Microarray analysis of gene expression mirrors the biology of an ovarian cancer model

Identification of New Molecular Biomarkers in Ovarian Cancer Using the Gene Expression Profile

Ovarian cancer is a common cause of death among women worldwide. The current diagnostic and prognostic procedures available for the treatment of ovarian cancer are either not specific or are very expensive. Gene expression profiling has proved to be a very effective tool in the exploration of new molecular markers in patients with ovarian cancer, although the link between such markers and patient survival and clinical outcomes is still elusive. We are looking for genes that may function in the development and progression of ovarian cancer. The aim of our study was to evaluate the expression of selected suppressor genes (ATM, BRCA1, BRCA2), proto-oncogenes (KRAS, c-JUN, c-FOS), pro-apoptotic genes (NOXA, PUMA), genes related to chromatin remodeling (MEN1), and genes related to carcinogenesis (NOD2, CHEK2, EGFR). Tissue samples from 30 normal ovaries and 60 ovarian carcinoma tumors were provided for analysis of the gene and protein expression. Gene expression analysis was performed using the real-time PCR method. The protein concentrations from tissue homogenates were determined using the ELISA technique according to the manufacturers’ protocols. An increase in the expression level of mRNA and protein in women with ovarian cancer was observed for KRAS, c-FOS, PUMA, and EGFR. No significant changes in the transcriptional levels we observed for BRCA1, BRCA2, NOD2, or CHEK2. In conclusion, we suggest that KRAS, NOXA, PUMA, c-FOS, and c-JUN may be associated with poor prognosis in ovarian cancer.

Hindsight: Review of Preclinical Disease Models for the Development of New Treatments for Uveal Melanoma

The molecular, histopathological, genomic and transcriptomic characteristics of uveal melanoma (UM) have identified four molecular subgroups with different clinical outcomes. Despite the improvements in UM classification and biological pathology, current treatments do not reduce the occurrence of metastasis. The development of effective adjuvant and metastatic therapies for UM has been slow and extremely limited. Preclinical models that closely resemble the molecular and genetic UM subgroups are essential for translating molecular findings into improved clinical treatment. In this review, we provide a retrospective view of the existing preclinical models used to study UM, and give an overview of their strengths and limitations. We review targeted therapy clinical trial data to evaluate the gap in the translation of preclinical findings to human studies. Reflecting on the current high attrition rates of clinical trials for UM, preclinical models that effectively recapitulate the human in vivo situation and/or accurately reflect the subtype classifications would enhance the translational impact of experimental data and have crucial implications for the advancement of personalised medicine.

Bruton's tyrosine kinase (Btk) inhibitor ibrutinib suppresses stem-like traits in ovarian cancer

According to a Prognoscan database, upregulation of Bruton's tyrosine kinase (Btk) is associated with low overall survival in ovarian cancer patients. We found that spheroids-forming ovarian cancer cell, which highly expressed cancer stem-like cell (CSC) markers and Btk, were cisplatin resistant. We next treated CSCs and non-CSCs by a combination of ibrutinib and cisplatin. We found that chemoresistance was dependent on Btk and JAK2/STAT3, which maintained CSC by inducing Sox-2 and prosurvival genes. We suggest that addition of ibrutinib to cisplatin may improve treatment outcome in ovarian cancer.

Highly and moderately aggressive mouse ovarian cancer cell lines exhibit differential gene expression

Patients with advanced epithelial ovarian cancer often experience disease recurrence after standard therapies, a critical factor in determining their five-year survival rate. Recent reports indicated that long-term or short-term survival is associated with varied gene expression of cancer cells. Thus, identification of novel prognostic biomarkers should be considered. Since the mouse genome is similar to the human genome, we explored potential prognostic biomarkers using two groups of mouse ovarian cancer cell lines (group 1: IG-10, IG-10pw, and IG-10pw/agar; group 2: IG-10 clones 2, 3, and 11) which display highly and moderately aggressive phenotypes in vivo. Mice injected with these cell lines have different survival time and rates, capacities of tumor, and ascites formations, reflecting different prognostic potentials. Using an Affymetrix Mouse Genome 430 2.0 Array, a total of 181 genes were differentially expressed (P < 0.01) by at least twofold between two groups of the cell lines. Of the 181 genes, 109 and 72 genes were overexpressed in highly and moderately aggressive cell lines, respectively. Analysis of the 109 and 72 genes using Ingenuity Pathway Analysis (IPA) tool revealed two cancer-related gene networks. One was associated with the highly aggressive cell lines and affiliated with MYC gene, and another was associated with the moderately aggressive cell lines and affiliated with the androgen receptor (AR). Finally, the gene enrichment analysis indicated that the overexpressed 89 genes (out of 109 genes) in highly aggressive cell lines had a function annotation in the David database. The cancer-relevant significant gene ontology (GO) terms included Cell cycle, DNA metabolic process, and Programmed cell death. None of the genes from a set of the 72 genes overexpressed in the moderately aggressive cell lines had a function annotation in the David database. Our results suggested that the overexpressed MYC and 109 gene set represented highly aggressive ovarian cancer potential biomarkers while overexpressed AR and 72 gene set represented moderately aggressive ovarian cancer potential biomarkers. Based on our knowledge, the current study is first time to report the potential biomarkers relevant to different aggressive ovarian cancer. These potential biomarkers provide important information for investigating human ovarian cancer prognosis.

Anti-metastatic action of FAK inhibitor OXA-11 in combination with VEGFR-2 signaling blockade in pancreatic neuroendocrine tumors

The present study sought to determine the anti-tumor effects of OXA-11, a potent, novel small-molecule amino pyrimidine inhibitor (1.2 pM biochemical IC(50)) of focal adhesion kinase (FAK). In studies of cancer cell lines, OXA-11 inhibited FAK phosphorylation at phospho-tyrosine 397 with a mechanistic IC(50) of 1 nM in TOV21G tumor cells, which translated into functional suppression of proliferation in 3-dimensional culture with an EC(50) of 9 nM. Studies of OXA-11 activity in TOV21G tumor-cell xenografts in mice revealed a pharmacodynamic EC(50) of 1.8 nM, indicative of mechanistic inhibition of pFAK [Y397] in these tumors. OXA-11 inhibited TOV21G tumor growth in a dose-dependent manner and also potentiated effects of cisplatin on tumor cell proliferation and apoptosis in vitro and on tumor growth in mice. Studies of pancreatic neuroendocrine tumors in RIP-Tag2 transgenic mice revealed OXA-11 suppression of pFAK [Y397] and pFAK [Y861] in tumors and liver. OXA-11 given daily from age 14 to 17 weeks reduced tumor vascularity, invasion, and when given together with the anti-VEGFR-2 antibody DC101 reduced the incidence, abundance, and size of liver metastases. Liver micrometastases were found in 100 % of mice treated with vehicle, 84 % of mice treated with OXA-11, and 79 % of mice treated with DC101 (19-24 mice per group). In contrast, liver micrometastases were found in only 52 % of 21 mice treated with OXA-11 plus DC101, and those present were significantly smaller and less numerous. Together, these findings indicate that OXA-11 is a potent and selective inhibitor of FAK phosphorylation in vitro and in vivo. OXA-11 slows tumor growth, potentiates the anti-tumor actions of cisplatin and--when combined with VEGFR-2 blockade--reduces metastasis of pancreatic neuroendocrine tumors in RIP-Tag2 mice.

Derivation and characterization of matched cell lines from primary and recurrent serous ovarian cancer

Background

Cell line models have proven to be effective tools to investigate a variety of ovarian cancer features. Due to the limited number of cell lines, particularly of the serous subtype, the heterogeneity of the disease, and the lack of cell lines that model disease progression, there is a need to further develop cell line resources available for research. This study describes nine cell lines derived from three ovarian cancer cases that were established at initial diagnosis and at subsequent relapse after chemotherapy.

