Identification of genomic DNA signatures predicting relapse in low- and intermediate-risk neuroblastoma using a case control design and high-density SNP genotyping: A Children's Oncology Group (COG) study

9500 Background: Neuroblastoma (NB) is a childhood malignancy with a heterogeneous clinical course. Clinical and genomic markers are powerful predictors of outcome and are used to stratify cases for treatment intensity, but imprecision remains. Methods: We identified all disease recurrences from the recently closed COG low- (P9641: 903 eligible, 63 events) and intermediate-risk (A3961: 467 eligible, 40 events) NB phase III trials. To date, tumor DNA from 35 cases and 90 controls (P9641/A3961 patients without event) was used for whole genome copy number and genotype evaluation on the Illumina HumanHap550 (550K SNPs) array. An in-house algorithm was developed to assign genomic copy number and loss of heterozygosity based on probe intensity (log R ratio) and degree of allelic imbalance (B allele frequency). Results: A total of 988 chromosomal aberrations were identified; 231 (23.4%) were whole chromosome (WC) copy number aberrations (CNA). Unsupervised hierarchical clustering identified 10 tumor subsets, with 2 highly enriched with cases showing progression events (13/21; 61%), and 2 dominated by WC gains (chromosomes 2, 6, 7 and 18) with only 2/20 events. Regional aberrations most highly associated with EFS included loss of 11q14-qter (p=0.036), and gain of 11p (p=0.003), 11q13 (p=0.020), and 17q23-qter (p=0.005). Other regional CNAs at borderline univariate significance for EFS included partial gain at 2p, 2q, 6q, 7q, 12q and 13q. The pattern 11p and proximal 11q gain associated with loss of distal 11q was associated with relapse and death (p=0.006 and p=0.023). Conclusion: Whole genome SNP genotyping detects patterns of chromosomal CNAs predictive of EFS, even in situations where events are rare such as low- and intermediate- risk NB. These data support chromosomal 11 and 17 structural CNAs as being most highly predictive of relapse in otherwise favorable NBs, but also suggest that other CNAs likely cooperate and may improve precisions for risk prediction. These data can be used to identify patients eligible for chemotherapy reduction/elimination, and perhaps others for intensification. Ongoing analyses of the remaining samples will extend these conclusions. No significant financial relationships to disclose.

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