Normal Ovarian Tissue Samples Research Articles

Survivin in ovary tumors.

Survivin is a member of the inhibitor of apoptosis protein (IAP) family which are selectively overexpressed in human neoplasms, and its expression has been shown to be connected with cell proliferation. We analyzed survivin expression in ovarian epithelial neoplasms to evaluate its role in the development of ovarian tumors. Immunohistochemistry assays were conducted in 137 cases (48 ovarian carcinoma, 43 borderline ovarian carcinoma, 46 benign ovarian tumor and 20 samples of normal ovarian tissue of ovarian epithelial neoplasms. Histological types included serous (n = 68) and mucinous (n = 69) tumors. All tumors were reviewed histopathologically and classified according to the WHO criteria. Survivin expression in the group of serous neoplasms was detected in 24.0% (6 of 25) of benign cases, in 60.0% (12 of 20) of borderline tumors, and 91.0% (24 of 47) of ovarian carcinomas. In the group of mucinous tumors, survivin expression was found in 33.5% (7 of 21) of benign cases, 43.5% (10 of 23) of borderline tumors, and 80.0% (20 of 25) of malignant tumors. Our results demonstrate that survivin overexpression may play a crucial role in the development of epithelial ovarian neoplasms and be an important prognostic factor for the influence of survivin expression on epithelial ovarian cancers.

Cumulative methylation alternations of gene promoters and protein markers for diagnosis of epithelial ovarian cancer.

DNA methylation plays an important role in carcinogenesis and cancer development. In this study, we examined gene methylation in epithelial ovarian cancer (EOC) using cationic conjugated polymer (CCP)-based fluorescence resonance energy transfer (FRET) to evaluate the application of cumulative methylation alternations of genes associated with cancer antigen 125 for early cancer diagnosis. The methylation status of 3 genes (Ras association domain family 1 isoform A, RASSF1A; opioid-binding protein/cell adhesion molecule, OPCML; homeobox A9, HOXA9) were examined and compared in 35 EOC samples and 11 normal ovarian tissue samples using CCP-based FRET. Gene methylation levels were clustered into 3 sections and assigned a value; values for the 3 genes were summed. Although methylation of the OPCML gene was significantly associated with stage, histological types, grade, and ascites and that of RASSF1A and HOXA9 was not, the sum for the 3 genes was significantly associated with stage and ascites. The sum showed higher sensitivity (85.7%) and specificity (100%) for discriminating EOC from normal ovarian tissues than did the methylation status of RASSF1A, OPCML, and HOXA9 (48.6, 77.1, 77.1, and 100, 88.1, 100%, respectively). Combining cancer antigen 125 levels with the sum increased the sensitivity to 94.3%. The detection and analysis of a panel of genes' methylation status with the CCP-based FRET technique may be useful for diagnosis and screening of EOC; the associated cancer antigen 125 can be used to increase diagnostic sensitivity.

MiR-200c modulates ovarian cancer cell metastasis potential by targeting zinc finger E-box-binding homeobox 2 (ZEB2) expression.

This study was to investigate the effect of miR-200c on regulation of ovarian cancer cell metastasis potential and explore the underlying molecular events. qRT-PCR was used to analyze the level of miR-200c expression in 48 ovarian cancer and 30 normal ovarian tissue samples. pre-miR-200c was used to manipulate miR-200c expression in ovarian cancer cells for detection of changed phenotypes of tumor cells. Bioinformatics analysis was then used to predict target genes of miR-200c and GO and pathway analyses drew the miR-200c-related gene network. Luciferase reporter assay confirmed the target of miR-200c as ZEB2. Western blot was used to detect gene expressions in ovarian cancer cells. Level of miR-200c expression was much higher in ovarian cancer than in normal ovarian tissues, and miR-200c expression was inversely associated with advanced clinical stage and lymph node metastasis of ovarian cancer (p < 0.01). The database search predicted 186 miR-200c-targeting genes, and GO analysis showed that functions of these target genes were enriched in the protein binding and other biological processes. Furthermore, miR-200c expression inhibited ovarian cancer cell ES-2 migration and invasion capacity by suppression of ZEB2 expression (p < 0.01). Overexpression of miR-200c regulated E-cadherin and vimentin expression in ovarian cancer cells. This study demonstrated high miR-200c expression in ovarian cancer tissues and ZEB2 as a targeting gene of miR-200c, which mediated the effects of miR-200c on regulation of ovarian cancer cell migration and invasion capacity and epithelial-to-mesenchymal transition. Thus, targeting of miR-200c or ZEB2 may serve as a potential therapeutic strategy for control of ovarian cancer.

