Identification of differentially expressed genes from ovarian cancer cells by MICROMAX cDNA microarray system

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.

Evaluation of local and circulating osteopontin in malignant and benign primary bone tumors

Purpose

The development of novel and efficient biomarkers for primary bone cancers is of grave importance.

Methods

The expression pattern of osteopontin (OPN) was investigated in the 153 patients with benign (n = 72) and malignant (n = 81) primary bone cancers. Both local and circulating OPN mRNA expression levels and their protein concentration in serum and tumor site were assessed using real-time qRT-PCR, ELISA, and immunohistochemistry techniques, respectively. As a control, 29 healthy individuals were considered. The number of 153 tumor tissue specimens and the 153 paired margins were taken on surgical resection from the patients. 153 blood samples were also drained from all participants, then peripheral blood mononuclear cells (PBMC) and sera were separated.

Results

The mean mRNA expression was significantly higher in all of the cancerous tissues than the paired margins and the PBMC of the patients than the controls. Consistently, the protein concentrations of OPN in serum and tumor tissues were significantly higher in the patients. Furthermore, the malignant cases had significantly elevated the mRNA levels and the protein compared to the benign cases. OPN could potentially differentiate the patients from the controls with 100% sensitivity and specificity in serum. Moreover, OPN could predict some of the malignant cases' clinicopathological features, including metastasis, recurrence, grade, and response to chemotherapy.

Conclusions

In conclusion, OPN might be involved in the pathogenesis of primary bone tumors and can be considered as a potential biomarker to bone cancer diagnosis.

Aziz NH, Teik CK, Shafiee MN, Kampan NC. New Predictive Biomarkers for Ovarian Cancer

Ovarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, with the development of chemoresistance in up to 75% of patients with subsequent poor treatment response and reduced survival. Therefore, there is a critical need to revisit existing, and identify potential biomarkers that could lead to the development of novel and more effective predictors for ovarian cancer diagnosis and prognosis. The capacity of these biomarkers to predict the existence, stages, and associated therapeutic efficacy of ovarian cancer would enable improvements in the early diagnosis and survival of ovarian cancer patients. This review not only highlights current evidence-based ovarian-cancer-specific prognostic and diagnostic biomarkers but also provides an update on various technologies and methods currently used to identify novel biomarkers of ovarian cancer.

Role of biomarkers for early detection of ovarian cancer recurrence

Ovarian cancer is frequently diagnosed at an advanced stage and a fraction of these patients fail to respond to primary therapy and relapses in 70% of cases. On account of the high recurrence probability and the poor outcomes after recurrence, there is an urgent need to predict progression as early as possible and thus found the strategies to detect and prevent a recurrence. Considering that biomarkers have contributed to the management of ovarian cancer by distinguishing benign and malignant pelvic masses and monitoring response to treatment, in this review, we aim to discuss the latest evidence reported in the literature about the use of biomarkers to detect OC recurrence. In detail, we summarized all the evidence of the most quoted biomarkers like HE4, osteopontin, mesothelin (MSLN), Folate receptor α (FOLR1), paraneoplastic antigens, miRNA, cancer stem cells (CSCs) and a combination of them to evaluate their role as prognostic biomarkers for ovarian cancer recurrence.

Regulation of G2/M Transition by Inhibition of WEE1 and PKMYT1 Kinases

In the cell cycle, there are two checkpoint arrests that allow cells to repair damaged DNA in order to maintain genomic integrity. Many cancer cells have defective G1 checkpoint mechanisms, thus depending on the G2 checkpoint far more than normal cells. G2 checkpoint abrogation is therefore a promising concept to preferably damage cancerous cells over normal cells. The main factor influencing the decision to enter mitosis is a complex composed of Cdk1 and cyclin B. Cdk1/CycB is regulated by various feedback mechanisms, in particular inhibitory phosphorylations at Thr14 and Tyr15 of Cdk1. In fact, Cdk1/CycB activity is restricted by the balance between WEE family kinases and Cdc25 phosphatases. The WEE kinase family consists of three proteins: WEE1, PKMYT1, and the less important WEE1B. WEE1 exclusively mediates phosphorylation at Tyr15, whereas PKMYT1 is dual-specific for Tyr15 as well as Thr14. Inhibition by a small molecule inhibitor is therefore proposed to be a promising option since WEE kinases bind Cdk1, altering equilibria and thus affecting G2/M transition.

Diagnostic values of osteopontin combined with CA125 for ovarian cancer: a meta-analysis

Osteopontin (OPN) is currently one of the most studied serum biomarkers of ovarian cancer (OC). This meta-analysis aims to ascertain whether OPN is a useful diagnostic biomarker for OC and determine the overall diagnostic accuracy of OPN measurement when combined with cancer antigen 125 (CA125). A systematic literature search was conducted in Cochrane Library, PubMed, EMBASE, CBM, and China National Knowledge Infrastructure databases. Information was independently extracted by two investigators. The Quality Assessment for Studies of Diagnostic Accuracy tool was applied to examine the quality of eligible studies, and a bivariate model was used to calculate the pooled estimates. We identified 17 and 10 studies that evaluated the role of OPN alone and OPN combined with CA125 in diagnosing ovarian tumor, respectively. The overall diagnostic sensitivity and specificity of OPN in OC were 0.766 (95% CI 0.685-0.831) and 0.897 (95% CI 0.849-0.931), correspondingly. When OPN was combined with CA125, the sensitivity and specificity were 0.871 (95% CI 0.788-0.924) and 0.881 (95% CI 0.837-0.914), respectively. OPN is a useful tumor biomarker in future screening tests of OC and can be a promising adjunct to CA125. Additional studies with multicenter trials and carefully selected controls are needed to further verify the results.