Methods

The cell lines from three women diagnosed with high-grade serous ovarian cancer (1369, 2295 and 3133) were derived from solid tumor (TOV) and ascites (OV), at specific time points at diagnosis and relapse (R). Primary treatment was a combination of paclitaxel/carboplatin (1369, 3133), or cisplatin/topotecan (2295). Second line treatment included doxorubicin, gemcitabine and topotecan. In addition to molecular characterization (p53, HER2), the cell lines were characterized based on cell growth characteristics including spheroid growth, migration potential, and anchorage independence. The in vivo tumorigenicity potential of the cell lines was measured. Response to paclitaxel and carboplatin was assessed using a clonogenic assay.

Results

All cell lines had either a nonsense or missense TP53 mutations. The ability to form compact spheroids or aggregates was observed in six of nine cell lines. Limited ability for migration and anchorage independence was observed. The OV3133(R) cell line, formed tumors at subcutaneous sites in SCID mice. Based on IC₅₀ values and dose response curves, there was clear evidence of acquired resistance to carboplatin for TOV2295(R) and OV2295(R2) cell lines.

Conclusion

The study identified nine new high-grade serous ovarian cancer cell lines, derived before and after chemotherapy that provides a unique resource for investigating the evolution of this common histopathological subtype of ovarian cancer.

Pivotal Role of AKAP12 in the Regulation of Cellular Adhesion Dynamics: Control of Cytoskeletal Architecture, Cell Migration, and Mitogenic Signaling

Cellular dynamics are controlled by key signaling molecules such as cAMP-dependent protein kinase (PKA) and protein kinase C (PKC). AKAP12/SSeCKS/Gravin (AKAP12) is a scaffold protein for PKA and PKC which controls actin-cytoskeleton reorganization in a spatiotemporal manner. AKAP12 also acts as a tumor suppressor which regulates cell-cycle progression and inhibits Src-mediated oncogenic signaling and cytoskeletal pathways. Reexpression of AKAP12 causes cell flattening, reorganization of the actin cytoskeleton, and the production of normalized focal adhesion structures. Downregulation of AKAP12 induces the formation of thickened, longitudinal stress fibers and the proliferation of adhesion complexes. AKAP12-null mouse embryonic fibroblasts exhibit hyperactivation of PKC, premature cellular senescence, and defects in cytokinesis, relating to the loss of PKC scaffolding activity by AKAP12. AKAP12-null mice exhibit increased cell senescence and increased susceptibility to carcinogen-induced oncogenesis. The paper describes the regulatory and scaffolding functions of AKAP12 and how it regulates cell adhesion, signaling, and oncogenic suppression.

Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples

Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort.

Emerging Roles for SSeCKS/Gravin/AKAP12 in the Control of Cell Proliferation, Cancer Malignancy, and Barriergenesis

Emerging data suggest that SSeCKS/Gravin/AKAP12 ("AKAP12"), originally identified as an autoantigen in cases of myasthenia gravis, controls multiple biological processes through its ability to scaffold key signaling proteins such as protein kinase (PK) C and A, calmodulin, cyclins, phosphoinositides, "long" β-1,4 galactosyltransferase (GalTase) isoform, Src, as well as the actin cytoskeleton in a spatiotemporal manner. Specialized functions attributed to AKAP12 include the suppression of cancer malignancy, especially aspects of metastatic progression, regulation of blood-brain and blood-retina barrier formation, and resensitization of β2-adrenergic pain receptors. Recent data identify a direct role for AKAP12 in cytokinesis completion, further suggesting a function as a negative regulator of cell senescence. The current review will discuss the emerging knowledge base of AKAP12-related biological roles and how the factors that affect AKAP12 expression or that interact with AKAP12 at the protein level control cancer progression and blood-tissue barrier formation.

Trophoblast invasion: assessment of cellular models using gene expression signatures

Invasive, extravillous trophoblasts (EVT) of the human placenta are critically involved in successful pregnancy outcome since they remodel the uterine spiral arteries to increase blood flow and oxygen delivery to the placenta and the developing fetus. To gain more insights into their biological role different primary cell culture models are commonly utilised. However, access to early placental tissue may be limited and primary trophoblasts rapidly cease proliferation in vitro impairing genetic manipulation. Hence, trophoblastic cell lines have been widely used as surrogates to study EVT function. Although the cell lines share some molecular markers with their primary counterpart, it is unknown to what extent they recapitulate the invasive phenotype of EVT. Therefore, we here report the first thorough GeneChip analyses of SGHPL-5, HTR-8/SVneo, BeWo, JEG-3 and the novel ACH-3P trophoblast cells in comparison to previously analysed primary villous cytotrophoblasts (CTBs) and extravillous trophoblasts (EVTs). Analyses of approximately 14,000 commonly expressed genes revealed that EVTs most closely resemble CTBs with considerable differences to the group of choriocarcinoma cells (JEG-3, BeWo, ACH-3P) and the group of SV40 Large T Antigen-selected cell types (SGHPL-5, HTR-8/SVneo). Similarly, analyses of 912 genes discriminating EVT from CTB, or 370 EVT-specific genes did not unravel a particular cell line with close similarity to any of the primary cell types, although molecular signatures common to EVT and each group of cell lines could be identified. Considering the diversity of mRNA expression patterns it is suggested that molecular studies in trophoblast cell lines require verification of the critical steps in an appropriate primary model system.

Effect of ovarian cancer ascites on cell migration and gene expression in an epithelial ovarian cancer in vitro model

A third of patients with epithelial ovarian cancer (EOC) present ascites. The cellular fraction of ascites often consists of EOC cells, lymphocytes, and mesothelial cells, whereas the acellular fraction contains cytokines and angiogenic factors. Clinically, the presence of ascites correlates with intraperitoneal and retroperitoneal tumor spread. We have used OV-90, a tumorigenic EOC cell line derived from the malignant ascites of a chemonaive ovarian cancer patient, as a model to assess the effect of ascites on migration potential using an in vitro wound-healing assay. A recent report of an invasion assay described the effect of ascites on the invasion potential of the OV-90 cell line. Ascites sampled from 31 ovarian cancer patients were tested and compared with either 5% fetal bovine serum or no serum for their nonstimulatory or stimulatory effect on the migration potential of the OV-90 cell line. A supervised analysis of data generated by the Affymetrix HG-U133A GeneChip identified differentially expressed genes from OV-90 cells exposed to ascites that had either a nonstimulatory or a stimulatory effect on migration. Ten genes (IRS2, CTSD, NRAS, MLXIP, HMGCR, LAMP1, ETS2, NID1, SMARCD1, and CD44) were upregulated in OV-90 cells exposed to ascites, allowing a nonstimulatory effect on cell migration. These findings were validated by quantitative polymerase chain reaction. In addition, the gene expression of IRS2 and MLXIP each correlated with prognosis when their expression was assessed in an independent set of primary cultures established from ovarian ascites. This study revealed novel candidates that may play a role in ovarian cancer cell migration.

Characterization of the molecular differences between ovarian endometrioid carcinoma and ovarian serous carcinoma

The histopathological diagnosis of high-grade endometrioid and serous carcinoma of the ovary is poorly reproducible under the current morphology based classification system, especially for anaplastic, high-grade tumours. The transcription factor Wilms' tumour-1 (WT1) is differentially expressed among the gynaecological epithelia from which epithelial ovarian cancers (EOCs) are believed to originate. In EOCs, WT1 protein is observed in the majority of serous carcinomas and in up to 30% of endometrioid carcinomas. It is unclear whether the latter is a reflection of the actual incidence of WT1 protein expression in endometrioid carcinomas, or whether a significant number of high-grade serous carcinomas have been misclassified as endometrioid carcinoma. Several genetic aberrations are reported to occur in EOCs. These include mutation of the TP53 gene, aberrant activation of beta-catenin signalling and loss of PTEN protein expression, among others. It is unclear whether these aberrations are histotype-specific. The aim of this study was to better define the molecular characteristics of serous and endometrioid carcinomas in an attempt to address the problems with the current histopathological classification methods. Gene expression profiles were analysed to identify reproducible gene expression phenotypes for endometrioid and serous carcinomas. Tissue microarrays (TMA) were used to assess the incidence of TP53, beta-catenin and PTEN aberrations in order to correlate their occurrence with WT1 as an immunohistochemistry based biomarker of serous histotype. It was found that nuclear WT1 protein expression can identify misclassified high-grade endometrioid carcinomas and these tumours should be reassigned to serous histotype. Although low-grade endometrioid carcinomas rarely progress to high-grade carcinomas, a combined WT1-negative, TP53-positive immunophenotype may identify an uncommon high-grade subtype of ovarian endometrioid carcinoma. GEO database: array data accession number GSE6008.

