title: Molecular characterization of human adenomyosis.
abstract: 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.
authors.affiliation: Neurocrine Biosciences, Discovery Biology, San Diego, CA, USA and School of Medicine, University of Baja California, Mexicali, Mexico. ahever@neurocrine.com
authors.forename: A
authors.initials: A
authors.lastname: Hever
authors.forename: R B
authors.initials: RB
authors.lastname: Roth
authors.forename: P A
authors.initials: PA
authors.lastname: Hevezi
authors.forename: J
authors.initials: J
authors.lastname: Lee
authors.forename: D
authors.initials: D
authors.lastname: Willhite
authors.forename: E C
authors.initials: EC
authors.lastname: White
authors.forename: E M
authors.initials: EM
authors.lastname: Marin
authors.forename: R
authors.initials: R
authors.lastname: Herrera
authors.forename: H M
authors.initials: HM
authors.lastname: Acosta
authors.forename: A J
authors.initials: AJ
authors.lastname: Acosta
authors.forename: A
authors.initials: A
authors.lastname: Zlotnik
mesh_terms: D000704:Analysis of Variance; D015415:Biomarkers; D014408:Biomarkers, Tumor; D003937:Diagnosis, Differential; D004715:Endometriosis / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D004717:Endometrium / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D007889:Leiomyoma / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism; D009215:Myometrium / Q000378:metabolism; D009363:Neoplasm Proteins / Q000096:biosynthesis / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D025341:Principal Component Analysis; D014594:Uterine Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism
chemical_list: D015415:Biomarkers; D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins