[CANCER RESEARCH 60, 5007–5011, September 15, 2000] Advances in Brief Identification by cDNA Microarray of Genes Involved in Ovarian Carcinogenesis 1 Kenji Ono, Toshihiro Tanaka, Tatsuhiko Tsunoda, Osamu Kitahara, Chikashi Kihara, Aikou Okamoto, Kazunori Ochiai, Toshihisa Takagi, and Yusuke Nakamura 2 Laboratories of Molecular Medicine [K. On., T. Tan., O. K., C. K., Y. N.] and Genome Database [T. Ts., T. Tak.], Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan, and Department of Obstetrics and Gynecology, Jikei University School of Medicine, Tokyo, Japan [A. O., K. Oc.] Abstract To identify genes involved in the development or progression of ovarian cancer, we analyzed gene expression profiles of nine ovarian tumors using a DNA microarray consisting of 9121 genes. Comparison of expression patterns between carcinomas and the corresponding normal ovarian tis- sues enabled us to identify 55 genes that were commonly up-regulated and 48 genes that were down-regulated in the cancer specimens. When the five serous adenocarcinomas were analyzed separately from the four muci- nous adenocarcinomas, we identified 115 genes that were expressed dif- ferently between the two types of tumor. Investigation of these genes should help to disclose the molecular mechanism(s) of ovarian carcino- genesis and define molecular separation of the two most common histo- logical types of ovarian cancer. Introduction Ovarian carcinoma has the worst prognosis among gynecological malignancies because most cases are not diagnosed until the disease is at an advanced stage. Although various therapeutic approaches are followed in clinical practice, most of them are not lifesaving. Hence, the discovery of ways to diagnose ovarian cancer at an early stage and establish more effective therapies is a critical and urgent issue. To achieve this goal, identification and characterization of key molecules that participate in ovarian carcinogenesis are essential steps. Like cancers in other tissues, ovarian carcinomas are considered to result from a serial accumulation of genetic changes in a cell lineage (1). Mutations of the p53, c-erbB-2, c-myc, and K-ras genes appear to play important roles in this disease (2). However, his- topathological differences that are reflected as serous, mucinous, endometrioid, clear cell, or transitional cell types of ovarian cancer cannot be explained by the presence or absence of those particular genetic changes. We also have no good parameters for distinguishing a variety of biological behaviors such as metastatic ability, invasive- ness, and chemosensitivity. To better understand ovarian carcinogenesis, we need to obtain a large body of information regarding each type of cancer material. To this end, we have applied recently established cDNA microarray technology, which can reveal the expression profiles of thousands of genes simultaneously (3, 4). Studies of this kind have identified genes related to carcinomas of the cervix, colon, breast, and prostate (5–9). The successful molecular classification of such tumors on the basis of gene expression profiles revealed on cDNA microarrrays indicates that this technology is likely to become an essential resource for the development of personalized medical treatments in the future (10 –12). Here we report the identification of dozens of genes whose expres- sion was up- or down-regulated in multiple specimens of ovarian carcinoma using the cDNA microarray technique coupled with T7- based RNA amplification. In addition, we found a number of genes that were expressed differently between two major histological types, serous and mucinous carcinomas of the ovary. Materials and Methods Tissue Specimens. Ovarian cancer tissues, along with noncancerous ovar- ian tissues from the same patients, were excised during surgery after obtaining informed preoperative consent from the patients. Five samples diagnosed as serous adenocarcinoma and four samples of mucinous adenocarcinoma were selected for this study. Each corresponding normal tissue was confirmed histopathologically to be free of cancer cells. Clinical stages were determined on the basis of criteria outlined in 1988 by the International Federation of Gynecology and Obstetrics (FIGO). T7-based RNA Amplification. Total RNA was extracted from each spec- imen using Trizol (Life Technologies, Inc.) according to the manufacturer’s instructions. After treatment with DNase I (Nippon Gene), T7-based RNA amplification was carried out as described previously (13), with a few modi- fications. Using 2 g of total RNA from each tissue sample as starting material, we performed two rounds of amplification; the amount of each amplified aRNA 3 was measured by a spectrophotometer, and its quality was checked by agarose gel electrophoresis. Preparation of Target DNA. We first selected known cancer-related genes to be spotted onto glass slides, followed by other genes including housekeeping genes from a list provided by the Laboratory of Cancer Genetics, National Center for Human Genome Research, NIH as well as ESTs and hybridization controls. In all, 9121 genes were chosen as target cDNAs, and their sequences were retrieved from the UniGene database (National Center for Biotechnology Information). Polyadenylated RNA isolated from the liver, spleen, thyroid, placenta, skeletal muscle, small intestine, brain, heart, fetal lung, fetal liver, fetal kidney, and fetal brain (Clontech) were used for target cDNA preparation. RNA was reverse transcribed using oligo(dT) primer and Superscript II reverse transcriptase (Life Technologies, Inc.). We amplified cDNA segments of 200-1100-bp long without repetitive or polyadenylated sequences. The PCR products were purified and spotted in duplicate on type 7 glass slides (Amersham Pharmacia Biotech) using a Microarray Spotter Gen- eration III (Amersham). Labeling, Hybridization, and Scanning. The cDNA probes were pre- pared from aRNA as described elsewhere (13). Five-g aliquots of aRNA from normal ovarian tissues and the corresponding cancers were labeled with Cy5-dCTP and Cy3-dCTP (Amersham Pharmacia Biotech), respectively. La- beled probes were mixed with microarray hybridization solution version 2 (Amersham) and formamide (Sigma) to a final concentration of 50%. After hybridization for 14 –16 h at 42°C, the slides were washed in 2 SSC and 1% SDS for 10 min at 55°C, washed in 0.2 SSC and 0.1% SDS for 10 min at 55°C, washed in 0.1 SSC for 1 min at room temperature, and then scanned using the Array Scanner Generation III (Amersham). The intensity of each hybridization signal was evaluated photometrically by the ArrayVision computer program (Amersham) and normalized to the aver- aged signals of housekeeping genes. The Cy3:Cy5 ratio for each sample was calculated by averaging spots. A cutoff value for each expression level was Received 5/4/00; accepted 8/3/00. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. 1 Supported in part by Research for the Future Program Grant 96L00102 from the Japan Society for the Promotion of Science. 2 To whom requests for reprints should be addressed, at Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. Phone: 81-3-5449-5372; Fax: 81-3-5449-5433; E-mail: yusuke@ims.u-tokyo.ac.jp. 3 The abbreviations used are: aRNA, antisense RNA; EST, expressed sequence tag; RT-PCR, reverse transcription-PCR. 5007 on June 9, 2015. © 2000 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from