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Neuroblastoma is a heterogeneous neoplasm that has served as a paradigm for the clinical utility of somatically acquired genomic aberrations. DNA copy number alterations (CNA) are currently used to predict prognosis, including MYCN amplification and deletions at chromosome bands 1p36 and 11q23. We predicted that genome-wide assessment of DNA aberrations in neuroblastoma tumors would provide a more precise estimation of clinical phenotype, and could be used to predict outcome. We measured CNAs in a representative set of 82 diagnostic tumors on a customized high-resolution BAC array-based CGH platform supplemented with additional clones across 1p36, 2p24, 3p21-22, 11q14-24, and 16p12-13, and integrated these data with RNA expression data. We used an unbiased statistical method to define a set of minimal common regions (MCRs) of aberration. Unsupervised hierarchical clustering identified four distinct genomic subclasses. First, a subset of tumors with a clinically benign phenotype showed predominantly whole chromosome gains and losses. Second, tumors with MYCN amplification had a unique genomic signature of 1p deletion and 17q gain, but few other rearrangements. Third, tumors with an aggressive clinical phenotype without MYCN amplification, showed multiple structural rearrangements. Most notable were deletions of 3p, 4p, and 11q and gain of 1q, 2p, 12q, and 17q. Lastly, there was a subset of tumors with an aggressive clinical phenotype and no detectable DNA CNAs. The genomic subsets were highly correlated with patient outcome, and individual MCRs remained prognostic in a multivariable model. DNA signature patterns embed important prognostic information in diagnostic neuroblastoma samples, and can identify candidate cancer-related genes.