A ten-microRNA signature identified from a genome-wide microRNA expression profiling in human epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.

Potential molecular signatures in epithelial ovarian cancer by genome wide expression profiling

Ovarian cancer is the deadliest of all gynecologic cancers because of its late diagnosis and poor treatment outcomes. This study aimed to identify potential molecular signatures associated with biological processes that are implicated in epithelial ovarian cancer (EOC). Expression profiling was carried out on 16 fresh frozen EOC and normal ovarian tissue samples using the Illumina Whole Genome DASL assay (cDNA-mediated annealing, selection, extension and ligation). The differentially expressed genes were analyzed using the GeneSpring GX11.5 and Pathway Studio 8.0 software. The microarray results were validated using the immunohistochemistry analyses. Unpaired t-test identified 652 (270 up- and 382 downregulated) significant differentially expressed genes (P < 0.001 and fold change ≥2.0). Hierarchical clustering analysis displayed a distinct separation of cancer and normal samples. Gene set enrichment analysis identified alterations in the expression of genes associated with cancer development and progression. Positive immunostaining of claudin-7, ephrin receptor A1 and Forkhead Box M1 in EOC was consistent with the upregulation of these genes in the microarray result. However, the positive immunostaining of fibroblast growth factor-7 in cancer tissues was not in accordance with the downregulation of this gene in the microarray result. These results identify significant genes and their related biological processes which may contribute to the better understanding of development and progression of epithelial ovarian cancer.

Global methylation profiling in serous ovarian cancer is indicative for distinct aberrant DNA methylation signatures associated with tumor aggressiveness and disease progression

ObjectiveTo characterize at high resolution the DNA methylation changes which occur in the genome of serous epithelial ovarian cancer (EOC) in association with tumor aggressiveness. MethodsMethylated DNA immunoprecipitation in combination with CpG island-tiling arrays was used to compare the methylation profiles of five borderline, five grade 1/stage III/IV, five grade 3/stage I and five grade 3/stage III/IV serous EOC tumors, to those of five normal human ovarian tissue samples. ResultsWe found widespread DNA hypermethylation that occurs even in low-malignant potential (borderline) tumors and which predominantly includes key developmental/homeobox genes. Contrary to DNA hypermethylation, significant DNA hypomethylation was observed only in grade 3 serous EOC tumors. The latter observation was further confirmed when comparing the DNA methylation profiles of primary cell cultures derived from matched tumor samples obtained prior to, and following chemotherapy treatment from two serous EOC patients with advanced disease. To our knowledge this is the first report that has shown the presence of massive DNA hypomethylation in advanced serous EOC, associated with tumor malignancy and disease progression. ConclusionsOur data raise the concern that demethylating drugs that are currently being used in advanced EOC disease (representing the majority of serous EOC cases) might have adverse effects due to activation of oncogenes and prometastatic genes. Understanding the relative roles of hypomethylation and hypermethylation in cancer could have clear implications on the therapeutic use of agents targeting the DNA methylation machinery.

Systematic analysis and validation of differential gene expression in ovarian serous adenocarcinomas and normal ovary

Cancer of the ovary confers the worst prognosis among women with gynecological malignancies, primarily because most ovarian cancers are diagnosed at late stage. Hence, there is a substantial need to develop new diagnostic biomarkers to enable detection of ovarian cancer at earlier stages, which would confer better prognosis. In addition, the identification of druggable targets is of substantial interest to find new therapeutic strategies for ovarian cancer. The expression of 22,500 genes in a series of 67 serous papillary carcinomas was compared with 9 crudely enriched normal ovarian tissue samples by RNA hybridization on oligonucleotide microarrays. Multiple genes with near-uniformly expression were elevated in carcinomas of varying grade and malignant potential, including several previously described genes (e.g., MUC-1, CD9, CD24, claudin 3, and mesothelin). We performed immunohistochemical staining with antibodies against several of the proteins encoded by differentially expressed genes in an independent cohort of 71 cases of paraffin-embedded ovarian cancer samples. We found striking differences in EpCAM (p < 0.005), CD9 (p < 0.001), MUC-1 (p < 0.001), and claudin 3 proteins (p < 0.001) but not for mesothelin (p > 0.05) using the Mann-Whitney U test. Protein expression of a majority of the differentially expressed genes tested was found to be elevated in ovarian carcinomas and, as such, define potential new biomarkers or targets.

