A better understanding of the molecular circuitry in normal ovarian tissues and in ovarian cancer will likely provide new targets for diagnosis and therapy. Recently, much has been learned about the genes expressed in ovarian cancer through studies with cDNA arrays and serial analysis of gene expression. However, these methods do not allow highly quantitative analysis of gene expression on a large number of specimens. Here, we have used quantitative real-time RT-PCR in a panel of 39 microdissected ovarian carcinomas of various subtypes to systematically analyze the expression of 13 genes, many of which were previously identified as up-regulated in a subset of ovarian cancers by serial analyses of gene expression. The genes analyzed are glutathione peroxidase 3 (GPX3), apolipoprotein J/clusterin, insulin-like growth factor-binding protein 2, epithelial cell adhesion molecule/GA733-2, Kop protease inhibitor, matrix gla protein, tissue inhibitor of metalloproteinase 3, folate receptor 1, S100A2, signal transducer and activator of transcription 1, secretory leukocyte protease inhibitor, apolipoprotein E, and ceruloplasmin. All of the genes were found overexpressed, some at extremely high levels, in the vast majority of ovarian carcinomas irrespective of the subtype. Interestingly, GPX3 was found at much higher levels in tumors with clear cell histology and may represent a biomarker for this subtype. Some of the genes studied here may thus represent targets for early detection ovarian cancer. The gene expression patterns were not associated with age at diagnosis, stage, or K-ras mutation status in ovarian cancer. We find that several genes are coordinately regulated in ovarian cancer, likely representing the fact that many genes are activated as part of common signaling pathways or that extensive cross-talk exists between several pathways in ovarian cancer. A statistical analysis shows that genes commonly up-regulated in ovarian cancer may result from the aberrant activation of a limited number of pathways, providing promising targets for novel therapeutic strategies.