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Every year, ovarian cancer kills approximately 14,000 women in the United States and more than 140,000 women worldwide. Most of these deaths are caused by tumors of the serous histological type, which is rarely diagnosed before it has disseminated. By deep paired-end sequencing of mRNA from serous ovarian cancers, followed by deep sequencing of the corresponding genomic region, we identified a recurrent fusion transcript. The fusion transcript joins the 59 exons of ESRRA, encoding a ligand-independent member of the nuclear-hormone receptor superfamily, to the 39 exons of C11orf20, a conserved but uncharacterized gene located immediately upstream of ESRRA in the reference genome. To estimate the prevalence of the fusion, we tested 67 cases of serous ovarian cancer by RT-PCR and sequencing and confirmed its presence in 10 of these. Targeted resequencing of the corresponding genomic region from two fusion-positive tumor samples identified a nearly clonal chromosomal rearrangement positioning ESRRA upstream of C11orf20 in one tumor, and evidence of local copy number variation in the ESRRA locus in the second tumor. We hypothesize that the recurrent novel fusion transcript may play a role in pathogenesis of a substantial fraction of serous ovarian cancers and could provide a molecular marker for detection of the cancer. Gene fusions involving adjacent or nearby genes can readily escape detection but may play important roles in the development and progression of cancer. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian carcinoma is a significant cause of cancer mortality in women worldwide and in the United States. Epithelial ovarian cancer comprises several histological subtypes, each with distinct clinical and molecular characteristics. The natural history of this heterogeneous disease, including the cell types of origin, is poorly understood. This study applied recently developed methods for high-throughput DNA methylation profiling to characterize ovarian cancer cell lines and tumors, including representatives of three major histologies. Methodology/Principal Findings: We obtained DNA methylation profiles of 1,505 CpG sites (808 genes) in 27 primary epithelial ovarian tumors and 15 ovarian cancer cell lines. We found that the DNA methylation profiles of ovarian cancer cell lines were markedly different from those of primary ovarian tumors. Aggregate DNA methylation levels of the assayed CpG sites tended to be higher in ovarian cancer cell lines relative to ovarian tumors. Within the primary tumors, those of the same histological type were more alike in their methylation profiles than those of different subtypes. Supervised analyses identified 90 CpG sites (68 genes) that exhibited 'subtype-specific' DNA methylation patterns (FDR<1%) among the tumors. In ovarian cancer cell lines, we estimated that for at least 27% of analyzed autosomal CpG sites, increases in methylation were accompanied by decreases in transcription of the associated gene. Significance: The significant difference in DNA methylation profiles between ovarian cancer cell lines and tumors underscores the need to be cautious in using cell lines as tumor models for molecular studies of ovarian cancer and other cancers. Similarly, the distinct methylation profiles of the different histological types of ovarian tumors reinforces the need to treat the different histologies of ovarian cancer as different diseases, both clinically and in biomarker studies. These data provide a useful resource for future studies, including those of potential tumor progenitor cells, which may help illuminate the etiology and natural history of these cancers. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) are small regulatory RNAs that are implicated in cancer pathogenesis and have recently shown promise as blood-based biomarkers for cancer detection. Epithelial ovarian cancer is a deadly disease for which improved outcomes could be achieved by successful early detection and enhanced understanding of molecular pathogenesis that leads to improved therapies. A critical step toward these goals is to establish a comprehensive view of miRNAs expressed in epithelial ovarian cancer tissues as well as in normal ovarian surface epithelial cells. Methodology: We used massively parallel pyrosequencing (i.e., ''454 sequencing'') to discover and characterize novel and known miRNAs expressed in primary cultures of normal human ovarian surface epithelium (HOSE) and in tissue from three of the most common histotypes of ovarian cancer. Deep sequencing of small RNA cDNA libraries derived from normal HOSE and ovarian cancer samples yielded a total of 738,710 high-quality sequence reads, generating comprehensive digital profiles of miRNA expression. Expression profiles for 498 previously annotated miRNAs were delineated and we discovered six novel miRNAs and 39 candidate miRNAs. A set of 124 miRNAs was differentially expressed in normal versus cancer samples and 38 miRNAs were differentially expressed across histologic subtypes of ovarian cancer. Taqman qRT-PCR performed on a subset of miRNAs confirmed results of the sequencing-based study. Conclusions: This report expands the body of miRNAs known to be expressed in epithelial ovarian cancer and provides a useful resource for future studies of the role of miRNAs in the pathogenesis and early detection of ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer. Methods and Findings: We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers-MUC16, WFDC2, MSLN and MMP7-warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer. Conclusions: By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection. [ABSTRACT FROM AUTHOR]

Background: Elucidation of the repertoire of secreted and cell surface proteins of tumor cells is relevant to molecular diagnostics, tumor imaging and targeted therapies. We have characterized the cell surface proteome and the proteins released into the extra-cellular milieu of three ovarian cancer cell lines, CaOV3, OVCAR3 and ES2 and of ovarian tumor cells enriched from ascites fluid. Methodology and Findings: To differentiate proteins released into the media from protein constituents of media utilized for culture, cells were grown in the presence of [13C]-labeled lysine. A biotinylation-based approach was used to capture cell surface associated proteins. Our general experimental strategy consisted of fractionation of proteins from individual compartments followed by proteolytic digestion and LC-MS/MS analysis. In total, some 6,400 proteins were identified with high confidence across all specimens and fractions. Conclusions and Significance: Protein profiles of the cell lines had substantial similarity to the profiles of human ovarian cancer cells from ascites fluid and included protein markers known to be associated with ovarian cancer. Proteomic analysis indicated extensive shedding from extra-cellular domains of proteins expressed on the cell surface, and remarkably high secretion rates for some proteins (nanograms per million cells per hour). Cell surface and secreted proteins identified by indepth proteomic profiling of ovarian cancer cells may provide new targets for diagnosis and therapy. [ABSTRACT FROM AUTHOR]