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Gene-expression based classification of neuroblastoma patients using a customized oligonucleotide-microarray outperforms current clinical risk stratification

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50183

Haas,  Stefan
Gene Structure and Array Design (Stefan Haas), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zitation

Oberthuer, A., Berthold, F., Warnat, P., Hero, B., Kahlert, Y., Spitz, R., et al. (2006). Gene-expression based classification of neuroblastoma patients using a customized oligonucleotide-microarray outperforms current clinical risk stratification. Journal of Clinical Oncology: Jco; Official Journal of the American Society of Clinical Oncology, 24(31), 5070-5078. doi:10.1200/JCO.2006.06.1879.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-834D-7
Zusammenfassung
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.