Eight-color panel for immune phenotype monitoring by flow cytometry

Flow cytometry (FC) is a fast and highly informative technology that has gained prominence in immune phenotype monitoring. FC standardization is crucial to obtain reliable results that are comparable among laboratories and immune monitoring studies, as this method is influenced by several variables, including equipment, reagents, staining procedures, and pre-analytical and analytical factors. Recent studies have standardized antibody panels and analytical procedures to analyze circulating immune cells in peripheral blood (PB). However, these panels cannot be adapted for laboratories that perform eight-color FC with liquid reagents. The aim of this study was to design and test an eight-color panel, intended to phenotype the main immune cell subsets in PB using liquid reagents and fresh whole blood samples. Samples were collected from healthy individuals recruited from staff and students and from six chemotherapy patients with leukopenia. The antibody panel was designed on the basis of previous studies. Quality controls comprised antibody titration, fluorescence minus one controls, internal controls, and compensation controls. Samples were analyzed by two operators using an eight-color three-laser FACSCanto II flow cytometer (BD Biosciences, USA) and Infinicyt software (Cytognos, Spain). The proposed eight-color panel is composed of six tubes. Analysis of these tubes allowed evaluation of frequencies and classification of various immune cells, such as naive T, central memory T, effector memory T, CDRA(+) effector memory T, activated T, and regulatory T cells; class-switched B, non-switched B, memory B, regulatory B cells, and plasmablasts; myeloid and plasmacytoid dendritic cells, classical and non-classical monocytes; and immature neutrophils. Immunophenotyping of leukocytes using the proposed panel was efficient to correctly differentiate the majority of immune cell subtypes. It is a promising tool to determine the immunological profile of patients in clinical trials and establish associations with disease prognosis, complications, and outcomes.