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Updated: Feb 23, 2026
Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells
Published on: March 24, 2023
PhenoGraph and viSNE facilitate the identification of abnormal T-cell populations in routine clinical flow cytometric
Joseph A DiGiuseppe1, Jolene L Cardinali1, William N Rezuke1
1Department of Pathology and Laboratory Medicine, Hartford Hospital, Connecticut.
Background:
Flow cytometric identification of neoplastic T-cell populations is complicated by the wide range of phenotypic abnormalities in T-cell neoplasia, and the diverse repertoire of reactive T-cell phenotypes. We evaluated whether a recently described clustering algorithm, PhenoGraph, and dimensionality-reduction algorithm, viSNE, might facilitate the identification of abnormal T-cell populations in routine clinical flow cytometric data.
Methods:
We applied PhenoGraph and viSNE to peripheral blood mononuclear cells labeled with a single 8-color T/NK-cell antibody combination. Individual peripheral blood samples containing either a T-cell neoplasm or reactive lymphocytosis were analyzed together with a cohort of 10 normal samples, which established the location and identity of normal mononuclear-cell subsets in viSNE displays.
Results:
PhenoGraph-derived subpopulations from the normal samples formed regions of phenotypic similarity in the viSNE display describing normal mononuclear-cell subsets, which correlated with those obtained by manual gating (r2 = 0.99, P < 0.0001). In 24 of 24 cases of T-cell neoplasia with an aberrant phenotype, compared with 4 of 17 cases of reactive lymphocytosis (P = 1.4 × 10-7 , Fisher Exact test), PhenoGraph-derived subpopulations originating exclusively from the abnormal sample formed one or more distinct phenotypic regions in the viSNE display, which represented the neoplastic T cells, and reactive T-cell subpopulations not present in the normal cohort, respectively. The numbers of neoplastic T cells identified using PhenoGraph/viSNE correlated with those obtained by manual gating (r2 = 0.99; P < 0.0001).
Conclusions:
PhenoGraph and viSNE may facilitate the identification of abnormal T-cell populations in routine clinical flow cytometric data. © 2017 Clinical Cytometry Society.