Gene Expression Patterns That Characterize Advanced Stage Serous Ovarian Cancers

OBJECTIVE

To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis.

METHODS

Using genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR).

RESULTS

Hierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively.

CONCLUSION

Global expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making.

Correlation between OPN gene polymorphisms and the risk of nasopharyngeal carcinoma

Previous studies suggest that osteopontin (OPN) levels are associated with the incidence and development of multiple types of cancer. This study analyzes the correlation between OPN gene variants and nasopharyngeal carcinoma (NPC). A total of 150 NPC patients and 150 healthy adults were enrolled and divided into NPC and control groups. In both groups, four OPN polymorphisms including rs1126772, rs4754, rs11728697 and rs9138 were quantitatively genotyped by SNaPshot SNP genotyping assay. Allele frequencies of four OPN polymorphisms were compared between two groups. No statistical significance was noted regarding genotype frequency of four OPN polymorphisms between male NPC and healthy subjects (all P > 0.05). Female subjects between two groups significantly differed in terms of genotype frequency of rs1172869 (P = 0.002). No statistical significance was observed in allele frequencies in each of four OPN polymorphisms between two groups (all P > 0.05). For NPC patients, the polymorphisms information content (PIC) ranged from 0.2961 to 0.3584 and 0.3047 to 0.3655 for normal controls. Additionally, rs11728697 had the highest effective number of alleles (Ne), expected heterozygosity (HE) and PIC in two groups. Female subjects in two groups significantly differed in the genotype frequency of rs1172869 while no statistical significance was noted for male counterparts. All subjects in the NPC and control groups had similar allele frequency. All the four OPN polymorphisms were moderately polymorphic. The mean NA, Ne, Ho, He and PIC of each OPN polymorphism in the control group were higher than those in the NPC group without a significant difference.

Molecular diagnostics: a new frontier in cancer prevention

The promise of molecular diagnostics for cancer prevention in terms of early detection rests on two premises: assays can be developed to measure proteins, DNA, RNA or metabolites that accurately and reproducibly detect incipient neoplasias; and that this early detection will eventually result in a decrease in morbidity and mortality and therefore benefit patients. Novel molecular technologies, including laser capture microdissection, time-of-flight mass spectrometry, DNA microarrays, tissue arrays, protein microarrays and antibody microarrays, are being developed to investigate the molecular differences between disease and normal cells and detect cancer-specific alterations in proteins, DNA and RNA in body fluids. Although literally hundreds of articles are published each year describing alterations in genes or proteins that are associated with cancer, very few result in useful molecular diagnostics for early cancer detection. Thus, there remains a critical need for new biomarkers for use in early detection and for assay methods that allow the translation of these biomarkers from the laboratory to the clinic.

LMX1A as a prognostic marker in ovarian mucinous cystadenocarcinoma

This study aimed to evaluate the relationship of LMX1A and osteopontin (OPN) expression with clinicopathologic parameters for the 4 most common ovarian surface epithelial carcinomas. Both biomarkers were investigated immunohistochemically using tissue microarrays of 249 specimens including 91 serous cystadenocarcinomas, 56 mucinous cystadenocarcinomas, 64 endometrioid adenocarcinomas, 26 clear cell carcinomas, and 12 normal ovarian tissues. All 4 carcinomas showed significant expression of LMX1A and OPN. In addition, higher immunostaining scores and percentage of cells stained for LMX1A in mucinous cystadenocarcinomas correlated with T stage, American Joint Committee on Cancer clinical stage, poorer tumor differentiation, and poorer survival rate. In serous cystadenocarcinoma, higher percentage of staining for OPN and higher intensity or immunostaining scores for LMX1A correlated with poorer tumor differentiation. Thus, the expression of LMX1A may be an independent prognostic risk factor in mucinous cystadenocarcinoma and a helpful marker in evaluating this tumor's aggressiveness.

Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer

Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding "angiogenesis signature" was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.

Differential hRad17 expression by histologic subtype of ovarian cancer

BACKGROUND

In the search for unique ovarian cancer biomarkers, ovarian specific cDNA microarray analysis identified hRad17, a cell cycle checkpoint protein, as over-expressed in ovarian cancer. The aim of this study was to validate this expression.

METHODS

Immunohistochemistry was performed on 72 serous, 19 endometrioid, 10 clear cell, and 6 mucinous ovarian cancers, 9 benign ovarian tumors, and 6 normal ovarian tissue sections using an anti-hRad17 antibody. Western blot analysis and quantitative PCR were performed using cell lysates and total RNA prepared from 17 ovarian cancer cell lines and 6 normal ovarian epithelial cell cultures (HOSE).

RESULTS

Antibody staining confirmed upregulation of hRad17 in 49.5% of ovarian cancer cases. Immunohistochemistry demonstrated that only 42% of serous and 47% of endometrioid subtypes showed overexpression compared to 80% of clear cell and 100% of mucinous cancers. Western blot confirmed overexpression of hRad17 in cancer cell lines compared to HOSE. Quantitative PCR demonstrated an upregulation of hRad17 RNA by 1.5-7 fold. hRad17 RNA expression differed by subtype.

CONCLUSIONS

hRad17 is over-expressed in ovarian cancer. This over-expression varies by subtype suggesting a role in the pathogenesis of these types. Functional studies are needed to determine the potential role of this protein in ovarian cancer.

Osteopontin-c splicing isoform contributes to ovarian cancer progression

Ovarian carcinoma is one of the most aggressive gynecological diseases and generally diagnosed at advanced stages. Osteopontin (OPN) is one of the proteins overexpressed in ovarian cancer and is involved in tumorigenesis and metastasis. Alternative splicing of OPN leads to 3 isoforms, OPNa, OPNb, and OPNc. However, the expression pattern and the roles of each of these isoforms have not been previously characterized in ovarian cancer. Herein, we have evaluated the expression profiling of OPN isoforms in ovarian tumor and nontumor samples and their putative roles in ovarian cancer biology using in vitro and in vivo functional assays. OPNa and OPNb were expressed both in tumor and nontumor ovarian samples, whereas OPNc was specifically expressed in ovarian tumor samples. The isoform OPNc significantly activated OvCar-3 cell proliferation, migration, invasion, anchorage-independent growth and tumor formation in vivo. Additionally, we have also shown that some of the OPNc-dependent protumorigenic roles are mediated by PI3K/Akt signaling pathway. OPNc stimulated immortalized ovarian epithelial IOSE cell proliferation, indicating a role for this isoform in ovarian cancer tumorigenesis. Functional assays using OPNc conditioned medium and an anti-OPNc antibody have shown that most cellular effects observed herein were promoted by the secreted OPNc. According to our data, OPNc-specific expression in ovarian tumor samples and its role on favoring different aspects of ovarian cancer progression suggest that secreted OPNc contributes to the physiopathology of ovarian cancer progression and tumorigenesis. Altogether, the data open possibilities of new therapeutic approaches for ovarian cancer that selectively down regulate OPNc, altering its properties favoring ovarian tumor progression.

Microarray-Based Gene Expression Studies in Ovarian Cancer

Background

DNA microarray technology is a powerful genomic tool that has the potential to elucidate the relationship between clinical features of cancers and their underlying biological alterations.

Methods

We performed a systemic search in PubMed and Medline databases for recently published articles. The search terms used included “genome-wide,” “microarrays,” “ovarian cancer,” “prognosis” “gene expression profiling,” “molecular marker,” and “molecular biomarker.”

Results

Genome-wide expression profiling using DNA microarray technology has enhanced our understanding of the genes that influence ovarian cancer development, histopathologic subtype, progression, response to therapy, and overall survival.

Conclusions

Gene expression profiling has demonstrated its utility in ovarian cancer research. It is hoped that with technologic, statistical, and bioinformatic advances, the reliability and reproducibility of this technique will increase, spawning clinical applications that may enhance our understanding of the disease and our ability to care for patients in the future.

Biomarkers in oncology research and treatment: early detection research network: a collaborative approach

Several important criteria are essential for the development of biomarkers in clinical oncology. First, the biomarkers should be easily measured using standardized and cost-efficient methods. Second, biomarkers should be easily attainable from clinical materials such as body fluids and cells. Third, biomarkers should have clearly defined cutoff values with high sensitivity and specificity. Lastly, the predictive value of biomarkers should be possible in strata as large as possible. Single biomarkers may not be able to meet all of these criteria, which necessitates the development of biomarker panels. High-throughput technologies will be necessary for measuring these biomarker sets and translation of these methods into a clinical setting will be necessary in order to employ these biomarkers in a healthcare setting. One of the most important aspects of biomarker development will be standardization and statistical evaluation of biomarker studies. Guidelines for biomarker studies need to be developed that will enable standardization to take place. The Early Detection Research Network has been in the forefront of this objective. Early detection of cancer through appropriately validated biomarkers will provide for decreased morbidity and mortality and allow for the development of new therapeutic tools targeted specifically toward eradication of these early malignancies, hopefully increasing the survival rate of patients diagnosed with early-stage cancer.

Elevated MAL expression is accompanied by promoter hypomethylation and platinum resistance in epithelial ovarian cancer

We previously found that the gene encoding the Myelin and Lymphocyte protein, MAL, was among the most highly expressed genes in serous ovarian cancers from short-term survivors (<3 years) relative to those of long-term survivors (>7 years). In the present study, we have found that this difference in expression is partially attributable to differences in DNA methylation at a specific region within the MAL promoter CpG island. While MAL was largely unmethylated at the transcription start site (Region 1; -48 to +73 bp) in primary serous ovarian cancers, methylation of an upstream region (Region 2; -452 to -266 bp) was inversely correlated with MAL transcription in the primary cancers (R = -0.463) and ovarian cancer cell lines (R = -0.444). Following treatment of the OVCA432 cell line with 5-azacytidine, methylation of Region 2 decreased from 73.3% to 34.7% (p = 0.007) while Region 1 was unaffected. This was accompanied by a 10-fold increase in MAL expression. Since MAL transcripts are elevated in tumors from short-term survivors, all of whom were treated with platinum-based therapy, MAL may have a role in cisplatin response. We therefore determined the 50% growth inhibitory dose of cisplatin in 30 ovarian cancer cell lines and compared this to MAL expression. MAL transcript levels were higher in the resistant ovarian cell lines (p = 0.04). MAL methylation status may therefore serve as a marker of platinum sensitivity while MAL protein may be a target for development of novel therapies aimed at enhancing sensitivity to platinum-based drugs in ovarian cancer.

Beyond CA125: the coming of age of ovarian cancer biomarkers. Are we there yet?

Ovarian cancer (OC) is the fourth leading cause of cancer deaths among women in the United States, despite its relatively low incidence of 50 per 100,000. Even though advances in therapy have been made, the OC fatality-to-case ratio remains exceedingly high, due to the lack of accurate tools to diagnose early-stage disease when cure is still possible. The most studied marker for OC, CA125, is only expressed by 50-60% of patients with early stage disease. Large efforts have been deployed to identify novel serum markers, yet no single marker has emerged as a serious competitor for CA125. Various groups are investing in combination approaches to increase the diagnostic value of existing markers, but many markers may still lie in under-explored areas of ovarian cancer biology, such as tumor vasculature environment and post-translational modifications (glycomics).

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.

Lipocalin2 expressions correlate significantly with tumor differentiation in epithelial ovarian cancer

We recently identified lipocalin2 (LCN2) as being upregulated in ovarian cancer cell lines. The purpose of this study was to validate LCN2 upregulation in ovarian cancers and to investigate its potential as a serum biomarker. We assayed LCN2 expression in ovarian cancers using real-time PCR and IHC. To evaluate the potential of LCN2 as a biomarker, we measured serum LCN2 levels in 54 ovarian cancers, 15 borderline and 53 benign ovarian tumors, and 90 healthy controls. SYBR green PCR and IHC showed LCN2 overexpression in ovarian cancers. LCN2 immunoreactivity was significantly associated with tumor differentiation (p=0.009), as well-differentiated tumors showed the highest LCN2 expression. Serum LCN2 level in ovarian cancer was significantly higher than in the other study groups (p<0.001), and in accordance with IHC results, it also correlated with tumor differentiation, with well-differentiated tumors having the highest value. The sensitivity and specificity of LCN2 in detecting ovarian cancer was 72.2% and 50.4%, respectively. By Cox univariate analysis, LCN2 positivity was an independent prognostic factor for overall survival (hazard ratio = 1.47, p=0.012). In conclusion, LCN2 expressions are upregulated and related to tumor differentiation in ovarian cancers and should be included in future research assessing potential biomarkers for ovarian cancer.

Ovarian cancer biomarkers: current options and future promise

As more effective, less toxic cancer drugs reach patients, the need for accurate and reliable cancer diagnostics and prognostics has become widely appreciated. Nowhere is this need more dire than in ovarian cancer; here most women are diagnosed late in disease progression. The ability to sensitively and specifically predict the presence of early disease and its status, stage, and associated therapeutic efficacy has the potential to revolutionize ovarian cancer detection and treatment. This article reviews current ovarian cancer diagnostics and prognostics and potential biomarkers that are being studied and validated. Some of the most recent molecular approaches being used to identify genes and proteins are presented, which may represent the next generation of ovarian cancer diagnostics and prognostics.

Conventional and Proteomic Technologies for the Detection of Early Stage Malignancies: Markers for Ovarian Cancer

Our understanding of the tumor microenvironment continues to evolve and allows for the identification of biomarkers that should detect the presence of early stage malignancies. Recent advances in computational analysis and biomedical technologies have come together to elucidate signatures associated with cancer and that are capable of identifying unique tumor-specific proteins. Within the tumor microenvironment, we continue to characterize the proteophysiology of the different steps associated with tumor progression. The urgent need for biomarkers accurately detecting early-stage epithelial ovarian cancer has prompted us, and others, to engage in a search for specific peptide signatures that may discriminate transformed cells from those of the normal ovarian microenvironment. This endeavor also provides new insights into the biology of the disease, which may not only be applicable to detection but may also help to initiate new therapies and optimize patient care.

Osteopontin promotes ovarian cancer progression and cell survival and increases HIF-1alpha expression through the PI3-K/Akt pathway

Osteopontin (OPN) is a secreted, integrin-binding matrix phosphorylated glycoprotein that is overexpressed in many advanced cancers. However, the functional mechanisms by which OPN contributes to the development of ovarian cancer are poorly understood. Here, we reveal that acquired expression of OPN by HO-8910 ovarian cancer cells greatly promoted the progression of ovarian cancer. OPN expression dramatically increased the colony formation of ovarian cancer cells in vitro and tumor growth in vivo. Under the stress induced by serum depletion or curcumin treatment, OPN expression promoted the survival of ovarian cells through preventing stress-induced apoptosis. At the molecular level, both endogenous and exogenous OPN expression activated the PI3-K/Akt survival pathway and dramatically decreased p53 expression under serum depletion. In addition, HIF-1alpha was induced in OPN-producing cells under normoxia. Furthermore, we also found that inhibition of the PI3-K/Akt pathway attenuated OPN-mediated HIF-1alpha up-regulation in ovarian cancer cells. Taken together, these results indicate that OPN can increase the survival of ovarian cancer cells under stress conditions in vitro and promote the late progression of ovarian cancer in vivo, and the survival-promoting functions of OPN are mediated through Akt activation and the induction of HIF-1alpha expression.

Gene-expression profiling in epithelial ovarian cancer

DNA-microarray technology has made it possible to simultaneously analyze the expression of thousands of genes in a small sample of tumor tissue. In epithelial ovarian cancer, gene-expression profiling has been used to provide prognostic information, to predict response to first-line platinum-based chemotherapy, and to discriminate between different histologic subtypes. Furthermore, DNA-microarray technology might permit identification of novel markers for early detection of disease and provide insights into the mechanisms of cancer growth and chemotherapy resistance. In this Review, we summarize the contributions of gene-expression profiling to the diagnosis and management of epithelial ovarian cancer and discuss ways in which this technique could become a useful tool in clinical management.

