Current concepts in ovarian epithelial tumorigenesis: correlation between morphological and molecular data

Ovarian carcinoma is the most lethal gynaecological malignancy, most tumours being advanced at presentation. However, little is known about precursor lesions and the cell of origin of epithelial ovarian malignancy. In this review, the proposed cell of origin is discussed as well as recent molecular data relating to ovarian cancers of different morphological types. It is stressed that ovarian carcinoma is a heterogeneous group of neoplasms with several different morphological types, each with their own underlying molecular genetic events. Recent data suggest that mucinous ovarian cancers and a small subset of serous cancers (low grade ovarian serous carcinoma) develop through a well-defined adenoma-carcinoma sequence while the much more common high grade ovarian serous carcinoma develops de novo from the ovarian surface epithelium or the epithelium of cortical inclusion cysts. The realisation that various morphological types of epithelial ovarian cancer are associated with different molecular genetic events is a major advance in the study of ovarian cancer. It can be anticipated that this will lead to the development of specific therapeutic agents of value against a specific tumour type.     

Connecting Prognostic Ligand Receptor Signaling Loops in Advanced Ovarian Cancer

Understanding cancer cell signal transduction is a promising lead for uncovering therapeutic targets and building treatment-specific markers for epithelial ovarian cancer. To brodaly assay the many known transmembrane receptor systems, previous studies have employed gene expression data measured on high-throughput microarrays. Starting with the knowledge of validated ligand-receptor pairs (LRPs), these studies postulate that correlation of the two genes implies functional autocrine signaling. It is our goal to consider the additional weight of evidence that prognosis (progression-free survival) can bring to prioritize ovarian cancer specific signaling mechanism. We survey three large studies of epithelial ovarian cancers, with gene expression measurements and clinical information, by modeling survival times both categorically (long/short survival) and continuously. We use differential correlation and proportional hazards regression to identify sets of LRPs that are both prognostic and correlated. Of 475 candidate LRPs, 77 show reproducible evidence of correlation; 55 show differential correlation. Survival models identify 16 LRPs with reproduced, significant interactions. Only two pairs show both interactions and correlation (PDGFAPDGFRA and COL1A1CD44) suggesting that the majority of prognostically useful LRPs act without positive feedback. We further assess the connectivity of receptors using a Gaussian graphical model finding one large graph and a number of smaller disconnected networks. These LRPs can be organized into mutually exclusive signaling clusters suggesting different mechanisms apply to different patients. We conclude that a mix of autocrine and endocrine LRPs influence prognosis in ovarian cancer, there exists a heterogenous mix of signaling themes across patients, and we point to a number of novel applications of existing targeted therapies which may benefit ovarian cancer.     

Epithelial Glycoprotein-2 Expression is Subject to Regulatory Processes in Epithelial–mesenchymal Transitions During Metastases: an Investigation of Human Cancers Transplanted into Severe Combined Immunodeficient Mice

The human cell-surface antigen epithelial glycoprotein-2 recognized by the monoclonal antibody MOC-31 is an epithelial tumour-associated glycoprotein expressed in non-squamous carcinomas. MOC-31 immunoreactivity was investigated in human breast, colon, ovarian and lung cancer cell lines, grown either in vitro or in severe combined immunodeficient (SCID) mice as solid tumours and/or metastases. Three of four small-cell lung cancer cell lines (NCI-H69, OH3 and SW2) and three of four ovarian cancer cell lines (SoTü 1, 3 and 4) expressed epithelial glycoprotein-2. In contrast, all three breast (MCF-7, BT20, T47D) and all three colon (HT29, CACO2, SW480) cancer cell lines strongly reacted with monoclonal antibody MOC-31. A notable difference in MOC-31 immunoreactivity was observed in spontaneously formed lung metastases of HT29 colon cancer cells. Whereas larger metastases (> 30 cells) re acted with a similar staining pattern to the primary tumour, smaller metastases did not. These findings indicate that differentiation processes during the epithelial–mesenchymal transition occur in metastases, which lead to a transient loss of epithelial glycoprotein-2 expression during the migratory and early post- migratory period. This loss of antigen expression indicates that the process of metastases formation is a regulatory event, and this transient loss of antigen expression might represent a potential obstacle to antibody-based therapy in the setting of minimal residual disease.     

