Predicting biomarkers for ovarian cancer using gene-expression microarrays

Hepsin colocalizes with desmosomes and induces progression of ovarian cancer in a mouse model

Hepsin is a serine protease that is widely expressed in different tissues and cell types, most prominently in the normal liver and kidney. Overexpression of hepsin has been associated with prostate cancers, ovarian cancers and renal cell carcinomas. The physiological functions of hepsin in normal tissues and tumors are poorly understood. To gain insight into its function in ovarian cancer, we analyzed the expression and subcellular localization of hepsin protein in ovarian cancer cell lines and tumors. We showed that the membrane-associated hepsin protein is present at desmosomal junctions, where it colocalizes with its putative proteolytic substrate hepatocyte growth factor. Consistent with the growing evidence that desmosomal junctions and their constituents play a role in cancer progression, we demonstrated that overexpression of hepsin promotes ovarian tumor growth in a mouse model. The ability of ectopic hepsin to induce tumor growth in mice is abrogated by the mutation of 3 critical residues in the catalytic domain, thus implicating the enzymatic activity of hepsin in promoting tumor progression.

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.

Prediction of ovarian cancer prognosis and response to chemotherapy by a serum-based multiparametric biomarker panel

Currently, there are no effective biomarkers for ovarian cancer prognosis or prediction of therapeutic response. The objective of this study was to examine a panel of 10 serum biochemical parameters for their ability to predict response to chemotherapy, progression and survival of ovarian cancer patients. Sera from ovarian cancer patients were collected prior and during chemotherapy and were analysed by enzyme-linked immunosorbent assay for CA125, kallikreins 5, 6, 7, 8, 10 and 11, B7-H4, regenerating protein IV and Spondin-2. The odds ratio and hazard ratio and their 95% confidence interval (95% CI) were calculated. Time-dependent receiver-operating characteristic (ROC) curves were utilised to evaluate the prognostic performance of the biomarkers. The levels of several markers at baseline (c₀), or after the first chemotherapy cycle (rc₁), predicted chemotherapy response and overall or progression-free survival in univariate analysis. A multiparametric model (c₀ of CA125, KLK5, KLK7 and rc₁ of CA125) provided predictive accuracy with area under the ROC curve (AUC) of 0.82 (0.62 after correction for overfitting). Another marker combination (c₀ of KLK7, KLK10, B7-H4, Spondin-2) was useful in predicting short-term (1-year) survival with an AUC of 0.89 (0.74 after correction for overfitting). All markers examined, except KLK7 and regenerating protein IV, were powerful predictors of time to progression (TTP) among chemotherapy responders. Individual and panels of biomarkers from the kallikrein family (and other families) can predict response to chemotherapy, overall survival, short-term (1-year) survival, progression-free survival and TTP of ovarian cancer patients treated with chemotherapy.

Mammaglobin B expression in human endometrial cancer

Mammaglobin B (MGB-2) is an uteroglobin gene family member recently found highly differentially expressed in ovarian cancer by gene expression profiling. To evaluate its potential as a novel endometrial cancer biomarker, in this study we quantified and compared MGB-2 expression at messenger RNA and protein levels in endometrial tumors (endometrioid endometrial cancer [EEC]) with different grades of differentiation. MGB-2 expression was evaluated by real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) in fresh frozen biopsies and paraffin-embedded tissues derived from a total of 70 patients including 50 primary EEC and 20 normal endometria (NECs). High levels of MGB-2 gene expression were detected in 10 of 11 EEC G1 cases (91%), 16 of 17 EEC G2 cases (94%), and 6 of 22 EEC G3 cases (27%) by real-time PCR. In contrast, normal endometrial cells expressed low to negligible levels of MGB-2 by real-time PCR (P= 0.002 EEC vs NEC). Well- and moderately differentiated EECs overexpressed MGB-2 gene at significant higher levels when compared to NECs (P< 0.01). Pairwise differences between both G2 and G1 vs G3 cases for MGB-2 relative gene expression values were also statistically significant (G2 vs G3 P< 0.001, G1 vs G3 P= 0.016). MGB-2 protein expression was detected in 31 (86%) of 36 EEC and 0 of 5 atrophic NEC controls, while seven of eight (88%) of the proliferative/secretory/hyperplastic NECs focally expressed MGB-2 by IHC. MGB-2 is highly expressed in EEC, particularly in well- and moderately differentiated tumors, and may represent a novel molecular marker for EEC.

HMGA2 gene is a promising target for ovarian cancer silencing therapy

Ovarian cancer is one of the most lethal gynecological malignancies and the small success rate of routine therapeutic methods justifies efforts to develop new approaches. Evaluation of targets for effective inhibition of ovarian cancer cell growth should precipitate clinical application of gene silencing therapy. In our previous work, we showed upregulation of HMGA2 gene expression as a result of Ras-induced rat ovarian surface epithelial cell transformation. This gene codes the HMGA2 protein, a member of the high-mobility group AT-hook (HMGA) family of nonhistone chromatin proteins. Genome-wide studies revealed upregulation of the HMGA2 gene in human ovarian carcinomas. Herein we have evaluated over-expression of the HMGA2 gene, relevant to ovarian cancer, in subsets of human specimens and cell lines by in situ RNA hybridization and RT-PCR. Transient silencing of HMGA2 gene by means of siRNA inhibited proliferation of those ovarian cancer cells, which over-express this gene initially. Growth suppression was mediated by cell-cycle arrest. Stable silencing of highly expressed HMGA2 gene by shRNAi in A27/80, Ovcar-3 and OAW-42 ovarian cancer cell lines resulted in growth inhibition because of G1 arrest and increase of apoptosis as well. The tumor growth inhibition effect of HMGA2 silencing for Ovcar-3 cells was validated in vivo. Our findings revealed that the HMGA2 gene represents a promising target for gene silencing therapy in ovarian cancer.

A multiparametric panel for ovarian cancer diagnosis, prognosis, and response to chemotherapy

PURPOSE

Our goal was to examine a panel of 11 biochemical variables, measured in cytosolic extracts of ovarian tissues (normal, benign, and malignant) by quantitative ELISAs for their ability to diagnose, prognose, and predict response to chemotherapy of ovarian cancer patients.

EXPERIMENTAL DESIGN

Eleven proteins were measured (9 kallikreins, B7-H4, and CA125) in cytosolic extracts of 259 ovarian tumor tissues, 50 tissues from benign conditions, 35 normal tissues, and 44 tissues from nonovarian tumors that metastasized to the ovary. Odds ratios and hazard ratios and their 95% confidence interval were calculated. Time-dependent receiver operating characteristic curves for censored survival data were used to evaluate the performance of the biomarkers. Resampling was used to validate the performance.