Early detection of ovarian cancer

Ovarian cancer is associated with an overall mortality of 75%, but can be cured in up to 90% of cases if diagnosed while still limited to the ovaries. Given the low prevalence of ovarian cancer in the general population, an effective screening strategy must not only have a high sensitivity for early-stage disease (>75%), but must also have a very high specificity (99.6%) to prompt no more than ten operations for each case of ovarian cancer diagnosed (positive predictive value [PPV] of 10%). Attempts to develop an effective screening strategy for ovarian cancer have utilized ultrasonography and serum tumor markers. Transvaginal sonography (TVS) and the serum marker CA125 have received the most attention to date. Used individually on a single occasion, neither of these approaches provides an adequate PPV and the cost of annual TVS is significant. Recent clinical trials have focused on serial monitoring of CA125 and the sequential use of a rising CA125 to prompt TVS in a limited number of women screened. Sequential monitoring of CA125 has significantly improved specificity of the assay in women over 50 years of age. The limited sensitivity of CA125 has, however, prompted a search for multiple serum markers that, in combination, would detect more than 90% of early-stage disease. Recent developments in genomic and proteomic research have identified a number of candidate biomarkers. Platforms have been developed that can assay more than 50 analytes in a few hundred microliters of serum. Panels of biomarkers have been discovered with high sensitivity and specificity for early-stage disease, but these require prospective validation. Several biomarkers have also been detected in urine, raising the possibility of a less expensive, more convenient screening test. Imaging techniques have been improved and mathematical methods developed that, in aggregate, promise to provide an effective screening strategy for ovarian cancer. In this review, we will assess the current status and describe future directions in ovarian cancer screening.

The role of osteopontin in tumor progression and metastasis in breast cancer

The use of cancer biomarkers to anticipate the outlines of disease has been an emerging issue, especially as cancer treatment has made such positive steps in the last few years. Progress in the development of consistent malignancy markers is imminent because advances in genomics and bioinformatics have allowed the examination of immense amounts of data. Osteopontin is a phosphorylated glycoprotein secreted by activated macrophages, leukocytes, and activated T lymphocytes, and is present in extracellular fluids, at sites of inflammation, and in the extracellular matrix of mineralized tissues. Several physiologic roles have been attributed to osteopontin, i.e., in inflammation and immune function, in mineralized tissues, in vascular tissue, and in kidney. Osteopontin interacts with a variety of cell surface receptors, including several integrins and CD44. Binding of osteopontin to these cell surface receptors stimulates cell adhesion, migration, and specific signaling functions. Overexpression of osteopontin has been found in a variety of cancers, including breast cancer, lung cancer, colorectal cancer, stomach cancer, ovarian cancer, and melanoma. Moreover, osteopontin is present in elevated levels in the blood and plasma of some patients with metastatic cancers. Therefore, suppression of the action of osteopontin may confer significant therapeutic activity, and several strategies for bringing about this suppression have been identified. This review looks at the recent advances in understanding the possible mechanisms by which osteopontin may contribute functionally to malignancy, particularly in breast cancer. Furthermore, the measurement of osteopontin in the blood or tumors of patients with cancer, as a way of providing valuable prognostic information, will be discussed based on emerging clinical data.

An apoptotic molecular network identified by microarray: on the TRAIL to new insights in epithelial ovarian cancer

BACKGROUND

In a previous microarray expression analysis, the authors identified candidate genes that were expressed differentially between ovarian tumors with low malignant potential and invasive serous epithelial ovarian tumors. Among them, the apoptosis-related candidate genes tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), caspase 8 (CASP8), FLICE-inhibitory protein (FLIP), and cytochrome C (CYC) were identified.

METHODS

For the current study, the authors conducted immunohistochemical analyses of a tissue array comprised of 235 serous tumors of different grades and stages to evaluate whether there was differential protein expression for these candidates and for the 4 death cell receptors of Trail: Dr4, Dr5, DcR1, and DcR2.

RESULTS

All proteins except DcR1 and DcR2 had significantly differential expression levels between grade 0 tumors (low malignant potential) and grade 2 and 3 tumors. Trail also showed differential expression between grade 0 tumors and grade 1 tumors. When all tumors were compared, the expression levels of Trail, Dr4, Dr5, DcR1, and Flip differed significantly between early-stage and advanced-stage disease. High Dr5 expression was associated with a poor prognosis in patients who had invasive tumors and in the subgroup of patients who had grade 3 tumors. Furthermore, the combinations of 2 proteins (Trail and Dr5, DcR2 and Cyc, Flip and Dr5, Flip and DcR2, DcR1 and Dr5 or Dr4 and Flip) revealed an association with patient prognosis.

CONCLUSIONS

The identification of new proteins in the initial diagnosis and prognosis of patients with epithelial ovarian cancer may lead to a better understanding of the disease, highlighting new potential therapeutic targets, and may be useful in patient management.

Molecular biomarkers for cancer detection in blood and bodily fluids

Cancer is a major and increasing public health problem worldwide. Traditionally, the diagnosis and staging of cancer, as well as the evaluation of response to therapy have been primarily based on morphology, with relatively few cancer biomarkers currently in use. Conventional biomarker studies have been focused on single genes or discrete pathways, but this approach has had limited success because of the complex and heterogeneous nature of many cancers. The completion of the human genome project and the development of new technologies have greatly facilitated the identification of biomarkers for assessment of cancer risk, early detection of primary cancers, monitoring cancer treatment, and detection of recurrence. This article reviews the various approaches used for development of such markers and describes markers of potential clinical interest in major types of cancer. Finally, we discuss the reasons why so few cancer biomarkers are currently available for clinical use.

An Integrated Genomic-Based Approach to Individualized Treatment of Patients With Advanced-Stage Ovarian Cancer

Purpose

The purpose of this study was to develop an integrated genomic-based approach to personalized treatment of patients with advanced-stage ovarian cancer. We have used gene expression profiles to identify patients likely to be resistant to primary platinum-based chemotherapy and also to identify alternate targeted therapeutic options for patients with de novo platinum-resistant disease.

