Dresden 2026 – scientific programme
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BP: Fachverband Biologische Physik
BP 14: Poster Session II
BP 14.56: Poster
Tuesday, March 10, 2026, 18:00–21:00, P2
Adaptive NK cell analysis by t-SNE — •Andrea Schneider1, Wiebke Moskorz2, Jörg Timm2, and Thomas Heinzel1 — 1Heinrich-Heine University Duesseldorf — 2University Hospital od Duesseldorf
High-dimensional flow cytometry data from Natural Killer (NK) cells, collected using a comprehensive panel of typical and adaptive NK cell markers, poses a challenge for the characterization of complex cell subsets. To visualize the complete receptor expression profile in a two-dimensional cellular plot, we applied t-distributed Stochastic Neighbor Embedding (t-SNE) to the multi-parameter dataset. The resulting t-SNE projection successfully resolved distinct immune subpopulations regarding NK cell development and adaptive NK cells. Crucially, the map enabled the simultaneous visualization and comparison of different definitions of adaptive NK cells (including NKG2C+ and FceRIg- subsets within mature NK cells), visually confirming their close relatedness. Furthermore, while CD95 is known to be increased in adaptive NK cells, the t-SNE visualization clearly confirmed that this high expression level is consistently shared across all defined adaptive cell clusters, which were tightly localized within the embedding. This methodology demonstrates the power of non-linear embedding techniques for validating complex immunological phenotypes. Moreover, it establishes a visual framework for comparative studies of NK cells across different patient groups, including Hepatitis C Virus (HCV) seronegative, chronically HCV infected, and HCV resolved donors, with each cohort further stratified by Cytomegalovirus serostatus.
Keywords: t-SNE; adaptive NK cells; Hepatitis C Virus; Dimensionality reduction