Abstract 4270: Novel stromal angiogenic factor MFAP5 in ovarian cancer progression

Abstract Using transcriptome profiling analysis, we identified a gene signature in the fibroblastic stromal component of high grade serous ovarian tumor tissue. One of the most differentially expressed proteins was microfibrillar associated protein 5 (MFAP5). This study aims at validating the differential expression patterns of MFAP5 in ovarian cancer stroma, evaluating the clinical significance of stromal MFAP5 over-expression and delineating the functional role and mechanism of MFAP5 in modulating angiogenesis and tumor progression. Quantitative RT-PCR analysis was first performed on RNA isolated from microdissected normal and malignant ovarian tissue samples and immunolocalization of MFAP5 protein was performed on paraffin tissue sections (n=102) to validate differential stromal MFAP5 expression. Both demonstrated significant higher levels of MFAP5 expression in the fibroblastic stromal component of cancer tissue samples. Kaplan Meier analysis demonstrated a significant correlation between stromal MFAP5 expression and poor overall patient survival (p&amp;lt;0.001). Cox regression analysis showed a hazard ratio of 2.603 (p&amp;lt;0.001). Further correlation studies showed that MFAP5 expression correlated with CD34 positive microvessel densities, suggested a pro-angiogenic role of MFAP5. Thus, functional studies of exogenous MFAP5 on angiogenesis modulation and ovarian cancer cell growth were performed. Motility assay and tube formation assay were conducted on human microvascular endothelial cell 1 (hMEC-1) and telomerase immortalized microvascular endothelial cells (TIME). Increased motility and tube formation were observed in the presence of exogenous MFAP5 in both cell lines. In addition, both anti-αVα3 integrin antibody and cell permeant calcium chelator, BAPTA, AM, attenuated MFAP5 stimulated motility. These suggested that MFAP5 exerts its biological activity through the αVα3 integrin receptor and calcium signal transduction. The hypothesis is further supported by the successful detection of calcium influx and increased amplitude and change of distribution of traction force exerted by endothelial cells after treatment with MFAP5. In vivo, extensive CD34 positive tubular network was formed in the matrigel mixed with recombinant MFAP5 injected subcutaneously into mice when compared to the control. Co-injection of MFAP5 overexpressing ovarian fibroblasts and cancer cells subcutaneously into mice led to increased tumor size and increased number of CD34 positive microvessels within the tumor tissue. Finally, in vivo silencing of stromal MFAP5 using MFAP5 specific siRNA delivered in chitosan nanoparticle significantly decreased tumor sizes and intratumor microvessel densities. To conclude, stromal MFAP5 is a novel angiogenic factor that acts on αVα3 integrin receptor. It modulates endothelial cell behavior through calcium signaling which may lead to tumor progression and subsequent poor patient survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4270. doi:1538-7445.AM2012-4270

Multidrug resistance-associated biomarkers PGP, GST-π, Topo-II and LRP as prognostic factors in primary ovarian carcinoma

