Abstract
PURPOSE: This study utilized both cDNA microarray and 2D protein gel electrophoresis technology to investigate the multiple interactions of the genes and proteins involved in the pathophysiology of uterine leiomyomas. Also, Gene Ontology (GO) analysis was used to systematically characterize the global expression profiles, which were found to correlate with the leiomyosarcomas. MATERIALS AND METHODS: The uterine leiomyoma biopsies were obtained from patients in the Department of Obstetrics and Gynecology, The Catholic University of Korea. Differentially expressed transcriptome and proteome, in 6 paired leiomyoma and normal myometrium, were profiled. The total RNAs from the leiomyoma and normal myometrium were labeled with Cy5 and Cy3. All specimens were punch-biopsy-obtained, and frozen in liquid nitrogen. RESULTS: Screening of up to 17,000 genes identified 71 that were either up-regulated or down-regulated (21 and 50, respectively). The gene expression profiles were classified into 420 mutually dependent functional sets, resulting in 611 cellular processes, according to the gene ontology. Also, the protein analysis, using 2D gel electrophoresis, identified 33 proteins (17 up-regulated and 16 down-regulated) with more than 500 total spots, which were classified into 302 cellular processes. O f these functional profilings, transcriptomes and proteoms down-regulations were shown in the cell adhesion, cell motility, organogenesis, enzyme regulator, structural molecule activity and responses to external stimulus functional activities, which are supposed to play important roles in the pathophysiology. In contrast, up-regulation was only shown in the nucleic acid binding activity. The CDKN2A, ADH1A, DCX, IGF2, CRABP2 and KIF5C were found to increase the reliability of this study, and correlate with the leiomyosarcomas. CONCLUSION: Potentially significant pathogenetic cellular processes showed that down-regulated functional profiling has an important impact on the discovery of the pathogenic pathways in leiomyomas and leiomyosarcomas. GO analysis can also overcome the complexity of the expression profiles of cDNA microarrays and 2D protein analyses, via a cellular process level approach. Thereby, a valuable prognostic candidate gene, with real relevance to disease-specific pathogenesis, can be found at cellular process levels.