Gene Expression Patterns That Characterize Advanced Stage Serous Ovarian Cancers

CASC11 and PVT1 spliced transcripts play an oncogenic role in colorectal carcinogenesis

Cancer is fundamentally a genetic disorder that alters cellular information flow toward aberrant growth. The coding part accounts for less than 2% of the human genome, and it has become apparent that aberrations within the noncoding genome drive important cancer phenotypes. The numerous carcinogenesis-related genomic variations in the 8q24 region include single nucleotide variations (SNVs), copy number variations (CNVs), and viral integrations occur in the neighboring areas of the MYC locus. It seems that MYC is not the only target of these alterations. The MYC-proximal mutations may act via regulatory noncoding RNAs (ncRNAs). In this study, gene expression analyses indicated that the expression of some PVT1 spliced linear transcripts, CircPVT1, CASC11, and MYC is increased in colorectal cancer (CRC). Moreover, the expression of these genes is associated with some clinicopathological characteristics of CRC. Also, in vitro studies in CRC cell lines demonstrated that CASC11 is mostly detected in the nucleus, and different transcripts of PVT1 have different preferences for nuclear and cytoplasmic parts. Furthermore, perturbation of PVT1 expression and concomitant perturbation in PVT1 and CASC11 expression caused MYC overexpression. It seems that transcription of MYC is under regulatory control at the transcriptional level, i.e., initiation and elongation of transcription by its neighboring genes. Altogether, the current data provide evidence for the notion that these noncoding transcripts can significantly participate in the MYC regulation network and in the carcinogenesis of colorectal cells.

Differential gene expression and network analysis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have collected genomic data of HNSCC patients from The Cancer Genome Atlas (TCGA) and analyzed them to get deeper insights into the gene expression pattern. Initially, 793 differentially expressed genes (DEGs) were categorized, and their enrichment analysis was performed. Later, a protein-protein interaction network for the DEGs was constructed using the STRING plugin in Cytoscape to study their interactions. A set of 10 hub genes was selected based on Maximal Clique Centrality score, and later their survival analysis was studied. The elucidated set of 10 genes, i.e., PRAME, MAGEC2, MAGEA12, LHX1, MAGEA3, CSAG1, MAGEA6, LCE6A, LCE2D, LCE2C, referred to as potential candidates to be explored as HNSCC biomarkers. The Kaplan-Meier overall survival of the selected genes suggested that the alterations in the candidate genes were linked to the decreased survival of the HNSCC patients. Altogether, the results of this study signify that the genomic alterations and differential expression of the selected genes can be explored in therapeutic interpolations of HNSCC, exploiting early diagnosis and target-propelled therapy.

Differential expression analysis in ovarian cancer: A functional genomics and systems biology approach

BACKGROUND

Ovarian cancer is one of the rarest lethal oncologic diseases that have hardly any specific biomarkers. The availability of high-throughput genomic data and advancement in bioinformatics tools allow us to predict gene biomarkers and apply systems biology approaches to get better diagnosis, and prognosis of the disease with a tentative drug that may be repurposed.

OBJECTIVE

To perform genome-wide association studies using microarray gene expression of ovarian cancer and identify gene biomarkers, construction and analyze networks, perform survival analysis, and drug interaction studies for better diagnosis, prognosis, and treatment of ovarian cancer.

METHOD

The gene expression profiles of both healthy and serous ovarian cancer epithelial samples were considered. We applied a series of bioinformatics methods and tools, including fold-change statistics for differential expression analysis, DisGeNET and NCBI-Gene databases for gene-disease association mapping, DAVID 6.8 for GO enrichment analysis, GeneMANIA for network construction, Cytoscape 3.8 with its plugins for network visualization, analysis, and module detection, the UALCAN for patient survival analysis, and PubChem, DrugBank and DGIdb for gene-drug interaction.

RESULTS

We identified 8 seed genes that were subjected for drug-gene interaction studies. Because of over-expression in all the four stages of ovarian cancer, we discern that genes HMGA1 and PSAT1 are potential therapeutic biomarkers for its diagnosis at an early stage (stage I). Our analysis suggests that there are 11 drugs common in the seed genes. However, hypermethylated seed genes HMGA1 and PSAT1 showcased a good interaction affinity with drugs cisplatin, cyclosporin, bisphenol A, progesterone, and sunitinib, and are crucial in the proliferation of ovarian cancer.

CONCLUSION

Our study reveals that HMGA1 and PSAT1 can be deployed for initial screening of ovarian cancer and drugs cisplatin, bisphenol A, cyclosporin, progesterone, and sunitinib are effective in curbing the epigenetic alteration.

Gene expression profile association with poor prognosis in epithelial ovarian cancer patients

Ovarian cancer (OC) is the eighth most common type of cancer for women worldwide. The current diagnostic and prognostic routine available for OC management either lack specificity or are very costly. Gene expression profiling has shown to be a very effective tool in exploring new molecular markers for patients with OC, although association of such markers with patient survival and clinical outcome is still elusive. Here, we performed gene expression profiling of different subtypes of OC to evaluate its association with patient overall survival (OS) and aggressive forms of the disease. By global mRNA microarray profiling in a total of 196 epithelial OC patients (161 serous, 15 endometrioid, 11 mucinous, and 9 clear cell carcinomas), we found four candidates-HSPA1A, CD99, RAB3A and POM121L9P, which associated with OS and poor clinicopathological features. The overexpression of all combined was correlated with shorter OS and progression-free survival (PFS). Furthermore, the combination of at least two markers were further associated with advanced grade, chemotherapy resistance, and progressive disease. These results indicate that a panel comprised of a few predictors that associates with a more aggressive form of OC may be clinically relevant, presenting a better performance than one marker alone.

The role of the cancer testis antigen PRAME in tumorigenesis and immunotherapy in human cancer

Preferentially expressed antigen in melanoma (PRAME), which belongs to the cancer/testis antigen (CTA) gene family, plays a pivotal role in multiple cellular processes and immunotherapy response in human cancers. PRAME is highly expressed in different types of cancers and is involved in cell proliferation, apoptosis, differentiation and metastasis as well as the outcomes of patients with cancer. In this review article, we discuss the potential roles and physiological functions of PRAME in various types of cancers. Moreover, this review highlights immunotherapeutic strategies that target PRAME in human malignancies. Therefore, the modulation of PRAME might be useful for the treatment of patients with cancer.