This study aims to investigate the expression of P-glycoprotein (PGP), glutathione S-transferase π (GST-π), DNA topoisomerase II (Topo-II) and lung resistance-related protein (LRP) in ovarian carcinoma, thus providing better chemotherapy choice and post-operative prognosis for ovarian carcinoma patients. A total of 80 primary ovarian carcinoma, 16 benign ovarian epithelial neoplasm, and 12 normal ovarian tissue samples were collected. Immunohistochemistry was used to detect the expression of PGP, GST-π, Topo-II and LRP, and the results were analysed by correlation with clinicopathological parameters. Positive expression rates of PGP, GST-π, Topo-II and LRP in patients with ovarian carcinoma (57.5%, 58.8%, 76.3% and 73.8%, respectively) were all higher than those found in normal and benign tissue (P<0.05). In clinical stages I/II vs. III/IV, the expression rates of PGP, GST-π, Topo-II and LRP were 40.7% vs. 66% (P<0.05), 40.7% vs. 67.9% (P<0.05), 66.7% vs. 81.1% (P>0.05) and 55.6% vs. 83.0% (P<0.05), respectively. Carcinoma differentiation ranged from well to poor, and expression levels of each marker were as follows: PGP, 57.9%, 62.1% and 53.1% (P>0.05); GST-π, 36.8%, 55.2% and 75.0% (P<0.05); Topo-II, 52.6%, 79.3% and 87.5% (P<0.05); and LRP, 84.2%, 69.0% and 71.9% (P>0.05). Ovarian carcinoma patients with PGP-, GST-π-, Topo-II- and LRP-positive expression had a shorter median survival time than those who were negative for these markers (PGP: 36 months vs. 48 months [P=0.0017]; GST-π: 36 months vs. 41 months [P=0.0103]; Topo-II: 37 months vs. 39 months [P=0.3811]; LRP: 37 months vs. 55 months [P=0.002]). COX regression analysis demonstrated that the clinical stage of the tumour, and the expression of PGP, GST-π or LRP, may influence patient survival time after surgery. The relative death risk for patients with clinical stage III/IV tumours increased 9.46-fold compared to those with stage I/II tumours. The relative death risk in the PGP-, GST-π- and LRP-positive groups increased by 2.049-, 2.452- or 2.609-fold, respectively, compared with the corresponding negative groups. PGP, GST-π, Topo-II and LRP are all expressed in primary ovarian carcinoma, indicating the presence of multidrug resistance in this disease. Combined evaluation of PGP, GST-π, Topo-II and LRP expression may enable better chemotherapeutic choice and provide an accurate prognosis for ovarian carcinoma patients.

High-throughput DNA hypermethylation profiling in different ovarian epithelial cancer subtypes using universal bead array

DNA hypermethylation is common and plays a critical role in the regulation of gene expression. It is considered a major cause of carcinogenesis. High-throughput profiling method has been developed to analyze the methylation status of hundreds of pre-selected genes simultaneously. The aim of this study was to analyze promoter hypermethylation profiles of each subtype of ovarian epithelial cancer (OEC), to improve the understanding of the role of epigenetic silencing in carcinogenesis. DNA hypermethylation profiles on fresh frozen tissue samples of 5 serous, 3 mucinous, 5 endometrioid and 4 clear cell types of OEC, as well as 5 normal ovarian tissue samples as control. We used a high-throughput method for analyzing the hypermethylation status of 1,505 CpG loci selected from 871 genes simultaneously by GoldenGate Methylation Cancer Panel I (Illumina Human-6 v2 Expression BeadChip). Methylation status of seven genes was verified by methylation specific PCR (MSP). We identified 20, 37, 15 and 56 hypermethylated CpG locations in serous, mucinous, endometrioid and clear cell type OEC compared to control. Only 6 CpG loci were commonly hypermethylated across all subtypes of OEC. Hypermethylated loci of serous 17 (81.0%) and endometrioid type 10 (71.4%) were identical to that of clear cell type. However, mucinous type showed 17 peculiar loci (43.6%) out of 39 hypermethylated loci. The unique DNA hypermethylation patterns identified in different OEC subtypes suggest that their cause may involve different epigenetic mechanisms and the Bead chip used in this study is a useful tool to analyze DNA hypermethylation.

High-throughput DNA hypermethylation profiling in different ovarian epithelial cancer subtypes using universal bead array

DNA hypermethylation is common and plays a critical role in the regulation of gene expression. It is considered a major cause of carcinogenesis. High-throughput profiling method has been developed to analyze the methylation status of hundreds of pre-selected genes simultaneously. The aim of this study was to analyze promoter hypermethylation profiles of each subtype of ovarian epithelial cancer (OEC), to improve the understanding of the role of epigenetic silencing in carcinogenesis. DNA hypermethylation profiles on fresh frozen tissue samples of 5 serous, 3 mucinous, 5 endometrioid and 4 clear cell types of OEC, as well as 5 normal ovarian tissue samples as control. We used a high-throughput method for analyzing the hypermethylation status of 1,505 CpG loci selected from 871 genes simultaneously by GoldenGate Methylation Cancer Panel I (Illumina Human-6 v2 Expression BeadChip). Methylation status of seven genes was verified by methylation specific PCR (MSP). We identified 20, 37, 15 and 56 hypermethylated CpG locations in serous, mucinous, endometrioid and clear cell type OEC compared to control. Only 6 CpG loci were commonly hypermethylated across all subtypes of OEC. Hypermethylated loci of serous 17 (81.0%) and endometrioid type 10 (71.4%) were identical to that of clear cell type. However, mucinous type showed 17 peculiar loci (43.6%) out of 39 hypermethylated loci. The unique DNA hypermethylation patterns identified in different OEC subtypes suggest that their cause may involve different epigenetic mechanisms and the Bead chip used in this study is a useful tool to analyze DNA hypermethylation.

