Summary: The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery. : Hartmann et al. provide an experimental framework to identify and characterize all major human immune cell lineages in a single assay using mass cytometry (CyTOF). This validated and readily available workflow ensures comprehensive immunophenotypic analysis, improves data comparability, and allows identification of disease-associated immune signatures and biomarkers for human immunotherapy. Keywords: immunotherapy, cancer, phenotyping, monitoring, mass cytometry, biomarker, CyTOF, bone marrow transplantation
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