Chromosomal and microRNA expression patterns reveal biologically distinct subgroups of 11q- neuroblastoma

Abstract

Purpose: The purpose of this study was to further define the biology of the 11q- neuroblastoma tumor subgroup by the integration of array-based comparative genomic hybridization with microRNA (miRNA) expression profiling data to determine if improved patient stratification is possible.

Experimental design: A set of primary neuroblastoma (n = 160), which was broadly representative of all genetic subtypes, was analyzed by array-based comparative genomic hybridization and for the expression of 430 miRNAs. A 15-miRNA expression signature previously shown to be predictive of clinical outcome was used to analyze an independent cohort of 11q- tumors (n = 37).

Results: Loss of 4p and gain of 7q occurred at a significantly higher frequency in the 11q- tumors, further defining the genetic characteristics of this subtype. The 11q- tumors could be split into two subgroups using a miRNA expression survival signature that differed significantly in clinical outcome and the overall frequency of large-scale genomic imbalances, with the poor survival subgroup having significantly more imbalances. miRNAs from the expression signature, which were upregulated in unfavorable tumors, were predicted to target downregulated genes from a published mRNA expression classifier of clinical outcome at a higher-than-expected frequency, indicating the miRNAs might contribute to the regulation of genes within the signature.

Conclusion: We show that two distinct biological subtypes of neuroblastoma with loss of 11q occur, which differ in their miRNA expression profiles, frequency of segmental imbalances, and clinical outcome. A miRNA expression signature, combined with an analysis of segmental imbalances, provides greater prediction of event-free survival and overall survival outcomes than 11q status by itself, improving patient stratification.

Figure 1. Summary of DNA copy number aberrations across the genome

Regions of hemizygous loss (red bars) and gains (green bars) are plotted for each autosome with the observed frequency (percent) of each aberration detected in the tumor series plotted on the Y-axis. The frequency of MYCN and ALK amplifications is also plotted (blue).

Figure 2. Stratification of 11q− tumors based on a miRNA survival signature

Thirty-seven 11q− tumors could split by the unsupervised K-MEANS partitional algorithm into two groups (A & B) on the basis of a 15 miRNA survival signature previously described by Bray et al (38). Median survival time for group A was 800 days and 1445 days for group. Information related to death due to disease, events, age at diagnosis and disease stage are presented at the top of the 15 miRNA heat map. Information on genomic imbalances present in each tumor (black) is presented below the heat map. Red on the heat map is associated with higher expression, green with lower expression. The number of genomic imbalances for the unfavorable cluster (A) was significantly higher (1.5 fold) than the favorable cluster (B)(P = 0.015). Kaplan Meier curves for EFS and OS demonstrate a statistically significant difference for patient outcome between both groups.