Expression of EMSY gene in sporadic ovarian cancer

The majority of familial breast and ovarian cancers arise from mutations in the BRCA1 and BRCA2 genes. Amplification at the 11q13.5 locus is commonly observed in breast and ovarian cancers. In 2003, Hughes-Davies et al. identified a novel gene (EMSY) at this locus which binds BRCA2 within a region deleted in some cancers. Although little is known about the cellular role of EMSY, indirect evidence suggests that this nuclear protein is capable of silencing the activation potential of BRCA2. In this study we aimed to investigate expression of the EMSY gene and its protein product in sporadic ovarian cancer. Real-time quantitative RT-PCR was performed in 50 ovarian cancer and 17 normal ovarian tissue samples. Overexpression of the EMSY gene was found in 6/50 cases (12%), but in none of the control samples. To determine the EMSY protein by Western blotting, semi-quantitative analysis of the EMSY protein was performed using the Scion Image Gel Analysis Program. Statistical analysis was performed using SPSS 11.5. All patients having EMSY overexpression also displayed increased levels of the EMSY protein. Sporadic ovarian cancer shows overexpression of EMSY at a prevalence similar to that found in breast cancer and the overexpression is correlated with the protein level.

Heparanase-2 Expression in Normal Ovarian Epithelium and in Benign and Malignant Ovarian Tumors

Studies have highlighted the changes that take place in the environment between the cell and the extracellular matrix during the process of neoplastic expansion. Several papers have associated the expression of heparanase 1 with various malignant tumors. Heparanase 2 is probably related to loss of cell adhesion. The aim of this study was to evaluate the expression of heparanase 2 in epithelial neoplasia of the ovaries and in samples of normal ovarian tissue. Seventy-five ovary specimens were analyzed and divided into 3 groups: 23 malignant and 35 benign epithelial ovarian neoplasia and 17 without ovarian disease. We used 2 methodological techniques for evaluating the immunoexpression of heparanase 2. The first followed the qualitative criterion of positive or negative in relation to enzymatic expression, and the second involved computerized quantification of this expression, performed on the same slides. In the quantitative analysis, we found positivity indices for heparanase 2 expression of 72.2% and 87.3% in the samples of benign and malignant neoplasias, respectively. In these, the intensity of expression and the expression index were 147.2 and 121.2, respectively, for the benign neoplasia and 134.1 and 118.0 for the malignant neoplasia. Qualitatively, its expression was strong or moderate in 44.2% of the benign and 78.2% of the malignant tumors; its expression in all of the nonneoplastic samples was negative, with the exception of one that was weakly positive. Heparanase 2 is involved in neoplastic proliferation, but it was not exclusively associated with the malignant process. Furthermore, there was no difference in its expression between benign and malignant ovarian epithelial neoplasia.

Overexpression of Aurora B is associated with poor prognosis in epithelial ovarian cancer patients

Recent studies have indicated that Aurora B expression is related to cell proliferation and prognosis in many cancers, but its association with epithelial ovarian carcinoma is not fully understood. Therefore, we examined the Aurora B kinase expression in epithelial ovarian cancer patients. Using immunohistochemistry, the expression levels of Aurora B and phosphohistone H3 (Ser(10)) (mitosis-specific marker) were measured in 156 patients with epithelial ovarian cancer. The expression levels of Aurora B at the protein and messenger RNA levels were examined using Western blotting and reverse transcriptase polymerase chain reaction. In total, 53 tumorous ovarian samples (34.0%) showed Aurora B overexpression, which was significantly higher than that found in the 15 normal ovarian tissue samples (0%, p = 0.006). The overexpression of Aurora B was also significantly higher in cases showing phosphohistone H3 (Ser(10)) overexpression (44.3% vs. 27.4%, p = 0.03). In addition, the expression of Aurora B in poorly and moderately differentiated carcinomas of the ovary was significantly higher than in well-differentiated carcinomas (53.6% vs. 28.2% vs.10.0%, respectively, p = 0.02). The overexpression of Aurora B was significantly higher in cases with lymph node metastasis (p = 0.01) and a positive ascites cytology (p = 0.008). Overall, the Aurora B overexpression group demonstrated a significantly shorter progression-free survival (p = 0.001) and overall survival (p = 0.023) than the Aurora B low expression group using univariate analysis (log-rank statistic). Aurora B is an effective predictor of aggressive epithelial ovarian carcinoma in terms of differentiation, metastasis, and prognosis.

