Literature DB >> 15016320

Expression profiling to predict postoperative prognosis for estrogen receptor-negative breast cancers by analysis of 25,344 genes on a cDNA microarray.

Takemitsu Nagahata1, Masamitsu Onda, Mitsuru Emi, Hisaki Nagai, Koji Tsumagari, Takashi Fujimoto, Akira Hirano, Takamichi Sato, Kiyohiro Nishikawa, Futoshi Akiyama, Goi Sakamoto, Fujio Kasumi, Yoshio Miki, Toshihiro Tanaka, Tatsuhiko Tsunoda.   

Abstract

Estrogen receptor (ER) status is an essential determinant of clinical and biological behavior of human breast cancers. While ER-positive breast cancers respond well to adjuvant hormone therapy, ER-negative tumors are generally resistant. To date, no attempts have succeeded in finding molecular markers for classifying ER-negative breast cancers with respect to postoperative prognosis. To identify a set of prognostic markers for this type of cancer, we used a cDNA microarray consisting of 25,344 human genes to investigate expression profiles of ten primary breast cancers from patients who had died of breast cancer within 5 years after surgery (5y-D) and 10 from patients who had survived disease-free for more than 5 years (5y-S). Sets of genes characterizing each group were identified by Mann-Whitney and random-permutation tests. We documented 71 genes with higher expression in the 5y-D group than in the 5y-S group, and 15 with higher expression in the 5y-S group than in the 5y-D group. Semi-quantitative RT-PCR experiments were carried out to confirm the results of the microarray analysis. We established a scoring system for predicting postoperative prognosis of ER-negative breast cancers on the basis of aberrant gene expression. The list of genes reported here provides valuable information with regard to progression of breast cancer and is a source of possible target molecules for development of novel drugs to treat patients with ER-negative breast cancers.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15016320     DOI: 10.1111/j.1349-7006.2004.tb02206.x

Source DB:  PubMed          Journal:  Cancer Sci        ISSN: 1347-9032            Impact factor:   6.716


  8 in total

1.  TDRD3 is an effector molecule for arginine-methylated histone marks.

Authors:  Yanzhong Yang; Yue Lu; Alexsandra Espejo; Jiacai Wu; Wei Xu; Shoudan Liang; Mark T Bedford
Journal:  Mol Cell       Date:  2010-12-22       Impact factor: 17.970

2.  A clinical prognostic prediction of lymph node-negative breast cancer by gene expression profiles.

Authors:  Dingfeng Jiang; Naiqing Zhao
Journal:  J Cancer Res Clin Oncol       Date:  2006-06-08       Impact factor: 4.553

Review 3.  Protein arginine methyltransferases and cancer.

Authors:  Yanzhong Yang; Mark T Bedford
Journal:  Nat Rev Cancer       Date:  2012-12-13       Impact factor: 60.716

4.  A gene signature for predicting outcome in patients with basal-like breast cancer.

Authors:  Robin M Hallett; Anna Dvorkin-Gheva; Anita Bane; John A Hassell
Journal:  Sci Rep       Date:  2012-01-17       Impact factor: 4.379

5.  Arginine methylation of USP9X promotes its interaction with TDRD3 and its anti-apoptotic activities in breast cancer cells.

Authors:  Nithya Narayanan; Zhihao Wang; Ling Li; Yanzhong Yang
Journal:  Cell Discov       Date:  2017-01-03       Impact factor: 10.849

6.  Tudor Domain Containing Protein 3 Promotes Tumorigenesis and Invasive Capacity of Breast Cancer Cells.

Authors:  Alan Morettin; Geneviève Paris; Younes Bouzid; R Mitchell Baldwin; Theresa J Falls; John C Bell; Jocelyn Côté
Journal:  Sci Rep       Date:  2017-07-11       Impact factor: 4.379

7.  TDRD3, a novel Tudor domain-containing protein, localizes to cytoplasmic stress granules.

Authors:  Isabelle Goulet; Sophie Boisvenue; Sophie Mokas; Rachid Mazroui; Jocelyn Côté
Journal:  Hum Mol Genet       Date:  2008-07-15       Impact factor: 6.150

8.  Production and characterisation of monoclonal antibodies against RAI3 and its expression in human breast cancer.

Authors:  Hannah Jörissen; Nuran Bektas; Edgar Dahl; Arndt Hartmann; Anette ten Haaf; Stefano Di Fiore; Hans Kiefer; Andreas Thess; Stefan Barth; Torsten Klockenbring
Journal:  BMC Cancer       Date:  2009-06-24       Impact factor: 4.430

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.