Literature DB >> 16245302

Transcriptomic analysis of an in vitro murine model of ovarian carcinoma: functional similarity to the human disease and identification of prospective tumoral markers and targets.

Ulises Urzúa1, Katherine F Roby, Lisa M Gangi, James M Cherry, John I Powell, David J Munroe.   

Abstract

Ovarian cancer is an aggressive disease of poor prognostic when detected at advanced stage. It is widely accepted that the ovarian surface epithelium plays a central role in disease etiology, but little is known about disease progression at the molecular level. To identify genes involved in ovarian tumorigenesis, we carried out a genome-wide transcriptomic analysis of six spontaneously transformed mouse ovarian surface epithelial (MOSE) cell lines, an in vitro model for human ovarian carcinoma. Loess normalization followed by statistical analysis with control of multiple testing resulted in 509 differentially expressed genes using an adjusted P-value < or = 0.05 as cut-off. The top 20 differentially expressed genes included 10 genes (Spp1, Cyp1b1, Btg1, Cfh, Mt1, Mt2, Igfbp5, Gstm1, Gstm2, and Esr1) implicated in various aspects of ovarian carcinomas, and other 3 genes (Gsto1, Lcn7, and Alcam) associated to breast cancer. Upon functional analysis, the majority of alterations affected genes involved in glutathione metabolism and MAPK signaling pathways. Interestingly, over 20% of the aberrantly expressed genes were related to extracellular components, suggestive of potential markers of disease progression. In addition, we identified the genes Pura, Cnn3, Arpc1b, Map4k4, Tgfb1i4, and Crsp2 correlated to in vivo tumorigenic parameters previously reported for these cells. Taken together, our findings support the utility of MOSE cells in studying ovarian cancer biology and as a source of novel diagnostic and therapeutic targets. Copyright 2005 Wiley-Liss, Inc.

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Year:  2006        PMID: 16245302     DOI: 10.1002/jcp.20522

Source DB:  PubMed          Journal:  J Cell Physiol        ISSN: 0021-9541            Impact factor:   6.384


  22 in total

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2.  Lowered HGK expression inhibits cell invasion and adhesion in hepatocellular carcinoma cell line HepG2.

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Journal:  World J Gastroenterol       Date:  2010-09-28       Impact factor: 5.742

3.  miR-511 promotes the proliferation of human hepatoma cells by targeting the 3'UTR of B cell translocation gene 1 (BTG1) mRNA.

Authors:  Shu-Qin Zhang; Zhe Yang; Xiao-Li Cai; Man Zhao; Ming-Ming Sun; Jiong Li; Guo-Xing Feng; Jin-Yan Feng; Li-Hong Ye; Jun-Qi Niu; Xiao-Dong Zhang
Journal:  Acta Pharmacol Sin       Date:  2017-06-12       Impact factor: 6.150

4.  FSH stimulates ovarian cancer cell growth by action on growth factor variant receptor.

Authors:  Y Li; S Ganta; C Cheng; R Craig; R R Ganta; L C Freeman
Journal:  Mol Cell Endocrinol       Date:  2007-01-16       Impact factor: 4.102

5.  Generation of Cyp17iCre transgenic mice and their application to conditionally delete estrogen receptor alpha (Esr1) from the ovary and testis.

Authors:  Phillip J Bridges; Yongbum Koo; Dong-Wook Kang; Susan Hudgins-Spivey; Zi-Jian Lan; Xueping Xu; Francesco DeMayo; Austin Cooney; CheMyong Ko
Journal:  Genesis       Date:  2008-09       Impact factor: 2.487

6.  Advantages of the avian model for human ovarian cancer.

Authors:  Ana DE Melo Bernardo; Sólveig Thorsteinsdóttir; Christine L Mummery
Journal:  Mol Clin Oncol       Date:  2015-08-11

7.  Proteomic Analysis of Human Dermal Fibroblast Conditioned Medium (DFCM).

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Journal:  Protein J       Date:  2018-12       Impact factor: 2.371

8.  A fast score test for generalized mixture models.

Authors:  Rui Duan; Yang Ning; Shuang Wang; Bruce G Lindsay; Raymond J Carroll; Yong Chen
Journal:  Biometrics       Date:  2019-12-31       Impact factor: 2.571

9.  Mitf dosage as a primary determinant of melanocyte survival after ultraviolet irradiation.

Authors:  Thomas J Hornyak; Shunlin Jiang; Esther A Guzmán; Beth N Scissors; Chinisada Tuchinda; Hongbin He; James D Neville; Faith M Strickland
Journal:  Pigment Cell Melanoma Res       Date:  2009-02-03       Impact factor: 4.693

10.  Ovarian cancer mouse models: a summary of current models and their limitations.

Authors:  Miranda Y Fong; Sham S Kakar
Journal:  J Ovarian Res       Date:  2009-09-28       Impact factor: 4.234

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