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Objective The Gynecologic Oncology Group (GOG) performed a detailed analysis of p53 overexpression in previously-untreated women with invasive early or advanced stage epithelial ovarian cancer (EOC).

Therapeutic strategies based on antiangiogenic approaches are beginning to show great promise in clinical studies. However, full realization of these approaches requires identification of key differences in gene expression between endothelial cells from tumors versus their normal counterparts. Here, we examined gene expression differences in purified endothelial cells from 10 invasive epithelial ovarian cancers and 5 normal ovaries using Affymetrix U133 Plus 2.0 microarrays. More than 400 differentially expressed genes were identified in tumor-associated endothelial cells. We selected and validated 23 genes that were overexpressed by 3.6- to 168-fold using real-time reverse transcription-PCR and/or immunohistochemistry. Among these, the polycomb group protein enhancer of Zeste homologue 2 (EZH2), the Notch ligand Jagged1, and PTK2 were elevated 3- to 4.3-fold in tumor-associated endothelial cells. Silencing these genes individually with small interfering RNA blocked endothelial cell migration and tube formation in vitro. The present study shows that tumor and normal endothelium differ at the molecular level, which may have significant implications for the development of antiangiogenic therapies. [Cancer Res 2007;67(4):1757–68]

Endometrial cancer is the third most common gynecologic malignancy and the ninth most common malignancy for females overall in Hong Kong. Approximately 80% or more of these cancers are endometrioid endometrial adenocarcinomas. The aim of this study was to reveal genes contributing to the development of endometrioid endometrial cancer, which may impact diagnosis, prognosis and treatment of the disease. Whole-genome gene expression analysis was completed for a set of 55 microdissected sporadic endometrioid endometrial adenocarcinomas and 29 microdissected normal endometrium specimens using the Affymetrix Human U133 Plus 2.0 oligonucleotide microarray. Selected genes of interest were validated by quantitative real-time-polymerase chain reaction (qRT-PCR). Pathway analysis was performed to reveal gene interactions involved in endometrial tumorigenesis. Unsupervised hierarchical clustering displayed a distinct separation between the endometrioid adenocarcinomas and normal endometrium samples. Supervised analysis identified 117 highly differentially regulated genes (>or=4.0-fold change), which distinguished the endometrial cancer specimens from normal endometrium. Twelve novel genes including DKK4, ZIC1, KIF1A, SAA2, LOC16378, ALPP2, CCL20, CXCL5, BST2, OLFM1, KLRC1 and MBC45780 were deregulated in the endometrial cancer, and further validated in an independent set of 56 cancer and 29 normal samples using qRT-PCR. In addition, 10 genes were differentially regulated in late-stage cancer, as compared to early-stage disease, and may be involved in tumor progression. Pathway analysis of the expression data from this tumor revealed an interconnected network consisting of 21 aberrantly regulated genes involved in angiogenesis, cell proliferation and chromosomal instability. The results of this study highlight the molecular features of endometrioid endometrial cancer and provide insight into the events underlying the development and progression of endometrioid endometrial cancer.

Purpose: We investigated the role of the KLF6 tumor suppressor gene and its alternatively spliced isoform KLF6-SV1 in epithelial ovarian cancer (EOC).Experimental Design: We first analyzed tumors from 68 females with EOC for KLF6 gene inactivation using fluorescent loss of heterozygosity (LOH) analysis and direct DNA sequencing and then defined changes in KLF6 and KLF6-SV1 expression levels by quantitative real-time PCR. We then directly tested the effect of KLF6 and KLF6-SV1 inhibition in SKOV-3 stable cell lines on cellular invasion and proliferation in culture and tumor growth, i.p. dissemination, ascites production, and angiogenesis in vivo using BALB/c nu/nu mice. All statistical tests were two sided.Results: LOH was present in 59% of samples in a cell type–specific manner, highest in serous (72%) and endometrioid (75%) subtypes, but absent in clear cell tumors. LOH was significantly correlated with tumor stage and grade. In addition, KLF6 expression was decreased in tumors when compared with ovarian surface epithelial cells. In contrast, KLF6-SV1 expression was increased ∼5-fold and was associated with increased tumor grade regardless of LOH status. Consistent with these findings, KLF6 silencing increased cellular and tumor growth, angiogenesis, and vascular endothelial growth factor expression, i.p. dissemination, and ascites production. Conversely, KLF6-SV1 down-regulation decreased cell proliferation and invasion and completely suppressed in vivo tumor formation.Conclusion: Our results show that KLF6 and KLF6-SV1 are associated with key clinical features of EOC and suggest that their therapeutic targeting may alter ovarian cancer growth, progression, and dissemination.

