Using cDNA microarrays to identify human CD19+ B cell gene products (ESTs) originated from systemic lupus erythematosus susceptibility loci

Genetic susceptibility loci in rheumatoid arthritis establish transcriptional regulatory networks with other genes

Linkage studies have identified the human leukocyte antigen (HLA)-DRB1 as a putative rheumatoid arthritis (RA) susceptibility locus (SL). Nevertheless, it was estimated that its contribution was partial, suggesting that other non-HLA genes may play a role in RA susceptibility. To test this hypothesis, we conducted microarray transcription profiling of peripheral blood mononuclear cells in 15 RA patients and analyzed the data, using bioinformatics programs (significance analysis of microarrays method and GeneNetwork), which allowed us to determine the differentially expressed genes and to reconstruct transcriptional networks. The patients were grouped according to disease features or treatment with tumor necrosis factor blocker. Transcriptional networks that were reconstructed allowed us to identify the interactions occurring between RA SL and other genes, for example, HLA-DRB1 interacting with FNDC3A (fibronectin type III domain containing 3A). Given that fibronectin fragments can stimulate mediators of matrix and cartilage destruction in RA, this interaction is of special interest and may contribute to a clearer understanding of the functional role of HLA-DRB1 in RA pathogenesis.

Transcriptional Response of Peripheral Lymphocytes to Early Fibrosarcoma: A Model System for Cancer Detection Based on Hybridization Signatures

Since circulating leukocytes, mainly B and T cells, continuously maintain vigilant and comprehensive immune surveillance, these cells could be used as reporters for signs of infection or other pathologies, including cancer. Activated lymphocyte clones trigger a sensitive transcriptional response, which could be identified by gene expression profiling. To assess this hypothesis, we conducted microarray analysis of the gene expression profile of lymphocytes isolated from immunocompetent BALB/c mice subcutaneously injected with different numbers of tumorigenic B61 fibrosarcoma cells. Flow cytometry demonstrated that the number of circulating T (CD3+CD4+ or CD3+CD8+) or B (CD19+) cells did not change. However, the lymphocytes isolated from tumor cell–injected animals expressed a unique transcriptional profile that was identifiable before the development of a palpable tumor mass. This finding demonstrates that the transcriptional response appears before alterations in the main lymphocyte subsets and that the gene expression profile of peripheral lymphocytes can serve as a sensitive and accurate method for the early detection of cancer.

Gene expression profiles stratified according to type 1 diabetes mellitus susceptibility regions

The MHC region (6p21) aggregates the major genes that contribute to susceptibility to type 1 diabetes (T1D). Three additional relevant susceptibility regions mapped on chromosomes 1p13 (PTPN22), 2q33 (CTLA-4), and 11p15 (insulin) have also been described by linkage studies. To evaluate the contribution of these susceptibility regions and the chromosomes that house these regions, we performed a large-scale differential gene expression on lymphomononuclear cells of recently diagnosed T1D patients, pinpointing relevant modulated genes clustered in these regions and their respective chromosomes. A total of 4608 cDNAs from the IMAGE library were spotted onto glass slides using robotic technology. Statistical analysis was carried out using the SAM program, and data regarding gene location and biological function were obtained at the SOURCE, NCBI, and FATIGO programs. Three induced genes were observed spanning around the MHC region (6p21-6p23), and seven modulated genes (5 repressed and 2 repressed) were seen spanning around the 6q21-24 region. Additional modulated genes were observed in and around the 1p13, 2q33, and 11p15 regions. Overall, modulated genes in these regions were primarily associated with cellular metabolism, transcription factors and signaling transduction. The differential gene expression characterization may identify new genes potentially involved with diabetes pathogenesis.

Profiling meta-analysis reveals primarily gene coexpression concordance between systemic lupus erythematosus and rheumatoid arthritis

Consensus gene expression profiling by meta-analysis of 4,500 cDNA sequence microarray data obtained from patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) was assembled and systematically analyzed. The normalized data were statistically analyzed by the significance analysis of microarray (SAM) program (false discovery rate <or= 0.01). Patient data input was realized together, in the Cluster and Tree-View program, using the unsupervised function. Individual expression signatures permitted a hierarchical clustering of samples, separately identifying SLE and RA patients and the transcriptome profiling featured modules of the specifically induced or repressed and the comodulated genes. Gene expression profiling meta-analysis showed that patients with SLE or RA share gene modulation but also present genes whose expression patterns are exclusive (induced or repressed) in corroboration with their clinical features. Among the genes that were differentially expressed, we found those that could play specific roles in these two diseases. This approach permits a clearer understanding of the molecular basis of SLE and RA concordance/divergence.