The target genes research for diagnosis, therapy and prognosis in cases with ovarian cancer

16060 Background: Epithelial ovarian cancer has one of the worst prognoses among gynecologic malignancies. Molecular genetic analyses of ovarian cancers have uncovered genetic alterations of several genes. Normal tissues were readily distinguished from tumor tissues. These studies identified several genes, such as High mobility group A2 (HMG A2) proteins. The expression of HMG A2 gene is detected in foetal stage of human development and stopped in normal adult tissues. Elevation of the HMG A2 gene expression was shown for several human malignant tumours. Targeted supression of HMG A2 protein synthesis can be one of important directions for anti-tumour therapy in cases of ovarian cancer Methods: The HMG A2 gene expression was searched in 48 flash-frozen samples of ovarian serous papillary adenocarcinoma and 12 samples of normal ovarian tissue. The HMG A2 gene expression was investigated by RNA in situ hybridisation. Results: High and middle level of HMG A2 gene expression was shown in 37 from 48 (77%) ovarian cancer samples. HMG A2 mRNA was not detected in normal ovarian surface epithelium. Low grade tumour differentiation (G3) was detected in 24 cases from 37 (64,9%), middle differentiation (G2) was detected in 12 cases (32,4%) and high grade differentiation (G1) was detected in 1 case (2,7%). Conclusions: HMG A2 high expression is a typical and important feature of serouse type of ovarian carcinoma. High level of HMG A2 gene expression correlate with low grade tumour differentiation. No significant financial relationships to disclose.

Expression of sperm protein 17 (Sp17) in ovarian cancer.

Sperm protein 17 (Sp17) is an antigenic protein highly expressed in spermatozoa. Sp17 expression was demonstrated recently in multiple myeloma, suggesting that it may be a novel cancer-testis antigen. Expression of Sp17 mRNA and protein was examined in human ovarian tumors. Sp17 mRNA was evaluated by reverse transcription-polymerase chain reaction (RT-PCR) and Northern blot analysis of RNA derived from epithelial ovarian tumors and normal tissues. RT-PCR analysis detected Sp17 transcripts in 15 of 18 (83%) primary ovarian tumors. The transcript was not detected in RNA derived from normal uterus or cervix, whereas weak expression was noted in some normal ovarian tissue samples. Northern blot analysis showed no detectable Sp17 mRNA expression in normal tissues, including normal ovary, but showed Sp17 expression in 17 of 25 ovarian tumors (68%). To evaluate protein expression, mouse monoclonal antibodies were produced against recombinant Sp17 protein and used in Western blot and immunohistochemical analyses of normal reproductive tissue and primary ovarian tumor samples. Sp17 protein was detected by Western blot analysis in normal spermatozoa and in 8 of 19 ovarian tumor samples. Immunohistochemical studies showed Sp17 expression in spermatozoa, ciliated cells of the female reproductive tract, and most ovarian tumors evaluated. Tumors showed a predominantly nuclear localization of Sp17 expression, with some cytoplasmic staining. These results demonstrate that Sp17, a protein with restricted expression in somatic tissues, is expressed in ovarian tumors. Because Sp17 is immunogenic, it may represent a novel target for immunotherapeutic interventions for ovarian cancer patients.

Loss of expression and altered localization of KAI1 and CD9 protein are associated with epithelial ovarian cancer progression.