IGFBP2: integrative hub of developmental and oncogenic signaling network

Insulin-like growth factor (IGF) binding protein 2 (IGFBP2) was discovered and identified as an IGF system regulator, controlling the distribution, function, and activity of IGFs in the pericellular space. IGFBP2 is a developmentally regulated gene that is highly expressed in embryonic and fetal tissues and markedly decreases after birth. Studies over the last decades have shown that in solid tumors, IGFBP2 is upregulated and promotes several key oncogenic processes, such as epithelial-to-mesenchymal transition, cellular migration, invasion, angiogenesis, stemness, transcriptional activation, and epigenetic programming via signaling that is often independent of IGFs. Growing evidence indicates that aberrant expression of IGFBP2 in cancer acts as a hub of an oncogenic network, integrating multiple cancer signaling pathways and serving as a potential therapeutic target for cancer treatment.

Magellan: A Web Based System for the Integrated Analysis of Heterogeneous Biological Data and Annotations; Application to DNA Copy Number and Expression Data in Ovarian Cancer

Recent advances in high throughput biological methods allow researchers to generate enormous amounts of data from a single experiment. In order to extract meaningful conclusions from this tidal wave of data, it will be necessary to develop analytical methods of sufficient power and utility. It is particularly important that biologists themselves be able to perform many of these analyses, such that their background knowledge of the experimental system under study can be used to interpret results and direct further inquiries. We have developed a web-based system, Magellan, which allows the upload, storage, and analysis of multivariate data and textual or numerical annotations. Data and annotations are treated as abstract entities, to maximize the different types of information the system can store and analyze. Annotations can be used in analyses/visualizations, as a means of subsetting data to reduce dimensionality, or as a means of projecting variables from one data type or data set to another. Analytical methods are deployed within Magellan such that new functionalities can be added in a straightforward fashion. Using Magellan, we performed an integrated analysis of genome-wide comparative genomic hybridization (CGH), mRNA expression, and clinical data from ovarian tumors. Analyses included the use of permutation-based methods to identify genes whose mRNA expression levels correlated with patient survival, a nearest neighbor classifier to predict patient survival from CGH data, and curated annotations such as genomic position and derived annotations such as statistical computations to explore the quantitative relationship between CGH and mRNA expression data.

ELF3 is a negative regulator of epithelial-mesenchymal transition in ovarian cancer cells

Transcription factors are master switches for various biochemical pathways. However, transcription factors involved in the pathogenesis of ovarian cancer have yet to be explored thoroughly. Therefore, in the present study, we assessed the prognostic value of the transcription factor E74-like factor 3 (ELF3) identified via transcriptome profiling of the epithelial components of microdissected ovarian tumor samples isolated from long- and short-term survivors and determined its roles in ovarian cancer pathogenesis. Immunohistochemical analysis of ELF3 in tumor tissue sections suggested that ELF3 was exclusively expressed by epithelial ovarian cancer cells. Furthermore, using 112 high-grade ovarian cancer samples isolated from patients and The Cancer Genome Atlas (TCGA) data, we found that downregulation of ELF3 expression was markedly associated with reduced survival. Functional studies demonstrated that overexpression of ELF3 in ovarian cancer cells suppressed proliferation and anchorage-dependent growth of the cells and that ELF3 silencing increased cell proliferation. Furthermore, upregulation of ELF3 increased expression of epithelial markers, decreased expression of mesenchymal markers, and mediated translocation of epithelial-mesenchymal transition (EMT) signaling molecules in ovarian cancer cells. Finally, we validated the tumor-inhibitory roles of ELF3 using animal models. In conclusion, ELF3 is a favorable prognostic marker for ovarian cancer. As a negative regulator of EMT, ELF3-modulated reversal of EMT may be a new effective modality in the treatment of ovarian cancer.

KCNN4 and S100A14 act as predictors of recurrence in optimally debulked patients with serous ovarian cancer

Approximately 50-75% of patients with serous ovarian carcinoma (SOC) experience recurrence within 18 months after first-line treatment. Current clinical indicators are inadequate for predicting the risk of recurrence. In this study, we used 7 publicly available microarray datasets to identify gene signatures related to recurrence in optimally debulked SOC patients, and validated their expressions in an independent clinic cohort of 127 patients using immunohistochemistry (IHC). We identified a two-gene signature including KCNN4 and S100A14 which was related to recurrence in optimally debulked SOC patients. Their mRNA expression levels were positively correlated and regulated by DNA copy number alterations (CNA) (KCNN4: p=1.918e-05) and DNA promotermethylation (KCNN4: p=0.0179; S100A14: p=2.787e-13). Recurrence prediction models built in the TCGA dataset based on KCNN4 and S100A14 individually and in combination showed good prediction performance in the other 6 datasets (AUC:0.5442-0.9524). The independent cohort supported the expression difference between SOC recurrences. Also, a KCNN4 and S100A14-centered protein interaction subnetwork was built from the STRING database, and the shortest regulation path between them, called the KCNN4-UBA52-KLF4-S100A14 axis, was identified. This discovery might facilitate individualized treatment of SOC.

Targeting Stromal-Cancer Cell Crosstalk Networks in Ovarian Cancer Treatment

Ovarian cancer is a histologically, clinically, and molecularly diverse disease with a five-year survival rate of less than 30%. It has been estimated that approximately 21,980 new cases of epithelial ovarian cancer will be diagnosed and 14,270 deaths will occur in the United States in 2015, making it the most lethal gynecologic malignancy. Ovarian tumor tissue is composed of cancer cells and a collection of different stromal cells. There is increasing evidence that demonstrates that stromal involvement is important in ovarian cancer pathogenesis. Therefore, stroma-specific signaling pathways, stroma-derived factors, and genetic changes in the tumor stroma present unique opportunities for improving the diagnosis and treatment of ovarian cancer. Cancer-associated fibroblasts (CAFs) are one of the major components of the tumor stroma that have demonstrated supportive roles in tumor progression. In this review, we highlight various types of signaling crosstalk between ovarian cancer cells and stromal cells, particularly with CAFs. In addition to evaluating the importance of signaling crosstalk in ovarian cancer progression, we discuss approaches that can be used to target tumor-promoting signaling crosstalk and how these approaches can be translated into potential ovarian cancer treatment.