Characterization of the 3p12.3-pcen region associated with tumor suppression in a novel ovarian cancer cell line model genetically modified by chromosome 3 fragment transfer

The genetic analysis of nontumorigenic radiation hybrids generated by transfer of chromosome 3 fragments into the tumorigenic OV-90 ovarian cancer cell line identified the 3p12.3-pcen region as a candidate tumor suppressor gene (TSG) locus. In the present study, polymorphic microsatellite repeat analysis of the hybrids further defined the 3p12.3-pcen interval to a 16.1 Mb common region containing 12 known or hypothetical genes: 3ptel-ROBO2-ROBO1-GBE1-CADM2-VGLL3-CHMP2B-POU1F1-HTR1F-CGGBP1-ZNF654-C3orf38-EPHA3-3pcen. Seven of these genes, ROBO1, GBE1, VGLL3, CHMP2B, CGGBP1, ZNF654, and C3orf38, exhibited gene expression in the hybrids, placing them as top TSG candidates for further analysis. The expression of all but one (VGLL3) of these genes was also detected in the parental OV-90 cell line. Mutations were not identified in a comparative sequence analysis of the predicted protein coding regions of these candidates in OV-90 and donor normal chromosome 3 contig. However, the nondeleterious sequence variants identified in the transcribed regions distinguished parent of origin alleles for ROBO1, VGLL3, CHMP2B, and CGGBP1 and cDNA sequencing of the hybrids revealed biallelic expression of these genes. Interestingly, underexpression of VGLL3 and ZNF654 were observed in malignant ovarian tumor samples as compared with primary cultures of normal ovarian surface epithelial cells or benign ovarian tumors, and this occurred regardless of allelic content of 3p12.3-pcen. The results taken together suggest that dysregulation of VGLL3 and/or ZNF654 expression may have affected pathways important in ovarian tumorigenesis which was offset by the transfer of chromosome 3 fragments in OV-90, a cell line hemizygous for 3p.

Comparative proteomic study of two closely related ovarian endometrioid adenocarcinoma cell lines using cIEF fractionation and pathway analysis

The proteomic profiles from two distinct ovarian endometrioid tumor-derived cell lines, (MDAH-2774 and TOV-112D) each with different morphological characteristics and genetic mutations, have been studied. Characterization of the differential global protein expression between these two cell lines has important implications for the understanding of the pathogenesis of ovarian endometrioid carcinoma. In this comparative proteomic study, extensive fractionation of peptides generated from whole-cell trypsin digestion was achieved by coupling cIEF in the first-dimensional separation with capillary LC (RP-HPLC) in the second dimensional separation. Online analysis was performed using tandem mass spectra acquired by a linear ion trap mass spectrometer from triplicate runs. A total of 1749 and 1955 proteins with protein probability above 0.95 were identified from MDAH-2774 and TOV-112D after filtering through Peptide Prophet/Protein Prophet software. Differentially expressed proteins were further investigated by ingenuity pathway analysis (IPA) to reveal the association with important biological functions. Canonical pathway analysis using IPA demonstrates that important signaling pathways are highly associated with one of these two cell lines versus the other, such as the PI3K/AKT pathway, which is found to be significantly predominant in MDAH-2774 but not in TOV-112D. Also, protein network analysis using IPA highlights p53 as a central hub relating to other proteins from the connectivity map. These results illustrate the utility of high throughput proteomics methods using large-scale proteome profiling combined with bioinformatics tools to identify differential signaling pathways, thus contributing to the understanding of mechanisms of deregulation in neoplastic cells.

The chemiluminescence based Ziplex automated workstation focus array reproduces ovarian cancer Affymetrix GeneChip expression profiles

Background

As gene expression signatures may serve as biomarkers, there is a need to develop technologies based on mRNA expression patterns that are adaptable for translational research. Xceed Molecular has recently developed a Ziplex^® technology, that can assay for gene expression of a discrete number of genes as a focused array. The present study has evaluated the reproducibility of the Ziplex system as applied to ovarian cancer research of genes shown to exhibit distinct expression profiles initially assessed by Affymetrix GeneChip^® analyses.

Methods

The new chemiluminescence-based Ziplex^® gene expression array technology was evaluated for the expression of 93 genes selected based on their Affymetrix GeneChip^® profiles as applied to ovarian cancer research. Probe design was based on the Affymetrix target sequence that favors the 3' UTR of transcripts in order to maximize reproducibility across platforms. Gene expression analysis was performed using the Ziplex Automated Workstation. Statistical analyses were performed to evaluate reproducibility of both the magnitude of expression and differences between normal and tumor samples by correlation analyses, fold change differences and statistical significance testing.

Results

Expressions of 82 of 93 (88.2%) genes were highly correlated (p < 0.01) in a comparison of the two platforms. Overall, 75 of 93 (80.6%) genes exhibited consistent results in normal versus tumor tissue comparisons for both platforms (p < 0.001). The fold change differences were concordant for 87 of 93 (94%) genes, where there was agreement between the platforms regarding statistical significance for 71 (76%) of 87 genes. There was a strong agreement between the two platforms as shown by comparisons of log₂ fold differences of gene expression between tumor versus normal samples (R = 0.93) and by Bland-Altman analysis, where greater than 90% of expression values fell within the 95% limits of agreement.

Conclusion

Overall concordance of gene expression patterns based on correlations, statistical significance between tumor and normal ovary data, and fold changes was consistent between the Ziplex and Affymetrix platforms. The reproducibility and ease-of-use of the technology suggests that the Ziplex array is a suitable platform for translational research.

Reprogramming of the transcriptome in a novel chromosome 3 transfer tumor suppressor ovarian cancer cell line model affected molecular networks that are characteristic of ovarian cancer

Tumor suppression as a consequence of the transfer of chromosome 3p fragments was previously observed in a novel epithelial ovarian cancer (EOC) OV-90 cell line model harboring loss of 3p. Microarray analysis revealed that tumor suppression was associated with a modified transcriptome. To investigate the relevance of the altered transcriptome, the differentially expressed genes identified by Affymetrix analysis in the 3p transfer studies, were integrated with a comparative microarray analysis of normal ovarian surface epithelial (NOSE) cells and malignant ovarian (TOV) cancers. Data from 219 significantly differentially expressed genes exhibited patterns in the direction predicted by the analysis of 3p transfer study. The 30 genes with the highest statistically significant differences (P < 1 x 10(-8)) in expression were found consistently differentially expressed between NOSE and TOV samples. The investigation of these genes in benign serous ovarian tumors and EOC cell lines also exhibited predictable expression patterns. Within the group of differentially expressed genes were SPARC, DAB2, CP, EVI1, ELF3, and EHD2, known to play a role in ovarian cancer, genes implicated in other cancers, such as GREM1 and GLIPR1, as well as genes not previously reported in a cancer context such as AKAP2 and ATAD4. A number of the differentially expressed genes are implicated in the TGF-beta signaling pathway. These findings suggest that the reprogramming of the transcriptome that occurred as a consequence of the chromosome 3 transfer and tumor suppression affected molecular networks that are characteristic of ovarian carcinogenesis thus validating our novel ovarian cancer cell line model.

Analysis of gene expression in early-stage ovarian cancer

PURPOSE

Gene expression profile was analyzed in 68 stage I and 15 borderline ovarian cancers to determine if different clinical features of stage I ovarian cancer such as histotype, grade, and survival are related to differential gene expression.

EXPERIMENTAL DESIGN

Tumors were obtained directly at surgery and immediately frozen in liquid nitrogen until analysis. Glass arrays containing 16,000 genes were used in a dual-color assay labeling protocol.

