Table of Contents Author Guidelines Submit a Manuscript
Cellular Oncology
Volume 32, Issue 1-2, Pages 87-99
http://dx.doi.org/10.3233/CLO-2009-0499

Microarray Analysis of Suppression Subtracted Hybridisation Libraries Identifies Genes Associated with Breast Cancer Progression

Dong Liu Barraclough,1,2 Susan Sewart,1,2 Philip S. Rudland,1,2 Balvinder S. Shoker,3 D. Ross Sibson,4,5 Roger Barraclough,2 and Michael P. A. Davies4,5

1Cancer Tissue Bank Research Centre, University of Liverpool, Liverpool, UK
2School of Biological Sciences, University of Liverpool, Liverpool, UK
3Department of Cellular Pathology, Royal Hampshire County Hospital, Winchester, Hampshire, UK
4Clatterbridge Cancer Research Trust, Clatterbridge Hospital, Bebington, Wirral, UK
5School of Cancer Studies, University of Liverpool, Liverpool, UK

Copyright © 2010 Hindawi Publishing Corporation and the authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background: A major challenge of cancer research is to identify key molecules which are responsible for the development of the malignant metastatic phenotype, the major cause of cancer death.

Methods: Four subtracted cDNA libraries were constructed representing mRNAs differentially expressed between benign and malignant human breast tumour cells and between micro-dissected breast carcinoma in situ and invasive carcinoma. Hundreds of differentially expressed cDNAs from the libraries were micro-arrayed and screened with mRNAs from human breast tumor cell lines and clinical specimens. Gene products were further examined by RT-PCR and correlated with clinical data.

Results: The combination of subtractive hybridisation and microarray analysis has identified a panel of 15 cDNAs which shows strong correlations with estrogen receptor status, malignancy or relapse. This panel included S100P, which was associated with aneuploidy in cell lines and relapse/death in patients, and AGR2 which was associated with estrogen receptor and with patient relapse. X-box binding protein-1 is also an estrogen-dependent gene and is associated with better survival for breast cancer patients.

Conclusions: The combination of subtracted cDNA libraries and microarray analysis has thus identified potential diagnostic/prognostic biomarkers and targets for cancer therapy, which have not been identified from common prognostic gene signatures.