Literature DB >> 17878516

Contribution of DNA and tissue microarray technology to the identification and validation of biomarkers and personalised medicine in breast cancer.

Donal J Brennan1, Catherine Kelly, Elton Rexhepaj, Peter A Dervan, Michael J Duffy, William M Gallagher.   

Abstract

Completion of the human genome project has revolutionised translational medicine. High-throughput technology now permits investigators to systematically interrogate the genome, transcriptome, proteome and metabolome. It is expected that these advances will eventually be translated into new more sensitive diagnostic tests and less toxic therapeutics. A major shift is expected in clinical oncology over the next few decades as we start to move away from currently practiced, population-based approaches to personalised medicine. In this emerging approach, the molecular and pathophysiological characteristics of an individual patient and tumour will be measured and tailored therapeutic regimens will be administered based on these profiles. One of the key steps in this process will be the identification and validation of biomarkers. Whilst great advances have been made in the discovery of putative biomarkers, disappointingly few have been translated into clinically applicable assays. It is widely believed that this is due to a lack of well-designed, thorough validation studies. Here, we review the role of DNA microarrays and tissue microarrays in the validation of biomarkers in breast cancer, with emphasis on their potential application to determine mode of personalised therapy in the future.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17878516

Source DB:  PubMed          Journal:  Cancer Genomics Proteomics        ISSN: 1109-6535            Impact factor:   4.069


  14 in total

1.  Proteomic studies in breast cancer (Review).

Authors:  Xian-Ju Qin; Bruce X Ling
Journal:  Oncol Lett       Date:  2012-01-18       Impact factor: 2.967

2.  Clinicopathological significance of RASSF1A reduced expression and hypermethylation in hepatocellular carcinoma.

Authors:  Lang Hu; Gang Chen; Hongping Yu; Xiaoqiang Qiu
Journal:  Hepatol Int       Date:  2010-01-29       Impact factor: 6.047

3.  Altered cytoplasmic-to-nuclear ratio of survivin is a prognostic indicator in breast cancer.

Authors:  Donal J Brennan; Elton Rexhepaj; Sallyann L O'Brien; Elaine McSherry; Darran P O'Connor; Ailís Fagan; Aedín C Culhane; Desmond G Higgins; Karin Jirstrom; Robert C Millikan; Goran Landberg; Michael J Duffy; Stephen M Hewitt; William M Gallagher
Journal:  Clin Cancer Res       Date:  2008-05-01       Impact factor: 12.531

4.  Validation of cytoplasmic-to-nuclear ratio of survivin as an indicator of improved prognosis in breast cancer.

Authors:  Elton Rexhepaj; Karin Jirstrom; Darran P O'Connor; Sallyann L O'Brien; Goran Landberg; Michael J Duffy; Donal J Brennan; William M Gallagher
Journal:  BMC Cancer       Date:  2010-11-23       Impact factor: 4.430

5.  Polyisoprenylated methylated protein methyl esterase overexpression and hyperactivity promotes lung cancer progression.

Authors:  Felix Amissah; Randolph Duverna; Byron J Aguilar; Rosemary A Poku; Gebre-Egziabher Kiros; Nazarius S Lamango
Journal:  Am J Cancer Res       Date:  2014-03-01       Impact factor: 6.166

Review 6.  Antibody-based proteomics: fast-tracking molecular diagnostics in oncology.

Authors:  Donal J Brennan; Darran P O'Connor; Elton Rexhepaj; Fredrik Ponten; William M Gallagher
Journal:  Nat Rev Cancer       Date:  2010-08-19       Impact factor: 60.716

7.  Systematic antibody generation and validation via tissue microarray technology leading to identification of a novel protein prognostic panel in breast cancer.

Authors:  Patrick C O Leary; Sarah A Penny; Roisin T Dolan; Catherine M Kelly; Stephen F Madden; Elton Rexhepaj; Donal J Brennan; Amanda H McCann; Fredrik Pontén; Mathias Uhlén; Radoslaw Zagozdzon; Michael J Duffy; Malcolm R Kell; Karin Jirström; William M Gallagher
Journal:  BMC Cancer       Date:  2013-04-02       Impact factor: 4.430

8.  Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

Authors:  Paolo Martini; Davide Risso; Gabriele Sales; Chiara Romualdi; Gerolamo Lanfranchi; Stefano Cagnin
Journal:  BMC Bioinformatics       Date:  2011-04-11       Impact factor: 3.169

9.  Impact of biospecimens handling on biomarker research in breast cancer.

Authors:  Loris De Cecco; Valeria Musella; Silvia Veneroni; Vera Cappelletti; Italia Bongarzone; Maurizio Callari; Barbara Valeri; Marco A Pierotti; Maria Grazia Daidone
Journal:  BMC Cancer       Date:  2009-11-24       Impact factor: 4.430

10.  GERD-Barrett-Adenocarcinoma: Do We Have Suitable Prognostic and Predictive Molecular Markers?

Authors:  Romana Illig; Eckhard Klieser; Tobias Kiesslich; Daniel Neureiter
Journal:  Gastroenterol Res Pract       Date:  2013-03-20       Impact factor: 2.260

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.