RESULTS

Unsupervised analysis identified eight major patient partitions, one of which was statistically associated to overall survival, grading, and histotype and another with grading and histotype. Supervised analysis allowed detection of gene profiles clearly associated to histotype or to degree of differentiation. No difference was found between borderline and grade 1 tumors. As to recurrence, a subset of genes able to differentiate relapsers from nonrelapsers was identified. Among these, cyclin E and minichromosome maintenance protein 5 were found particularly relevant, as their expression was inversely correlated to progression-free survival (P = 0.00033 and 0.017, respectively).

CONCLUSIONS

Specific molecular signatures define different histotypes and prognosis of stage I ovarian cancer. Mucinous and clear cells histotypes can be distinguished from the others regardless of tumor grade. Cyclin E and minichromosome maintenance protein 5, whose expression was found previously to be related to a bad prognosis of advanced ovarian cancer, appear to be potential prognostic markers in stage I ovarian cancer too, independent of other pathologic and clinical variables.

A snapshot of microarray-generated gene expression signatures associated with ovarian carcinoma

It was hypothesized that analysis of global gene expression in ovarian carcinoma can identify dysregulated genes that can serve as molecular markers and provide further insight into carcinogenesis and provide the basis for development of new diagnostic tools as well as new targeted therapy protocols. By applying bioinformatics tools for screening of biomedical databases, a gene expression profile databank, specific for ovarian carcinoma, was constructed with utilizable data sets published in 28 studies that applied different array technology platforms. The data sets were divided into four compartments: (i) genes associated with carcinogenesis: in 14 studies, 1881 genes were extracted, 75 genes were identified in more than one study, and only 4 genes (PRKCBP1, SPON1, TACSTD1, and PTPRM) were identified in three studies. (ii) Genes associated with histologic subtypes: in four studies, 463 genes could be identified, but none of them was identified in more than a single study. (iii) Genes associated with therapy response: in seven studies, 606 genes were identified from which 38 were differentially regulated in at least two studies, 3 genes (TMSB4X, GRN, and TJP1) in three studies, and 1 gene (IFITM1) in four studies. (iv) Genes associated with prognosis and progression: 254 genes were found in seven studies. From these genes, merely three were identified in at least two different studies. This snapshot of available gene expression data not only provides independently described potential diagnostic and therapeutic targets for ovarian carcinoma but also emphasizes the drawbacks of the current state of global gene expression analyses in ovarian cancer.

Influence of monolayer, spheroid, and tumor growth conditions on chromosome 3 gene expression in tumorigenic epithelial ovarian cancer cell lines

Background

Expression microarray analyses of epithelial ovarian cancer (EOC) cell lines may be exploited to elucidate genetic and epigenetic events important in this disease. A possible variable is the influence of growth conditions on discerning candidates. The present study examined the influence of growth conditions on the expression of chromosome 3 genes in the tumorigenic EOC cell lines, OV-90, TOV-21G and TOV-112D using Affymetrix GeneChip^® HG-U133A expression microarray analysis.

Methods

Chromosome 3 gene expression profiles (n = 1147 probe sets, representing 735 genes) were extracted from U133A expression microarray analyses of the EOC cell lines OV-90, TOV-21G and TOV-112D that were grown as monolayers, spheroids or nude mouse xenografts and monolayers derived from these tumors. Hierarchical cluster analysis was performed to compare chromosome 3 transcriptome patterns of each growth condition. Differentially expressed genes were identified and characterized by two-way comparative analyses of fold-differences in gene expression between monolayer cultures and each of the other growth conditions, and between the maximum and minimum values of expression of all growth conditions for each EOC cell line.

Results

An overall high degree of similarity (> 90%) in gene expression was observed when expression values of alternative growth conditions were compared within each EOC cell line group. Two-way comparative analysis of each EOC cell line grown in an alternative condition relative to the monolayer culture showed that overall less than 15% of probe sets exhibited at least a 3-fold difference in expression profile. Less than 23% of probe sets exhibited greater than 3-fold differences in gene expression in comparisons of the maximum and minimum value of expression of all growth conditions within each EOC cell line group. The majority of these differences were less than 5-fold. There were 17 genes in common which were differentially expressed in all EOC cell lines. However, the patterns of expression of these genes were not necessarily the same for each growth condition when one cell line was compared with another.

Conclusion

The various alternative in vivo and in vitro growth conditions of tumorigenic EOC cell lines appeared to modestly influence the global chromosome 3 transcriptome supporting the notion that the in vitro cell line models are a viable option for testing gene candidates.

Transcriptome analysis of serous ovarian cancers identifies differentially expressed chromosome 3 genes

Cytogenetic, molecular genetic and functional analyses have implicated chromosome 3 genes in epithelial ovarian cancers (EOC). To further characterize their contribution to EOC, the Affymetrix U133A GeneChip(R) was used to perform transcriptome analyses of chromosome 3 genes in primary cultures of normal ovarian surface epithelial (NOSE) cells (n = 14), malignant serous epithelial ovarian tumors (TOV) (n = 17), and four EOC cell lines (TOV-81D, TOV-112D, TOV-21G, and OV-90). A two-way comparative analysis of 735 known genes and expressed sequences identified 278 differentially expressed genes, where 43 genes were differentially expressed in at least 50% of the TOV samples. Three genes, RIS1 (at 3p21.31), GBE1 (at 3p12.2), and HEG1 (at 3q21.2), were similarly underexpressed in all TOV samples. Deregulation of the expression of these genes was not associated with loss of heterozygosity (LOH) of the genetic loci harboring them. LOH analysis of the RIS1, GBE1, and HEG1 loci was observed at frequencies of 14.3%, 13.7%, and 9.2%, respectively, in a series of 66 malignant TOV samples of the serous subtype. Reduced expression levels of RIS1, GBE1, and HEG1 were observed only in the tumorigenic EOC cell lines (TOV-21G, TOV-112D, and OV-90) and did not correlate with LOH. These results combined suggest that RIS1, GBE1, and HEG1, unlike classical tumor suppressor genes, are not likely to be primary targets of inactivation. This study provides a comprehensive analysis of chromosome 3 gene expression in NOSE and in EOC samples and identifies chromosome 3 gene candidates for further study.

Characterization of ovarian cancer ascites on cell invasion, proliferation, spheroid formation, and gene expression in an in vitro model of epithelial ovarian cancer

At least one third of all cases of epithelial ovarian cancer are associated with the production of ascites, although its effect on tumor cell microenvironment remains poorly understood. This study addresses the effect of the heterologous acellular fraction of ovarian cancer-derived ascites on a cell line (OV-90) derived from the chemotherapy-naïve ovarian cancer patient. Ascites were assayed for their effect on cell invasion, growth, and spheroid formation. When compared to either no serum or 5% serum, ascites fell into one of two categories: stimulatory or inhibitory. RNA from OV-90 cells exposed to selected ascites were arrayed on an Affymetrix HG-U133A GeneChip. A supervised analysis identified a number of differentially expressed genes and quantitative polymerase chain reaction validation based on OV-90 cells exposed to 54 independent ascites demonstrated that stimulatory ascites affected the expression of ISGF3G, TRIB1, MKP1, RGS4, PLEC1, and MOSPD1 genes. In addition, TRIB1 expression was shown to independently correlate with prognosis when its expression was ascertained in an independent set of primary cultures established from ovarian ascites. The data support the validity of the strategy to uncover molecular events that are associated with tumor cell behavior and highlight the impact of ascites on the cellular and molecular parameters of ovarian cancer.