RESULTS

Most biomarkers effectively separated cancer from noncancer groups. A composite marker provided an area under the curve of 0.97 (95% confidence interval, 0.95-0.99) for discriminating normal and cancer groups. Univariately, hK5 and hK6 were positively associated with progression. After adjusting for clinical variables in multivariate analysis, both hK10 and hK11 significantly predicted time to progression. Increasing levels of hK13 were associated with chemotherapy response, and the predictive power of hK13 to chemotherapy response was improved by a panel of five biomarkers.

CONCLUSIONS

The evidence shows that a group of kallikreins and multiparametric combinations with other biomarkers and clinical variables can significantly assist with ovarian cancer classification, prognosis, and response to platinum-based chemotherapy. In particular, we developed a multiparametric strategy for predicting ovarian cancer response to chemotherapy, comprising several biomarkers and clinical features.

Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach

OBJECTIVE

The advent of microarrays has attracted considerable interest from biologists due to the potential for high throughput analysis of hundreds of thousands of gene transcripts. Subsequent analysis of the data may identify specific features which correspond to characteristics of interest within the population, for example, analysis of gene expression profiles in cancer patients to identify molecular signatures corresponding with prognostic outcome. These high throughput technologies have resulted in an unprecedented rate of data generation, often of high complexity, highlighting the need for novel data analysis methodologies that will cope with data of this nature.

METHODS

Stepwise methods using artificial neural networks (ANNs) have been developed to identify an optimal subset of predictive gene transcripts from highly dimensional microarray data. Here these methods have been applied to a gene microarray dataset to identify and validate gene signatures corresponding with estrogen receptor and lymph node status in breast cancer.

RESULTS

Many gene transcripts were identified whose expression could differentiate patients to very high accuracies based upon firstly whether they were positive or negative for estrogen receptor, and secondly whether metastasis to the axillary lymph node had occurred. A number of these genes had been previously reported to have a role in cancer. Significantly fewer genes were used compared to other previous studies. The models using the optimal gene subsets were internally validated using an extensive random sample cross-validation procedure and externally validated using a follow up dataset from a different cohort of patients on a newer array chip containing the same and additional probe sets. Here, the models retained high accuracies, emphasising the potential power of this approach in analysing complex systems. These findings show how the proposed method allows for the rapid analysis and subsequent detailed interrogation of gene expression signatures to provide a further understanding of the underlying molecular mechanisms that could be important in determining novel prognostic markers associated with cancer.

15-Lipoxygenase-2 is differentially expressed in normal and neoplastic ovary

Ovarian cancer is a major cause of lethality from gynecological malignancies, and there is a lack of reliable and specific serum markers for this disease. Eicosanoid-related enzymes have previously been implicated in the pathogenesis of various types of cancer, but little is known about the relevance of lipoxygenase isoforms in ovarian cancer and the results on cyclooxygenases are conflicting. For this study, we quantified the expression of eicosanoid-related enzymes (cyclooxygenase-1 and cyclooxygenase-2, 15-lipoxygenase-1 and lipoxygenase-2, 5-lipoxygenase) in normal and malignant human ovarian tissue by real-time polymerase chain reaction and found a 22-fold elevated expression of 15-lipoxygenase-2 in malignant specimens when compared with normal ovarian tissue (P=0.001). In ovarian carcinoma metastases, expression of the enzyme was also augmented (20-fold upregulation, P=0.004). For 15-lipoxygenase-1 and cyclooxygenase-2, we did not observe differential expression, but there was a trend for increased steady-state concentrations of cyclooxygenase-1 (P=0.1 for ovarian carcinoma, P=0.011 for metastases) and 5-lipoxygenase (P=0.1 for ovarian carcinoma, P=0.018 for metastases, respectively). These data indicate that expression of 15-lipoxygenase-2 mRNA is strongly augmented during ovarian carcinogenesis and that the enzyme may constitute a suitable candidate as a tumor marker.

Linking the ovarian cancer transcriptome and immunome

Background

Autoantigens have been reported in a variety of tumors, providing insight into the interplay between malignancies and the immune response, and also giving rise to novel diagnostic and therapeutic concepts. Why certain tumor-associated proteins induce an immune response remains largely elusive.

Results

This paper analyzes the proposed link between increased abundance of a protein in cancerous tissue and the increased potential of the protein for induction of a humoral immune response, using ovarian cancer as an example. Public domain data sources on differential gene expression and on autoantigens associated with this malignancy were extracted and compared, using bioinformatics analysis, on the levels of individual genes and proteins, transcriptional coregulation, joint functional pathways, and shared protein-protein interaction networks. Finally, a selected list of ovarian cancer-associated, differentially regulated proteins was tested experimentally for reactivity with antibodies prevalent in sera of ovarian cancer patients.

Genes reported as showing differential expression in ovarian cancer exhibited only minor overlap with the public domain list of ovarian cancer autoantigens. However, experimental screening for antibodies directed against antigenic determinants from ovarian cancer-associated proteins yielded clear reactions with sera.

Conclusion

A link between tumor protein abundance and the likelihood of induction of a humoral immune response in ovarian cancer appears evident.

Expression and biological role of the prostaglandin D synthase/SOX9 pathway in human ovarian cancer cells

New therapeutic strategies for ovarian cancer include the identification of involved signaling pathways that could potentially serve as a source of biomarkers for early stages of the disease. In this study, we show that the embryonic male prostaglandin D synthase (Pgds)/SOX9 pathway is expressed at both the RNA and protein levels in different types of human ovarian tumors, pointing to Pgds and SOX9 as possible diagnostic markers for ovarian carcinomas. Using ovarian cancer cell lines, we found, first, that components of the Pgds/SOX9 pathway are expressed in these cells, and second, that treatment of these cells with prostaglandin D2 (PGD2) can inhibit their growth via its DP1 receptor and induce apoptosis. Finally, using siRNA and overexpression strategies, we demonstrate that SOX9 expression is induced by PDG2 and is responsible for PDG2-mediated growth inhibition. Accordingly, as stimulating the PGD2/DP1 signal transduction pathway upregulates SOX9 expression, either activators of this pathway or DP1 agonists may be useful as new therapeutic agents.

Overexpression of mammaglobin B in epithelial ovarian carcinomas

OBJECTIVE

Mammaglobin B is a uteroglobin gene family member recently found highly differentially expressed in serous papillary ovarian cancer by gene expression profiling. In order to evaluate its potential as a novel ovarian cancer biomarker, in this study we quantified and compared Mammaglobin B expression in various histologic types of epithelial ovarian carcinomas (EOC).

METHODS

Mammaglobin B expression was evaluated by real-time PCR and/or immunohistochemistry in fresh-frozen biopsies and paraffin-embedded tissues derived from a total of 137 patients including 69 primary EOC with different histologies, 28 serous papillary omental metastasis, 8 borderline tumors, 26 benign cystadenomas and 14 normal ovaries.

