Tomas Bonome

Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer

MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of ≈15% and at least ≈36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.

Expression Profiling of Serous Low Malignant Potential, Low-Grade, and High-Grade Tumors of the Ovary

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.

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

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

Gene alterations identified by expression profiling in tumor-associated endothelial cells from invasive ovarian carcinoma.

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.

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.

A Gene Signature Predictive for Outcome in Advanced Ovarian Cancer Identifies a Survival Factor: Microfibril-Associated Glycoprotein 2

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

Identification of molecular markers and signaling pathway in endometrial cancer in Hong Kong Chinese women by genome-wide gene expression profiling

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 (⩾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.

Expression Profiling Identifies Altered Expression of Genes That Contribute to the Inhibition of Transforming Growth Factor-β Signaling in Ovarian Cancer

Ovarian cancer is resistant to the antiproliferative effects of transforming growth factor-beta (TGF-beta); 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-beta 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-beta signaling (DACH1, BMP7, and EVI1) were up-regulated in advanced-stage ovarian cancers and, conversely, genes that enhance TGF-beta 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-beta signaling in immortalized normal ovarian epithelial cells, and a dominant-negative DACH1, DACH1-Delta DS, partially restored signaling in an ovarian cancer cell line resistant to TGF-beta. These results suggest that altered expression of these genes is responsible for disrupted TGF-beta signaling in ovarian cancer and they may be useful as new and novel therapeutic targets for ovarian cancer.

Roles of KLF6 and KLF6-SV1 in Ovarian Cancer Progression and Intraperitoneal Dissemination

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.

Expression Profiling of Mucinous Tumors of the Ovary Identifies Genes of Clinicopathologic Importance

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.