Construction of a chromosome 17 transcriptome in serous ovarian cancer identifies differentially expressed genes

Cytogenetic, molecular genetic, and functional analyses have implicated chromosome 17 genes in epithelial ovarian cancer (EOC). To further characterize the contribution of chromosome 17 genes in EOC, the Affymetrix U133A GeneChip was used to perform transcriptome analyses of 15 primary cultures of normal ovarian surface epithelial (NOSE) cells and 17 malignant ovarian tumor (TOV) samples of the serous histopathologic subtype. A two-way comparative analysis of 776 known genes and expressed sequences identified 253 genes that exhibited at least a threefold difference in expression in at least one TOV sample compared to the mean of NOSE samples. Within this data set, 99 of the 253 (39.1%) genes exhibited similar patterns of expression across all tested samples, suggesting a high degree of concordance in the chromosome 17 transcriptome. This observation was supported by hierarchical clustering analysis that segregated the TOV and NOSE samples into two separate groups. There were 77 genes that were differentially expressed in at least 50% of the TOV samples. Five genes (AdoRA(2B)at 17p12, CCL2 at 17q12, ACLY at 17q21.2, WIPI1 at 17q24.2, and SLC16A3 at 17q25.3) were significantly (P < 5.13E-11) differentially expressed at least threefold in all serous TOV samples, and all five genes were underexpressed in these TOV samples as compared to the NOSE samples. Interestingly, several of these differentially expressed genes have been previously associated with response to hypoxia.

Ganoderma lucidum polysaccharides in human monocytic leukemia cells: from gene expression to network construction

BACKGROUND

Ganoderma lucidum has been widely used as a herbal medicine for promoting health and longevity in China and other Asian countries. Polysaccharide extracts from Ganoderma lucidum have been reported to exhibit immuno-modulating and anti-tumor activities. In previous studies, F3, the active component of the polysaccharide extract, was found to activate various cytokines such as IL-1, IL-6, IL-12, and TNF-alpha. This gave rise to our investigation on how F3 stimulates immuno-modulating or anti-tumor effects in human leukemia THP-1 cells.

RESULTS

Here, we integrated time-course DNA microarray analysis, quantitative PCR assays, and bioinformatics methods to study the F3-induced effects in THP-1 cells. Significantly disturbed pathways induced by F3 were identified with statistical analysis on microarray data. The apoptosis induction through the DR3 and DR4/5 death receptors was found to be one of the most significant pathways and play a key role in THP-1 cells after F3 treatment. Based on time-course gene expression measurements of the identified pathway, we reconstructed a plausible regulatory network of the involved genes using reverse-engineering computational approach.

CONCLUSION

Our results showed that F3 may induce death receptor ligands to initiate signaling via receptor oligomerization, recruitment of specialized adaptor proteins and activation of caspase cascades.

Molecular description of a 3D in vitro model for the study of epithelial ovarian cancer (EOC)

Epithelial ovarian cancer (EOC) cell lines are useful tools for the molecular and biological characterization of ovarian cancer. The use of an in vitro multidimensional (3-D) culture model recapitulates some of the growth conditions encountered by tumor cells in vivo. Here we describe a molecular comparison of spheroid based 3D EOC models versus monolayer cultures and xenografts using cell lines from malignant ovarian tumors (TOV-21G and TOV-112D) and ascites (OV-90) previously established and characterized in our laboratory. Gene expression analyses of the three models were performed using the Affymetrix HG-U133A high density DNA array. Cluster analysis identified a set of genes that stratified expression profiles from the EOC cell lines grown as spheroids and xenografts from that of monolayer cultures. The gene expression analysis results were validated by Q-PCR analyses on an independent set of RNAs. Differential expression observed for the S100A6 gene between the monolayer, spheroid cultures and xenografts was confirmed at the protein level by immunohistochemistry. The analysis was extended to various ovarian tumor tissues using an EOC tissue array. This result represents an example of a gene that, if studied in vitro, is more representative of the in vivo disease in a 3D model rather than the monolayer culture. Identification of genes in spheroid models that mimic the in vivo tumor gene expression patterns may allow a better understanding of the community effect observed in human disease that is determined by direct or indirect interactions of cells with their environment or other surrounding cells.

Comparative proteome analysis of human epithelial ovarian cancer

Background

Epithelial ovarian cancer is a devastating disease associated with low survival prognosis mainly because of the lack of early detection markers and the asymptomatic nature of the cancer until late stage. Using two complementary proteomics approaches, a differential protein expression profile was carried out between low and highly transformed epithelial ovarian cancer cell lines which realistically mimic the phenotypic changes observed during evolution of a tumour metastasis. This investigation was aimed at a better understanding of the molecular mechanisms underlying differentiation, proliferation and neoplastic progression of ovarian cancer.

Results

The quantitative profiling of epithelial ovarian cancer model cell lines TOV-81D and TOV-112D generated using iTRAQ analysis and two-dimensional electrophoresis coupled to liquid chromatography tandem mass spectrometry revealed some proteins with altered expression levels. Several of these proteins have been the object of interest in cancer research but others were unrecognized as differentially expressed in a context of ovarian cancer. Among these, series of proteins involved in transcriptional activity, cellular metabolism, cell adhesion or motility and cytoskeleton organization were identified, suggesting their possible role in the emergence of oncogenic pathways leading to aggressive cellular behavior.

Conclusion

The differential protein expression profile generated by the two proteomics approaches combined to complementary characterizations studies will open the way to more exhaustive and systematic representation of the disease and will provide valuable information that may be helpful to uncover the molecular mechanisms related to epithelial ovarian cancer.

The role of gene expression profiling in the clinical management of ovarian cancer

Several studies have addressed the clinical value of gene expression profiling in the field of ovarian cancer. This paper reviews the current status of knowledge that can be derived from such studies. Gene expression profiles can be used to reveal sets of genes that can distinguish normal ovarian tissue from invasive ovarian carcinomas. Independent validation of these sets may result in the identification of (a set of) markers valuable for the detection in an early stage. Microarray analysis has shown that different histological subtypes of ovarian cancer might be partly reflected by a different aetiology through the deregulation and activation of different pathways. In addition, this heterogeneity could therefore also lead to different tumour behaviours. Worldwide, the combination of paclitaxel and platinum chemotherapy has been incorporated in the standard protocol for the management of patients with advanced stage ovarian cancer, although the outcome in individual patients is uncertain. Gene expression profiling was found to be a prognostic tool with respect to chemosensitivity and had a predictive performance of 78-86%. With increasing numbers of data from published reports, access to these data for the reproducibility of its results and pooling becomes more and more important and will possibly lead to more individualisation of therapy.

Establishment of three human breast epithelial cell lines derived from carriers of the 999del5 BRCA2 Icelandic founder mutation

Germ line mutations in BRCA1 and BRCA2 account for a large proportion of inherited breast and ovarian cancer. Both genes are involved in DNA repair by homologous recombination and are thought to play a vital role in maintaining genomic stability. A major drawback for long-term functional studies of BRCA in general and BRCA2 in particular has been a lack of representative human breast epithelial cell lines. In the present study, we have established three cell lines from two patients harboring the 999del5 germ line founder mutation in the BRCA2 gene. Primary cultures were established from cellular outgrowth of explanted tissue and subsequently transfected with a retroviral construct containing the HPV-16 E6 and E7 oncogenes. Paired cancer-derived and normal-derived cell lines were established from one patient referred to as BRCA2-999del5-2T and BRCA2-999del5-2N, respectively. In addition, one cell line was derived from cancer-associated normal tissue from another patient referred to as BRCA2-999del5-1N. All three cell lines showed characteristics of breast epithelial cells as evidenced by expression of breast epithelial specific cytokeratins. Cytogenetic analysis showed marked chromosomal instability with tetraploidy and frequent telomeric associations. In conclusion, we have established three breast epithelial cell lines from two patients carrying the BRCA2 Icelandic 999del5 founder mutation. These cell lines form the basis for further studies on carcinogenesis and malignant progression of breast cancer on a defined genetic background.

Molecular prognostic markers in ovarian cancer: toward patient-tailored therapy

In ovarian cancer the ceiling seems to be reached with chemotherapeutic drugs. Therefore a paradigm shift is needed. Instead of treating all patients according to standard guidelines, individualized molecular targeted treatment should be aimed for. This means that molecular profiles of the distinct ovarian cancer subtypes should be established. Until recently, most studies trying to identify molecular targets were single-marker studies. The prognostic role of key components of apoptotic and prosurvival pathways such as p53, EGFR, and HER2 has been extensively studied because resistance to chemotherapy is often caused by failure of tumor cells to go into apoptosis. However, it is more than likely that different ovarian cancer subtypes with extensive molecular heterogeneity exist. Therefore, exploration of the potential of specific tumor-targeted therapy, based on expression of a prognostic tumor profile, may be of interest. Recently, new profiling techniques, such as DNA and protein microarrays, have enabled high-throughput screening of tumors. In this review an overview of the current status of prognostic marker and molecular targeting research in ovarian cancer, including microarray studies, is presented.

