Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features
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* Corresponding author: Åslaug Helland aslaug.helland@rr-research.no
1 Dept of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
2 Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, 0316 Oslo, Norway
3 Dept of Oncology, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
4 Biomedical Research Group, Department of Informatics, University of Oslo, 0316 Oslo, Norway
5 Center for Cancer Biomedicine, University of Oslo, 0310 Oslo, Norway
6 Department of Clinical Molecular Biology, Division of Medicine and Laboratory Sciences, Institute for Clinical Medicine, Akershus University Hospital, University of Oslo, 0316 Oslo, Norway
7 Dept of Surgery, Akerhus University Hospital, 1478 Lørenskog, Norway
8 Dept of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
9 Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
10 Dept of Radiology, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
11 Dept of Radiology, University Hospital of North Norway, 9038 Tromsø, Norway
12 Dept of Radiology, Buskerud Hospital, 3004 Drammen, Norway
13 Dept of Radiology, Innlandet Hospital, 2609 Lillehammer, Norway
14 Institute of Health Promotion, Akershus University Hospital, 1478 Lørenskog, Norway
15 The Norwegian Cancer Registry, 0304 Oslo, Norway
16 Dept of Nutrition, School of Medicine, 0316 University of Oslo, Oslo, Norway
17 Dept of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA 90089, USA
BMC Medical Genomics 2011, 4:77 doi:10.1186/1755-8794-4-77
Published: 1 November 2011Abstract
Background
Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk.
Methods
Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets.
Results
Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions.
Conclusion
This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.