Expression profiles of 290 ESTs mapped to chromosome 3 in human epithelial ovarian cancer cell lines using DNA expression oligonucleotide microarrays

Subtype specific elevated expression of hyaluronidase-1 (HYAL-1) in epithelial ovarian cancer

Background

Epithelial ovarian cancer (EOC) is morphologically heterogeneous being classified as serous, endometrioid, clear cell, or mucinous. Molecular genetic analysis has suggested a role for tumor suppressor genes located at chromosome 3p in serous EOC pathogenesis. Our objective was to evaluate the expression of HYAL1, located at chromosome 3p21.3, in these EOC subtypes, and to investigate its correlation with the expression of steroid hormone receptors.

Methodology/Principal Findings

We determined the mRNA expression of HYAL1, estrogen receptor (ER)-α, ERβ and progesterone receptor (PR) in EOC tumor samples and cell lines using quantitative RT-PCR. We also examined the expression of these genes in a publicly available microarray dataset. HYAL-1 enzyme activity was measured in EOC cell lines and in plasma samples from patients. We found that HYAL1 mRNA expression was elevated in clear cell and mucinous EOC tissue samples, but not in serous and endometrioid samples, normal ovaries or benign tumors. Similar results were obtained by two different techniques and with tissue sample cohorts from two independent institutions. Concordantly, HYAL1 mRNA levels and enzymatic activity were elevated only in EOC cell lines derived from clear cell and mucinous subtypes. We also showed that HYAL1 mRNA was inversely correlated to that of ERα specifically in clear cell and mucinous EOCs. Additionally, ectopic expression of ERα in a clear cell EOC cell line (ER- and PR-negative) induced 50% reduction of HYAL1 mRNA expression, supporting a role of ERα in HYAL1 gene regulation. Significantly, HYAL-1 activity was also high in the plasma of patients with these EOC subtypes.

Conclusions/Significance

This is the first report showing high HYAL-1 levels in EOC and demonstrating HYAL1 gene repression by ERα. Our results identify Hyaluronidase-1 as a potential target/biomarker for clear cell and mucinous EOCs and especially in tumors with low ERα levels.

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.

Biomarker discovery in ovarian cancer

Ovarian cancer is a leading cause of gynecologic cancer death among women. Tumors diagnosed early (in stage I) have a cure rate approaching 90%. However, because specific symptoms and screening tools are lacking, most ovarian cancers are very advanced when finally diagnosed. CA125 expression and pelvic ultrasonography are of limited efficacy in screening, and the search for new, complementary ovarian cancer biomarkers continues. New technology and research techniques have allowed the identification of over 100 possible tumor markers, many of which are still being evaluated for clinical relevance and several of which have entered clinical trials. Here, we review the methods of biomarker discovery, address the significance and functions of newly identified ovarian cancer tumor markers, and provide further insight into the future of ovarian cancer biomarkers.

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.

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.

Biomarker discovery in epithelial ovarian cancer by genomic approaches

Ovarian cancer is the fifth most common form of cancer in women in the United States. It is a complex disease composed of different histological grades and histological types. Most of epithelial ovarian cancer cases are detected at an advanced stage. Patients usually respond to primary treatment with surgery and chemotherapy. However, the disease usually recurs and is ultimately fatal. So far, a satisfactory screening procedure and regime to treat the recurrence disease are not available. High-throughput genomic analyses have the potential to change the detection and the treatment of ovarian neoplasms. They can help diagnose subtypes of disease and predict patient survival. New diagnostic and prognostic markers for ovarian cancer are emerging. One day, profiling may influence treatment decisions, informing both which patients should receive chemotherapy and what type of chemotherapeutic agents should be employed. As greater numbers of tumor samples are analyzed, the power of these profiling studies will increase, raising the possibility that novel molecular targets and less toxic therapies will be identified. These powerful techniques hold the potential to unravel the genetic origins of ovarian cancer. Hopefully, this will translate into earlier diagnosis and better patient outcome from disease.

