Using array-comparative genomic hybridization to define molecular portraits of primary breast cancers

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Abstract
We analysed 148 primary breast cancers using BAC-arrays containing 287 clones representing cancer-related gene/loci to obtain genomic molecular portraits. Gains were detected in 136 tumors (91.9%) and losses in 123 tumors (83.1%). Eight tumors (5.4%) did not have any genomic aberrations in the 281 clones analysed. Common (more than 15% of the samples) gains were observed at 8q11–qtel, 1q21–qtel, 17q11–q12 and 11q13, whereas common losses were observed at 16q12–qtel, 11ptel–p15.5, 1p36–ptel, 17p11.2–p12 and 8ptel–p22. Patients with tumors registering either less than 5% (median value) or less than 11% (third quartile) total copy number changes had a better overall survival (log-rank test: P=0.0417 and P=0.0375, respectively). Unsupervised hierarchical clustering based on copy number changes identified four clusters. Women with tumors from the cluster with amplification of three regions containing known breast oncogenes (11q13, 17q12 and 20q13) had a worse prognosis. The good prognosis group (Nottingham Prognostic Index (NPI) ⩽3.4) tumors had frequent loss of 16q24–qtel. Genes significantly associated with estrogen receptor (ER), Grade and NPI were used to build k-nearest neighbor (KNN) classifiers that predicted ER, Grade and NPI status in the test set with an average misclassification rate of 24.7, 25.7 and 35.7%, respectively. These data raise the prospect of generating a molecular taxonomy of breast cancer based on copy number profiling using tumor DNA, which may be more generally applicable than expression microarray analysis.

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