A breast cancer meta-analysis of two expression measures of chromosomal instability reveals a relationship with younger age at diagnosis and high risk histopathological variables
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1 Cancer Research UK London Research Institute, London, WC2A 3LY, United Kingdom.
2 Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), University College London, Physics Building, Gower Street, London, WC1E 6BT
3 Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.
4 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark.
5 Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology ([email protected]), Harvard Medical School, Boston, MA 02115, USA.
6 University of Applied Sciences, Südallee 2, 53424 Remagen, Germany.
7 Royal Marsden Hospital, Breast and Drug Development Units, Dept Medicine, Sutton, SM2 5PT, UK.
* These authors contributed equally
Received: April 6, 2011; Accepted: June 24, 2011; Published: June 25, 2011;
Charles Swanton, email:
Trevor A. Graham, email:
Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome.
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