Cellular and molecular processes in ovarian cancer metastasis. A Review in the Theme: Cell and Molecular Processes in Cancer Metastasis

Ovarian cancer is the most lethal gynecological malignancy. It is usually diagnosed at a late stage, with a 5-yr survival rate of <30%. The majority of ovarian cancer cases are diagnosed after tumors have widely spread within the peritoneal cavity, limiting the effectiveness of debulking surgery and chemotherapy. Owing to a substantially lower survival rate at late stages of disease than at earlier stages, the major cause of ovarian cancer deaths is believed to be therapy-resistant metastasis. Although metastasis plays a crucial role in promoting ovarian tumor progression and decreasing patient survival rates, the underlying mechanisms of ovarian cancer spread have yet to be thoroughly explored. For many years, researchers have believed that ovarian cancer metastasizes via a passive mechanism by which ovarian cancer cells are shed from the primary tumor and carried by the physiological movement of peritoneal fluid to the peritoneum and omentum. However, the recent discovery of hematogenous metastasis of ovarian cancer to the omentum via circulating tumor cells instigated rethinking of the mode of ovarian cancer metastasis and the importance of the "seed-and-soil" hypothesis for ovarian cancer metastasis. In this review we discuss the possible mechanisms by which ovarian cancer cells metastasize from the primary tumor to the omentum, the cross-talk signaling events between ovarian cancer cells and various stromal cells that play crucial roles in ovarian cancer metastasis, and the possible clinical implications of these findings in the management of this deadly, highly metastatic disease.

Clinicians' expectations for gene-driven cancer therapy

A new era of medicine is rapidly approaching, which will change not only pathological diagnosis but also medical decision-making. This paper raises the question of how well prepared doctors are to address the new issues that will soon confront them. The human genome has been completely sequenced and general understanding about cancer biology has increased enormously with understanding that unregulated gene function and complicated changes in signal pathways are related to uncontrolled cell growth. Thus, gene-driven therapy involving alterations to genes are recognized to present new therapy options. This advance will necessitate major changes to the decision-making aspect of physicians. This article focuses on defining the pertinent changes and addressing what they mean for practicing physicians.

Calcium-dependent FAK/CREB/TNNC1 signalling mediates the effect of stromal MFAP5 on ovarian cancer metastatic potential

Ovarian cancer is the most lethal gynecologic malignancy in the United States, and advanced serous ovarian adenocarcinoma is responsible for most ovarian cancer deaths. However, the stroma-derived molecular determinants that modulate patient survival have yet to be characterized. Here we identify a stromal gene signature for advanced high-grade serous ovarian cancer using microdissected stromal ovarian tumor samples and find that stromal microfibrillar-associated protein 5 (MFAP5) is a prognostic marker for poor survival. Further functional studies reveal that FAK/CREB/TNNC1 signaling pathways mediate the effect of MFAP5 on ovarian cancer cell motility and invasion potential. Targeting stromal MFAP5 using MFAP5 specific siRNA encapsulated in chitosan nanoparticles significantly decreases ovarian tumor growth and metastasis in vivo, suggesting that it may be a new modality of ovarian cancer treatment.

Ovarian cancer: genomic analysis

OBJECTIVES

Despite improvements in the management of ovarian cancer patients over the last 30 years, there has been only a minimal improvement in overall survival. While targeted therapeutic approaches for the treatment of cancer have evolved, major challenges in ovarian cancer research persist, including the identification of predictive biomarkers with clinical relevance, so that empirical drug selection can be avoided. In this article, we review published genomic analysis studies including data generated in our laboratory and how they have been incorporated into modern clinical trials in a rational and effective way.

METHODS

Multiple published genomic analysis studies were collected for review and discussion with emphasis on their potential clinical applicability.

RESULTS

Genomic analysis has been shown to be a powerful tool to identify dysregulated genes, aberrantly activated pathways and to uncover uniqueness of subclasses of ovarian tumors. The application of this technology has provided a solid molecular basis for different clinical behaviors associated with tumor histology and grade. Genomic signatures have been obtained to predict clinical end points for patients with cancer, including response rates, progression-free survival, and overall survival. In addition, genomic analysis has provided opportunities to identify biomarkers, which either result in a modification of existing clinical management or to stratification of patients to novel therapeutic approaches designed as clinical trials.

CONCLUSIONS

Genomic analyses have accelerated the identification of relevant biomarkers and extended our understanding of the molecular biology of ovarian cancer. This in turn, will hopefully lead to a paradigm shift from empirical, uniform treatment to a more rational, personalized treatment of ovarian cancers. However, validation of potential biomarkers on both the statistical and biological levels is needed to confirm they are of clinical relevance, in order to increase the likelihood that the desired outcome can be predicted and achieved.

miR-193b promotes cell proliferation by targeting Smad3 in human glioma

Studies have shown that several miRNAs play important roles in regulating a variety of cellular processes in gliomas. In these reports, upregulation of miR-193b has been found to be associated with a poor prognosis for glioma, but its functional mechanism in glioma remains unclear. This study investigates the roles of miR-193b in glioma tumor growth. We first showed that the expression of miR-193b was elevated in both glioma samples and glioma cells. Furthermore, downregulation of miR-193b by inhibitors was statistically correlated with a decrease in cell growth and a restored G1 accumulation. Luciferase assay and Western blot analysis revealed that Smad3 is a direct target of miR-193b. To prove that miR-193b regulated cell growth through the transforming growth factor-β (TGF-β) pathway in glioma cells by regulating Smad3, we tested endogenous targets of the TGF-β pathway by measuring the accumulation of p21 mRNAs after downregulation of miR-193b. The results confirmed that induction of p21 was promoted by miR-193b inhibitors in glioma cells, although this induction disappeared when Smad3 was knocked down with siRNA. Moreover, downregulation of Smad3 mitigates the miR-193b suppression of glioma proliferation. In conclusion, these results suggest that miR-193b regulated cell growth in glioma through the TGF-β pathway by regulating Smad3. Thus, our study indicates that miR-193b promotes cell proliferation by targeting Smad3 in human glioma, which may serve as a potentially useful target for development of miRNA-based therapies in the future.

Amplification of PVT-1 is involved in poor prognosis via apoptosis inhibition in colorectal cancers

Background:

We previously conducted gene expression microarray analyses to identify novel indicators for colorectal cancer (CRC) metastasis and prognosis from which we identified PVT-1 as a candidate gene. PVT-1, which encodes a long noncoding RNA, mapped to chromosome 8q24 whose copy-number amplification is one of the most frequent events in a wide variety of malignant diseases. However, PVT-1 molecular mechanism of action remains unclear.

Methods:

We conducted cell proliferation and invasion assays using colorectal cancer cell lines transfected with PVT-1siRNA or negative control siRNA. Gene expression microarray analyses on these cell lines were also carried out to investigate the molecular function of PVT-1. Further, we investigated the impact of PVT-1 expression on the prognosis of 164 colorectal cancer patients by qRT–PCR.

Results:

CRC cells transfected with PVT-1 siRNA exhibited significant loss of their proliferation and invasion capabilities. In these cells, the TGF-β signalling pathway and apoptotic signals were significantly activated. In addition, univariate and multivariate analysis revealed that PVT-1 expression level was an independent risk factor for overall survival of colorectal cancer patients.

Conclusion:

PVT-1, which maps to 8q24, generates antiapoptotic activity in CRC, and abnormal expression of PVT-1 was a prognostic indicator for CRC patients.

