Identification of T cell-restricted genes, and signatures for different T cell responses, using a comprehensive collection of microarray datasets

Tanya Chtanova, Rebecca Newton, Sue M Liu, Lilach Weininger, Timothy R Young, Diego G Silva, Francesco Bertoni, Andrea Rinaldi, Stephane Chappaz, Federica Sallusto, Michael S Rolph, Charles R Mackay

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91 Citations (Scopus)

Abstract

We used a comprehensive collection of Affymetrix microarray datasets to ascertain which genes or molecules distinguish the known major subsets of human T cells. Our strategy allowed us to identify the genes expressed in most T cell subsets: TCR alphabeta+ and gammadelta+, three effector subsets (Th1, Th2, and T follicular helper cells), T central memory, T effector memory, activated T cells, and others. Our genechip dataset also allowed for identification of genes preferentially or exclusively expressed by T cells, compared with numerous non-T cell leukocyte subsets profiled. Cross-comparisons between microarray datasets revealed important features of certain subsets. For instance, blood gammadelta T cells expressed no unique gene transcripts, but did differ from alphabeta T cells in numerous genes that were down-regulated. Hierarchical clustering of all the genes differentially expressed between T cell subsets enabled the identification of precise signatures. Moreover, the different T cell subsets could be distinguished at the level of gene expression by a smaller subset of predictor genes, most of which have not previously been associated directly with any of the individual subsets. T cell activation had the greatest influence on gene regulation, whereas central and effector memory T cells displayed surprisingly similar gene expression profiles. Knowledge of the patterns of gene expression that underlie fundamental T cell activities, such as activation, various effector functions, and immunological memory, provide the basis for a better understanding of T cells and their role in immune defense.
Original languageEnglish
Pages (from-to)7837 - 7847
Number of pages11
JournalJournal of Immunology
Volume175
Issue number12
Publication statusPublished - 2005
Externally publishedYes

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