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Data_Sheet_1_Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential.PDF

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NIAID Data Ecosystem2026-03-12 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Multi-Factor_Clustering_Incorporating_Cell_Motility_Predicts_T_Cell_Expansion_Potential_PDF/14394176
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Expansion of an initial population of T cells is essential for cellular immunotherapy. In Chronic Lymphocytic Leukemia (CLL), expansion is often complicated by lack of T cell proliferation, as these cells frequently show signs of exhaustion. This report seeks to identify specific biomarkers or measures of cell function that capture the proliferative potential of a starting population of cells. Mixed CD4+/CD8+ T cells from healthy donors and individuals previously treated for CLL were characterized on the basis of proliferative potential and in vitro cellular functions. Single-factor analysis found little correlation between the number of populations doublings reached during expansion and either Rai stage (a clinical measure of CLL spread) or PD-1 expression. However, inclusion of in vitro IL-2 secretion and the propensity of cells to align onto micropatterned features of activating proteins as factors identified three distinct groups of donors. Notably, these group assignments provided an elegant separation of donors with regards to proliferative potential. Furthermore, these groups exhibited different motility characteristics, suggesting a mechanism that underlies changes in proliferative potential. This study describes a new set of functional readouts that augment surface marker panels to better predict expansion outcomes and clinical prognosis.
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2021-04-09
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