These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer‐reviewed by leading experts in the field, making this an essential research companion.

CD8 T cells infiltrating tumors are largely dysfunctional, but whether a subset maintains superior functionality remains ill defined. By high-dimensional single cell analysis of millions of CD8 T cells from 53 individuals with lung cancer, we defined those subsets that are enriched in tumors compared with cancer-free tissues and blood. Besides exhausted and activated cells, we identified CXCR5 TIM-3 CD8 T cells with a partial exhausted phenotype, while retaining gene networks responsible for stem-like plasticity and cytotoxicity, as revealed by single cell sequencing of the whole transcriptome. Ex vivo, CXCR5 TIM-3 CD8 T cells displayed enhanced self-renewal and multipotency compared with more differentiated subsets and were largely polyfunctional. Analysis of inhibitory and costimulatory receptors revealed PD-1, TIGIT, and CD27 as possible targets of immunotherapy. We thus demonstrate a hierarchy of differentiation in the context of T cell exhaustion in human cancer similar to that of chronically infected mice, which is further shown to disappear with disease progression.

Background: Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response. Methods: Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45 + cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human. Results: We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti–tumor necrosis factor therapy and cardiac toxicity during anti–PD-1 cancer immunotherapy, respectively. Conclusions: Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.

T cell memory relies on the generation of antigen-specific progenitors with stem-like properties.However, the identity of these progenitors has remained unclear, precluding a full understanding of the differentiation trajectories that underpin the heterogeneity of antigen-experienced T cells.We used a systematic approach guided by single-cell RNA sequencing data to map the organizational structure of the human CD8 + memory T cell pool under physiological conditions. We identified two previously unrecognized subsets of clonally, epigenetically, functionally, phenotypically, and transcriptionally distinct stem-like CD8 + memory T cells. Progenitors lacking the inhibitory receptors programmed death-1 (PD-1) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) were committed to a functional lineage, whereas progenitors expressing PD-1 and TIGIT were committed to a dysfunctional, exhausted-like lineage.Collectively, these data revealed the existence of parallel differentiation programs in the human CD8 + memory T cell pool, with potentially broad implications for the development of immunotherapies and vaccines. 3 MAIN TEXTAntigen recognition by CD8 + naive T cells initiates a program of clonal expansion and effector differentiation that leads to the clearance of infected or malignant cells and the subsequent formation of heterogeneous memory populations that confer durable immunity 1 . These memory populations are thought to be organized in a developmental hierarchy, according to which stem cell memory T (TSCM) cells self-renew and generate long-lived central memory T (TCM) cells and short-lived effector memory T (TEM) cells 2-6 . However, the mechanisms that underlie the enhanced multipotency of TSCM cells relative to TCM cells have not been clearly defined in molecular terms 7 .Memory T cell differentiation can become corrupted under conditions of persistent antigenic stimulation, as observed during chronic viral infections and progressive malignancies, which promote a state of T cell exhaustion, characterized by an orderly loss of effector functions, impaired proliferation, and the upregulation of inhibitory receptors 8 . This dynamic process occurs over a period of weeks after the initial priming event 9,10 and involves the genome-wide accumulation of epigenetic modifications 11,12 . Recent studies have shown that exhausted T (TEX) cell populations are developmentally and functionally heterogeneous, incorporating stem-like progenitors that express T cell factor 1 (TCF1) which give rise to highly differentiated TEX cells that are constitutively dysfunctional and lack TCF1 [13][14][15][16] . Importantly, the therapeutic benefits of immune checkpoint blockade in the context of chronic viral infections and various cancers are thought to operate via these TCF1 + progenitors, which appear susceptible to interventions that specifically target the inhibitory receptor programmed death-1 (PD-1) 13,15,17-20 .

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Multidimensional single‐cell analysis requires approaches to visualize complex data in intuitive 2D graphs. In this regard, t‐distributed stochastic neighboring embedding (tSNE) is the most popular algorithm for single‐cell RNA sequencing and cytometry by time‐of‐flight (CyTOF), but its application to polychromatic flow cytometry, including the recently developed 30‐parameter platform, is still under investigation. We identified differential distribution of background values between samples, generated by either background calculation or spreading error (SE), as a major source of variability in polychromatic flow cytometry data representation by tSNE, ultimately resulting in the identification of erroneous heterogeneity among cell populations. Biexponential transformation of raw data and limiting SE during panel development dramatically improved data visualization. These aspects must be taken into consideration when using computational approaches as discovery tools in large sets of samples from independent experiments or immunomonitoring in clinical trials.