Figure 3.
viSNE analysis of NK cell subset in NDMM and control subjects. (A) Representative samples of two viSNE analyses. NK cells were identified by traditional Boolean gating before performing the viSNE analysis with equal sampling across all samples. The gated population is the CD56bright population. (B) Within the CD56dim population, multiple subpopulations (labeled A-F) can also be identified. (C) viSNE analysis of mass cytometry data allows multiple NK subsets to be identified based on immune marker expression, cytokine production, proliferation, and granzyme and perforin expression. The gated population is the CD56bright subset; the ungated region is the CD56dim subset. (D) Patterns of marker expression across the CD56dim subpopulations reveal distinct populations with different phenotypic and functional characteristics. Statistically significant differences between NDMM and control expression are seen for the HLA-DR population F (***P ≤ .001) and granzyme population D (****P ≤ .0001).

viSNE analysis of NK cell subset in NDMM and control subjects. (A) Representative samples of two viSNE analyses. NK cells were identified by traditional Boolean gating before performing the viSNE analysis with equal sampling across all samples. The gated population is the CD56bright population. (B) Within the CD56dim population, multiple subpopulations (labeled A-F) can also be identified. (C) viSNE analysis of mass cytometry data allows multiple NK subsets to be identified based on immune marker expression, cytokine production, proliferation, and granzyme and perforin expression. The gated population is the CD56bright subset; the ungated region is the CD56dim subset. (D) Patterns of marker expression across the CD56dim subpopulations reveal distinct populations with different phenotypic and functional characteristics. Statistically significant differences between NDMM and control expression are seen for the HLA-DR population F (***P ≤ .001) and granzyme population D (****P ≤ .0001).

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