Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes.
BACKGROUND
Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients.


METHODS
We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms.


RESULTS
In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification.


CONCLUSIONS
Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome.
Warnat
Patrick
P
Department of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, Germany. pwarnat@web.de <pwarnat@web.de>
Oberthuer
André
A
Fischer
Matthias
M
Westermann
Frank
F
Eils
Roland
R
Brors
Benedikt
B
D014408:Biomarkers, Tumor / Q000032:analysis; D003430:Cross-Sectional Studies; D018450:Disease Progression; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D009367:Neoplasm Staging; D009447:Neuroblastoma / Q000145:classification* / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D009687:Nuclear Proteins / Q000235:genetics; D015513:Oncogene Proteins / Q000235:genetics*; D011237:Predictive Value of Tests; D011379:Prognosis; D016271:Proto-Oncogene Proteins c-myc / Q000235:genetics*; D012334:RNA, Neoplasm / Q000032:analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012680:Sensitivity and Specificity; D016019:Survival Analysis
D014408:Biomarkers, Tumor; C489427:MYC protein, human; D009687:Nuclear Proteins; D015513:Oncogene Proteins; D016271:Proto-Oncogene Proteins c-myc; D012334:RNA, Neoplasm