Papillary serous low malignant potential (LMP) tumors are characterized by malignant features and metastatic potential yet display a benign clinical course. The role of LMP tumors in the development of invasive epithelial cancer of the ovary is not clearly defined. The aim of this study is to determine the relationships among LMP tumors and invasive ovarian cancers and identify genes contributing to their phenotypes. Affymetrix U133 Plus 2.0 microarrays (Santa Clara, CA) were used to interrogate 80 microdissected serous LMP tumors and invasive ovarian malignancies along with 10 ovarian surface epithelium (OSE) brushings. Gene expression profiles for each tumor class were used to complete unsupervised hierarchical clustering analyses and identify differentially expressed genes contributing to these associations. Unsupervised hierarchical clustering analysis revealed a distinct separation between clusters containing borderline and high-grade lesions. The majority of low-grade tumors clustered with LMP tumors. Comparing OSE with high-grade and LMP expression profiles revealed enhanced expression of genes linked to cell proliferation, chromosomal instability, and epigenetic silencing in high-grade cancers, whereas LMP tumors displayed activated p53 signaling. The expression profiles of LMP, low-grade, and high-grade papillary serous ovarian carcinomas suggest that LMP tumors are distinct from high-grade cancers; however, they are remarkably similar to low-grade cancers. Prominent expression of p53 pathway members may play an important role in the LMP tumor phenotype.

Purpose: To evaluate the possible mechanisms influencing the infiltration of CD8 T lymphocytes into the tumor epithelium of advanced-stage serous ovarian cancers.Experimental Design: Immunohistochemical localization of CD8 T lymphocytes was done on a homogeneous population of 184 high-grade, advanced-stage serous ovarian cancer tissue specimens. Microarray analysis was done on microdissected tumor epithelium from 38 specimens to identify genes up-regulated or down-regulated in specimens with differing numbers of tumor-infiltrating CD8 T lymphocytes. Quantitative real-time PCR and immunohistochemistry were used to validate a candidate gene. Univariate and multivariate survival analyses were done combining CD8 T lymphocyte number and HLA-DMB expression with standard prognostic factors.Results: Marked CD8 T lymphocyte infiltration of the tumor epithelium is associated with a 20-month improvement in median overall survival. Additionally, when combined with cytoreduction status and age, CD8 T lymphocyte status is an independent prognostic factor for survival. Microarray analysis showed HLA-DMB, a component of the MHC II antigen presentation machinery, to be differentially expressed in specimens with an abundance of tumor-infiltrating CD8 T lymphocytes. This relationship was validated at both mRNA and protein levels. As well, high HLA-DMB expression in the tumor epithelium was associated with a significant improvement in median overall survival in both univariate and multivariate analyses.Conclusions: Tumor cell expression of HLA-DMB is associated with increased numbers of tumor-infiltrating CD8 T lymphocytes and both are associated with improved survival in advanced-stage serous ovarian cancer.

Ovarian cancer is resistant to the antiproliferative effects of transforming growth factor-β (TGF-β); however, the mechanism of this resistance remains unclear. We used oligonucleotide arrays to profile 37 undissected, 68 microdissected advanced-stage, and 14 microdissected early-stage papillary serous cancers to identify signaling pathways involved in ovarian cancer. A total of seven genes involved in TGF-β signaling were identified that had altered expression >1.5-fold (P < 0.001) in the ovarian cancer specimens compared with normal ovarian surface epithelium. The expression of these genes was coordinately altered: genes that inhibit TGF-β signaling (DACH1, BMP7, and EVI1) were up-regulated in advanced-stage ovarian cancers and, conversely, genes that enhance TGF-β signaling (PCAF, TFE3, TGFBRII, and SMAD4) were down-regulated compared with the normal samples. The microarray data for DACH1 and EVI1 were validated using quantitative real-time PCR on 22 microdissected ovarian cancer specimens. The EVI1 gene locus was amplified in 43% of the tumors, and there was a significant correlation (P = 0.029) between gene copy number and EVI1 gene expression. No amplification at the DACH1 locus was found in any of the samples. DACH1 and EVI1 inhibited TGF-β signaling in immortalized normal ovarian epithelial cells, and a dominant-negative DACH1, DACH1-ΔDS, partially restored signaling in an ovarian cancer cell line resistant to TGF-β. These results suggest that altered expression of these genes is responsible for disrupted TGF-β signaling in ovarian cancer and they may be useful as new and novel therapeutic targets for ovarian cancer. (Cancer Res 2006; 66(17): 8404-12)

