Comparative Analysis of the Global Transcriptional Profile of Human Skin-Homing Memory T Lymphocytes vs. Non-Skin Homing Memory and Naive T Lymphocytes.

Abstract

T lymphocytes play a central role in the pathogenesis of a number of inflammatory, autoimmune and neoplastic skin diseases. Transcriptional profiling can provide substantial insights into the mechanisms regulating the development and function of the T cell populations involved in these disorders. We have applied oligonucleotide microarray technology (GeneChip Probe Array System, Affymetrix) to perform the first global comparison of gene expression between skin-related and non-skin related T cell populations. We report a comparative simultaneous analysis of 7100 human gene expression products between resting naive (CD45RA+), skin-homing memory (cutaneous lymphocyte antigen (CLA)+, CD45RO+) and non-skin homing memory (CLA-, CD45RO+) T cells. Overall, we identified 21 genes with statistically significant expression level differences (? 2-fold) in memory T cells compared with naive cells and 11 genes with differential expression in skin-homing (CLA+) vs. non-skin homing (CLA-) memory T cells. 1,076 genes displayed identical levels of expression (p < 0.001) across all three T lymphocyte populations including several genes that have not previously been reported in the context of T lymphocyte function and a sizable number that have not yet been functionally characterized. To test the utility of this technique in the analysis of cutaneous disease, the gene expression profile of T cells obtained from a patient with leukemic cutaneous T cell lymphoma (CTCL) (CD4+, CD45RO+, CD7-, CD25+, CLA+) was compared with that of normal non-transformed CLA+ memory T cells. 290 genes with statistically significant increased expression in CTCL cells were identified. Using a novel integrated information management system (linked to GeneBank, Locus Link, SWISS-PROT, OMIM, TIGR, Medline, etc) developed in collaboration with a team of software engineers we have annotated and functionally clustered this set of over-expressed genes. Our analysis indicates that several of these genes may play a pathogenic role in CTCL. Genome-wide parallel analysis of the expression patterns of T cell populations involved in skin diseases has the potential to provide unique insights into the multiple gene-gene interactions underlying the complex nature of these disorders.