In recent years the volume and complexity of flow cytometry data has increased substantially. This has led to a greater number of identifiable cell populations in a single measurement. Consequently, new gating strategies and new approaches for cell population definition are required. Here we describe how the EuroFlow Lymphoid Screening Tube (LST) reference data base for peripheral blood (PB) samples was designed, constructed and validated for automated gating of the distinct lymphoid (and myeloid) subsets in PB of patients with chronic lymphoproliferative disorders (CLPD). A total of 46 healthy/reactive PB samples which fulfilled pre-defined technical requirements, were used to construct the LST-PB reference data base. In addition, another set of 92 PB samples (corresponding to 10 healthy subjects, 51 B-cell CLPD and 31 T/NK-cell CLPD patients), were used to validate the automated gating and cell-population labeling tools with the Infinicyt software. An overall high performance of the LST-PB data base was observed with a median percentage of alarmed cellular events of 0.8% in 10 healthy donor samples and of 44.4% in CLPD data files containing 49.8% (range: 1.3-96%) tumor cells. The higher percent of alarmed cellular events in every CLPD sample was due to aberrant phenotypes (75.6% cases) and/or to abnormally increased cell counts (86.6% samples). All 18 (22%) data files that only displayed numerical alterations, corresponded to T/NK-cell CLPD cases which showed a lower incidence of aberrant phenotypes (41%) vs B-cell CLPD cases (100%). Comparison between automated vs expert-bases manual classification of normal (r2 = 0.96) and tumor cell populations (rho = 0.99) showed a high degree of correlation. In summary, our results show that automated gating of cell populations based on the EuroFlow LST-PB data base provides an innovative, reliable and reproducible tool for fast and simplified identification of normal vs pathological B and T/NK lymphocytes in PB of CLPD patients.
Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.