Patients and Methods

A gene expression model that predicts response to platinum-based therapy was developed using a training set of 83 advanced-stage serous ovarian cancers and tested on a 36-sample external validation set. In parallel, expression signatures that define the status of oncogenic signaling pathways were evaluated in 119 primary ovarian cancers and 12 ovarian cancer cell lines. In an effort to increase chemotherapy sensitivity, pathways shown to be activated in platinum-resistant cancers were subject to targeted therapy in ovarian cancer cell lines.

Results

Gene expression profiles identified patients with ovarian cancer likely to be resistant to primary platinum-based chemotherapy with greater than 80% accuracy. In patients with platinum-resistant disease, we identified expression signatures consistent with activation of Src and Rb/E2F pathways, components of which were successfully targeted to increase response in ovarian cancer cell lines.

Conclusion

We have defined a strategy for treatment of patients with advanced-stage ovarian cancer that uses therapeutic stratification based on predictions of response to chemotherapy, coupled with prediction of oncogenic pathway deregulation, as a method to direct the use of targeted agents.

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.

High expression of insulin-like growth factor binding protein-2 messenger RNA in epithelial ovarian cancers produces elevated preoperative serum levels

The molecular etiology of epithelial ovarian cancer remains unclear. Using microarray expression analysis, we recently reported that expression of the insulin-like growth factor binding protein-2 (IGFBP-2) gene is elevated in advanced epithelial ovarian cancers. The aim of this study was to further delineate the role of IGFBP-2 in the pathoetiology of epithelial ovarian cancer and determine if elevated ovarian cancer IGFBP-2 gene expression is reflected in serum. Relative IGFBP-2 expression was measured using quantitative real-time polymerase chain reaction in 113 epithelial ovarian cancers and 6 normal ovarian surface epithelial samples. Preoperative serum IGFBP-2 levels were measured by radioimmunoassay in 84 women (42 ovarian cancers, 26 benign gynecological conditions, and 10 healthy female controls). Ovarian cancers demonstrated 38-fold higher mean IGFBP-2 expression than normal ovarian epithelium (P < 0.01). Serum IGFBP-2 levels were elevated in women with early- and advanced-stage ovarian cancer compared to controls and patients with benign gynecological conditions (P = 0.05 and P < 0.01, respectively). Epithelial ovarian cancers express high levels of IGFBP-2 relative to normal ovarian epithelium, and this is associated with elevated serum IGFBP-2 levels compared to both normal controls and patients with benign gynecological disease. Our findings provide further support that the insulin-like growth factor pathway plays a significant role in epithelial ovarian cancer pathogenesis. Further, IGFBP-2 may represent an additional serum biomarker with utility in detection and monitoring of epithelial ovarian cancer.

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.

Preoperative plasma osteopontin level as a biomarker complementary to carbohydrate antigen 125 in predicting ovarian cancer

AIM

New biomarkers other than carbohydrate antigen (CA) 125 are needed for the detection of ovarian cancer. Osteopontin (OPN) is one of the candidates identified by high-throughput complementary DNA microarray techniques. We evaluated the preoperative plasma OPN level as a diagnostic biomarker for ovarian cancer in comparison with CA125.

METHODS

Preoperative plasma OPN and CA125 levels were measured and compared in 32 patients with ovarian cancer, 34 patients with benign ovarian tumor, 30 patients with other gynecologic cancers and 31 healthy women. Preoperative plasma OPN levels were also assessed according to tumor stage, the volume of ascites and histological types. The sensitivity and specificity for predicting ovarian cancer was compared between OPN and CA125.

RESULTS

Preoperative plasma OPN levels were significantly higher in patients with ovarian cancer than in those with benign ovarian tumor, in other gynecologic patients or in healthy women. Stage IV ovarian cancer patients and ovarian cancer patients with ascites had higher plasma OPN levels than those without ascites and in a lower stage. There was no relation between OPN and the histological type. The sensitivity of preoperative plasma OPN in detecting ovarian cancer was 81.3% and almost reached that of CA125. The specificity was moderate. Sensitivity increased to 93.8% with the combination of CA125, compared to 84.4% with CA125 alone.

CONCLUSION

Preoperative OPN is a useful biomarker for predicting ovarian cancer. It is especially useful when used complementary to CA125. Larger studies of patients with ovarian cancer showing a low CA125 level or in early stages of ovarian cancer are needed.

Identification of overexpression and amplification of ABCF2 in clear cell ovarian adenocarcinomas by cDNA microarray analyses

PURPOSE

Patients with ovarian clear cell adenocarcinoma generally have a poor response to combination chemotherapy and have overall poorer prognosis than patients with other histologic types of ovarian cancer. Genetic changes in this group of cancer have not been thoroughly explored. Identification of these changes may provide us new therapeutic targets to treat this disease.

EXPERIMENTAL DESIGN

Genomic and expression array analyses were applied on 30 clear cell ovarian cancer cases and 19 serous cases using a 10,816-element cDNA microarray platform. Further validation and clinical correlation studies were done on differentially expressed genes that are related to chemoresistance.

RESULTS

Based on array analyses, 12 genes showed a significant increase in DNA and mRNA copy number and 5 genes showed a significant decrease in DNA and RNA copy number in clear cell tumors compared with those in the serous type. One of the genes was ABCF2, which belongs to the ATP-binding cassette gene superfamily and has been shown to amplify in other tumor types. Validation studies were done using real-time quantitative PCR and immunohistochemistry. The results showed significantly higher ABCF2 DNA and mRNA copy number and protein levels in clear cell cases compared with those in serous cases. Furthermore, in 20 clear cell cases with chemo-response data available, ABCF2 cytoplasmic staining was significantly higher in nonresponders than that in the responders (60.0% versus 28.5%; P = 0.0002).

