Literature DB >> 18059348

Mechanisms of Disease: biomarkers and molecular targets from microarray gene expression studies in prostate cancer.

Colin S Cooper1, Colin Campbell, Sameer Jhavar.   

Abstract

Molecular biomarkers can serve as useful diagnostic markers, as prognostic markers for predicting clinical behavior, or as targets for new therapeutic strategies. Application of expression microarray technology, which allows the expression of all or most of the genes in the human genome to be analyzed simultaneously, has dramatically enhanced the discovery of prostate cancer biomarkers. The diagnostic markers identified include AMACR (alpha-methylacyl CoA racemase), a protein that has already been translated into clinical use as an aid in distinguishing prostate cancer from benign disease. Individual genes, such as the polycomb gene EZH2 whose expression indicates poor survival, have been identified. The power of microarray technology is that it has allowed the identification of gene signatures (each composed of multiple genes) that might provide improved prediction of clinical outcomes in human prostate cancer. The development of a new method for analyzing expression microarray data, called COPA, has led to the discovery of TMPRSS2-ERG gene fusion involvement in the development of prostate cancer, while expression analysis of castration-resistant prostate cancer has suggested the use of novel therapeutic approaches for advanced disease. Despite these successes, there are limitations in the application of microarray technology to prostate cancer; for example, unlike with other cancers, this approach has failed to provide a consistent unsupervised classification of the disease. Overcoming the reasons for these failures represents a major challenge for future research endeavors.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18059348     DOI: 10.1038/ncpuro0946

Source DB:  PubMed          Journal:  Nat Clin Pract Urol        ISSN: 1743-4270


  11 in total

1.  From transcriptome analysis to therapeutic anti-CD40L treatment in the SOD1 model of amyotrophic lateral sclerosis.

Authors:  John M Lincecum; Fernando G Vieira; Monica Z Wang; Kenneth Thompson; Gerald S De Zutter; Joshua Kidd; Andrew Moreno; Ricardo Sanchez; Isarelis J Carrion; Beth A Levine; Bashar M Al-Nakhala; Shawn M Sullivan; Alan Gill; Steven Perrin
Journal:  Nat Genet       Date:  2010-03-28       Impact factor: 38.330

2.  Bioinformatic analysis of differential expression and core GENEs in breast cancer.

Authors:  Hongchang Dong; Shuai Zhang; Yu Wei; Chunyan Liu; Na Wang; Pan Zhang; Jingling Zhu; Jin Huang
Journal:  Int J Clin Exp Pathol       Date:  2018-03-01

Review 3.  Innovations in the systemic therapy of prostate cancer.

Authors:  Dale R Shepard; Derek Raghavan
Journal:  Nat Rev Clin Oncol       Date:  2009-12-08       Impact factor: 66.675

4.  An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes.

Authors:  Atif Noorul Hasan; Mohammad Wakil Ahmad; Inamul Hasan Madar; B Leena Grace; Tarique Noorul Hasan
Journal:  Bioinformation       Date:  2015-05-28

5.  Expression data analysis to identify biomarkers associated with asthma in children.

Authors:  Wen Xu
Journal:  Int J Genomics       Date:  2014-03-27       Impact factor: 2.326

6.  Differential expression of apoptotic genes PDIA3 and MAP3K5 distinguishes between low- and high-risk prostate cancer.

Authors:  Nicole Chui Pressinotti; Helmut Klocker; Georg Schäfer; Van-Duc Luu; Markus Ruschhaupt; Ruprecht Kuner; Eberhard Steiner; Annemarie Poustka; Georg Bartsch; Holger Sültmann
Journal:  Mol Cancer       Date:  2009-12-27       Impact factor: 27.401

7.  Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

Authors:  Hongyu Diao; Xinxing Li; Sheng Hu; Yunhui Liu
Journal:  PLoS One       Date:  2012-12-28       Impact factor: 3.240

8.  No-match ORESTES explored as tumor markers.

Authors:  Barbara P Mello; Eduardo F Abrantes; César H Torres; Ariane Machado-Lima; Rogério da Silva Fonseca; Dirce M Carraro; Ricardo R Brentani; Luiz F L Reis; Helena Brentani
Journal:  Nucleic Acids Res       Date:  2009-03-06       Impact factor: 16.971

9.  miR-1 and miR-133b are differentially expressed in patients with recurrent prostate cancer.

Authors:  Omer Faruk Karatas; Esra Guzel; Ilknur Suer; Isin D Ekici; Turhan Caskurlu; Chad J Creighton; Michael Ittmann; Mustafa Ozen
Journal:  PLoS One       Date:  2014-06-26       Impact factor: 3.240

10.  Longitudinal Analysis of Gene Expression Changes During Cervical Carcinogenesis Reveals Potential Therapeutic Targets.

Authors:  Lijun Yu; Meiyan Wei; Fengyan Li
Journal:  Evol Bioinform Online       Date:  2020-05-18       Impact factor: 1.625

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.