ALX1 induces snail expression to promote epithelial-to-mesenchymal transition and invasion of ovarian cancer cells

Ovarian cancer is a highly invasive and metastatic disease with a poor prognosis if diagnosed at an advanced stage, which is often the case. Recent studies argue that ovarian cancer cells that have undergone epithelial-to-mesenchymal transition (EMT) acquire aggressive malignant properties, but the relevant molecular mechanisms in this setting are not well-understood. Here, we report findings from an siRNA screen that identified the homeobox transcription factor ALX1 as a novel regulator of EMT. RNA interference-mediated attenuation of ALX1 expression restored E-cadherin expression and cell-cell junction formation in ovarian cancer cells, suppressing cell invasion, anchorage-independent growth, and tumor formation. Conversely, enforced expression of ALX1 in ovarian cancer cells or nontumorigenic epithelial cells induced EMT. We found that ALX1 upregulated expression of the key EMT regulator Snail (SNAI1) and that it mediated EMT activation and cell invasion by ALX1. Our results define the ALX1/Snail axis as a novel EMT pathway that mediates cancer invasion.

Identification of differentially expressed genes according to chemosensitivity in advanced ovarian serous adenocarcinomas: expression of GRIA2 predicts better survival

Background:

The purpose of this study was to identify genes that are differentially expressed in chemosensitive serous papillary ovarian carcinomas relative to those expressed in chemoresistant tumours.

Methods:

To identify novel candidate biomarkers, differences in gene expression were analysed in 26 stage IIIC/IV serous ovarian adenocarcinomas (12 chemosensitive tumours and 14 chemoresistant tumours). We subsequently investigated the immunohistochemical expression of GRIA2 in 48 independent sets of advanced ovarian serous carcinomas.

Results:

Microarray analysis revealed a total of 57 genes that were differentially expressed in chemoresistant and chemosensitive tumours. Of the 57 genes, 39 genes were upregulated and 18 genes were downregulated in chemosensitive tumours. Five differentially expressed genes (CD36, LIFR, CHL1, GRIA2, and FCGBP) were validated by quantitative real-time PCR. The expression of GRIA2 was validated at the protein level by immunohistochemistry, and patients with GRIA2 expression showed a longer progression-free and overall survival (P=0.051 and P=0.031 respectively).

Conclusions:

We found 57 differentially expressed genes to distinguish between chemosensitive and chemoresistant tumours. We also demonstrated that the expression of GRIA2 among the differentially expressed genes provides better prognosis of patients with advanced serous papillary ovarian adenocarcinoma.

Identifying microRNA/mRNA dysregulations in ovarian cancer

BACKGROUND

MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA).

METHODS

TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA.

RESULTS

We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory mechanisms.

CONCLUSIONS

Our findings identify novel microRNA/mRNA relationships that can be verified experimentally. We identify both generic microRNA/mRNA regulation mechanisms in the ovary as well as specific microRNA/mRNA controls which are turned on or off in ovarian tumours. Our results suggest that the disease process uses specific mechanisms which may be significant for their utility as early detection biomarkers or in the development of microRNA therapies in treating ovarian cancers. The positively correlated microRNA/mRNA pairs suggest the existence of novel regulatory mechanisms that proceed via intermediate states (indirect regulation) in ovarian tumorigenesis.

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

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

GENE EXPRESSION DATA ANALYSIS IN SUBTYPES OF OVARIAN CANCER USING COVARIANCE ANALYSIS

Many studies have used microarray technology to identify the molecular signatures of human cancer, yet the critical features of these often unmanageably large set of signatures remain elusive. We have investigated co-expression pattern in four subtypes of ovarian cancer from 104 cancer patients using covariance analysis, treating each subtype of ovarian cancer as a distinct disease entity. We sought gene pairs that were transcriptionally co-expressed in one or multiple subtypes of ovarian cancer, establishing a high confidence network of 87 genes interconnected by significantly high co-expression links that were observed in at least two subtypes of ovarian cancer. We have shown that certain groups of co-expressed gene pairs are cancer subtype specific, through demonstrating significant differences in co-expression patterns of gene pairs between subtypes of ovarian cancer. In addition, we identified a set of 24 genes that classified patients into specific cancer subtypes with a misclassification error rate of less than 5%. Our findings illustrate how large public microarray gene expression datasets could be exploited for identification of cancer subtype specific molecular signatures, and how to classify cancer patients into specific subtypes of cancer using gene expression profiles.

Expression profiling of the ovarian surface kinome reveals candidate genes for early neoplastic changes

OBJECTIVES

We tested the hypothesis that co-coordinated up-regulation or down-regulation of several ovarian cell surface kinases may provide clues for better understanding of the disease and help in rational design of therapeutic targets.

STUDY DESIGN

We compared the expression signature of 69 surface kinases in normal ovarian surface epithelial cells (OSE), with OSE from patients at high risk and with ovarian cancer.

RESULTS

Seven surface kinases, ALK, EPHA5, EPHB1, ERBB4, INSRR, PTK, and TGFbetaR1 displayed a distinctive linear trend in expression from normal, highrisk, and malignant epithelium. We confirmed these results using semiquantitative reverse transcription-polymerase chain reaction and tissue array of 202 ovarian cancer samples. A strong correlate was shown between disease-free survival and the expression of ERBB4. DNA sequencing revealed two novel mutations in ERBB4 in two cancer samples.

CONCLUSIONS

A distinct subset of the ovarian surface kinome is altered in the transition from high risk to invasive cancer and genetic mutation is not a dominant mechanism for these modifications. These results have significant implications for early detection and targeted therapeutic approaches for women at high risk of developing ovarian cancer.

Integrated analysis of multiple microarray datasets identifies a reproducible survival predictor in ovarian cancer

BACKGROUND

Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival.

METHODOLOGY/PRINCIPAL FINDINGS

Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets was demonstrated using Subclass Mapping. Previously established molecular phenotypes in the 2(nd) validation set were correlated with high and low-risk outcome groups. Functional representational and pathway analysis was used to explore gene networks associated with high and low risk phenotypes. A 19-gene model showed optimal performance in the training set (median OS 31 and 78 months, p < 0.01), 1(st) validation set (median OS 32 months versus not-yet-reached, p = 0.026) and 2(nd) validation set (median OS 43 versus 61 months, p = 0.013) maintaining independent prognostic power in multivariate analysis. There was strong molecular correspondence of the respective high- and low-risk tumors between training and 1(st) validation set. Low and high-risk tumors were enriched for favorable and unfavorable molecular subtypes and pathways, previously defined in the public 2(nd) validation set.