Mutation and expression analysis of LZTS1 in ovarian cancer

LZTS1 has been shown to have tumour suppressor activities against prostate and breast cancer and is located within a region of frequent loss of heterozygosity (LOH) at 8p22 in ovarian cancer. We have analysed the expression of LZTS1 in ovarian cancer and found no evidence of loss of expression relative to normal ovarian surface epithelial cells. We have also analysed the coding region of the LZTS1 gene in 87 primary ovarian adenocarcinomas by DHPLC and detected a single silent somatic mutation. These data indicate that LZTS1 is not the target of LOH at 8p22 in ovarian cancer.

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

Emerging issues of the expression profiling technologies for the study of gynecologic cancer

Evaluation of the prognostic parameters of gynecologic cancer has shown their failure for classification according to the clinical behavior or the prediction of its outcome. This weakness has important implications on prognosis and treatment. The increasing understanding of the complexity of the human genome, coupled with the development of high throughput analysis techniques and bioinformatics tools, has changed our concepts on cancer biology, by shifting our targets to a global analysis of the transcriptome and the proteome, linking genes and their products into functional pathways. These approaches permit the documentation of expression patterns of thousands of genes within a cell. With the use of DNA microarray technology, it is feasible to identify signature patterns of expression in tumor samples that faithfully correlate with its biology, providing accurate prognosis for each cancer patient and thus a rational customized treatment. At this stage, there is a need for systematic studies for the validation of these novel approaches. In this review, we provide a basic background of the concept of the technology, highlight several emerging issues from their applications on gynecologic cancer, discuss a series of important themes and problems regarding their interpretation and relevance for the clinicians, and comment on future areas of research.

Discrimination between serous low malignant potential and invasive epithelial ovarian tumors using molecular profiling

Tumors of low malignant potential (LMP) represent 20% of epithelial ovarian cancers (EOCs) and are associated with a better prognosis than the invasive tumors (TOV). Defining the relationship between LMPs and TOVs remains an important goal towards understanding the molecular pathways that contribute to prognosis, as well as providing molecular markers, for these EOCs. To this end, DNA microarray analyses were performed either in a primary culture or a tumor tissue model system and selected candidate genes showing a distinctive expression profile between LMPs and TOVs were identified using a class prediction approach based on three statistical methods of analysis. Both model systems appear relevant as candidate genes identified by either model allowed the proper reclassification of samples as either LMPs or TOVs. Selected candidate genes (CAS, CCNE1, LGALS8, ITGbeta3, ATP1B1, FLIP, KRT7 and KRT19) were validated by real-time quantitative PCR analysis and show differential expression between LMPs and TOVs. Immunohistochemistry analyses showed that the two tumor classes were distinguishable by their expression of CAS, TNFR1A, FLIP, CKS1 and CCNE1. These results define signature patterns for gene expression of LMPs and TOVs and identify gene candidates that warrant further study to deepen our understanding of the biology of EOC.

Distinction between serous tumors of low malignant potential and serous carcinomas based on global mRNA expression profiling

OBJECTIVES

The molecular pathogenesis of ovarian serous tumors of low malignant potential (S-LMP) is not well understood, although the collective data suggest that they arise through molecular mechanisms distinct from those leading to conventional serous carcinomas (S-Ca). To further examine the molecular differences between these two diseases, we studied the gene expression pattern of ovarian S-LMP and S-Ca using high-density spotted cDNA and tissue microarrays.

METHODS

Total RNA from 23 ovarian S-LMP and S-Ca was analyzed on 43,200 spot cDNA microarrays and the differential expression of proteins encoded by differentially expressed genes was validated using tissue microarrays.

RESULTS

Unsupervised hierarchical clustering analysis of filtered data showed a complete separation between S-LMP and S-Ca, based predominantly on a small set of genes expressed at higher levels in S-LMP than in S-Ca. Many genes previously identified as up-regulated in ovarian carcinoma relative to normal ovarian tissue were expressed at even higher levels in S-LMP. These genes included mucin-1, mesothelin, HE4, PAX 8, and apolipoprotein J/clusterin. Immunohistochemical staining of tissue microarrays confirmed higher expression of selected proteins encoded by these genes in the S-LMP. Few genes were expressed at a higher level in S-Ca; these included E2F1, topoisomerase IIalpha, and cyclin E, with higher levels of cyclin E protein confirmed by immunohistochemistry.

CONCLUSIONS

S-LMP and S-Ca are distinguished at the molecular level by a relatively small gene set, suggesting the pathogenesis of S-LMP as well as S-Ca may involve molecular pathways that escape detection by global gene expression profiling. In order to obtain biologically and clinically relevant information about the mechanisms involved in ovarian carcinogenesis, future studies based on molecular profiles of ovarian cancer should include analyses of low malignant potential tumors. Inclusion of such tumors is also critical to the evaluation of the efficacy of potential new diagnostic and/or therapeutic biomarkers.

Human epididymis protein 4 (HE4) is a secreted glycoprotein that is overexpressed by serous and endometrioid ovarian carcinomas

Among the genes most commonly identified in gene expression profiles of epithelial ovarian carcinomas (EOC) is the gene for human epididymis protein 4 (HE4). To ascertain its clinical utility, we did a comprehensive assessment of HE4 protein expression in benign and malignant ovarian and nonovarian tissues by immunohistochemistry. In comparison with normal surface epithelium, which does not express HE4, we found that cortical inclusion cysts lined by metaplastic Mullerian epithelium abundantly express the protein. Its expression in tumors was restricted to certain histologic subtype: 93% of serous and 100% of endometrioid EOCs expressed HE4, whereas only 50% and 0% of clear cell carcinomas and mucinous tumors, respectively, were positive. Tissue microarrays revealed that the majority of nonovarian carcinomas do not express HE4, consistent with our observation that HE4 protein expression is highly restricted in normal tissue to the reproductive tracts and respiratory epithelium. HE4 is predicted to encode a secreted protein. Using reverse transcription-PCR, we identified ovarian cancer cell lines that endogenously overexpress HE4. Cultured medium from these cells revealed a secreted form of HE4 that is N-glycosylated. This observation is consistent with the recent report that HE4 circulates in the bloodstream of patients with EOC. Therefore, HE4 is a secreted glycoprotein that is overexpressed by serous and endometrioid EOCs. Its expression in cortical inclusion cysts suggests that formation of Mullerian epithelium is a prerequisite step in the development of some types of EOCs.

Identification of hemoglobin-alpha and -beta subunits as potential serum biomarkers for the diagnosis and prognosis of ovarian cancer

The development of new biomarkers for ovarian cancer is clearly necessary for the improved detection and monitoring of the disease. Surface enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF-MS) can be employed in the identification of differentially expressed proteins in cancer cells. The objective of this study was, then, to identify potential diagnostic serological biomarkers for ovarian cancer. We performed protein expression difference analyses of 45 serum samples using SELDI protein chip array. Forty-five sera obtained from ovarian cancer patients (n=35) and normal healthy females (n=10), were profiled on the surface of SELDI protein chip. The candidate biomarkers were purified by CM-Sepharose, and their N-terminal amino sequence was determined. The amounts of hemoglobin (Hb) in cancer patient's sera versus that of normal sera were measured by ELISA. Nine sera proteins that were found to be significantly differentially expressed (P<0.05) between the sera of ovarian cancer patients and that of normal healthy females were selected using the WCX2 array. The most distinctive polypeptide peaks detected in the ovarian cancer samples were at 15.1 and 15.8 kDa and these two peaks were identified as the hemoglobin-alpha (Hb-alpha) and -beta (Hb-beta) chain, respectively. ELISA indicated that the sensitivity for intact Hb level was 77% in sera obtained from ovarian cancer patients, as compared with normal healthy female sera. In conclusion, two ovarian cancer biomarker proteins were discovered and identified as Hb-alpha and Hb-beta. Hb levels were significantly different in ovarian cancer serum samples and those obtained from normal healthy females, as determined by ELISA. Additional studies are required to further validate Hb-alpha and Hb-beta biomarkers.

