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Analysis of gene expression profiles associated with cisplatin resistance in human ovarian cancer cell lines and tissues using cDNA microarray
Authors:Sakamoto M  Kondo A  Kawasaki K  Goto T  Sakamoto H  Miyake K  Koyamatsu Y  Akiya T  Iwabuchi H  Muroya T  Ochiai K  Tanaka T  Kikuchi Y  Tenjin Y
Institution:Dept. of Gynecology, Sasaki Institute Kyoundo Hospital. quaser@bekkoame.ne.jp
Abstract:Gene expression profiles were analyzed by using cDNA microarray for a cisplatin-sensitive cell line (KF), and three- and thirty-fold cisplatin-resistant ovarian cancer cell lines (KFr and KFrP200) both showing no p53 mutation within exon 5, 6, 7, 8 and no pglycoprotein overexpression. Expression of GST-pi mRNA increased as the level of resistance to cisplatin became high. Microarray analysis revealed that DNA repair associated genes, i.e., XRCC5, XRCC6, ERCC5, hMLH1 were over-expressed in three-fold cisplatin-resistant cell line, KFr as compared to cisplatin-sensitive parental cell line, KF. Apoptosis inhibitors, i.e., IGFR type I and II were over-expressed, and apoptosis inducer, i.e., caspase 3 and BAK were underexpressed in highly cisplatin-resistant cell line, KFrP200 as compared to KFr. As for clinical cases, cDNA microarray was used to compare gene expression profiles directly between two groups, i.e., the chemotherapy (CAP) sensitive group (n = 2) and the resistant group (n = 2). Six genes such as beta tubulin, high-mobility group (nonhistone chromosomal) protein 1, connective tissue growth factor, insulin-like growth factor binding protein 2, alpha tubulin, and RAS-related gene were overexpressed in CAP therapy resistance group, whereas seven genes such as CD9 antigen, alpha-2-macroglobulin, caveolin 2, interleukin 1 receptor antagonist, Rho GTPase activating protein 1, reticulon 3, cyclin-dependent kinase 10, keratin 7 were underexpressed in CAP therapy resistance group. By increasing clinical case number and gene number of microarray to be used in the analysis of expression profile of gene cluster affecting anticancer drug resistance and sensitivity of the ovarian cancer, it would be possible to apply microarray analysis to personalization of chemotherapy such as selection of effective chemotherapy protocol and prediction of therapeutic effect in the near future.
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