CONCLUSIONS/SIGNIFICANCE

Integration of previously generated cancer microarray datasets may lead to robust and widely applicable survival predictors. These predictors are not simply a compilation of prognostic genes but appear to track true molecular phenotypes of good- and poor-outcome.

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.

Development of an ovarian cancer screening decision model that incorporates disease heterogeneity: implications for potential mortality reduction

BACKGROUND

Pathologic and genetic data suggest that epithelial ovarian cancer may consist of indolent and aggressive phenotypes. The objective of the current study was to estimate the impact of a 2-phenotype paradigm of epithelial ovarian cancer on the mortality reduction achievable using available screening technologies.

METHODS

The authors modified a Markov model of ovarian cancer natural history (the 1-phenotype model) to incorporate aggressive and indolent phenotypes (the 2-phenotype model) based on histopathologic criteria. Stage distribution, incidence, and mortality were calibrated to data from the Surveillance, Epidemiology, and End Results Program of the US National Cancer Institute. For validation, a Monte Carlo microsimulation (1000,000 events) of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) multimodality prevalence screen was performed. Mortality reduction and positive predictive value (PPV) were estimated for annual screening.

RESULTS

In validation against UKCTOCS data, the model-predicted percentage of screen-detected cancers diagnosed at stage I and II was 41% compared with 47% (UKCTOCS data), and the model-predicted PPV of screening was 27% compared with 35% (UKCTOCS data). The model-estimated PPV of a strategy of annual population-based screening in the United States at ages 50 to 85 years was 14%. The mortality reduction using annual postmenopausal screening was 14.7% (1-phenotype model) and 10.9% (2-phenotype model). Mortality reduction was lower with the 2-phenotype model than with the 1-phenotype model regardless of screening frequency or test sensitivity; 68% of cancer deaths are accounted for by the aggressive phenotype.

CONCLUSIONS

The current analysis suggested that reductions in ovarian cancer mortality using available screening technologies on an annual basis are likely to be modest. A model that incorporated 2 clinical phenotypes of ovarian carcinoma into its natural history predicted an even smaller potential reduction in mortality because of the more frequent diagnosis of indolent cancers at early stages.

p27Kip1 mediates addiction of ovarian cancer cells to MYCC (c-MYC) and their dependence on MYC paralogs

The MYCC (c-MYC) gene is amplified in 30-60% of human ovarian cancers. We assessed the functional significance of MYCC amplification by siRNA inhibition of MYCC or MYC paralogs in a panel of ovarian cancer cell lines expressing varying levels of MYCC. Inactivation of MYCC inhibited cell proliferation and induced replicative senescence only in lines with amplified MYCC, indicating that these cells are addicted to continued MYCC overexpression. In contrast, siRNA knockdown of all three MYC isoforms inhibited proliferation of MYCC non-amplified ovarian cancer cells without inducing replicative senescence, and did not inhibit the proliferation of telomerase-immortalized ovarian surface epithelial cells. The arrest induced by MYCC knockdown was accompanied by an increase in the level of the Cdk inhibitor p27(Kip1) and a decrease in cyclin A expression and Cdk2 activity, and could be reversed by RNAi knockdown of p27(Kip1) or Rb, or by overexpression of cyclin A/Cdk2. The arrest induced by knockdown of all three MYC isoforms could similarly be reversed by p27(Kip1) knockdown. Our findings indicate that the addiction of MYCC-amplified ovarian cancer cells to MYCC differs from the dependence of MYCC non-amplified cancer cells on MYC paralogs, but both are mediated, at least in part, by p27(Kip1). They also suggest that growth of ovarian cancers may be blocked by inhibition of MYCC or MYC paralogs.

Epigenetic inactivation of the potential tumor suppressor gene FOXF1 in breast cancer

The expression of several members of the FOX gene family is known to be altered in a variety of cancers. We show that in breast cancer, FOXF1 gene is a target of epigenetic inactivation and that its gene product exhibits tumor-suppressive properties. Loss or downregulation of FOXF1 expression is associated with FOXF1 promoter hypermethylation in breast cancer cell lines and in invasive ductal carcinomas. Methylation of FOXF1 in invasive ductal carcinoma (37.6% of 117 cases) correlated with high tumor grade. Pharmacologic unmasking of epigenetic silencing in breast cancer cells restored FOXF1 expression. Re-expression of FOXF1 in breast cancer cells with epigenetically silenced FOXF1 genes led to G(1) arrest concurrent with or without apoptosis to suppress both in vitro cell growth and in vivo tumor formation. FOXF1-induced G(1) arrest resulted from a blockage at G(1)-S transition of the cell cycle through inhibition of the CDK2-RB-E2F cascade. Small interfering RNA-mediated depletion of FOXF1 in breast cancer cells led to increased DNA re-replication, suggesting that FOXF1 is required for maintaining the stringency of DNA replication and genomic stability. Furthermore, expression profiling of cell cycle regulatory genes showed that abrogation of FOXF1 function resulted in increased expression of E2F-induced genes involved in promoting the progression of S and G(2) phases. Therefore, our studies have identified FOXF1 as a potential tumor suppressor gene that is epigenetically silenced in breast cancer, which plays an essential role in regulating cell cycle progression to maintain genomic stability.

Emerging roles of Kruppel-like factor 6 and Kruppel-like factor 6 splice variant 1 in ovarian cancer progression and treatment

Epithelial ovarian cancer is one of the most lethal gynecologic cancers and the fifth most frequent cause of female cancer deaths in the United States. Despite dramatic treatment successes in other cancers through the use of molecular agents targeted against genetically defined events driving cancer development and progression, very few insights into epithelial ovarian cancer have been translated from the laboratory to the clinic. If advances are to be made in the early diagnosis, prevention, and treatment of this disease, it will be critical to characterize the common and private (personalized) genetic defects underlying the development and spread of epithelial ovarian cancer. The tumor suppressor Kruppel-like factor 6 and its alternatively spliced, oncogenic isoform, Kruppel-like factor 6 splice variant 1, are members of the Kruppel-like zinc finger transcription factor family of proteins, which have diverse roles in cellular differentiation, development, proliferation, growth-related signal transduction, and apoptosis. Inactivation of Kruppel-like factor 6 and overexpression of Kruppel-like factor 6 splice variant 1 have been associated with the progression of a number of human cancers and even with patient survival. This article summarizes our recent findings demonstrating that a majority of epithelial ovarian cancer tumors have Kruppel-like factor 6 allelic loss and decreased expression coupled with increased expression of Kruppel-like factor 6 splice variant 1. The targeted reduction of Kruppel-like factor 6 in ovarian cancer cell lines results in marked increases in cell proliferation, invasion, tumor growth, angiogenesis, and intraperitoneal dissemination in vivo. In contrast, the inhibition of Kruppel-like factor 6 splice variant 1 decreases cellular proliferation, invasion, angiogenesis, and tumorigenicity; this provides the rationale for its potential therapeutic application. These results and our recent demonstration that the inhibition of Kruppel-like factor 6 splice variant 1 can dramatically prolong survival in a preclinical mouse model of ovarian cancer are reviewed and discussed.

