Breast carcinoma; RERG; Gene expression; Luminal; Oestrogen receptor; Immunohistochemistry
Abstract :
[en] Global gene expression profiling studies have classified breast cancer into a number of distinct biological and molecular classes with clinical relevance. The heterogeneous luminal group, which is largely characterised by oestrogen receptor (ER) expression, appears to contain distinct subgroups with differing behaviour. In this study, we analysed 47,293 gene transcripts in 128 invasive breast carcinomas (BC) using Artificial Neural Networks and a cross-validation analysis in combination with an ensemble sample classification to identify genes that can be used to subclassify ER+ luminal tumours. The results were validated using immunohistochemistry on TMAs containing 1,140 invasive breast cancers. Our results showed that the RERG gene is one of the highest ranked genes to differentiate between ER+ luminal-like and ER- non-luminal cancers based on a 10-fold external cross-validation analysis with an average classification accuracy of 89%. This was confirmed in our protein expression studies that showed RERG positive associations with markers of luminal differentiation including ER, luminal cytokeratins (CK19, CK18 and CK7/8) and FOXA1 (P = 0.004) and other markers of good prognosis in BC including small size, lower histologic grade and positive expression of androgen receptor, nuclear BRCA1, FHIT and cell cycle inhibitors p27 and p21. RERG expression was inversely associated with the proliferation marker MIB1 (P = 0.005) and p53. Strong RERG expression showed an association with longer breast cancer specific survival and distant metastasis free interval in the whole series as well as in the ER+ luminal group and these associations were independent of other prognostic variables. In conclusion, we used novel bioinformatics methods to identify candidate genes to characterise ER+ luminal-like breast cancer. RERG gene is a key marker of the luminal BC class and can be used to separate distinct prognostic subgroups.
Disciplines :
Biochemistry, biophysics & molecular biology
Identifiers :
UNILU:UL-ARTICLE-2011-372
Author, co-author :
Habashy, Hany O.; Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK
Powe, Desmond G.; Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK
Glaab, Enrico ; School of Computer Science, University of Nottingham, Nottingham, UK
Ball, Graham; John Van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK
Spiteri, Immaculada; Department of Oncology, University of Cambridge, Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
Krasnogor, Natalio; School of Computer Science, University of Nottingham, Nottingham, UK
Garibaldi, Jonathan M.; School of Computer Science, University of Nottingham, Nottingham, UK
Rakha, Emad A.; Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK
Green, Andrew R.; Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK
Caldas, Carlos; Department of Oncology, University of Cambridge, Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
Ellis, Ian O.; Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK
External co-authors :
yes
Language :
English
Title :
RERG (Ras-like, oestrogen-regulated, growth-inhibitor) expression in breast cancer: a marker of ER-positive luminal-like subtype