RESULTS

High levels of Mammaglobin B gene expression were detected in 100% (68 out of 68) of the ovarian cancer biopsies tested by real-time PCR. In contrast, normal human ovarian surface epithelium (HOSE) expressed negligible levels of Mammaglobin B mRNA (EOC versus HOSE, p<0.01). Although Mammaglobin B gene expression levels were higher in endometrioid, mucinous and undifferentiated tumors when compared to serous papillary tumors, clear cell tumors and those with mixed histology, these differences were not statistically significant. In agreement with real-time PCR results, EOC were found to express significantly higher levels of Mammaglobin B protein when compared to normal ovaries and benign cystadenomas (p<0.01). However, only 29 out of 68 (42%) of the EOC samples found positive for Mammaglobin B by real-time PCR showed immunoreactivity by IHC.

CONCLUSIONS

Mammaglobin B gene is highly expressed in EOC and may represent a novel molecular marker for multiple histological types of ovarian cancer. Additional studies to evaluate the clinical utility of Mammaglobin B as a diagnostic and/or therapeutic target in ovarian cancer are warranted.

Genetic intra-tumour heterogeneity in epithelial ovarian cancer and its implications for molecular diagnosis of tumours

Genetic analysis of solid tumours using DNA or cDNA expression microarrays may enable individualized treatment based on the profiles of genetic changes that are identified from each patient. This could result in better response to adjuvant chemotherapy and, consequently, improved clinical outcome. So far, most research studies that have tested the efficacy of such an approach have sampled only single areas of neoplastic tissue from tumours; this assumes that the genetic profile within solid tumours is homogeneous throughout. The aim of this study was to evaluate the extent of genetic intra-tumour heterogeneity (ITH) within a series of epithelial ovarian cancers. Several different regions (five to eight regions) of tumour tissue from 16 grade 3, serous epithelial ovarian cancers were analysed for genetic alterations using a combination of microsatellite analysis and single nucleotide polymorphism (SNP) analysis, in order to establish the extent of ITH. Maximum parsimony tree analysis was applied to the genetic data from each tumour to evaluate the clonal relationship between different regions within tumours. Extensive ITH was identified within all ovarian cancers using both microsatellite and SNP analysis. Evolutionary analysis of microsatellite data suggested that the origin of all tumours was monoclonal, but that subsequent clonal divergence created mixed populations of genetically distinct cells within the tumour. SNP analysis suggested that ITH was not restricted to random genetic changes, but affected genes that have an important functional role in ovarian cancer development. The frequent occurrence of ITH within epithelial ovarian cancers may have implications for the interpretation of genetic data generated from emerging technologies such as DNA and mRNA expression microarrays, and their use in the clinical management of patients with ovarian cancer. The basis of genetic ITH and the possible implications for molecular approaches to clinical diagnosis of ovarian cancers may apply to other tumour types.

Molecular targets in gynaecological cancers

The application of high throughput expression profiling and other advanced molecular biology laboratory techniques has revolutionised the management of cancers and is gaining attention in the field of gynaecological cancers. Such new approaches may help to improve our understanding of carcinogenesis and facilitate screening and early detection of gynaecological cancers and their precursors. Individualised prediction of patients' responses to therapy and design of personalised molecular targeted therapy is also possible. The studies of various molecular targets involved in the various signal pathways related to carcinogenesis are particularly relevant to such applications. At the moment, the application of detection and genotyping of human papillomavirus in management of cervical cancer is one of the most well established appliances of molecular targets in gynaecological cancers. Methylation, telomerase and clonality studies are also potentially useful, especially in assisting diagnosis of difficult clinical scenarios. This post-genomic era of clinical medicine will continue to make a significant impact in routine pathology practice. The contribution of pathologists is indispensable in analysis involving tissue microarray. On the other hand, both pathologists and bedside clinicians should be aware of the limitation of these molecular targets. Interpretation must be integrated with clinical and histopathological context to avoid misleading judgement. The importance of quality assurance of all such molecular techniques and their ethical implications cannot be over-emphasised.

Emerging roles for PAX8 in ovarian cancer and endosalpingeal development

OBJECTIVES

Epithelial ovarian carcinomas develop from ovarian surface epithelia that undergo complex differentiation to form distinguishable phenotypes resembling those of the epithelia of the female urogenital regions. While previous studies have implicated regulatory developmental homeobox (HOX) genes in this process, other factors responsible for this differentiation are largely unknown. Aberrant transcriptional expression of PAX8 has been reported in epithelial ovarian cancer, prompting us to initiate the molecular characterization of this master regulatory gene in ovarian cancer development.

METHODS

Immunohistochemistry, immunoblotting and RT-PCR were used to investigate the presence of PAX8 and its protein products in epithelial ovarian cancer subtypes, normal ovarian surface epithelia, ovarian inclusion cysts and normal endosalpingeal epithelia.

RESULTS

In this report, we confirm microarray results indicating that the transcription factor, PAX8, is highly expressed in epithelial ovarian cancer but absent from the precursor ovarian surface epithelia of healthy individuals. Furthermore, we report that PAX8 is localized to the nucleus of non-ciliated epithelia in simple ovarian epithelial inclusion cysts and in three epithelial ovarian cancer subtypes (serous, endometrioid and clear cell). We also determined that PAX8 is expressed in the non-ciliated, secretory cells of healthy fallopian tube mucosal linings but not in the adjacent ciliated epithelia.

CONCLUSION

These findings support the hypothesis that PAX8 plays parallel roles in the development of epithelial ovarian cancer and in the developmental differentiation of coelomic epithelia into endosalpingeal epithelia.

Human tissue kallikreins: the cancer biomarker family

Human tissue kallikreins (KLKs) are attracting increased attention due to their role as biomarkers for the screening, diagnosis, prognosis, and monitoring of various cancers including those of the prostate, ovarian, breast, testicular, and lung. Human tissue kallikrein genes represent the largest contiguous group of proteases within the human genome. Originally thought to consist of three genes, the identification of the human kallikrein locus has expanded this number to fifteen. These genes, and their encoded proteins, share a high degree of homology and are expressed in different tissues. Prostate-specific antigen (PSA), the most commonly known kallikrein, is a useful biomarker for prostate cancer. Several other kallikreins, including kallikreins 2 (KLK2) and 11 (KLK11) are emerging as complementary prostate cancer biomarkers. Along with these kallikreins, several others have been implicated in the other cancers. For example, KLK5, 6, 7, 10, 11, and 14 are emerging biomarkers for ovarian cancer. The identification of kallikrein substrates and the development of proteolytic cascade models implicate kallikrein proteins in cancer progression. This review describes the current status of kallikreins as cancer biomarkers.

Differential gene expression profiles between tumor biopsies and short-term primary cultures of ovarian serous carcinomas: Identification of novel molecular biomarkers for early diagnosis and therapy

OBJECTIVE

To identify novel molecular biomarkers useful for the early diagnosis and therapy of ovarian cancer by gene expression profiling. To compare the genetic fingerprints of flash-frozen ovarian serous carcinomas to those of matched highly purified primary tumor cell cultures.