An Outlook on Ovarian Cancer and Borderline Ovarian Tumors: Focus on Genomic and Proteomic Findings

Among the gynaecological malignancies, ovarian cancer is one of the neoplastic forms with the poorest prognosis and with the bad overall and disease-free survival rates than other gynaecological cancers. Ovarian tumors can be classified on the basis of the cells of origin in epithelial, stromal and germ cell tumors. Epithelial ovarian tumors display great histological heterogeneity and can be further subdivided into benign, intermediate or borderline, and invasive tumors. Several studies on ovarian tumors, have focused on the identification of both diagnostic and prognostic markers for applications in clinical practice. High-throughput technologies have accelerated the process of biomolecular study and genomic discovery; unfortunately, validity of these should be still demonstrated by extensive researches on sensibility and sensitivity of ovarian cancer novel biomarkers, determining whether gene profiling and proteomics could help differentiate between patients with metastatic ovarian cancer and primary ovarian carcinomas, and their potential impact on management. Therefore, considerable interest lies in identifying molecular and protein biomarkers and indicators to guide treatment decisions and clinical follow up. In this review, the current state of knowledge about the genoproteomic and potential clinical value of gene expression profiling in ovarian cancer and ovarian borderline tumors is discussed, focusing on three main areas: distinguishing normal ovarian tissue from ovarian cancers and borderline tumors, identifying different genotypes of ovarian tissue and identifying proteins linked to cancer or tumor development. By these targets, authors focus on the use of novel molecules, developed on the proteomics and genomics researches, as potential protein biomarkers in the management of ovarian cancer or borderline tumor, overlooking on current state of the art and on future perspectives of researches.Key Words: Ovarian cancer, borderline ovarian tumors, markers, genomics, proteomics, oncogenes.     

Oestradiol inhibits spontaneous and cisplatin-induced apoptosis in epithelial ovarian cancer cells: relationship to DNA repair capacity

A prospective role of sex steroid hormones in the pathogenesis of common epithelial ovarian cancer remains equivocal. We hypothesized that oestradiol can protect ovarian cells from apoptosis by augmenting their DNA repair capacity. Two established oestrogen receptor-positive human cancer cell lines of ovarian surface epithelial origin (OVCAR-3, SKOV-3) were studied during short-term (24 h) subculture in the absence or presence of oestradiol-17β and/or the DNA-damaging chemotherapeutic agent cisplatin. Apoptosis was monitored among individual cells by in situ DNA fragmentation analysis. Basal rates of apoptosis were diminished by exposure to oestradiol (progesterone or testosterone were without effect). Oestradiol also suppressed apoptosis induced by cisplatin and enhanced the repair of a cisplatin-damaged reporter chloramphenicol-O-acetyltransferase gene transfected into ovarian cells. The ability of oestrogen-responsive ovarian cancer cells to efficiently repair DNA and thereby avoid apoptosis may be related to propensity for clonal expansion and drug resistance. This revised version was published online in November 2006 with corrections to the Cover Date.     

Glucocorticoid regulation of SLIT/ROBO tumour suppressor genes in the ovarian surface epithelium and ovarian cancer cells

The three SLIT ligands and their four ROBO receptors have fundamental roles in mammalian development by promoting apoptosis and repulsing aberrant cell migration. SLITs and ROBOs have emerged as candidate tumour suppressor genes whose expression is inhibited in a variety of epithelial tumours. We demonstrated that their expression could be negatively regulated by cortisol in normal ovarian luteal cells. We hypothesised that after ovulation the locally produced cortisol would inhibit SLIT/ROBO expression in the ovarian surface epithelium (OSE) to facilitate its repair and that this regulatory pathway was still present, and could be manipulated, in ovarian epithelial cancer cells. Here we examined the expression and regulation of the SLIT/ROBO pathway in OSE, ovarian cancer epithelial cells and ovarian tumour cell lines. Basal SLIT2, SLIT3, ROBO1, ROBO2 and ROBO4 expression was lower in primary cultures of ovarian cancer epithelial cells when compared to normal OSE (P<0.05) and in poorly differentiated SKOV-3 cells compared to the more differentiated PEO-14 cells (P<0.05). Cortisol reduced the expression of certain SLITs and ROBOs in normal OSE and PEO-14 cells (P<0.05). Furthermore blocking SLIT/ROBO activity reduced apoptosis in both PEO-14 and SKOV-3 tumour cells (P<0.05). Interestingly SLIT/ROBO expression could be increased by reducing the expression of the glucocorticoid receptor using siRNA (P<0.05). Overall our findings indicate that in the post-ovulatory phase one role of cortisol may be to temporarily inhibit SLIT/ROBO expression to facilitate regeneration of the OSE. Therefore this pathway may be a target to develop strategies to manipulate the SLIT/ROBO system in ovarian cancer.     