CONCLUSIONS

These data suggest that ABCF2 protein may be a prognostic marker for ovarian clear cell ovarian adenocarcinoma.

Transcriptional response signature of human lymphoid cells to staphylococcal enterotoxin B

Two shock-inducing toxins that result in similar eventual outcome of disease were studied to determine host gene expression responses, for correlation of both similar and unique gene patterns. We initially used differential display (DD)-PCR and identified 859 cDNA fragments that were differentially expressed after 16 h of in vitro exposure of human peripheral blood mononuclear cells (PBMC) to staphylococcal enterotoxin B (SEB). Upon further examination using custom cDNA microarrays and RT-PCR analysis, we found unique set of genes to each toxin (SEB or lipopolysaccharide (LPS)), especially at early time periods. By 16 h, there was a convergence of some gene expression responses and many of those genes code for proteins such as proteinases, transcription factors, vascular tone regulators, and respiratory distress. In an attempt to replicate the findings in vivo, monkeys were challenged with SEB and the resultant gene expression responses indicated a pattern typical of SEB exposure when compared to LPS, with a similar outcome. We provide evidence that vastly diverse global gene analysis techniques used in unison can not only effectively identify pathogen-specific genomic markers and provide a solid foundation to mechanistic insights but also explain some of the toxin-related symptoms through gene functions.

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.

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.

Gene Expression Profiles Predict Early Relapse in Ovarian Cancer after Platinum-Paclitaxel Chemotherapy

PURPOSE

Women with advanced epithelial ovarian cancer are routinely treated with platinum-paclitaxel chemotherapy following cytoreductive surgery, yet only approximately 20% achieve long-term disease-free survival. We hypothesized that differences in gene expression before treatment could distinguish patients with short versus long time to recurrence after administration of platinum-paclitaxel combination chemotherapy.

EXPERIMENTAL DESIGN

To test this hypothesis, gene expression profiling of 79 primary surgically resected tumors from women with advanced-stage, high-grade epithelial ovarian cancer was done using cDNA microarrays containing 30,721 genes. Supervised learning algorithms were applied in an effort to develop a binary classifier that could discriminate women at risk for early (< or =21 months) versus late (>21 months) relapse after initial chemotherapy.

RESULTS

A 14-gene predictive model was developed using a set of training samples (n = 51) and subsequently tested using an independent set of test samples (n = 28). This model correctly predicted the outcome of 24 of the 28 test samples (86% accuracy) with 95% positive predictive value for early relapse.

CONCLUSIONS

Predictive markers for early recurrence can be identified for platinum-paclitaxel combination chemotherapy in primary ovarian carcinoma. The proposed 14-gene model requires further validation.

Clinical applications of microarray technology: creatine kinase B is an up-regulated gene in epithelial ovarian cancer and shows promise as a serum marker

OBJECTIVE

(1) To identify and (2) validate genes that are up-regulated in ovarian cancer, and (3) to investigate whether the activity of a candidate gene, creatine kinase B (CKB) is elevated in pre-operative sera from ovarian cancer patients compared to patients with benign pelvic masses and normal controls.

METHODS

MICROMAX cDNA microarray system and RNA derived from pooled ovarian cancer cell lines and normal ovary surface epithelial cells (HOSE) were used to identify differentially expressed genes. Using RNA from both cell lines and from tissue obtained through laser capture microdissection (LCM), we performed quantitative PCR in order to validate up-regulation of one of these genes, creatine kinase B (CKB). Using a commercially available enzyme assay, CKB activity was measured in pre-operative serum samples obtained from 45 ovarian cancer patients, 49 patients with a benign pelvic mass, as well as 37 normal controls. Statistical analysis was preformed using an unpaired Student's t test.

RESULTS

Microarray technology revealed that CKB gene expression had a cancer to HOSE ratio of 18. RNA levels of CKB, measured by real-time PCR, were elevated a mean (and standard error) of 36-fold (8.4) in cancer cell lines compared with HOSE cells and 22.75-fold (10.45) in microdissected ovarian cancer epithelial cells compared with normal ovarian epithelial cells. In serum, the mean (+/-standard error) of CKB enzyme activity in cancer cases was 24.7 U/L units (+/- 5.1) compared to 9.6 U/L (+/- 1.6) for benign mass cases (P = 0.0088) and to 8.5 U/L (1.7) for normal controls (P = 0.0096).

CONCLUSIONS

Microarray technology offers a method to identify tumor biomarkers with potential clinical usefulness. Our data indicated that CKB gene expression is up-regulated in ovarian cancer cells in vitro and in vivo and that CKB enzyme activity is significantly elevated in sera from ovarian cancer patients, including those with stage I disease. These findings suggest a potential role for CKB as a marker for early diagnosis.

Biomarkers of ovarian tumours

Ovarian cancer is one of the most aggressive gynaecological malignancies and most often the high mortality is a direct result of delays in diagnosis. The development of an ovarian cancer-specific biomarker for the early detection of disease has the capacity to improve the dismal survival rate. Currently, there are multiple investigations that are utilising both genomic and proteomic technologies to identify genes, gene products and proteins that may potentially identify diagnostic ovarian cancer biomarkers. Here, we review the studies that are involved in biomarker development for the detection of ovarian cancer.