COMMD1 disrupts HIF-1alpha/beta dimerization and inhibits human tumor cell invasion

The gene encoding COMM domain-containing 1 (COMMD1) is a prototypical member of the COMMD gene family that has been shown to inhibit both NF-kappaB- and HIF-mediated gene expression. NF-kappaB and HIF are transcription factors that have been shown to play a role in promoting tumor growth, survival, and invasion. In this study, we demonstrate that COMMD1 expression is frequently suppressed in human cancer and that decreased COMMD1 expression correlates with a more invasive tumor phenotype. We found that direct repression of COMMD1 in human cell lines led to increased tumor invasion in a chick xenograft model, while increased COMMD1 expression in mouse melanoma cells led to decreased lung metastasis in a mouse model. Decreased COMMD1 expression also correlated with increased expression of genes known to promote cancer cell invasiveness, including direct targets of HIF. Mechanistically, our studies show that COMMD1 inhibits HIF-mediated gene expression by binding directly to the amino terminus of HIF-1alpha, preventing its dimerization with HIF-1beta and subsequent DNA binding and transcriptional activation. Altogether, our findings demonstrate a role for COMMD1 in tumor invasion and provide a detailed mechanism of how this factor regulates the HIF pathway in cancer cells.

Insulin-like growth factor 2 expression modulates Taxol resistance and is a candidate biomarker for reduced disease-free survival in ovarian cancer

PURPOSE

This study was undertaken to examine the role of the insulin-like growth factor (IGF) signaling pathway in the response of ovarian cancer cells to Taxol and to evaluate the significance of this pathway in human epithelial ovarian tumors.

EXPERIMENTAL DESIGN

The effect of Taxol treatment on AKT activation in A2780 ovarian carcinoma cells was evaluated using antibodies specific for phospho-AKT. To study the drug-resistant phenotype, we developed a Taxol-resistant cell line, HEY-T30, derived from HEY ovarian carcinoma cells. IGF2 expression was measured by real-time PCR. A type 1 IGF receptor (IGF1R) inhibitor, NVP-AEW541, and IGF2 small interfering RNA were used to evaluate the effect of IGF pathway inhibition on proliferation and Taxol sensitivity. IGF2 protein expression was evaluated by immunohistochemistry in 115 epithelial ovarian tumors and analyzed in relation to clinical/pathologic factors using the chi(2) or Fisher's exact tests. The influence of IGF2 expression on survival was studied with Cox regression.

RESULTS

Taxol-induced AKT phosphorylation required IGF1R tyrosine kinase activity and was associated with upregulation of IGF2. Resistant cells had higher IGF2 expression compared with sensitive cells, and IGF pathway inhibition restored sensitivity to Taxol. High IGF2 tumor expression correlated with advanced stage (P < 0.001) and tumor grade (P < 0.01) and reduced disease-free survival (P < 0.05).

CONCLUSIONS

IGF2 modulates Taxol resistance, and tumor IGF2 expression is a candidate prognostic biomarker in epithelial ovarian tumors. IGF pathway inhibition sensitizes drug-resistant ovarian carcinoma cells to Taxol. Such novel findings suggest that IGF2 represents a therapeutic target in ovarian cancer, particularly in the setting of Taxol resistance.

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.

Smad3 protein levels are modulated by Ras activity and during the cell cycle to dictate transforming growth factor-beta responses

Transforming growth factor beta (TGF-beta) regulates many biological processes, and aberrant TGF-beta signaling is implicated in tumor development. Smad3 is a central component of the TGF-beta signaling pathway, and once activated, Smad3 forms complexes with Smad4 or other receptor-regulated Smads, which accumulate in the nucleus to transcriptionally regulate TGF-beta target genes. Because Smad3 plays a significant role in mediating the activities of TGF-beta, we examined its regulation during tumor development using a well characterized tumor model. We demonstrate that Smad3 levels are dramatically reduced in the tumorigenic cell line transformed with activated H-Ras compared with the normal parental epithelial cells. Interestingly, we also observe a cell cycle-dependent regulation of Smad3 in both cell types, with high Smad3 levels in quiescent cells and a significant drop in Smad3 protein levels in proliferating cells. Smad3 is regulated at the mRNA level and at the level of protein stability. In addition, functional analysis indicates that down-regulation of Smad3 levels is required for the tumor cells to proliferate in the presence of TGF-beta, because ectopic expression of Smad3 in the tumorigenic cell line restores the growth inhibitory response to TGF-beta. In contrast, expression of high levels of Smad3 did not interfere with the ability of these cells to undergo epithelial to mesenchymal transition upon TGF-beta stimulation. Altogether, our results suggest that the level of Smad3 protein is an important determinant of the progression of tumorigenesis. High levels of Smad3 are required for the tumor suppressor activities of TGF-beta, whereas lower levels are sufficient for the tumor promoting functions.

A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: microfibril-associated glycoprotein 2

Advanced stage papillary serous tumors of the ovary are responsible for the majority of ovarian cancer deaths, yet the molecular determinants modulating patient survival are poorly characterized. Here, we identify and validate a prognostic gene expression signature correlating with survival in a series of microdissected serous ovarian tumors. Independent evaluation confirmed the association of a prognostic gene microfibril-associated glycoprotein 2 (MAGP2) with poor prognosis, whereas in vitro mechanistic analyses demonstrated its ability to prolong tumor cell survival and stimulate endothelial cell motility and survival via the alpha(V)beta(3) integrin receptor. Increased MAGP2 expression correlated with microvessel density suggesting a proangiogenic role in vivo. Thus, MAGP2 may serve as a survival-associated target.

Gene expression profiling and real-time PCR analyses identify novel potential cancer-testis antigens in multiple myeloma

Cancer-testis (CT) Ags are attractive targets for immunotherapeutic strategies since they are aberrantly expressed in malignant cells and not, or in limited number, in somatic tissues, except germ cells. To identify novel CT genes in multiple myeloma, we used Affymetrix HG-U133 gene expression profiles of 5 testis, 64 primary multiple myeloma cells (MMC), and 24 normal tissue samples. A 5-filter method was developed to keep known CT genes while deleting non-CT genes. Starting from 44,928 probe sets, including probe sets for 18 previously described CT genes, we have obtained 82 genes expressed in MMC and testis and not detected in more than 6 normal tissue samples. This list includes 14 of the 18 known CT genes and 68 novel putative CT genes. Real-time RT-PCR was performed for 34 genes in 12 normal tissue samples, 5 MMC samples, and one sample of five pooled testes. It has validated the CT status of 23 of 34 genes (67%). We found one novel "testis-restricted" gene (TEX14, expression in testis and tumor only), eight "tissue-restricted" (mRNA detected in one or two nongametogenic tissues), and seven "differentially expressed" (mRNA detected in three to six nongametogenic tissues) CT genes. Further studies are warranted to determine the immunogenicity of these novel CT Ag candidates.

