Use of Mass Cytometry to Profile Human T Cell Exhaustion

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Mass cytometry has become an important technique for the deep analysis of single cell protein expression required for precision systems immunology. The ability to profile more than 40 markers per cell is particularly relevant for the differentiation of cell types for which low parametric characterization has proven difficult, such as exhausted CD8+ T cells (TEX). TEX with limited effector function accumulate in many chronic infections and cancers and are subject to inhibitory signaling mediated by several immune checkpoints (e.g., PD-1). Of note, TEX represent considerable targets for immune-stimulatory therapies and are beginning to be recognized as a major correlate of successful checkpoint blockade approaches targeting the PD-1 pathway. TEX exhibit substantial functional, transcriptomic and epigenomic differences compared to canonical functional T cell subsets [such as naïve (TN), effector (TEFF) and memory T cells (TMEM)]. However, phenotypic distinction of TEX from TEFF and TMEM can often be challenging since many molecules expressed by TEX can also be expressed by effector and memory T cell populations. Moreover, significant heterogeneity of TEX has been described, such as subpopulations of exhausted T cells with progenitor-progeny relationships or populations with different degrees of exhaustion or homeostatic potential that may directly inform about disease progression. In addition, TEX subsets have essential clinical implications as they differentially respond to antiviral and checkpoint therapies. The precise assessment of TEX thus requires a high-parametric analysis that accounts for differences to canonical T cell populations as well as for TEX subset heterogeneity. In this review, we discuss how mass cytometry can be used to reveal the role of TEX subsets in humans by combining exhaustion-directed phenotyping with functional profiling. Mass cytometry analysis of human TEX populations is instrumental to gain a better understanding of TEX in chronic infections and cancer. It has important implications for immune monitoring in therapeutic settings aiming to boost T cell immunity, such as during cancer immunotherapy.