Impairment of cell adhesion plays a vital role in tumor progression. E- and N-cadherin, CD9, and KAI1 are all adhesion molecules that have been implicated in the progression of several different tumor types. To help explain the potential role these adhesion molecules have in ovarian cancer, comparisons were made between expression patterns in normal ovary and various grades of primary and metastatic epithelial ovarian cancers. Thirty-two primary and 8 metastatic human ovarian epithelial carcinomas and 18 samples of normal ovarian tissue were examined for adhesion molecule expression using immunohistochemistry. KAI1 and CD9 revealed an inverse relationship between tumor grade and expression levels, characterized by high expression in low-grade tumors and low expression in high-grade tumors and metastases. KAI1 and CD9 also demonstrated a shift in cellular localization from the membrane in grade 1 tumors to the cytoplasm in grade 3 tumors. N-cadherin expression showed a positive trend between expression levels and tumor grade. E-cadherin expression varied little between different tumor grades and metastases. Inclusion cysts (n = 6) and surface invaginations often strongly expressed KAI1, CD9, and E-cadherin. KAI1 expression was variable in ovarian follicles and corpora lutea depending on their stage of development. Although sample size is limited, these findings suggest that progression of ovarian epithelial carcinomas is associated with down-regulation and altered cellular localization of KAI1 and CD9. In addition, variable KAI1 expression during follicular and luteal development suggests that it has a physiological function in the ovary. Further investigation will be needed to see if it is also regulated this way during progression of ovarian cancers.

Arrays of Arrays for High-Throughput Gene Expression Profiling

Gene expression profiling using DNA arrays is rapidly becoming an essential tool for research and drug discovery and may soon play a central role in disease diagnosis. Although it is possible to make significant discoveries on the basis of a relatively small number of expression profiles, the full potential of this technology is best realized through more extensive collections of expression measurements. The generation of large numbers of expression profiles can be a time-consuming and labor-intensive process with current one-at-a-time technology. We have developed the ability to obtain expression profiles in a highly parallel yet straightforward format using glass wafers that contain 49 individual high-density oligonucleotide arrays. This arrays of arrays concept is generalizable and can be adapted readily to other types of arrays, including spotted cDNA microarrays. It is also scalable for use with hundreds and even thousands of smaller arrays on a single piece of glass. Using the arrays of arrays approach and parallel preparation of hybridization samples in 96-well plates, we were able to determine the patterns of gene expression in 27 ovarian carcinomas and 4 normal ovarian tissue samples, along with a number of control samples, in a single experiment. This new approach significantly increases the ease, efficiency, and throughput of microarray-based experiments and makes possible new applications of expression profiling that are currently impractical.

Arrays of arrays for high-throughput gene expression profiling.

Gene expression profiling using DNA arrays is rapidly becoming an essential tool for research and drug discovery and may soon play a central role in disease diagnosis. Although it is possible to make significant discoveries on the basis of a relatively small number of expression profiles, the full potential of this technology is best realized through more extensive collections of expression measurements. The generation of large numbers of expression profiles can be a time-consuming and labor-intensive process with current one-at-a-time technology. We have developed the ability to obtain expression profiles in a highly parallel yet straightforward format using glass wafers that contain 49 individual high-density oligonucleotide arrays. This arrays of arrays concept is generalizable and can be adapted readily to other types of arrays, including spotted cDNA microarrays. It is also scalable for use with hundreds and even thousands of smaller arrays on a single piece of glass. Using the arrays of arrays approach and parallel preparation of hybridization samples in 96-well plates, we were able to determine the patterns of gene expression in 27 ovarian carcinomas and 4 normal ovarian tissue samples, along with a number of control samples, in a single experiment. This new approach significantly increases the ease, efficiency, and throughput of microarray-based experiments and makes possible new applications of expression profiling that are currently impractical.

Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer.

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in part because of the lack of effective early detection methods. Although alterations of several genes, such as c-erb-B2, c-myc, and p53, have been identified in a significant fraction of ovarian cancers, none of these mutations are diagnostic of malignancy or predictive of tumor behavior over time. Here, we used oligonucleotide microarrays with probe sets complementary to >6,000 human genes to identify genes whose expression correlated with epithelial ovarian cancer. We extended current microarray technology by simultaneously hybridizing ovarian RNA samples in a highly parallel manner to a single glass wafer containing 49 individual oligonucleotide arrays separated by gaskets within a custom-built chamber (termed "array-of-arrays"). Hierarchical clustering of the expression data revealed distinct groups of samples. Normal tissues were readily distinguished from tumor tissues, and tumors could be further subdivided into major groupings that correlated both to histological and clinical observations, as well as cell type-specific gene expression. A metric was devised to identify genes whose expression could be considered ideal for molecular determination of epithelial ovarian malignancies. The list of genes generated by this method was highly enriched for known markers of several epithelial malignancies, including ovarian cancer. This study demonstrates the rapidity with which large amounts of expression data can be generated. The results highlight important molecular features of human ovarian cancer and identify new genes as candidate molecular markers.