Overexpression and mislocalization of the chromosomal segregation protein separase in multiple human cancers

PURPOSE

Separase, an endopeptidase, plays a pivotal role in chromosomal segregation by separating sister chromatids during the metaphase to anaphase transition. Using a mouse mammary tumor model we have recently shown that overexpression of Separase induces aneuploidy and tumorigenesis (Zhang et al., Proc Natl Acad Sci 2008;105:13033). In the present study, we have investigated the expression level of Separase across a wide range of human tumors.

EXPERIMENTAL DESIGN

To examine the expression levels and localization of Separase in human tumors, we have performed immunofluorescence microscopy using human Separase antibody and tumor tissue arrays from osteosarcoma, colorectal, breast, and prostate cancers with appropriate normal controls.

RESULTS

We show that Separase is significantly overexpressed in osteosarcoma, breast, and prostate tumor specimens. There is a strong correlation of tumor status with the localization of Separase into the nucleus throughout all stages of the cell cycle. Unlike the normal control tissues, where Separase localization is exclusively cytoplasmic in nondividing cells, human tumor samples show significantly higher number of resting cells with a strong nuclear Separase staining. Additionally, overexpression of Separase transcript strongly correlates with high incidence of relapse, metastasis, and lower 5-year overall survival rate in breast and prostate cancer patients.

CONCLUSION

These results further strengthen our hypothesis that Separase might be an oncogene, whose overexpression induces tumorigenesis, and indicates that Separase overexpression and aberrant nuclear localization are common in many tumor types and may predict outcome in some human cancers.

BMP-2 signaling in ovarian cancer and its association with poor prognosis

BACKGROUND

We previously observed the over-expression of BMP-2 in primary cultures of epithelial ovarian cancer (EOC) cells as compared to normal epithelial cells based on Affymetrix microarray profiling 1. Here we investigate the effect of BMP-2 on several parameters of ovarian cancer tumorigenesis using the TOV-2223, TOV-1946 and TOV-112D EOC cell lines.

METHODS

We treated each EOC cell line with recombinant BMP-2 and assayed various parameters associated with tumorigenesis. More specifically, cell signaling events induced by BMP-2 treatment were investigated by western-blot using anti-phosphospecific antibodies. Induction of Id1, Snail and Smad6 mRNA expression was investigated by real time RT-PCR. The ability of cells to migrate was tested using the scratch assay. Cell-cell adhesion was analyzed by the ability of cells to form spheroids. We also investigated BMP-2 expression in tissue samples from a series of EOC patients.

RESULTS

Treatment of these cell lines with recombinant BMP-2 induced a rapid phosphorylation of Smad1/5/8 and Erk MAPKs. Increased expression of Id1, Smad6 and Snail mRNAs was also observed. Only in the TOV-2223 cell line were these signaling events accompanied by an alteration in cell proliferation. We also observed that BMP-2 efficiently increased the motility of all three cell lines. In contrast, BMP-2 treatment decreased the ability of TOV-1946 and TOV-112D cell lines to form spheroids indicating an inhibition of cell-cell adhesion. The expression of BMP-2 in tumor tissues from patients was inversely correlated with survival.

CONCLUSION

These results suggest that EOC cell secretion of BMP-2 in the tumor environment contributes to a modification of tumor cell behavior through a change in motility and adherence. We also show that BMP-2 expression in tumor tissues is associated with a poorer prognosis for ovarian cancer patients.

Gene expression profiling and prediction of clinical outcome in ovarian cancer

Epithelial ovarian cancer is the most lethal gynaecological cancer. Despite debulking surgery and platinum/taxane-based chemotherapy, the prognosis remains poor with approximately 25% 5-year survival. Current histo-clinical prognostic factors are insufficient to capture the complex cascade of events that drive the heterogeneous clinical behaviour of the disease. There is a crucial need to identify new prognostic subclasses of disease as well as new therapeutic targets. Today, DNA microarrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a tumour sample. They have been applied to ovarian cancer research for predicting initial surgical resectability, survival and response to first-line chemotherapy. The first results are promising. In this review, we describe recent applications of DNA microarrays in ovarian cancer research and discuss some issues to address in the near future to allow the technology to reach its full potential in clinical practice.

Angiogenesis-related gene expression profile with independent prognostic value in advanced ovarian carcinoma

Background

Ovarian carcinoma is the most important cause of gynecological cancer-related mortality in Western societies. Despite the improved median overall survival in patients receiving chemotherapy regimens such as paclitaxel and carboplatin combination, relapse still occurs in most advanced diseased patients. Increased angiogenesis is associated with rapid recurrence and decreased survival in ovarian cancer. This study was planned to identify an angiogenesis-related gene expression profile with prognostic value in advanced ovarian carcinoma patients.

Methodology/Principal Findings

RNAs were collected from formalin-fixed paraffin-embedded samples of 61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a carboplatin plus paclitaxel regimen. Expression levels of 82 angiogenesis related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. A 34-gene-profile which was able to predict the overall survival of ovarian carcinoma patients was identified. After a leave-one-out cross validation, the profile distinguished two groups of patients with different outcomes. Median overall survival and progression-free survival for the high risk group was 28.3 and 15.0 months, respectively, and was not reached by patients in the low risk group at the end of follow-up. Moreover, the profile maintained an independent prognostic value in the multivariate analysis. The hazard ratio for death was 2.3 (95% CI, 1.5 to 3.2; p<0.001).

Conclusions/Significance

It is possible to generate a prognostic model for advanced ovarian carcinoma based on angiogenesis-related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of angiogenesis genes in the prognosis of ovarian carcinoma.

