Customized oligonucleotide microarray gene expression based classification of neuroblastoma patients outperforms current clinical risk stratification

Purpose To develop a gene expression - based classifier for neuroblastoma patients that reliably predicts courses of the disease. Patients and Methods Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses ( n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set ( n = 174) by comparing results of the gene expression based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. Results The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [ favorable; n = 115] v 0.52 +/- 0.07 [ unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P <.0001) and separated risk groups of current neuroblastoma trials into subgroups with divergent outcome (NB2004: low-risk 3-year EFS 0.86 +/- 0.04 v 0.25 +/- 0.15, P <.0001; intermediate-risk 1.00 v 0.57 +/- 0.19, P =.018; high-risk 0.81 +/- 0.10 v 0.56 +/- 0.08, P =.06). In a multivariate Cox regression model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States ( P <.001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Conclusion Integration of gene expression - based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.