Loss of heterozygosity and transcriptome analyses of a 1.2 Mb candidate ovarian cancer tumor suppressor locus region at 17q25.1-q25.2

Loss of heterozygosity (LOH) analysis was performed in epithelial ovarian cancers (EOC) to further characterize a previously identified candidate tumor suppressor gene (TSG) region encompassing D17S801 at chromosomal region 17q25.1. LOH of at least one informative marker was observed for 100 (71%) of 140 malignant EOC samples in an analysis of 6 polymorphic markers (cen-D17S1839-D17S785-D17S1817-D17S801-D17S751-D17S722-tel). The combined LOH analysis revealed a 453 kilobase (Kb) minimal region of deletion (MRD) bounded by D17S1817 and D17S751. Human and mouse genome assemblies were used to resolve marker inconsistencies in the D17S1839-D17S722 interval and identify candidates. The region contains 32 known and strongly predicted genes, 9 of which overlap the MRD. The reference genomic sequences share nearly identical gene structures and the organization of the region is highly collinear. Although, the region does not show any large internal duplications, a 1.5 Kb inverted duplicated sequence of 87% nucleotide identity was observed in a 13 Kb region surrounding D17S801. Transcriptome analysis by Affymetrix GeneChip and reverse transcription (RT)-polymerase chain reaction (PCR) methods of 3 well characterized EOC cell lines and primary cultures of normal ovarian surface epithelial (NOSE) cells was performed with 32 candidates spanning D17S1839-D17S722 interval. RT-PCR analysis of 8 known or strongly predicted genes residing in the MRD in 10 EOC samples, that exhibited LOH of the MRD, identified FLJ22341 as a strong candidate TSG. The proximal repeat sequence of D17S801 occurs 8 Kb upstream of the putative promoter region of FLJ22341. RT-PCR analysis of the EOC samples and cell lines identified DKFZP434P0316 that maps proximal to the MRD, as a candidate. While Affymetrix technology was useful for initially eliminating less promising candidates, subsequent RT-PCR analysis of well-characterized EOC samples was essential to prioritize TSG candidates for further study.

Gene expression microarray analysis and genome databases facilitate the characterization of a chromosome 22 derived homogeneously staining region

Karyotype and fluorescence in situ hybridization (FISH) analyses previously identified a homogeneously staining region (HSR) derived from chromosome 22 in OV90, an epithelial ovarian cancer (EOC) cell line. Affymetrix expression microarrays in combination with the UniGene and Human Genome Browser databases were used to identify the candidate genes comprising the amplicon of the HSR, based on comparison of expression profiles of OV90, EOC cell lines lacking HSRs and primary cultures of normal ovarian surface epithelial (NOSE) cells. A group of probe sets displaying a minimum 3-fold overexpression with a high reliability score (P-call) in OV90 were identified which represented genes that mapped within a 1-2 Mb interval on chromosome 22. A large number of probe sets, some of which represent the same genes, displayed no evidence of overexpression and/or low reliability scores (A-call). An investigation of the probe set sequences with the Affymetrix and Sanger Institute Chromosome 22 Group databases revealed that some of the probe sets displaying discordant results for the same gene were complementary to intronic sequences and/or the antisense strand. Microarray results were validated by RT-PCR. Genomic analysis suggests that the HSR was derived from the amplification of a 1.1 Mb interval defined by the chromosomal map positions of ZNF74 and Hs.372662, at 22q11.21. The deduced amplicon is derived from a complex region of chromosome 22 that harbors low-copy repeats (LCRs). The amplicon contains 18 genes as likely targets for gene amplification. This study illustrates that large-scale expression microarray analysis in combination with genome databases is sufficient for deducing target genes associated with amplicons and stresses the importance of investigating probe set design before engaging in validation studies.

Gene expression profiling of advanced ovarian cancer: characterization of a molecular signature involving fibroblast growth factor 2

Epithelial ovarian cancer (EOC) is the gynecological disease with the highest death rate. We applied an automatic class discovery procedure based on gene expression profiling to stages III-IV tumors to search for molecular signatures associated with the biological properties and progression of EOC. Using a complementary DNA microarray containing 4451 cancer-related, sequence-verified features, we identified a subset of EOC characterized by the expression of numerous genes related to the extracellular matrix (ECM) and its remodeling, along with elements of the fibroblast growth factor 2 (FGF2) signaling pathway. A total of 10 genes were validated by quantitative real-time polymerase chain reaction, and coexpression of FGF2 and fibroblast growth factor receptor 4 in tumor cells was revealed by immunohistochemistry, confirming the reliability of gene expression by cDNA microarray. Since the functional relationships among these genes clearly suggested involvement of the identified molecular signature in processes related to epithelial-stromal interactions and/or epithelial-mesenchymal cellular plasticity, we applied supervised learning analysis on ovarian-derived cell lines showing distinct cellular phenotypes in culture. This procedure enabled construction of a gene classifier able to discriminate mesenchymal-like from epithelial-like cells. Genes overexpressed in mesenchymal-like cells proved to match the FGF2 signaling and ECM molecular signature, as identified by unsupervised class discovery on advanced tumor samples. In vitro functional analysis of the cell plasticity classifier was carried out using two isogenic and immortalized cell lines derived from ovarian surface epithelium and displaying mesenchymal and epithelial morphology, respectively. The results indicated the autocrine, but not intracrine stimulation of mesenchymal conversion and cohort/scatter migration of cells by FGF2, suggesting a central role for FGF2 signaling in the maintenance of cellular plasticity of ovary-derived cells throughout the carcinogenesis process. These findings raise mechanistic hypotheses on EOC pathogenesis and progression that might provide a rational underpinning for new therapeutic modalities.

Whole genome expression profiling of advance stage papillary serous ovarian cancer reveals activated pathways

Ovarian cancer is the most lethal type of gynecologic cancer in the Western world. The high case fatality rate is due in part because most ovarian cancer patients present with advanced stage disease which is essentially incurable. In order to obtain a whole genome assessment of aberrant gene expression in advanced ovarian cancer, we used oligonucleotide microarrays comprising over 40,000 features to profile 37 advanced stage papillary serous primary carcinomas. We identified 1191 genes that were significantly (P < 0.001) differentially regulated between the ovarian cancer specimens and normal ovarian surface epithelium. The microarray data were validated using real time RT-PCR on 14 randomly selected differentially regulated genes. The list of differentially expressed genes includes ones that are involved in cell growth, differentiation, adhesion, apoptosis and migration. In addition, numerous genes whose function remains to be elucidated were also identified. The microarray data were imported into PathwayAssist software to identify signaling pathways involved in ovarian cancer tumorigenesis. Based on our expression results, a signaling pathway associated with tumor cell migration, spread and invasion was identified as being activated in advanced ovarian cancer. The data generated in this study represent a comprehensive list of genes aberrantly expressed in serous papillary ovarian adenocarcinoma and may be useful for the identification of potentially new and novel markers and therapeutic targets for ovarian cancer.

Signature of a silent killer: expression profiling in epithelial ovarian cancer

With the sequencing of the human genome and the simultaneous development of high-throughput strategies, cancer biologists have entered an exciting new area for gene expression analysis, with the ability to glimpse higher order patterns of genetic and epigenetic alterations in complex diseases. Ovarian cancer biologists are rising to the challenge of applying these new technologies to this silent killer, with the eventual goal of improving the quality of life and long-term survival of patients. This review provides a summary of the disease, a description of available technologies and their application to the ovarian cancer problem, as well as a discussion on the challenges and opportunities related to DNA microarray expression profiling-based research, including downstream clinical applications.