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

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

Four potential biomarkers as prognostic factors in stage III serous ovarian adenocarcinomas

The mortality rate for patients with ovarian carcinomas is high and the available prognostic factors are insufficient. The use of biomarkers may contribute to better prediction and survival for these patients. We aimed to study the gene and protein expressions for 7 potential biomarkers, to determine if it is possible to use them as prognostic factors. Genes selected from our previous microarray analysis (2006), CLU, ITGB3, TACC1, MUC5B, CAPG, PRAME and TROAP, were analyzed in 19 of the tumors with quantitative real-time polymerase chain reaction (QPCR). We found that CLU and ITGB3 were more expressed in tumors from survivors and PRAME and CAPG were more expressed in tumors from deceased patients. None of the other 3 genes were significantly differently expressed. The protein expressions of CLU, ITGB3, PRAME and CAPG were analyzed in 43 of the tumors with western blot for semiquantitative analysis. We established that the mRNA and protein expressions correlated and that all 4 proteins were significantly differently expressed. Further, immunohistochemistry (IHC) was used to localize the expression of the proteins in the tumor samples. According to our results, the 4 biomarkers CLU, ITGB3, PRAME and CAPG may be used as prognostic factors for patients with stage III serous ovarian adenocarcinomas.

A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer

Despite the existence of morphologically indistinguishable disease, patients with advanced ovarian tumors display a broad range of survival end points. We hypothesize that gene expression profiling can identify a prognostic signature accounting for these distinct clinical outcomes. To resolve survival-associated loci, gene expression profiling was completed for an extensive set of 185 (90 optimal/95 suboptimal) primary ovarian tumors using the Affymetrix human U133A microarray. Cox regression analysis identified probe sets associated with survival in optimally and suboptimally debulked tumor sets at a P value of <0.01. Leave-one-out cross-validation was applied to each tumor cohort and confirmed by a permutation test. External validation was conducted by applying the gene signature to a publicly available array database of expression profiles of advanced stage suboptimally debulked tumors. The prognostic signature successfully classified the tumors according to survival for suboptimally (P = 0.0179) but not optimally debulked (P = 0.144) patients. The suboptimal gene signature was validated using the independent set of tumors (odds ratio, 8.75; P = 0.0146). To elucidate signaling events amenable to therapeutic intervention in suboptimally debulked patients, pathway analysis was completed for the top 57 survival-associated probe sets. For suboptimally debulked patients, confirmation of the predictive gene signature supports the existence of a clinically relevant predictor, as well as the possibility of novel therapeutic opportunities. Ultimately, the prognostic classifier defined for suboptimally debulked tumors may aid in the classification and enhancement of patient outcome for this high-risk population.

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.

A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer

Despite the existence of morphologically indistinguishable disease, patients with advanced ovarian tumors display a broad range of survival end points. We hypothesize that gene expression profiling can identify a prognostic signature accounting for these distinct clinical outcomes. To resolve survival-associated loci, gene expression profiling was completed for an extensive set of 185 (90 optimal/95 suboptimal) primary ovarian tumors using the Affymetrix human U133A microarray. Cox regression analysis identified probe sets associated with survival in optimally and suboptimally debulked tumor sets at a P value of <0.01. Leave-one-out cross-validation was applied to each tumor cohort and confirmed by a permutation test. External validation was conducted by applying the gene signature to a publicly available array database of expression profiles of advanced stage suboptimally debulked tumors. The prognostic signature successfully classified the tumors according to survival for suboptimally (P = 0.0179) but not optimally debulked (P = 0.144) patients. The suboptimal gene signature was validated using the independent set of tumors (odds ratio, 8.75; P = 0.0146). To elucidate signaling events amenable to therapeutic intervention in suboptimally debulked patients, pathway analysis was completed for the top 57 survival-associated probe sets. For suboptimally debulked patients, confirmation of the predictive gene signature supports the existence of a clinically relevant predictor, as well as the possibility of novel therapeutic opportunities. Ultimately, the prognostic classifier defined for suboptimally debulked tumors may aid in the classification and enhancement of patient outcome for this high-risk population.

Evaluation of biomarker panels for early stage ovarian cancer detection and monitoring for disease recurrence

OBJECTIVE

To determine the utility of novel combinations of biomarkers, using both a one-step and two-step assay format, to distinguish serum of early ovarian cancer patients from that of healthy controls and to discern the utility of these biomarkers in a monitoring capacity.

METHODS

For ovarian cancer detection, HE4, Glycodelin, MMP7, SLPI, Plau-R, MUC1, Inhibin A, PAI-1, and CA125 were evaluated in a cohort of 200 women with ovarian cancer and 396 healthy age-matched controls. Each biomarker was assessed by serum-based immunoassays utilizing novel monoclonal antibody pairs or commercial kits. For detection of disease recurrence, HE4, Glycodelin, MMP7 and CA125 were evaluated in 260 samples from 30 patients with OC monitored longitudinally after diagnosis.

RESULTS

Based upon ROC curve analysis, the sensitivity/specificity of specific biomarker combination algorithms ranged from 59.0%/99.7% to 80.5%/96.5% for detection of early stage ovarian cancer and 76.9%/99.7% to 89.2%/97.2% for detection of late stage cancer. In monitoring evaluation of 27 patients who experienced recurrence of OC, sensitivity for predicting recurrence was 100% for the biomarker panel and 96% for CA125. At least one of the panel biomarkers was elevated earlier (range 6-69 weeks) than CA125 and prior to clinical evidence of recurrence in 14/27 (52%) patients.

CONCLUSIONS

We have developed and demonstrated the utility of several one- and two-step multi-marker combinations with acceptable test characteristics for possible use in an ovarian cancer screening population. A subset of this panel may also provide adjunctive information to rising CA125 levels in disease monitoring.

Motility-related actinin alpha-4 is associated with advanced and metastatic ovarian carcinoma

Advanced and metastatic ovarian cancer is a leading cause of death from gynecologic malignancies. A more detailed understanding of the factors controlling invasion and metastasis may lead to novel anti-metastatic therapies. To model cellular interactions that occur during intraperitoneal metastasis, comparative cDNA microarray analysis and confirmatory real-time reverse transcription PCR (RT-PCR) were employed to uncover changes in gene expression that may occur in late stage ovarian cancer in response to microenvironmental cues, particularly native three-dimensional collagen I. Gene expression in human ovarian carcinoma tissues was evaluated on the RNA and protein level using real-time RT-PCR and immunohistochemistry. Cell invasion and migration were evaluated in a collagen invasion assay and a scratch wound assay. Three-dimensional collagen I culture led to differential expression of several genes. The role of actinin alpha-4 (ACTN4), a cytoskeleton-associated protein implicated in the regulation of cell motility, was examined in detail. ACTN4 RNA and protein expression were associated with advanced and metastatic human ovarian carcinoma. This report demonstrates that a cytoskeletal-associated protein ACTN4 is upregulated by three-dimensional collagen culture conditions, leading to increased invasion and motility of ovarian cancer cells. Expression of ACTN4 in human ovarian tumors was found to be associated with advanced-stage disease and peritoneal metastases.