Transcriptome analysis of salivary gland epithelial cell lines derived from patients with primary Sjögren’s syndrome.

Primary Sjögren’s syndrome (SS or autoimmune epithelitis) is a relatively common autoimmune disorder that is primarily characterized by chronic lymphoepithelial inflammatory reactions in the exocrine glands, mainly the salivary and lachrymal glands. It may extend from disease confined to the exocrine glands (organ-specific exocrinopathy) to various extraglandular manifestations (systemic disease) and the development of B-cell lymphoma. Several studies from our laboratory had provided evidence for the strong implication of ductal salivary gland epithelial cells (SGEC) in the pathogenesis of Sjögren’s syndrome (SS), including the development of salivary gland infiltrating lesions and of adverse systemic clinical complications, such as the development of B-cell lymphoma. In fact, the comparative assessment of non-neoplastic SGEC lines derived from SS patients and disease controls had indicated that the ductal epithelia of SS patients manifest an “intrinsically activated” status that is associated with distinct aberrant phenotypic and functional features encountered in “inflamed” cells. Herein, using microarray analysis, we sought to comparatively analyze the constitutive gene expression in long-term cultured non-neoplastic SGEC lines derived from non-SS sicca control individuals and from SS patients. The study aimed to reveal the genes that are differentially expressed between SGEC lines derived from SS patients and controls, as well as between SGEC lines derived from SS patients with moderate lymphocytic infiltrations (focus score<2; SS-Group-1) and SS patients with severe lymphocytic infiltrations (focus score ≥2; SS-Group-2). The transcriptome profiling analysis presented herein lends further support to the intrinsic activation status of patients’ ductal epithelia and its association with distinct proinflammatory and metabolism-related gene signatures, which occur primarily among patients with heavy tissue infiltrates and high risk for lymphoma development. Long-term cultured non-neoplastic secondary SGEC lines were established from minor salivary gland biopsies that were obtained with informed consent from patients with dryness complaints during their routine diagnostic work-up for SS. All SGEC lines studied (n=12) were of ductal type and were established and maintained under the same culture conditions in serum-free keratinocyte basal medium, as previously described (Dimitriou et al, Eur J Oral Sci, 2002, 110:21-30). The exclusive epithelial nature and ductal epithelial origin of cultured SGEC lines was verified by morphology, as well as by the uniform and consistent expression of epithelial specific markers and the absence of markers indicative of other types of cells. Transcriptome analyses were performed in total RNA specimens isolated from the non-neoplastic SGEC lines derived from 3 non-SS sicca controls (control-SGEC lines) and from 9 SS patients (SS-SGEC lines), using the Affymetrix microarray technology (GeneChipHuGene 1.0ST arrays with 28,869 annotated genes). The SS-SGEC lines studied were selected on the basis of the intensity of lymphoepithelial infiltrates in the respective MSG biopsies (all with sialadenitis focus score ≥1), and consisted of two subgroups; SS-Group-1 (n=3) derived from biopsies with moderate mononuclear infiltrations (focus score<2) and SS-Group-2 (n=6) derived from biopsies with heavy mononuclear infiltrations (focus score ≥2). Evidence of type-1 disease (high risk for lymphoma development) was exclusively manifested by patients belonging in SS-Group-2. Microarray analysis was performed with the R statistical environment version 2.13 using the Bioconductor package. RMA normalization was performed in the microarray and identification of differentially expressed genes was conducted with Student’s t-test (p-value<0.05). Gene ontology annotation of differentially expressed genes, signal pathway analysis and network construction was performed with the use of Ingenuity Pathway Analysis (IPA) software and he Kyoto Encyclopedia of Genes and Genomes (KEGG).