An RNA Interference Lethality Screen of the Human Druggable Genome to Identify Molecular Vulnerabilities in Epithelial Ovarian Cancer

Targeted therapies have been used to combat many tumor types; however, few have effectively improved the overall survival in women with epithelial ovarian cancer, begging for a better understanding of this deadly disease and identification of essential drivers of tumorigenesis that can be targeted effectively. Therefore, we used a loss-of-function screening approach to help identify molecular vulnerabilities that may represent key points of therapeutic intervention. We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting over 6,000 druggable genes and studied their effects on growth and/or survival of epithelial ovarian cancer (EOC) cell lines. The top 300 “hits” affecting the viability of A1847 cells were rescreened across additional EOC cell lines and non-tumorigenic, human immortalized ovarian epithelial cell lines. Fifty-three gene candidates were found to exhibit effects in all tumorigenic cell lines tested. Extensive validation of these hits refined the list to four high quality candidates (HSPA5, NDC80, NUF2, and PTN). Mechanistic studies show that silencing of three genes leads to increased apoptosis, while HSPA5 silencing appears to alter cell growth through G1 cell cycle arrest. Furthermore, two independent gene expression studies show that NDC80, NUF2 and PTN were significantly aberrantly overexpressed in serous adenocarcinomas. Overall, our functional genomics results integrated with the genomics data provide an important unbiased avenue towards the identification of prospective therapeutic targets for drug discovery, which is an urgent and unmet clinical need for ovarian cancer.     

Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.     

Ex Vivo Culture of Primary Human Fallopian Tube Epithelial Cells

Epithelial ovarian cancer is a leading cause of female cancer mortality in the United States. In contrast to other women-specific cancers, like breast and uterine carcinomas, where death rates have fallen in recent years, ovarian cancer cure rates have remained relatively unchanged over the past two decades ¹. This is largely due to the lack of appropriate screening tools for detection of early stage disease where surgery and chemotherapy are most effective ^{2, 3}. As a result, most patients present with advanced stage disease and diffuse abdominal involvement. This is further complicated by the fact that ovarian cancer is a heterogeneous disease with multiple histologic subtypes ^{4, 5}. Serous ovarian carcinoma (SOC) is the most common and aggressive subtype and the form most often associated with mutations in the BRCA genes. Current experimental models in this field involve the use of cancer cell lines and mouse models to better understand the initiating genetic events and pathogenesis of disease ^{6, 7}. Recently, the fallopian tube has emerged as a novel site for the origin of SOC, with the fallopian tube (FT) secretory epithelial cell (FTSEC) as the proposed cell of origin ^{8, 9}. There are currently no cell lines or culture systems available to study the FT epithelium or the FTSEC. Here we describe a novel ex vivo culture system where primary human FT epithelial cells are cultured in a manner that preserves their architecture, polarity, immunophenotype, and response to physiologic and genotoxic stressors. This ex vivo model provides a useful tool for the study of SOC, allowing a better understanding of how tumors can arise from this tissue, and the mechanisms involved in tumor initiation and progression.     

The Specificity of the FOXL2 c.402C>G Somatic Mutation: A Survey of Solid Tumors

Background

A somatic mutation in the FOXL2 gene is reported to be present in almost all (97%; 86/89) morphologically defined, adult-type, granulosa-cell tumors (A-GCTs). This FOXL2 c.402C>G mutation changes a highly conserved cysteine residue to a tryptophan (p.C134W). It was also found in a minority of other ovarian malignant stromal tumors, but not in benign ovarian stromal tumors or unrelated ovarian tumors or breast cancers.

Methodology/Principal Findings

Herein we studied other cancers and cell lines for the presence of this mutation. We screened DNA from 752 tumors of epithelial and mesenchymal origin and 28 ovarian cancer cell lines and 52 other cancer cell lines of varied origin. We found the FOXL2 c.402C>G mutation in an unreported A-GCT case and the A-GCT-derived cell line KGN. All other tumors and cell lines analyzed were mutation negative.

