Literature DB >> 16036111

High-resolution mapping of genomic imbalance and identification of gene expression profiles associated with differential chemotherapy response in serous epithelial ovarian cancer.

Marcus Bernardini1, Chung-Hae Lee, Ben Beheshti, Mona Prasad, Monique Albert, Paula Marrano, Heather Begley, Patricia Shaw, Al Covens, Joan Murphy, Barry Rosen, Salomon Minkin, Jeremy A Squire, Pascale F Macgregor.   

Abstract

Array comparative genomic hybridization (aCGH) and microarray expression profiling were used to subclassify DNA and RNA alterations associated with differential response to chemotherapy in ovarian cancer. Two to 4 Mb interval arrays were used to map genomic imbalances in 26 sporadic serous ovarian tumors. Cytobands 1p36, 1q42-44, 6p22.1-p21.2, 7q32.1-q34 9q33.3-q34.3, 11p15.2, 13q12.2-q13.1, 13q21.31, 17q11.2, 17q24.2-q25.3, 18q12.2, and 21q21.2-q21.3 were found to be statistically associated with chemotherapy response, and novel regions of loss at 15q11.2-q15.1 and 17q21.32-q21.33 were identified. Gene expression profiles were obtained from a subset of these tumors and identified a group of genes whose differential expression was significantly associated with drug resistance. Within this group, five genes (GAPD, HMGB2, HSC70, GRP58, and HMGB1), previously shown to form a nuclear complex associated with resistance to DNA conformation-altering chemotherapeutic drugs in in vitro systems, may represent a novel class of genes associated with in vivo drug response in ovarian cancer patients. Although RNA expression change indicated only weak DNA copy number dependence, these data illustrate the value of molecular profiling at both the RNA and DNA levels to identify small genomic regions and gene subsets that could be associated with differential chemotherapy response in ovarian cancer.

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Year:  2005        PMID: 16036111      PMCID: PMC1501280          DOI: 10.1593/neo.04760

Source DB:  PubMed          Journal:  Neoplasia        ISSN: 1476-5586            Impact factor:   5.715


  47 in total

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Journal:  Cancer Res       Date:  1997-07-01       Impact factor: 12.701

2.  Experimental assessment of the detection limit of genomic amplification by comparative genomic hybridization CGH.

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Authors:  K Kudoh; M Takano; T Koshikawa; M Hirai; S Yoshida; Y Mano; K Yamamoto; K Ishii; T Kita; Y Kikuchi; I Nagata; M Miwa; K Uchida
Journal:  Clin Cancer Res       Date:  1999-09       Impact factor: 12.531

4.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

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Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

5.  Alteration in copy numbers of genes as a mechanism for acquired drug resistance.

Authors:  Kohichiroh Yasui; Saori Mihara; Chen Zhao; Hiroyuki Okamoto; Fumiko Saito-Ohara; Akihiro Tomida; Tadao Funato; Akira Yokomizo; Seiji Naito; Issei Imoto; Takashi Tsuruo; Johji Inazawa
Journal:  Cancer Res       Date:  2004-02-15       Impact factor: 12.701

Review 6.  The use of cytogenetics in understanding ovarian cancer.

Authors:  M Bernardini; J Weberpals; J A Squire
Journal:  Biomed Pharmacother       Date:  2004-01       Impact factor: 6.529

7.  Transdominant DeltaTAp73 isoforms are frequently up-regulated in ovarian cancer. Evidence for their role as epigenetic p53 inhibitors in vivo.

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Journal:  Cancer Res       Date:  2004-04-01       Impact factor: 12.701

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Journal:  Cancer Res       Date:  1998-08-01       Impact factor: 12.701

Review 9.  Signature of a silent killer: expression profiling in epithelial ovarian cancer.

Authors:  Cécile Le Page; Diane Provencher; Christine M Maugard; Véronique Ouellet; Anne-Marie Mes-Masson
Journal:  Expert Rev Mol Diagn       Date:  2004-03       Impact factor: 5.225

10.  Mechanisms of paclitaxel-induced apoptosis in an ovarian cancer cell line and its paclitaxel-resistant clone.

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Journal:  Oncology       Date:  2004       Impact factor: 2.935

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  33 in total

Review 1.  A review of the past, present, and future directions of neoplasia.

Authors:  Alnawaz Rehemtulla; Brian D Ross
Journal:  Neoplasia       Date:  2005-12       Impact factor: 5.715

Review 2.  Chromosome 6p amplification and cancer progression.

Authors:  Gda C Santos; M Zielenska; M Prasad; J A Squire
Journal:  J Clin Pathol       Date:  2006-06-21       Impact factor: 3.411

3.  miR-200c inhibits metastasis of breast cancer cells by targeting HMGB1.

Authors:  Bao-Ping Chang; Dong-Sheng Wang; Jian-Wu Xing; Shao-Hua Yang; Qian Chu; Shi-Ying Yu
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4.  Mutation and methylation analysis of the chromodomain-helicase-DNA binding 5 gene in ovarian cancer.

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Journal:  Neoplasia       Date:  2008-11       Impact factor: 5.715

5.  Distinct patterns of structural and numerical chromosomal instability characterize sporadic ovarian cancer.

Authors:  Jane Bayani; Jana Paderova; Joan Murphy; Barry Rosen; Maria Zielenska; Jeremy A Squire
Journal:  Neoplasia       Date:  2008-10       Impact factor: 5.715

6.  High mobility group protein B1 is an activator of apoptotic response to antimetabolite drugs.

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7.  Analysis of DNA copy number alterations in ovarian serous tumors identifies new molecular genetic changes in low-grade and high-grade carcinomas.

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Review 8.  Cancer gene discovery in mouse and man.

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9.  Potential predictive markers of chemotherapy resistance in stage III ovarian serous carcinomas.

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Journal:  BMC Cancer       Date:  2009-10-18       Impact factor: 4.430

10.  The chemiluminescence based Ziplex automated workstation focus array reproduces ovarian cancer Affymetrix GeneChip expression profiles.

Authors:  Michael C J Quinn; Daniel J Wilson; Fiona Young; Adam A Dempsey; Suzanna L Arcand; Ashley H Birch; Paulina M Wojnarowicz; Diane Provencher; Anne-Marie Mes-Masson; David Englert; Patricia N Tonin
Journal:  J Transl Med       Date:  2009-07-06       Impact factor: 5.531

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