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Whole Genome Expression Profiling of Advance Stage Papillary Serous Oncogene (2004) 23, 8065–8077 & 2004 Nature Publishing Group All rights reserved 0950-9232/04 $30.00 www.nature.com/onc Whole genome expression profiling of advance stage papillary serous ovarian cancer reveals activated pathways Howard Donninger1,5, Tomas Bonome1,5, Mike Radonovich2, Cynthia A Pise-Masison2, John Brady2, Joanna H Shih3, JCarl Barrett 4, and Michael JBirrer* ,1 1Department of Cell and Cancer Biology, National Cancer Institute, Rockville, MD 20850, USA; 2Laboratory of Cellular Oncology Virus Tumor Biology Section, National Cancer Institute, Rockville, MD 20850, USA; 3Biometric Research Branch, National Cancer Institute, Rockville, MD 20852, USA; 4Laboratory of Biosystems and Cancer, National Cancer Institute, Rockville, MD 20850, USA Ovarian cancer is the most lethal type of gynecologic 2004, 24 400 women in the United States will be cancer in the Western world. The high case fatality rate is diagnosed with the disease, and an estimated 14 300 due in part because most ovarian cancer patients present will die from it (Jemal et al., 2003). It is the leading cause with advanced stage disease which is essentially incurable. of death from gynecologic cancers in the United States In order to obtain a whole genome assessment of aberrant and is the most lethal type of gynecologic cancer in the gene expression in advanced ovarian cancer, we used Western world. This high case fatality rate is due in part oligonucleotide microarrays comprising over 40 000 fea- to the fact that most ovarian cancer patients present tures to profile 37 advanced stage papillary serous with advanced stage disease where the disease is more primary carcinomas. We identified 1191 genes that were difficult to treat. Although patients presenting with significantly (Po0.001) differentially regulated between stage I ovarian cancer have a 5-year survival rate of over the ovarian cancer specimens and normal ovarian surface 85%, only 25% of patients presenting with advanced epithelium. The microarray data were validated using real stage disease survive to 5 years after initial diagnosis time RT–PCR on 14 randomly selected differentially (Friedlander, 1998). regulated genes. The list of differentially expressed genes There is substantial evidence that the majority of includes ones that are involved in cell growth, differentia- ovarian cancers comprise carcinomas arising from the tion, adhesion, apoptosis and migration. In addition, surface epithelium (Godwin et al., 1992; Testa et al., numerous genes whose function remains to be elucidated 1994; Nap et al., 1996; Auersperg et al., 1999). Of the were also identified. The microarray data were imported four main histologic subtypes, serous papillary, muci- into PathwayAssist software to identify signaling path- nous, endometrioid and clear cell, the serous adenocar- ways involved in ovarian cancer tumorigenesis. Based on cinomas are the most common subtype and comprise our expression results, a signaling pathway associated approximately 50% of all ovarian carcinomas (Scully with tumor cell migration, spread and invasion was et al., 1998), with the endometrioid subtype accounting identified as being activated in advanced ovarian cancer. for 20–25% of ovarian cancer. Thus, the majority of The data generated in this study represent a comprehen- poor prognosis ovarian cancers comprise the serous sive list of genes aberrantly expressed in serous papillary subtype. ovarian adenocarcinoma and may be useful for the Ovarian cancers are highly aneuploid and genetically identification of potentially new and novel markers and complex tumors that develop in a multistep process therapeutic targets for ovarian cancer. involving alterations of numerous genes. With the Oncogene (2004) 23, 8065–8077. doi:10.1038/sj.onc.1207959 advent of SAGE and DNA microarray technology, it Published online 13 September 2004 is now possible to study gene expression profiles of large numbers of tumor samples and to determine the Keywords: ovarian cancer; microarray; signaling path- characteristic gene expression patterns associated with ways those tumors. To date, a number of studies utilizing these technologies to determine gene expression profiles of ovarian cancer have been reported (Schummer et al., Introduction 1999; Wang et al., 1999; Hough et al., 2000; Ismail et al., 2000; Ono et al., 2000; Tapper et al., 2001; Tonin et al., Ovarian cancer is the fifth most common malignancy in 2001; Welsh et al., 2001; Wong et al., 2001; Schwartz women as well as the fifth leading cause of cancer deaths et al., 2002; Schaner et al., 2003; Adib et al., 2004), in women in the United States (Jemal et al., 2003). In however, only a few of these studies compare papillary serous ovarian cancer to normal ovarian epithelium (Schummer et al., 1999; Ono et al., 2000; Welsh et al., *Correspondence: M Birrer; E-mail: [email protected] 5These authors contributed equally to this work 2001; Schaner et al., 2003; Adib et al., 2004). Further- Received 6 May 2004; revised 8 June 2004; accepted 9 June 2004; more, only one of these studies exclusively analyses published online 13 September 2004 serous ovarian cancer to normal ovary (Welsh et al., Whole genome expression profiling of ovarian cancer H Donninger et al 8066 2001). The data generated from these studies have cell adhesion, apoptosis, growth and differentiation provided important information. These studies, how- (Figure 1). Since the cancer specimens were not ever, have scientific limitations such as small numbers of microdissected, it is possible that some of these genes tumors analysed, exclusive analysis of cell lines as are expressed in stromal cells rather than the epithelial opposed to primary tumors and normal epithelium, as tumor cells. well as limited numbers of features on the microarrays used in the studies. Thus, to date, a substantial analysis Validation of microarray data of the gene expression pattern of papillary serous ovarian cancer as compared to the normal ovarian To ensure the accuracy of our microarray, we performed epithelium has not been undertaken. an ‘electronic validation’ by comparing our list of In the present study, we used oligonucleotide micor- differentially expressed genes to those genes that have arrays containing over 40 000 features to profile 37 previously been documented to be differentially regu- advanced stage papillary serous ovarian adenocarcino- lated in advanced stage papillary serous ovarian cancer mas and compare their gene expression profiles with specimens. In all, 12 of the differentially expressed genes normal ovarian surface epithelium. Our microarray identified from our analysis have previously been analysis identified 1191 genes that were differentially reported to be differentially expressed (Table 2). Those regulated by 1.5-fold or greater between normal ovarian genes previously identified as being overexpressed in surface epithelium and papillary serous ovarian carci- serous ovarian cancer showed a similar pattern of noma (Po0.001). Fourteen genes from this list were expression in our study and, similarly, genes that were randomly chosen and used to validate the arrays by underexpressed in our study showed the same trend as quantitative real-time RT–PCR (qRT–PCR). In addi- that reported in previously published findings. tion, the microarray data were imported into To further validate the microarray results, 14 genes PathwayAssist software and signaling pathways poten- differentially expressed between the cancer and normal tially involved in ovarian cancer tumorigenesis were specimens were selected for qRT–PCR analysis on 10 of identified. The data generated in this study represent a the cancer specimens and four normal samples. The comprehensive list of genes aberrantly expressed in expression differences for both the over expressed genes serous papillary ovarian adenocarcinoma and may be (Figure 2a) and underexpressed genes (Figure 2b) in useful for the identification of potentially new and novel cancers as compared to normal samples were quite markers and therapeutic targets for ovarian cancer. apparent, and mirrored the microarray data. Although the quantitative change for each gene did not exactly correlate between the qRT–PCR and microarray ana- lyses, the general trend of being either overexpressed or Results underexpressed was consistent between the two techni- Whole genome expression profiles of papillary serous ques. ovarian adenocarcinoma versus normal ovarian epithelium Identification of signaling pathways contributing to Global gene expression profiles were examined for 37 ovarian tumorigenesis papillary serous ovarian adenocarcinomas and six normal ovarian surface epithelium cytobrushings using To identify signaling pathways that are associated with an oligonucleotide array consisting of 47 000 transcript ovarian tumorigenesis and that may contribute to tumor sequences. After initial filtering of the data, an progression and metastasis, we analysed our microarray informative data set consisting of 22 579 sequences was expression data using PathwayAssist (Iobion Infor- generated. Comparison of the gene expression profiles of matics, LLC). This software utilizes a proprietary the cancer specimens with the normal ovary brushings database containing over 140 000 references on protein revealed 1191 differentially expressed sequences that interactions obtained from PubMed to generate a differed by 1.5-fold or greater with a significance of biological association network (BAN) of known protein Po0.001. A representative list of differentially regulated interactions.
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