METHODS

Gene expression profiles of 19 flash-frozen ovarian serous papillary carcinoma (OSPC) were analyzed and compared to 15 controls (highly purified human ovarian surface epithelium short-term cultures, HOSE) using oligonucleotide microarrays complementary to >14,500 human genes. In addition, gene expression profiling of 5 highly purified primary OSPC cultured in vitro for less than 2 weeks was compared to flash-frozen ovarian carcinoma biopsies obtained from matched samples. Quantitative RT-PCR and IHC staining techniques were used to validate microarray data at RNA and protein levels for some of the differentially expressed genes.

RESULTS

Unsupervised analysis of gene expression data readily distinguished normal tissue from flash-frozen OSPC and identified 901 and 557 genes that exhibited >3-fold up-regulation or down-regulation, respectively, in OSPC when compared to HOSE. Mammaglobin 2, an ovarian secreted protein, was identified as the top differentially expressed gene in OSPC (19 out 19 OSPC versus 0 out of 15 HOSE) with over 827-fold up-regulation relative to HOSE. The claudin and kallikrein family of proteins including the clostridium perfringens enterotoxin receptors claudin 3 and 4, kallikreins 6, 7, 8, 10, 11 and the immunomodulatory molecule B7-H4 were found among the most highly overexpressed genes in OSPC when compared to HOSE. Genetic fingerprints of flash-frozen OSPC were found to have high correlation with those of purified primary OSPC short-term in vitro cultures with only 31 out of 8,637 genes (0.35%) differentially expressed between the two groups.

CONCLUSIONS

Short-term in vitro culture of primary ovarian carcinomas may greatly increase the purity of ovarian tumor RNA available for gene expression profiling without causing major alteration in OSPC fingerprints. Mammaglobin 2, kallikreins 6, 7, 8, 10, 11, claudin 3 and 4 and B7-H4 gene expression products represent candidate biomarkers endowed with great potential for early screening and therapy of OSPC patients.

Expression analysis of stage III serous ovarian adenocarcinoma distinguishes a sub-group of survivors

It is difficult to predict the clinical outcome for patients with ovarian cancer. However, the use of biomarkers as additional prognostic factors may improve the outcome for these patients. In order to find novel candidate biomarkers, differences in gene expressions were analysed in 54 stage III serous ovarian adenocarcinomas with oligonucleotide microarrays containing 27,000 unique probes. The microarray data was verified with quantitative real-time polymerase chain reaction for the genes TACC1, MUC5B and PRAME. Using hierarchical cluster analysis we detected a sub-group that included 60% of the survivors. The gene expressions in tumours from patients in this sub-group of survivors were compared with the remaining tumours, and 204 genes were found to be differently expressed. We conclude that the sub-group of survivors might represent patients with favourable tumour biology and sensitivity to treatment. A selection of the 204 genes might be used as a predictive model to distinguish patients within and outside of this group. Alternative chemotherapy strategies could then be offered as first-line treatment, which may lead to improvements in the clinical outcome for these patients.

Genomics and the Impact of New Technologies on the Management of Colorectal Cancer

High-throughput genomic technologies have the potential to have a major impact on preclinical and clinical drug development and the selection and stratification of patients in clinical trials. These technologies, which are at varying stages of commercialization, include array-based comparative genomic hybridization, single-nucleotide polymorphism arrays, and (the most mature example) expression-based arrays. One of the rate-limiting steps in the routine clinical application of expression array-based technology is the need for suitable clinical samples. One of the major challenges moving forward, therefore, relates to the ability to use formalin-fixed, paraffin-embedded--derived tissue in expression profiling-based approaches.

Gene expression profiling of human ovarian tumours

There is currently a lack of reliable diagnostic and prognostic markers for ovarian cancer. We established gene expression profiles for 120 human ovarian tumours to identify determinants of histologic subtype, grade and degree of malignancy. Unsupervised cluster analysis of the most variable set of expression data resulted in three major tumour groups. One consisted predominantly of benign tumours, one contained mostly malignant tumours, and one was comprised of a mixture of borderline and malignant tumours. Using two supervised approaches, we identified a set of genes that distinguished the benign, borderline and malignant phenotypes. These algorithms were unable to establish profiles for histologic subtype or grade. To validate these findings, the expression of 21 candidate genes selected from these analyses was measured by quantitative RT–PCR using an independent set of tumour samples. Hierarchical clustering of these data resulted in two major groups, one benign and one malignant, with the borderline tumours interspersed between the two groups. These results indicate that borderline ovarian tumours may be classified as either benign or malignant, and that this classifier could be useful for predicting the clinical course of borderline tumours. Immunohistochemical analysis also demonstrated increased expression of CD24 antigen in malignant versus benign tumour tissue. The data that we have generated will contribute to a growing body of expression data that more accurately define the biologic and clinical characteristics of ovarian cancers.

Identification of genes associated with ovarian cancer metastasis using microarray expression analysis

Although the transition from early- to advanced-stage ovarian cancer is a critical determinant of survival, little is known about the molecular underpinnings of ovarian metastasis. We hypothesize that microarray analysis of global gene expression patterns in primary ovarian cancer and metastatic omental implants can identify genes that underlie the metastatic process in epithelial ovarian cancer. We utilized Affymetrix U95Av2 microarrays to characterize the molecular alterations that underlie omental metastasis from 47 epithelial ovarian cancer samples collected from multiple sites in 20 patients undergoing primary surgical cytoreduction for advanced-stage (IIIC/IV) serous ovarian cancer. Fifty-six genes demonstrated differential expression between ovarian and omental samples (P < 0.01), and twenty of these 56 differentially expressed genes have previously been implicated in metastasis, cell motility, or cytoskeletal function. Ten of the 56 genes are involved in p53 gene pathways. A Bayesian statistical tree analysis was used to identify a 27-gene expression pattern that could accurately predict the site of tumor (ovary versus omentum). This predictive model was evaluated using an external data set. Nine of the 27 predictive genes have previously been shown to be involved in oncogenesis and/or metastasis, and 10/27 genes have been implicated in p53 pathways. Microarray findings were validated by real-time quantitative PCR. We conclude that gene expression patterns that distinguish omental metastasis from primary epithelial ovarian cancer can be identified and that many of the genes have functions that are biologically consistent with a role in oncogenesis, metastasis, and p53 gene networks.

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.