Purpose: To elucidate the molecular mechanisms contributing to the unique clinicopathologic characteristics of mucinous ovarian carcinoma, global gene expression profiling of mucinous ovarian tumors was carried out. Experimental Design: Gene expression profiling was completed for 25 microdissected mucinous tumors [6 cystadenomas, 10 low malignant potential (LMP) tumors, and 9 adenocarcinomas] using Affymetrix U133 Plus 2.0 oligonucleotide microarrays. Hierarchical clustering and binary tree prediction analysis were used to determine the relationships among mucinous specimens and a series of previously profiled microdissected serous tumors and normal ovarian surface epithelium. PathwayAssist software was used to identify putative signaling pathways involved in the development of mucinous LMP tumors and adenocarcinomas. Results: Comparison of the gene profiles between mucinous tumors and normal ovarian epithelial cells identified 1,599, 2,916, and 1,765 differentially expressed in genes in the cystadenomas, LMP tumors, and adenocarcinomas, respectively. Hierarchical clustering showed that mucinous and serous LMP tumors are distinct. In addition, there was a close association of mucinous LMP tumors and adenocarcinomas with serous adenocarcinomas. Binary tree prediction revealed increased heterogeneity among mucinous tumors compared with their serous counterparts. Furthermore, the cystadenomas coexpressed a subset of genes that were differentially regulated in LMP and adenocarcinoma specimens compared with normal ovarian surface epithelium. PathwayAssist highlighted pathways with expression of genes involved in drug resistance in both LMP and adenocarcinoma samples. In addition, genes involved in cytoskeletal regulation were specifically up-regulated in the mucinous adenocarcinomas. Conclusions: These data provide a useful basis for understanding the molecular events leading to the development and progression of mucinous ovarian cancer.

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

Purpose: The presence of similar histologic subtypes of epithelial ovarian and endometrial cancers has long been noted, although the relevance of this finding to pathogenesis and clinical management is unclear. Despite similar clinical characteristics, histologic subtypes of cancers of the ovary and endometrium are treated according to organ of origin. This study compares the gene expression profiles of analogous histologic subtypes of cancers of the ovary and endometrium using the same genomic platform to determine the similarities and differences between these tumors. Experimental Design: Gene expression profiles of 75 cancers (endometrioid, serous, and clear cell) of the ovary and endometrium, five renal clear cell cancers, and seven normal epithelial brushings were determined using a 11,000-element cDNA array. All images were analyzed using BRB ArrayTools. Validation was done using real-time PCR on select genes and immunohistochemical staining. Results: Comparison across endometrial and ovarian cancers and serous and endometrioid tumors showed expression patterns reflecting their organ of origin. Clear cell tumors, however, showed remarkably similar expression patterns regardless of their origin, even when compared with renal clear cell samples. A set of 43 genes was common to comparisons of each of the three histologic subtypes of ovarian cancer with normal ovarian surface epithelium. Conclusions: The comparison of the gene expression profiles of endometrioid and serous subtypes of ovarian and endometrial cancer are largely unique to the combination of a particular subtype in a specific organ. In contrast, clear cell cancers show a remarkable similarity in gene expression profiles across organs (including kidney) and could not be statistically distinguished.

5552 Background: Prognostic gene expression signatures have been derived for undissected serous ovarian epithelial tumors, yet the specific contribution of stromal cells to patient survival has not been addressed. The aim of this study is to identify stromal genes impacting patient survival in the context of serous ovarian cancer. Methods: Expression profiling utilizing Affymetrix U133 Plus 2.0 oligonucleotide arrays was completed for 50 microdissected stromal samples derived from high-grade, late-stage serous tumors displaying a broad spectrum of survival endpoints. A semi-supervised dimension reduction method employing multivariate Cox regression and principal components analysis was applied to the expression data to identify genes associated with patient survival and establish a predictive model. qRT-PCR was employed to validate the microarray expression data. Results: Cox regression analysis identified 267 significant genes. The first 6 principal components of these genes, representing >65% of total variance, entered a multivariate Cox model through which the relative hazard of future patients can be predicted. To confirm our finding, the microarray data underwent leave-one-out validation. The patients were equally divided into low- and high-risk groups and non-parametric Kaplan-Meier analysis and log rank test demonstrated the two groups were significantly different in survival (p = 0.0115). Genes associated with cell survival and migration were identified in the prognostic signature. For validation, qRT-PCR data for all 50 specimens was correlated with microarray expression values for a series of select prognostic genes. Conculsions: In this study, we characterized and validated a stromal dervied prognostic signature associated with poor patient survival. Contained in this novel predictor may be stromal targets suitable for the design of new therapeutic interventions, or use as independent diagnostic markers. No significant financial relationships to disclose.

5032 Background: Though most patients with late stage serous ovarian cancer die within 2 years of diagnosis, a subset of patients, even with clinically and morphologically indistinguishable disease...

5000 Background: The benefit of optimal surgical cytoreduction for patients with advanced ovarian cancer is well established. Whether an optimal surgical cytoreductive procedure is dependent upon t...