Differential gene expression in ovarian carcinoma: identification of potential biomarkers

Ovarian cancer remains the fifth leading cause of cancer death for women in the United States. In this study, the gene expression of 20 ovarian carcinomas, 17 ovarian carcinomas metastatic to the omentum, and 50 normal ovaries was determined by Gene Logic Inc. using Affymetrix GeneChip HU_95 arrays containing approximately 12,000 known genes. Differences in gene expression were quantified as fold changes in gene expression in ovarian carcinomas compared to normal ovaries and ovarian carcinoma metastases. Genes up-regulated in ovarian carcinoma tissue samples compared to more than 300 other normal and diseased tissue samples were identified. Seven genes were selected for further screening by immunohistochemistry to determine the presence and localization of the proteins. These seven genes were: the beta8 integrin subunit, bone morphogenetic protein-7, claudin-4, collagen type IX alpha2, cellular retinoic acid binding protein-1, forkhead box J1, and S100 calcium-binding protein A1. Statistical analyses showed that the beta8 integrin subunit, claudin-4, and S100A1 provided the best distinction between ovarian carcinoma and normal ovary tissues, and may serve as the best candidate tumor markers among the seven genes studied. These results suggest that further exploration into other up-regulated genes may identify novel diagnostic, therapeutic, and/or prognostic biomarkers in ovarian carcinoma.

Chemosensitivity and radiosensitivity profiles of four new human epithelial ovarian cancer cell lines exhibiting genetic alterations in BRCA2, TGFbeta-RII, KRAS2, TP53 and/or CDNK2A

To address the cellular basis for the response to ovarian cancer treatment, we characterized the chemosensitivity and radiosensitivity of four human epithelial ovarian cancer cell lines that harbor different genetic alterations. The TOV-21G, TOV-81D, OV-90, and TOV-112D cell lines were derived from ovarian tumors (TOV) or ascites (OV) from chemotherapy- and radiotherapy-naive patients and were characterized by their mutation spectrum of BRCA2, TGFbeta-RII, KRAS2, TP53, and CDKN2A. Cells were monitored for survival following exposure at various concentrations to different cytotoxic agents including cisplatin, camptothecin or paclitaxel or to different doses of gamma-irradiation. At the lowest doses, the TGFbeta-RII-mutated and KRAS2-mutated cell line, TOV-21G, and the BRCA2-mutated cell line, TOV-81D, demonstrated a significantly higher sensitivity to cisplatin and gamma-irradiation than the TP53-mutated cell lines, TOV-112D and OV-90. At higher doses, differences between the TP53-mutated lines were observed with TOV-112D being less sensitive to cisplatin than OV-90 that also harbors a CDNK2A mutation. All cell lines were similarly sensitive to high doses of gamma-irradiation. In contrast, sensitivity to camptothecin or paclitaxel was not significantly different between all cell lines, irrespective of the mutation status of BRCA1, BRCA2, TGFbeta-RII, KRAS2, TP53, and CDKN2A. The observed responses to treatment are consistent with the current knowledge concerning BRCA2, TGFbeta-RII, KRAS2, TP53, and/or CDKN2A aberrant function.

Overexpression of the cell adhesion molecules DDR1, Claudin 3, and Ep-CAM in metaplastic ovarian epithelium and ovarian cancer

PURPOSE

A better understanding of the molecular pathways underlying the development of epithelial ovarian cancer (EOC) is critical to identify ovarian tumor markers for use in diagnostic or therapeutic applications. The aims of this study were to integrate the results from 14 transcript profiling studies of EOC to identify novel biomarkers and to examine their expression in early and late stages of the disease.

EXPERIMENTAL DESIGN

A database incorporating genes identified as being highly up-regulated in each study was constructed. Candidate tumor markers were selected from genes that overlapped between studies and by evidence of surface membrane or secreted expression. The expression patterns of three integral membrane proteins, discoidin domain receptor 1 (DDR1), claudin 3 (CLDN3), and epithelial cell adhesion molecule, all of which are involved in cell adhesion, were evaluated in a cohort of 158 primary EOC using immunohistochemistry.

RESULTS

We confirmed that these genes are highly overexpressed in all histological subtypes of EOC compared with normal ovarian surface epithelium, identifying DDR1 and CLDN3 as new biomarkers of EOC. Furthermore, we determined that these genes are also expressed in ovarian epithelial inclusion cysts, a site of metaplastic changes within the normal ovary, in borderline tumors and in low-grade and stage cancer. A trend toward an association between low CLDN3 expression and poor patient outcome was also observed.

CONCLUSIONS

These results suggest that up-regulation of DDR1, CLDN3, and epithelial cell adhesion molecule are early events in the development of EOC and have potential application in the early detection of disease.

Global analysis of HuR-regulated gene expression in colon cancer systems of reducing complexity

HuR, a protein that binds to target mRNAs and can enhance their stability and translation, is increasingly recognized as a pivotal regulator of gene expression during cell division and tumorigenesis. We sought to identify collections of HuR-regulated mRNAs in colon cancer cells by systematic, cDNA array-based assessment of gene expression in three systems of varying complexity. First, comparison of gene expression profiles among tumors with different HuR abundance revealed highly divergent gene expression patterns, and virtually no changes in previously reported HuR target mRNAs. Assessment of gene expression patterns in a second system of reduced complexity, cultured colon cancer cells expressing different HuR levels, rendered more conserved sets of HuR-regulated mRNAs. However, the definitive identification of direct HuR target mRNAs required a third system of still lower complexity, wherein HuR-RNA complexes immunoprecipitated from colon cancer cells were subject to cDNA array hybridization to elucidate the endogenous HuR-bound mRNAs. Comparison of the transcript sets identified in each system revealed a strikingly limited overlap in HuR-regulated mRNAs. The data derived from this systematic analysis of HuR-regulated genes highlight the value of low-complexity, biochemical characterization of protein-RNA interactions. More importantly, however, the data underscore the broad usefulness of integrated approaches comprising systems of low complexity (protein-nucleic acid) and high complexity (cells, tumors) to comprehensively elucidate the gene regulatory events that underlie biological processes.

Advantages and limitations of microarray technology in human cancer

Cancer is a highly variable disease with multiple heterogeneous genetic and epigenetic changes. Functional studies are essential to understanding the complexity and polymorphisms of cancer. The final deciphering of the complete human genome, together with the improvement of high throughput technologies, is causing a fundamental transformation in cancer research. Microarray is a new powerful tool for studying the molecular basis of interactions on a scale that is impossible using conventional analysis. This technique makes it possible to examine the expression of thousands of genes simultaneously. This technology promises to lead to improvements in developing rational approaches to therapy as well as to improvements in cancer diagnosis and prognosis, assuring its entry into clinical practice in specialist centers and hospitals within the next few years. Predicting who will develop cancer and how this disease will behave and respond to therapy after diagnosis will be one of the potential benefits of this technology within the next decade. In this review, we highlight some of the recent developments and results in microarray technology in cancer research, discuss potentially problematic areas associated with it, describe the eventual use of microarray technology for clinical applications and comment on future trends and issues.

Animal models of ovarian cancer

Ovarian cancer is the most lethal of all of the gynecological cancers and can arise from any cell type of the ovary, including germ cells, granulosa or stromal cells. However, the majority of ovarian cancers arise from the surface epithelium, a single layer of cells that covers the surface of the ovary. The lack of a reliable and specific method for the early detection of epithelial ovarian cancer results in diagnosis occurring most commonly at late clinical stages, when treatment is less effective. In part, the deficiency in diagnostic tools is due to the lack of markers for the detection of preneoplastic or early neoplastic changes in the epithelial cells, which reflects our rather poor understanding of this process. Animal models which accurately represent the cellular and molecular changes associated with the initiation and progression of human ovarian cancer have significant potential to facilitate the development of better methods for the early detection and treatment of ovarian cancer. This review describes some of the experimental animal models of ovarian tumorigenesis that have been reported, including those involving specific reproductive factors and environmental toxins. Consideration has also been given to the recent progress in modeling ovarian cancer using genetically engineered mice.