Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification.
OBJECTIVE
To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease.


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]).


CONCLUSIONS
Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.
Oberthuer
André
A
Children's Hospital, Department of Pediatric Oncology and Hematology, University of Cologne, Kerpener Strasse 62, D-50924 Cologne, Germany. andre.oberthuer@uk-koeln.de
Berthold
Frank
F
Warnat
Patrick
P
Hero
Barbara
B
Kahlert
Yvonne
Y
Spitz
Rüdiger
R
Ernestus
Karen
K
König
Rainer
R
Haas
Stefan
S
Eils
Roland
R
Schwab
Manfred
M
Brors
Benedikt
B
Westermann
Frank
F
Fischer
Matthias
M
D014408:Biomarkers, Tumor / Q000032:analysis* / Q000235:genetics; D018572:Disease-Free Survival; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D005858:Germany / Q000453:epidemiology; D006801:Humans; D007564:Japan / Q000453:epidemiology; D015999:Multivariate Analysis; D009447:Neuroblastoma / Q000737:chemistry*; D016017:Odds Ratio; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment; D016019:Survival Analysis; D014481:United States / Q000453:epidemiology
D014408:Biomarkers, Tumor