Effector T cells infiltrating the TME progressively differentiate toward an “exhausted” state, expressing high levels of inhibitory molecules that impair their ability to control tumor progression ( Wherry & Kurachi, 2015 Blank et al, 2019). Cancer, myelo-monocytic ( Kwak et al, 2020 Tcyganov et al, 2021), and regulatory T (Treg) cells ( De Simone et al, 2016 Ohue & Nishikawa, 2019) are widely recognized suppressors of anti-tumor T-cell immune response. The component characterization of the tumor microenvironment (TME), aimed at evaluating the heterogeneous cellular network that conditions anti-tumor immune responses ( Hiam-Galvez et al, 2021 Vitale et al, 2021), is of particular interest. These technological advances have enhanced the deep phenotype dissection and complex network characterization in heterogeneous tissues at a single cell level. High dimensional (HD) flow cytometry enables the analysis of a broad range of surface and intracellular antigens, by interrogating high numbers of cells and characterizing rare populations for the expression of multiple parameters ( Palit et al, 2019). Hence, this study provides a robust tool for high-dimensional flow cytometry analysis of complex T-cell populations, which could be adapted to characterize other relevant pathological tissues. This combined procedure permitted the optimal capturing of the phenotypic complexity of T cells infiltrating CRC-LM. Third, the dissociation of the CRC-LM samples was accurately tuned to preserve both the viability and antigenic integrity of the stained cells. Second, we set up a 26-color based antibody panel designed to assess the functional state of both conventional T-cell subsets and unconventional invariant natural killer T, mucosal associated invariant T, and gamma delta T (γδT)-cell populations, which are abundant in the liver. First, we applied a novel flow cytometer setting approach based on single positive cells rather than fluorescent beads, resulting in optimal sensitivity when compared with previously published protocols. We describe a multi-step high-dimensional (HD) flow cytometry workflow for the deep phenotypic characterization of T cells infiltrating metastatic tumor lesions in the liver, particularly derived from colorectal cancer (CRC-LM).

Flow cytometry interpretation