Human kallikrein 8 protein is a favorable prognostic marker in ovarian cancer

Human kallikrein 8 (hK8/neuropsin/ovasin; encoded by KLK8) is a steroid hormone-regulated secreted serine protease differentially expressed in ovarian carcinoma. KLK8 mRNA levels are associated with a favorable patient prognosis and hK8 protein levels are elevated in the sera of 62% ovarian cancer patients, suggesting that KLK8/hK8 is a prospective biomarker. Given the above, the aim of the present study was to determine if tissue hK8 bears any prognostic significance in ovarian cancer. Using a newly developed ELISA, hK8 was quantified in 136 ovarian tumor extracts and correlated with clinicopathologic variables and outcome [progression-free survival (PFS); overall survival (OS)] over a median follow-up period of 42 months. hK8 levels in ovarian tumor cytosols ranged from 0 to 478 ng/mg total protein, with a median of 30 ng/mg. An optimal cutoff value of 25.8 ng/mg total protein (74th percentile) was selected based on the ability of hK8 values to predict the PFS of the study population and to categorize tumors as hK8 positive or negative. Women with hK8-positive tumors most often had lower-grade tumors (G1), no residual tumor after surgery, and optimal debulking success (P < 0.05). Univariate and multivariate analyses revealed that patients with hK8-positive tumors had a significantly longer PFS and OS than hK8-negative patients (P < 0.05). Kaplan-Meier survival curves further confirmed a reduced risk of relapse and death in women with hK8-positive tumors (P = 0.001 and P = 0.014, respectively). These results indicate that hK8 is an independent marker of favorable prognosis in ovarian cancer.

Gene expression profiling of primary cultures of ovarian epithelial cells identifies novel molecular classifiers of ovarian cancer

In order to elucidate the biological variance between normal ovarian surface epithelial (NOSE) and epithelial ovarian cancer (EOC) cells, and to build a molecular classifier to discover new markers distinguishing these cells, we analysed gene expression patterns of 65 primary cultures of these tissues by oligonucleotide microarray. Unsupervised clustering highlights three subgroups of tumours: low malignant potential tumours, invasive solid tumours and tumour cells derived from ascites. We selected 18 genes with expression profiles that enable the distinction of NOSE from these three groups of EOC with 92% accuracy. Validation using an independent published data set derived from tissues or primary cultures confirmed a high accuracy (87–96%). The distinctive expression pattern of a subset of genes was validated by quantitative reverse transcription–PCR. An ovarian-specific tissue array representing tissues from NOSE and EOC samples of various subtypes and grades was used to further assess the protein expression patterns of two differentially expressed genes (Msln and BMP-2) by immunohistochemistry. This study highlights the relevance of using primary cultures of epithelial ovarian cells as a model system for gene profiling studies and demonstrates that the statistical analysis of gene expression profiling is a useful approach for selecting novel molecular tumour markers.

Early diagnosis and predictors of malignancy of adnexal masses

PURPOSE OF REVIEW

Ovarian cancer is an important cause of death among women with a malignant gynecological tumor. Cure rates for the disease at an early stage are around 80-90%, but survival is only 50% as the majority of women already show advanced disease upon diagnosis. The combination of gynecological examination, ultrasonography, and systemic tumor marker assay is considered to be a good strategy for the early diagnosis of ovarian neoplasia.

RECENT FINDINGS

Today, new technologies such as ultrasonography and tumor marker assay have increased the diagnosis rate for adnexal masses. These non-invasive methods, however, frequently do not distinguish benign conditions from malignant ones, which results in unnecessary surgery. Transvaginal ultrasonography is useful for diagnosing adnexal masses, but benign and malignant adnexal masses can present similar morphological characteristics. Combination with color Doppler ultrasonography and/or tumor markers may improve the accuracy of the method. Gene-expression array, proteomics and mathematical models form new approaches, but proper prospective studies are needed to validate them.

SUMMARY

The techniques of pelvic examination, ultrasonography, color Doppler ultrasonography, and tumor markers can be indicated for the diagnosis of ovarian cancer. The differentiation between benign and malignant ovarian tumor is, however, a clinical challenge. Until better diagnostic methods become available, patients and their physicians can use these techniques to decide on management.

Expression profiling correlates with treatment response in women with advanced serous epithelial ovarian cancer

The majority of epithelial ovarian carcinomas are of serous subtype, with most women presenting at an advanced stage. Approximately 70% respond to initial chemotherapy but eventually relapse. We aimed to find markers of treatment response that might be suitable for routine use, using the gene expression profile of tumor tissue. Thirty one women with histologically-confirmed late-stage serous ovarian cancer were classified into 3 groups based on response to treatment (nonresponders, responders with relapse less than 12 months and responders with no relapse within 12 months). Gene expression profiles of these specimens were analyzed with respect to treatment response and survival (minimum 36 months follow-up). Patients' clinical features did not correlate with prognosis, or with specific gene expression patterns of their tumors. However women who did not respond to treatment could be distinguished from those who responded with no relapse within 12 months based on 34 gene transcripts (p < 0.02). Poor prognosis was associated with high expression of inhibitor of differentiation-2 (ID2) (p = 0.001). High expression of decorin (DCN) and ID2 together was strongly associated with reduced survival (p = 0.003), with an estimated 7-fold increased risk of dying (95% CI 1.9-29.6; 14 months survival) compared with low expression (44 months). Immunohistochemical analysis revealed both nuclear and cytoplasmic distribution of ID2 in ovarian tumors. High percentage of nuclear staining was associated with poor survival, although not statistically significantly. In conclusion, elevated expression of ID2 and DCN was significantly associated with poor prognosis in a homogeneous group of ovarian cancer patients for whom survival could not be predicted from clinical factors.

Hepatocyte growth factor is a preferred in vitro substrate for human hepsin, a membrane-anchored serine protease implicated in prostate and ovarian cancers

Hepsin is a membrane-anchored, trypsin-like serine protease with prominent expression in the human liver and tumours of the prostate and ovaries. To better understand the biological functions of hepsin, we identified macromolecular substrates employing a tetrapeptide PS-SCL (positional scanning-synthetic combinatorial library) screen that rapidly determines the P1-P4 substrate specificity. Hepsin exhibited strong preference at the P1 position for arginine over lysine, and favoured threonine, leucine or asparagine at the P2, glutamine or lysine at the P3, and proline or lysine at the P4 position. The relative activity of hepsin toward individual AMC (7-amino-4-methylcoumarin)-tetrapeptides was generally consistent with the overall peptide profiling results derived from the PC-SCL screen. The most active tetrapeptide substrate Ac (acetyl)-KQLR-AMC matched with the activation cleavage site of the hepatocyte growth factor precursor sc-HGF (single-chain HGF), KQLR downward arrowVVNG (where downward arrow denotes the cleavage site), as identified by a database analysis of trypsin-like precursors. X-ray crystallographic studies with KQLR chloromethylketone showed that the KQLR peptide fits well into the substrate-binding cleft of hepsin. This hepsin-processed HGF induced c-Met receptor tyrosine phosphorylation in SKOV-3 ovarian cancer cells, indicating that the hepsin-cleaved HGF is biologically active. Activation cleavage site mutants of sc-HGF with predicted non-preferred sequences, DPGR downward arrowVVNG or KQLQ downward arrowVVNG, were not processed, illustrating that the P4-P1 residues can be important determinants for substrate specificity. In addition to finding macromolecular hepsin substrates, the extracellular inhibitors of the HGF activator, HAI-1 and HAI-2, were potent inhibitors of hepsin activity (IC50 4+/-0.2 nM and 12+/-0.5 nM respectively). Together, our findings suggest that the HGF precursor is a potential in vivo substrate for hepsin in tumours, where hepsin expression is dysregulated and may influence tumorigenesis through inappropriate activation and/or regulation of HGF receptor (c-Met) functions.

