Affiliations: Cancer Tissue Bank Research Centre, University of Liverpool, Liverpool, UK | School of Biological Sciences, University of Liverpool, Liverpool, UK | Department of Cellular Pathology, Royal Hampshire County Hospital, Winchester, Hampshire, UK | Clatterbridge Cancer Research Trust, Clatterbridge Hospital, Bebington, Wirral, UK | School of Cancer Studies, University of Liverpool, Liverpool, UK
Note: [] Present address: School of Clinical Sciences, University of Liverpool, Liverpool, L69 3GA, UK.
Note: [] Corresponding author: Dr. Roger Barraclough, School of Biological Sciences, University of Liverpool, Crown Street, Liverpool, L69 7ZB, UK. Tel.: +44 151 795 4469; Fax: +44 151 795 4406; E-mail: brb@liverpool.ac.uk.
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.
