarkers for T cell functionality (Figure 1C). The analysis of these targets alone and in combination can provide insight into the anti-tumor potential of CD8+ T cells. Evidence supports a co-stimulatory and anti-tumor role for ICOS receptor signaling, thus making ICOS an attractive therapeutic target. Granzyme B is often used as a biomarker for cytolytic activity and can correlate with CD8+ T cell anti-tumor responses. Conversely, PD-1, LAG-3 and TIM-3 are inhibitory receptors and while the expression of these three receptors has been linked to T cell exhaustion, a growing body of data suggests heterogeneity among sub-populations exists within the exhausted PD-1 expressing CD8+ T cells. This heterogeneity correlates with the expression pattern of these inhibitory receptors. This profile can help define different sub-populations that have distinct potential to be re-invigorated to proliferate and/or lyse tumor cells. Figure 2 illustrates how the MI-Expanded CompT™ panel can quantify cells with double and triple positive expression for inhibitory receptors and provide insight into the heterogeneous PD-1 expressing T cell subset and its functionality. Numerous other T cell activation and inhibitory receptors have been described and implicated in influencing tumor immune responses; these include TIGIT, OX-40, CD137, CTLA-4, and others. MI Bioresearch has experience analyzing many of these markers in ex vivo tumor analysis. With minimal developmental efforts, the MI-Expanded CompT™ can be customized to meet your unique pre-clinical needs.
Customization – NK/NKT Cell Analysis and Further Options
MI Bioresearch can configure custom panels with up to 18 colors, which creates options for the MI-Expanded CompT™ panel. In addition to substituting or adding different T cell activation/exhaustion markers as described in the previous section, NK/NKT cell analysis is a potentially valuable endpoint. This is enabled by the addition of CD49b/CD335 markers to the panel (Figure 3).
NK and NKT cells are an important source of IFNγ, have indirect effects on enhancing CD8+ T cell anti-tumor responses, and can directly lyse tumor cells by releasing cytolytic granules such as granzyme B.[7,8] Other options include IFNγ, TNFα, or other cytokine analyses for a more in depth profile of PD1+ and PD1– CD8+ T cells. Or add CD103 analysis to examine resident memory T cells for a deeper memory T cell profile in the tumor. MI Bioresearch’s team has extensive experience developing custom flow cytometry services. To learn more about how the MI-Expanded CompT™ panel can be incorporated into it into your preclinical research, contact the scientists at MI Bioresearch.
1Jiang, Y., Y. Li, and B. Zhu. “T-cell exhaustion in the tumor microenvironment.” Cell death & disease 6.6 (2015): e1792.
2Klebanoff, Christopher A., Luca Gattinoni, and Nicholas P. Restifo. “CD8+ T‐cell memory in tumor immunology and immunotherapy.” Immunological reviews 211.1 (2006): 214-224
3Mami-Chouaib, Fathia, et al. “Resident memory T cells, critical components in tumor immunology.” Journal for immunotherapy of cancer 6.1 (2018): 87.
4Amatore, Florent, Laurent Gorvel, and Daniel Olive. “Inducible Co-Stimulator (ICOS) as a potential therapeutic target for anti-cancer therapy.” Expert opinion on therapeutic targets 22.4 (2018): 343-351.
5Miller, Brian C., et al. “Subsets of exhausted CD8+ T cells differentially mediate tumor control and respond to checkpoint blockade.” Nature immunology 20.3 (2019): 326.
6Xiong, Huizhong, et al. “Coexpression of Inhibitory Receptors Enriches for Activated and Functional CD8+ T Cells in Murine Syngeneic Tumor Models.” Cancer immunology research 7.6 (2019): 963-976.
7Zhu, Yanting, Bo Huang, and Jue Shi. “Fas ligand and lytic granule differentially control cytotoxic dynamics of natural killer cell against cancer target.” Oncotarget 7.30 (2016): 47163.
8Zhao, Jie, et al. “Polyclonal type II natural killer T cells require PLZF and SAP for their development and contribute to CpG-mediated antitumor response.” Proceedings of the National Academy of Sciences 111.7 (2014): 2674-2679.
About the Author: Dr. David Draper is an immunologist and a member of the Scientific Development Group. He has been employed at MI Bioresearch since 2015. Dr. Draper holds a Ph.D. in Microbiology from North Carolina State University. His post-doctoral work at Duke University and the National Institutes of Health focused on uncovering the mechanisms of the host pulmonary immune response to bacterial, viral, and allergen challenge using genetically engineered animal models. This body of work provided the foundation of Dr. Draper’s technical expertise in the area of immune cell immunophenotypic and functional characterization.