Conclusions/Significance

In addition to proving that the KGN cell line is a useful model to study A-GCTs, these data show that the c.402C>G mutation in FOXL2 is not commonly found in a wide variety of other cancers and therefore it is likely pathognomonic for A-GCTs and closely related tumors.     

Gene expression profiling of human ovarian epithelial tumors by digo nucleotide microarray

Gene expression of human ovarian carcinoma cell lines and epithelial ovarian tumors was examined by oligonucleotide microarray for about 6000 human cDNAs. (1) Comparison of gene expression between CDDP-sensitive human ovarian serous adenocarcinoma cell lines and CDDP-resistant cell lines revealed that gamma-glutamylcysteine synthetase, glutathione peroxidase-like protein, dehydrogenase (UGDH), NAD(P)H: quinoneoxireductase, glucose-6-phosphatase, ornithine decarboxylase and dihydrodiol dehydrogenase were associated with a mechanism of CDDP-resistance. Comparison of gene expression between taxol-sensitive human ovarian cell lines and taxol-resistant cell lines showed that up-regulation of 30 kinds of gene expression including MDR and semaphorin E in taxol-resistant cell lines. (2) Comparison of gene expression among serous adenocarcinomas, clear cell adenocarcinomas and non-cancerous ovarian tissues by hierarchical clustering demonstrated that clear difference between carcinomas and non-cancerous ovarian tissues but not obvious difference between serous and clear adenocarcinomas. Genes that were up- and down-regulated specifically in these two types of ovarian carcinomas were further selected by the criteria that difference in the mRNA level by more than 4-fold between tumors and non-cancerous tissues. Tissue type specific alterations of gene expression are likely to play important roles in the carcinogenesis of epithelial ovarian tumors. cDNA microarray is a powerful and high-throughput tool to analyze gene expression of cancer development.     

An Epigenetic Signature in Peripheral Blood Predicts Active Ovarian Cancer

Background

Recent studies have shown that DNA methylation (DNAm) markers in peripheral blood may hold promise as diagnostic or early detection/risk markers for epithelial cancers. However, to date no study has evaluated the diagnostic and predictive potential of such markers in a large case control cohort and on a genome-wide basis.

Principal Findings

By performing genome-wide DNAm profiling of a large ovarian cancer case control cohort, we here demonstrate that active ovarian cancer has a significant impact on the DNAm pattern in peripheral blood. Specifically, by measuring the methylation levels of over 27,000 CpGs in blood cells from 148 healthy individuals and 113 age-matched pre-treatment ovarian cancer cases, we derive a DNAm signature that can predict the presence of active ovarian cancer in blind test sets with an AUC of 0.8 (95% CI (0.74–0.87)). We further validate our findings in another independent set of 122 post-treatment cases (AUC = 0.76 (0.72–0.81)). In addition, we provide evidence for a significant number of candidate risk or early detection markers for ovarian cancer. Furthermore, by comparing the pattern of methylation with gene expression data from major blood cell types, we here demonstrate that age and cancer elicit common changes in the composition of peripheral blood, with a myeloid skewing that increases with age and which is further aggravated in the presence of ovarian cancer. Finally, we show that most cancer and age associated methylation variability is found at CpGs located outside of CpG islands.

Significance

Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role.     

Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors

The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified candidate mechanisms and biological pathways associated with cisplatin resistance. OVCAR-8 human ovarian carcinoma cells were exposed to sub-lethal concentrations of cisplatin to create a matched cisplatin-resistant cell line, OVCAR-8R. Genome-wide gene expression profiling of sensitive and resistant ovarian cancer spheroids identified 3,331 significantly differentially expressed probesets coding for 3,139 distinct protein-coding genes (Fc >2, FDR < 0.05) (S2 Table). Despite significant expression changes in some transporters including MDR1, cisplatin resistance was not associated with differences in intracellular cisplatin concentration. Cisplatin resistant cells were significantly enriched for a mesenchymal gene expression signature. OVCAR-8R resistance derived gene sets were significantly more biased to patients with shorter survival. From the most differentially expressed genes, we derived a 17-gene expression signature that identifies ovarian cancer patients with shorter overall survival in three independent datasets. We propose that the use of cisplatin resistant cell lines in 3D spheroid models is a viable approach to gain insight into resistance mechanisms relevant to ovarian tumors in patients. Our data support the emerging concept that ovarian cancers can acquire drug resistance through an epithelial-to-mesenchymal transition.