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

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

A molecular map of mesenchymal tumors

A comprehensive study of the gene expression profile of 96 mesenchymal tumors identifies molecular fingerprints for most tumors in this group.

Background

Bone and soft tissue tumors represent a diverse group of neoplasms thought to derive from cells of the mesenchyme or neural crest. Histological diagnosis is challenging due to the poor or heterogenous differentiation of many tumors, resulting in uncertainty over prognosis and appropriate therapy.

Results

We have undertaken a broad and comprehensive study of the gene expression profile of 96 tumors with representatives of all mesenchymal tissues, including several problem diagnostic groups. Using machine learning methods adapted to this problem we identify molecular fingerprints for most tumors, which are pathognomonic (decisive) and biologically revealing.

Conclusion

We demonstrate the utility of gene expression profiles and machine learning for a complex clinical problem, and identify putative origins for certain mesenchymal tumors.

Evaluation of Lipophilins as Determinants of Tumor Cell Response to Estramustine

Estramustine administered orally as estramustine phosphate (EMP) remains a major tool in hormone refractory prostate cancer chemotherapy. The presence of estramustine binding protein, prostatin, in prostate tissue may be a determinant of response to treatment. Lipophilins are secretory proteins with homology to prostatin. Reverse transcription-polymerase chain reaction was performed to estimate expression patterns of lipophilins A to C in human biopsies and cell lines resistant to estramustine. Although lipophilin A was not expressed in prostate tissue, both lipophilins B and C were expressed in normal and tumor prostate without significant differences. For lipophilin C, a somatic mutation (T to C transition at positions 409 and 412) was found in human tumor samples and absent in normal prostate tissue. No consistent response to EMP was observed in enhanced green fluorescent protein (EGFP)-tagged lipophilin C-transfected PC3 cells compared with parental controls. Among these EGFP-lipophilin C clones, no direct correlation between response to EMP treatment (IC50 values) and EGFP expression was observed (p = 0.73). Lipophilin C mRNA levels did not vary significantly between wild-type and estramustine-resistant cells in prostate (DU145 and PC3) and ovarian (SKOV3) cancer cell lines. Overall, these results suggest that lipophilins are not specific determinants of estramustine efficacy.

Identification of new splice variants and differential expression of the human kallikrein 10 gene, a candidate cancer biomarker

The human kallikrein gene 10 (KLK10) is a member of the kallikrein gene family on chromosome 19q13.4. This gene was identified by its downregulation in breast cancer, and preliminary evidence suggests that it may act as a tumor suppressor. A computer-based analysis was performed on EST and SAGE clones from the Cancer Genome Anatomy Project and other databases. Experimental verification of differential expression of KLK10 in cancer was performed by PCR using gene-specific primers. The mRNA and EST analysis allowed the construction of the longest transcript of the gene and characterization of a 5' extension of the reported mRNA. In addition, seven new splice variants of KLK10 were identified. One of these variants, named KLK10 splice variant 3 (KLK10-SV3) which starts with a novel first exon, was experimentally verified. This variant is predicted to encode for the same protein as the 'classical' KLK10 mRNA, since the first exon is untranslated. One variant mRNA partially matches with the sequence of KLK10, while the rest of the mRNA matches with a portion of the polycystic kidney disease gene, found on chromosome 15. This variant could not be experimentally verified in either normal or cancerous tissues. There are 39 reported single nucleotide polymorphisms (SNPs) for the gene, in which three result in amino acid substitutions. SAGE analysis shows a clear upregulation of KLK10 in ovarian, pancreatic, colon, and gastric cancers. The gene is, however, downregulated in breast and prostate cancers. A three-fold decrease in expression levels was noted in actinic keratosis, compared to normal skin from the same patient. The differential regulation of KLK10 in ovarian and prostate cancers was experimentally verified by RT-PCR analysis. In addition, a significant number of clones were isolated from carcinomas of the head and neck. Fewer clones were found in carcinomas of the skin, brain and prostate. Orthologues were identified in three other species, with the highest degree of homology observed with the mouse and rat orthologues (42% in each). In conclusion new splice variants of the KLK10 gene were identified. These in silico analyses show a differential expression of the gene in various malignancies and provide the basis for directing experimental efforts to investigate the possible role of the gene as a cancer biomarker.

Potential markers that complement expression of CA125 in epithelial ovarian cancer

BACKGROUND

When ovarian carcinoma is diagnosed in stage I, up to 90% of patients can be cured with surgery and currently available chemotherapy. At present, less than 25% of cases are diagnosed at this stage. To increase the fraction of ovarian cancers detected at an early stage, screening strategies have been devised that utilize a rising serum CA125 level to trigger the performance of transvaginal sonography. One limitation of CA125 as an initial step in such a screening strategy is that up to 20% of ovarian cancers lack expression of the antigen. Serum tumor markers that can be detected in ovarian cancers that lack CA125 expression might improve the sensitivity for early detection.

METHODS

From 296 ovarian cancers, 65 (22%) were found to have weak or absent CA125 expression on immunoperoxidase staining. Tissue expression of CA125 was compared to serum CA125 levels. Using immunoperoxidase staining of tissue arrays, we have assessed expression of 10 potential serum tumor markers in the 65 epithelial ovarian cancers with little or no CA125 expression and in ovarian cystadenomas, tumors of low malignant potential, normal ovaries, and 16 other normal tissues.

RESULTS

Low or absent expression of CA125 in surgical specimens of epithelial ovarian cancer was associated with low levels of serum CA125 in pre-operative serum specimens. In ovarian cancers that lacked CA125, all specimens (100%) expressed human kallikrein 10 (HK10), human kallikrein 6 (HK6), osteopontin (OPN), and claudin 3. A smaller fraction of CA125-deficient ovarian cancers expressed DF3 (95%), vascular endothelial growth factor (VEGF) (81%), MUC1 (62%), mesothelin (MES) (34%), HE4 (32%), and CA19-9 (29%). When reactivity with normal tissues was considered, however, MES and HE4 showed the greatest specificity. Differential expression was also found for HK10, OPN, DF3, and MUC1.

CONCLUSIONS

At the level of tissue expression, each of 10 potential serum markers could be detected in 29-100% of ovarian cancers that had low or absent expression of CA125. Several markers exhibited more intense expression in cancers than in normal organs. Further investigation is needed to demonstrate complementary expression of markers in serum.

