Endometriosis affects 10 -20% of women of reproductive age and is associated with pelvic pain and infertility, and its pathogenesis is not well understood. We used genomewide transcriptional profiling to characterize endometriosis and found that it exhibits a gene expression signature consistent with an underlying autoimmune mechanism. Endometriosis lesions are characterized by the presence of abundant plasma cells, many of which produce IgM, and macrophages that produce BLyS/BAFF/TNFSF13B, a member of the TNF superfamily implicated in other autoimmune diseases. B lymphocyte stimulator (BLyS) protein was found elevated in the serum of endometriosis patients. These observations suggest a model for the pathology of endometriosis where BLySresponsive plasma cells interact with retrograde menstrual tissues to give rise to endometriosis lesions.autoimmunity ͉ cytokines ͉ microarrays
The Affymetrix GeneChip platform was used to build a gene expression database of the normal human body. Postmortem human tissues represent a valuable source of biological materials for this type of study, but their use entails some delays before harvesting such tissues. We first evaluated the RNA quality obtained from tissues obtained 3-5 h postmortem and found variations that were both tissue and donor-dependent. RNAs extracted from brain regions were of higher quality than those obtained from the gut, while the cause of death was a significant factor in donor-dependent differences. To avoid these variables, we used rat duodenum to determine the effects of RNA degradation on the analysis of gene expression. Surprisingly, even samples exhibiting significant RNA degradation yielded robust gene expression results, comparable to those obtained using intact samples at a certain signal intensity cutoff. We extended these findings to our human expression database and obtained similar results, indicating that the Affymetrix platform, which is biased to the 3' end of transcripts for detection, can tolerate significant RNA degradation, while still yielding high quality expression data. Our resulting body index expression database is a valuable research tool. As examples of potential uses, we report novel expression sites for four potential therapeutic targets--CCL27, GPR22, GPR113 and GPR128--and as well as a set of thymus-specific genes, including three not previously associated with the thymus.
Adenomyosis is a common gynaecological disorder characterized by the abnormal growth of endometrium into the myometrium and myometrial hypertrophy/hyperplasia. Uterine fibroids are benign neoplasms of the myometrium, and they represent a diagnostic pitfall for adenomyosis. In this study, we have used the genome-wide Affymetrix U133 Plus 2.0 microarray platform to compare the gene expression patterns of adenomyosis, uterine fibroids, normal endometrium and myometrium. Unsupervised principal component analysis (PCA) revealed that these four tissue types could be segregated from one another solely based on their gene expression profiles. Analysis of variance (ANOVA), followed by Tukey means separation test, significance analysis of microarrays (SAM) and 2-fold change threshold, identified 7415 probe sets as differentially expressed among the four groups of samples. Supervised cluster analysis based on these probe sets clustered adenomyosis most closely with endometrium and uterine fibroids with myometrium, consistent with the anatomic origin of these two diseases. The Tukey means separation post hoc testing found 2073 probe sets altered between adenomyosis and normal endometrium or myometrium, and 2327 probe sets altered in expression when comparing uterine fibroids with myometrium. Using Ingenuity Pathways Analysis (IPA), we found 9 highly significant functional networks in adenomyosis and 10 in uterine fibroids. Notably, the top network in both cases was associated with functions implicated in cancer and cell death. Finally, we compared the gene expression profiles of adenomyosis and uterine fibroids and identified 471 differentially expressed probe sets that may represent potential biomarkers for the differential diagnosis of these diseases.
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