Transfer of chromosome 3 fragments suppresses tumorigenicity of an ovarian cancer cell line monoallelic for chromosome 3p

Multiple chromosome 3p tumor suppressor genes (TSG) have been proposed in the pathogenesis of ovarian cancer based on complex patterns of 3p loss. To attain functional evidence in support of TSGs and identify candidate regions, we applied a chromosome transfer method involving cell fusions of the tumorigenic OV90 human ovarian cancer cell line, monoallelic for 3p and an irradiated mouse cell line containing a human chromosome 3 in order to derive OV90 hybrids containing normal 3p fragments. The resulting hybrids showed complete or incomplete suppression of tumorigenicity in nude mouse xenograft assays, and varied in their ability to form colonies in soft agarose and three-dimensional spheroids in a manner consistent with alteration of their in vivo tumorigenic phenotypes. Expression microarray analysis identified a set of common differentially expressed genes, such as SPARC, DAB2 and VEGF, some of which have been shown implicated in ovarian cancer. Genotyping assays revealed that they harbored normal 3p fragments, some of which overlapped candidate TSG regions (3p25-p26, 3p24 and 3p14-pcen) identified previously in loss of heterozygosity analyses of ovarian cancers. However, only the 3p12-pcen region was acquired in common by all hybrids where expression microarray analysis identified differentially expressed genes. The correlation of 3p12-pcen transfer and tumor suppression with a concerted re-programming of the cellular transcriptome suggest that the putative TSG may have affected key underlying events in ovarian cancer.

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.

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.

Analysis of Molecular Aberrations in Ovarian Cancer Allows Novel Target Identification

The completion of the Human Genome Project and recent advances in functional genomic, proteomic, and high-throughput screening methodologies have provided powerful tools for determining the mechanisms of human diseases, including complex polygenic diseases such as ovarian cancer. These developments may eventually lead to individualized molecular medicine, which is the treatment of patients based on the underlying genetic defects in their tumours and their own genetic makeup. A plethora of novel therapeutic agents that act on specific molecular targets defined by cancer genetics are under development. There is thus a great deal of interest in determining how specific genes and proteins function in cancers, in order to further the understanding of cancer initiation and progression; to aid in identifying biomarkers, therapeutic targets, and determinants of drug responsiveness; and to progress the development of novel antitumour agents.

Patterns of expression of chromosome 17 genes in primary cultures of normal ovarian surface epithelia and epithelial ovarian cancer cell lines

Oligonucleotide microarray analysis was applied to assess the expression profile of 332 probe sets representing 308 genes or expressed sequence tags (ESTs) that map to chromosome 17 in order to address epigenetic events that result in alterations in gene expression in epithelial ovarian cancer (EOC). Expression profiles were generated from 12 primary cultures derived from normal ovarian surface epithelium (NOSE) and four long-term cultures (TOV-81D, TOV-112D, TOV-21G and OV-90) derived from EOCs that have been previously characterized and shown to mimic features of the tumoral cells from which they were derived. The expression values of all 332 probe sets is highly correlated across the 12 NOSEs (89% correlation coefficients >0.90). In two-way comparisons, differential patterns of gene expression were observed for 157 probe sets for which the expression value of at least one EOC cell line fell outside the limits of the range of expression of the 12 NOSEs. When compared to NOSEs, four genes displayed similar differential patterns of gene expression across all four EOC cell lines, and 26 genes displayed similar differential patterns of gene expression across the three EOC cell lines (TOV-112D, TOV-21G and OV-90) representing tumoral cells derived from the most aggressive disease. A total of 17 genes displayed differential patterns of gene expression greater than threefold in at least one EOC cell line in comparison to NOSE, and three genes were differentially expressed greater than threefold across all aggressive cell lines. The analysis of a selected number of genes by RT-PCR revealed patterns of gene expression comparable to those observed by microarray analysis in the majority of samples tested. Comparison of expression profiles of differentially expressed genes identified by microarray analysis in two-way comparisons of the EOC cell lines and the NOSEs with published reports revealed 10 genes previously implicated in ovarian tumorigenesis and 18 in tumorigenesis of other types of cancer. The differential pattern of gene expression of genes that map to both the p and q arm of chromosome 17 is consistent with the hypothesis that a number of genes that map to this chromosome are implicated in the etiology of ovarian cancer.

New technologies for the identification of markers for early detection of ovarian cancer

PURPOSE OF REVIEW

The ovarian cancer screening regimens in current use fail to identify disease at an early curable stage.

RECENT FINDINGS

New technologies are emerging that facilitate the identification of diagnostic tumor markers. In particular, high throughput techniques using microarray technology and proteomic screening have enriched the study of protein expression by ovarian cancer cells.

SUMMARY

Further evaluation of serum proteins associated with ovarian cancer holds promise for the development of a tumor marker panel that could aid in the early diagnosis of ovarian cancer, and save lives.