Deregulated expression of Polycomb-group oncogenes in human malignant lymphomas and epithelial tumors

Genes belonging to the Polycomb-group (PcG) are epigenetic gene silencers with a vital role in the maintenance of cell identity. They contribute to regulation of various processes in both embryos and adults, including the cell cycle and lymphopoiesis. A growing body of work has linked human PcG genes to various hematological and epithelial cancers, identifying novel mechanisms of malignant transformation and paving the way to development of new cancer treatments and identification of novel diagnostic markers. This review addresses the current insights in the role of PcG genes in development of human malignancies.

In silico chromosomal clustering of genes displaying altered expression patterns in ovarian cancer

Ovarian cancer, the leading cause of death due to gynecological malignancy, is diagnosed in most cases at an advanced stage. Combined with the paucity of symptoms of early-stage disease, the need to develop novel effective markers for the detection of potentially curable, early-stage disease is self-evident. Comprehensive analyses of somatic gene expression patterns in ovarian cancer were reported previously (n=17) and yielded substantial information on somatically altered genes, information that can potentially be useful in developing early detection markers. To further substantiate the role that these genes play in ovarian cancer tumorogenesis, we surveyed these reports and arranged the significantly altered genes from all reported studies by their chromosomal location (in silico chromosomal clustering). Subsequent comparison of this clustering to known genomic somatic alterations at the DNA level from data obtained using comparative genomic hybridization (CGH) was carried out. The major chromosomal regions that displayed overexpressed genes were correlated with the major CGH-detectable DNA amplification areas at 20q (harboring HE4, SLPI, MYBL2, UBE2C, and SDC4) and 1q (harboring MUC1). These genes may provide insights into ovarian cancer pathogenesis and may also prove to be useful as early detection tools.

Human tissue kallikrein gene family: applications in cancer

Human tissue kallikrein genes, located on the long arm of chromosome 19, are a subgroup of the serine protease family of proteolytic enzymes. Initially thought to consist of three members, the human kallikrein locus has now been extended and includes 15 tandemly located genes. These genes, and their protein products, share a high degree of homology and are expressed in a wide array of tissues, mainly those that are under steroid hormone control. PSA (hK3) is one of the human kallikreins, and is the most useful tumor marker for prostate cancer screening, diagnosis, prognosis and monitoring. hK2, another prostate-specific kallikrein, has also been proposed as a complementary prostate cancer biomarker. In the past 5 years, the newly discovered kallikreins (KLK4-KLK15) have been associated with several types of cancer. For example, hK4, hK5, hK6, hK7, hK8, hK10, hK11, hK13 and hK14 are emerging biomarkers for ovarian, breast, prostate and testicular cancer. New evidence raises the possibility that some kallikreins are directly involved with cancer progression. We here review the evidence linking kallikreins and cancer and their applicability as novel biomarkers for cancer diagnosis and management.

Ovarian cancer diagnosis by hippocampus and neocortex-inspired learning memory structures

Early detection and accurate staging of ovarian cancer are the keys to improving survival rate. However, at present there is no single diagnosis modality that is sufficiently sensitive. DNA microarray analysis is an emerging technique that has potential for ameliorating the hardship in early detection and staging of ovarian disease. However, microarray data is ultra-huge and difficult to analyze. Hence, computational intelligence methods are often utilized to assist in the diagnosis and analysis process. Fuzzy Neural Networks (FNN) are more suitable for this task as FNN provides not only the accuracy, but also the interpretability of its reasoning process. Hippocampus-inspired Complementary Learning FNN (CLFNN) is able to rapidly derive fuzzy sets and formulate fuzzy rules. CLFNN uses positive and negative learning, and hence it reduces the effect of the curse of dimensionality and is capable of modeling the dynamics of the problem space with relatively good classification performance. One of its successors, a hybrid of complementary hippocampal learning and associative neocortical learning called Pseudo Associative Complementary Learning (PACL), is a structure that seeks to functionally model the memory consolidation process. Both PACL and CLFNN have human-like reasoning that allows physicians to examine their computation using familiar terms. They can construct intuitive fuzzy rules autonomously to justify their reasoning, which is important to generate trust among the users. Hence, CLFNN and PACL are applied as a diagnostic decision support system in ovarian cancer diagnosis. The experimental results are encouraging.

Expression profiling of primary tumors and matched lymphatic and lung metastases in a xenogeneic breast cancer model

Using a purpose-designed experimental model, we have defined new, statistically significant, differences in gene expression between heavily and weakly metastatic human breast cancer cell populations, in vivo and in vitro. The differences increased under selection pressures designed to increase metastatic proficiency. Conversely, the expression signatures of primary tumors generated by more aggressive variants, and their matched metastases in the lungs and lymph nodes, all tended to converge. However, the few persisting differences among these selectively enriched malignant growths in the breast, lungs, and lymph nodes were highly statistically significant, implying potential mechanistic involvement of the corresponding genes. The evidence that has emerged from the current work indicates that selective enhancement of metastatic proficiency by serial transplantation co-purifies a subliminal gene expression pattern within the tumor cell population. This signature most likely includes genes participating in metastasis pathogenesis, and we document manageable numbers of candidates for this role. The findings also suggest that metastasis to at least two different organs occurs through closely similar genetic mechanisms.

Ovarian cancer, the coagulation pathway, and inflammation

Epithelial ovarian cancer (EOC) represents the most frequent cause of death in the United States from a cancer involving the female genital tract. Contributing to the overall poor outcome in EOC patients, are the metastases to the peritoneum and stroma that are common in this cancer. In one study, cDNA microarray analysis was performed on fresh tissue to profile gene expression in patients with EOC. This study showed a number of genes with significantly altered expression in the pelvic peritoneum and stroma, and in the vicinity of EOC implants. These genes included those encoding coagulation factors and regulatory proteins in the coagulation cascade and genes encoding proteins associated with inflammatory responses. In addition to promoting the formation of blood clots, coagulation factors exhibit many other biologic functions as well as tumorigenic functions, the later including tumor cell proliferation, angiogenesis, invasion, and metastasis. Coagulation pathway proteins involved in tumorigenesis consist of factor II (thrombin), thrombin receptor (protease-activated receptors), factor III (tissue factor), factor VII, factor X and factor I (fibrinogen), and fibrin and factor XIII. In a recent study we conducted, we found that factor XII, factor XI, and several coagulation regulatory proteins, including heparin cofactor-II and epithelial protein C receptor (EPCR), were also upregulated in the peritoneum of EOC. In this review, we summarize evidence in support of a role for these factors in promoting tumor cell progression and the formation of ascites. We also discuss the different roles of coagulation factor pathways in the tumor and peritumoral microenvironments as they relate to angiogenesis, proliferation, invasion, and metastasis. Since inflammatory responses are another characteristic of the peritoneum in EOC, we also discuss the linkage between the coagulation cascade and the cytokines/chemokines involved in inflammation. Interleukin-8, which is considered an important chemokine associated with tumor progression, appears to be a linkage point for coagulation and inflammation in malignancy. Lastly, we review findings regarding the inflammatory process yielded by certain clinical trials of agents that target members of the coagulation cascade in the treatment of cancer. Current data suggest that disrupting certain elements of the coagulation and inflammation processes in the tumor microenvironment could be a new biologic approach to cancer therapeutics.