Identification of DNA copy number changes in microdissected serous ovarian cancer tissue using a cDNA microarray platform

We have established a method for using a cDNA array platform in combination with degenerate oligonucleotide primer polymerase chain reaction (DOP-PCR) and taramide signal amplification (TSA) to identify DNA copy number abnormalities (CNA) in cancer cell lines and cancer cells procured with laser-based microdissection. To determine the sensitivity and specificity for detecting single-copy gain and loss, receiver-operator curve analysis was performed on hybridization signal ratios generated from non-DOP and DOP amplified female and male DNA using a 10,816-element cDNA microarray. A cutoff value of 1.12 and 1.07 average signal ratio for X-chromosomal genes versus autosomal genes provided a sensitivity and specificity of 50 and 79%, respectively, for non-DOP amplified DNA and a sensitivity and specificity of 50 and 72%, respectively, for DOP amplified DNA. We used this approach to identify DNA copy number abnormalities in the ovarian cancer cell line OVCA633, which has previously been shown to have 12p amplification. Transcription profiling of OVCA633 was also performed. Two amplified and overexpressed genes located on 12p11, KRAS2 and LRMP, were identified; these were validated with quantitative real-time PCR. Subsequently, the same approach was used to identify CNAs and gene expression alterations in 11 microdissected serous ovarian adenocarcinoma cases. Validated data revealed amplification and overexpression of ERBB3 and FOS and deletion and underexpression of KRT6 and APXL in more than 50% of the tissue samples. These results show the feasibility of using the cDNA array platform to identify changes in DNA and mRNA copy number simultaneously in microdissected tumor tissues.

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.

Expression of candidate tumor markers in ovarian carcinoma and benign ovary: evidence for a link between epithelial phenotype and neoplasia

EpCAM, epithelial membrane antigen (EMA)-mucin 1 (MUC1), mesothelin, and CD9 have been reported to be overexpressed at the RNA level in ovarian carcinomas. By using immunohistochemistry, we profiled the protein expression of these gene products in ovarian carcinoma tissues and compared them with benign ovarian surface epithelium (OSE) and cortical inclusion cysts (CICs). Immunoreactivity for EMA and calretinin were used to define epithelial and mesothelial differentiation in nontumor tissues, respectively. Papillary serous (n = 16) and endometrioid (n = 10) tumors were immunopositive for EMA/MUC1 (100%), mesothelin (75% and 30%, respectively), CD9 (88% and 90%, respectively), and EpCAM (100%). All ovarian carcinomas and carcinoma cell lines tested were negative for calretinin. In nonneoplastic ovary, both OSE and CICs ranged from flat-to-cuboidal to stratified and ciliated in appearance. OSE with a cuboidal morphology had a similar immunoreactivity as omental peritoneum, expressing calretinin, mesothelin, and CD9. In contrast, CICs with stratified and ciliated epithelium show expression patterns similar to those in fallopian tubes. They frequently expressed EMA, EpCAM, mesothelin, and CD9. This immunophenotype is preserved in ovarian carcinomas, suggesting that Müllerian metaplasia signals the acquisition of these markers and that their expression is maintained in ovarian carcinomas that originate from this epithelium.

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.

Amplification of MGC2177, PLAG1, PSMC6P, and LYN in a malignant mixed tumor of salivary gland detected by cDNA microarray with tyramide signal amplification

Gene amplifications have been observed in many different tumor cells, and many of these changes are related to tumor pathogenesis. Comparative genomic hybridization (CGH) using metaphase chromosomes can detect changes in chromosome copy number with a resolution of 10-20 Mb. Current advances in CGH analysis in a microarray format allow us to refine such changes down to the gene level. We applied microarray technology to detect novel gene amplification in a malignant mixed tumor of salivary gland. Besides detecting previously known gene amplifications (MDM2 and MYC), we identified four other highly amplified genes located at 8q11.2 approximately q13: MGC2177, PLAG1, PSMC6P, and LYN. The amplification was further validated with real-time quantitative polymerase chain reaction.

Osteopontin as an Adjunct to CA125 in Detecting Recurrent Ovarian Cancer

Purpose: CA125 is currently the only tumor marker to have a validated role in the postoperative monitoring of ovarian cancer. Osteopontin (OPN) is a putative plasma biomarker that was recently identified using high-throughput cDNA microarray technology. The purpose of this study was to test the hypothesis that OPN is a clinically useful adjunct to CA125 in detecting recurrent ovarian cancer.

Experimental Design: Thirty-eight ovarian cancer patients had a single pretreatment blood sample and 200 postoperative specimens were prospectively collected during chemotherapy and follow-up. OPN measurements were performed using an enzyme-linked immunoassay, and CA125 levels were concurrently obtained. Wilcoxon’s signed rank-sum test was used to perform paired comparisons between pretreatment and postoperative OPN and CA125 measurements. Longitudinal mixed effects polynomial models were used to determine whether OPN and CA125 levels correlated with the development of recurrent ovarian cancer.

Results: The median pretreatment OPN level was 178 ng/ml (range, 12–3468) and the median CA125 measurement was 812 units/ml (range, 12–81,500). There was a trend for OPN levels to decline after treatment was initiated (P = 0.07), but decreasing CA125 measurements were more consistently observed (P = 0.0009). The quadratic functional trends of OPN and CA125 were each highly significant (P &lt; 0.0001). Although inferior to CA125 in predicting clinical response to therapy, OPN rose earlier in 90% (95% confidence interval, 56–100%) of the patients developing recurrent disease (median lead time, 3 months).

Conclusions: OPN may be a clinically useful adjunct to CA125 in detecting recurrent ovarian cancer.

Gene expression patterns in ovarian carcinomas

We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.