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.

Secretoglobins in the human pituitary: high expression of lipophilin B and its down-regulation in pituitary adenomas

Secretoglobins are small secreted proteins, the expression of which has mostly been associated with secretory mucosal epithelia. Several secretoglobins have been implicated in the development of various human cancers. Allelic deletions of chromosome 11q13 correlates with the invasiveness of pituitary tumors. Intriguingly, several secretoglobin genes are located on 11q13; however, for most of these genes the expression in the pituitary and pituitary tumors have not been investigated. Antibodies specific for the secretoglobin lipophilin B (SCGB1D2, BU101) were developed and used in an immunohistochemical analysis of a human normal tissue microarray. Prominent lipophilin B immunoreactivity was found in the secretory cells of the anterior pituitary. Eight of nine analyzed pituitary adenomas showed a reduction in lipophilin B immunoreactivity compared to normal pituitary. However, there was no apparent association between lipophilin B immunoreactivity and hormone production or tumor invasiveness. Expression of eight different secretoglobin mRNAs were analyzed in normal pituitary and the pituitary adenoma cell line HP75 by highly specific quantitative real-time reverse transcription-PCR assays. Lipophilins B and C (SCGB2A1, mammaglobin B) were the most prominently expressed secretoglobin mRNAs in the pituitary. No secretoglobin mRNA was detected in the HP75 cells. The present report demonstrates, for the first time, lipophilin B expression in the pituitary and its apparent down-regulation in pituitary adenomas.

FISH cytogenetics and prognosis in breast and non-small cell lung cancers

BACKGROUND

Interphase cytogenetics by fluorescence in situ hybridization (FISH) has been demonstrated to be a valuable diagnostic tool in effusions from patients with solid tumors. As the next step, we investigated whether certain patterns of numeric aberrations in malignant effusion cells supply prognostic information.

METHODS

From a large series of effusions from patients with solid tumors, 55 effusions from breast cancer and 39 effusions from non-small cell lung cancer (NSCLC) were classified as malignant by cytology or FISH. Tumor cells were classified as FISH aneuploid for chromosome 11 and/or 17 or as not aneuploid. Predominant cytogenetic anomalies and patterns of intratumor cytogenetic heterogeneity were brought in relation to overall survival rate.

RESULTS

There was no difference with respect to overall survival rate when effusions with or without aneuploidy for chromosomes 11 and 17 were compared. Likewise, in effusions with aneuploidy, there was no difference in overall survival rate among patients with different modal chromosome copy numbers (e.g., trisomy vs. tetrasomy 11) or among patients with a low or high grade of intratumor complexity (defined by the intratumor heterogeneity of FISH aneuploidy). In breast cancer, aneuploidy with gain of chromosome 11 was associated with a significantly superior survival rate, suggesting that amplification of chromosome 11 DNA is associated with a less aggressive phenotype.

CONCLUSIONS

Simple chromosomal changes as determined by FISH, such as gain of chromosome 11 copy numbers in breast cancer, may be prognostic. Prospective studies in primary tumors that classify distinct prognostic groups by FISH cytogenetics are warranted.

Laser capture microdissection, microarrays and the precise definition of a cancer cell

Most expression profiling studies of solid tumors have used biopsy samples containing large numbers of contaminating stromal and other cell types, thereby complicating any precise delineation of gene expression in nontumor versus tumor cell types. Combining laser capture microdissection, RNA amplification protocols, microarray technologies and our knowledge of the human genome sequence, it is possible to isolate pure populations of cells or even a single cell and interrogate the expression of thousands of sequences for the purpose of more precisely defining the biology of the tumor cell. Although many of the studies that currently allow for characterization of small sample preparations and single cells were performed utilizing noncancer cell types, and in some cases isolation protocols other than laser capture microdissection, a list of protocols are described that could be used for the expression analysis of individual tumor cells. Application of these experimental approaches to cancer studies may permit a more accurate definition of the biology of the cancer cell, so that ultimately, more specific targeted therapies can be developed.

The emerging roles of human tissue kallikreins in cancer

Human tissue kallikreins (hKs), which are encoded by the largest contiguous cluster of protease genes in the human genome, are secreted serine proteases with diverse expression patterns and physiological roles. Although primarily known for their clinical applicability as cancer biomarkers, recent evidence implicates hKs in many cancer-related processes, including cell-growth regulation, angiogenesis, invasion and metastasis. They have been shown to promote or inhibit neoplastic progression, acting individually and/or in cascades with other hKs and proteases, and might represent attractive targets for therapeutic intervention.

Gene expression profiling of epithelial ovarian tumours correlated with malignant potential

Background

Epithelial ovarian tumours exhibit a range of malignant potential, presenting distinct clinical phenotypes. Improved knowledge of gene expression changes and functional pathways associated with these clinical phenotypes may lead to new treatment targets, markers for early detection and a better understanding of disease progression.

Results

Gene expression profiling (Affymetrix, U95Av2) was carried out on 18 ovarian tumours including benign adenomas, borderline adenocarcinomas of low malignant potential and malignant adenocarcinomas. Clustering the expression profiles of samples from patients not treated with chemotherapy prior to surgery effectively classified 92% of samples into their proper histopathological group. Some cancer samples from patients treated with chemotherapy prior to surgery clustered with the benign adenomas. Chemotherapy patients whose tumours exhibited benign-like expression patterns remained disease free for the duration of this study as indicated by continued normal serum CA-125 levels. Statistical analysis identified 163 differentially expressed genes: 61 genes under-expressed in cancer and 102 genes over-expressed in cancer. Profiling the functional categories of co-ordinately expressed genes within this list revealed significant correlation between increased malignant potential and loss of both IGF binding proteins and cell adhesion molecules. Interestingly, in several instances co-ordinately expressed genes sharing biological function also shared chromosomal location.

Conclusion

Our findings indicate that gene expression profiling can reliably distinguish between benign and malignant ovarian tumours. Expression profiles of samples from patients pre-treated with chemotherapy may be useful in predicting disease free survival and the likelihood of recurrence. Loss of expression of IGF binding proteins as well as specific cell adhesion molecules may be a significant mechanism of disease progression in ovarian cancer. Expression levels in borderline tumours were intermediate between benign adenomas and malignant adenocarcinomas for a significant portion of the differentially expressed genes, suggesting that borderline tumours are a transitional state between benign and malignant tumours. Finally, genes displaying coordinated changes in gene expression were often genetically linked, suggesting that changes in expression for these genes are the consequence of regional duplications, deletions or epigenetic events.

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.