Abstract
Neuroblastoma is a common childhood tumor comprising cases with rapid disease progression as well as spontaneous regression. Although numerous prognostic factors have been identified, risk evaluation in individual patients remains difficult. To define a reliable prognostic predictor and gene signatures characteristic of biological subgroups, we performed mRNA expression profiling of 68 neuroblastomas of all stages. Expression data were analysed using support vector machines (SVM-rbf), prediction analysis of microarrays (PAM), k-nearest neighbors (k-NN) algorithms and multiple decision trees. SVM-rbf performed best of all methods, and predicted recurrence of neuroblastoma with an accuracy of 85% (sensitivity 77%, specificity 94%). PAM identified a classifier of 39 genes reliably predicting outcome with an accuracy of 80%. In comparison, conventional risk stratification based on stage, age and MYCN-status only reached a predictive accuracy of 64%. Kaplan–Meier analysis using the PAM classifier indicated a 5-year survival of 20 versus 78% for patients with unfavorably versus favorably predicted neuroblastomas, respectively (P=0.0001). Significance analysis of microarrays (SAM) identified additional genes differentially expressed among subgroups. MYCN-amplification and high expression of NTRK1/TrkA demonstrated a strong association with specific gene expression patterns. Our data suggest that microarray-derived data in addition to traditional clinical factors will be useful for risk assessment and defining biological properties of neuroblastoma.
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Abbreviations
- AWD:
-
alive with disease
- CR:
-
complete remission
- EFS:
-
event-free survival
- FDR:
-
false discovery rate
- k-NN:
-
k-nearest neighbors
- NED:
-
no evidence of disease
- PAM:
-
prediction analysis of microarrays
- SAM:
-
significance analysis of microarrays
- SVM-rbf:
-
support vector machines with a radial basis function kernel
- VGPR:
-
very good partial remission
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Acknowledgements
We thank Frank Berthold and Thorsten Simon from the German Neuroblastoma Study Trial Office at the University Children's Hospital of Cologne for providing the clinical patient data as well as a part of the primary tumor material from the neuroblastoma tumor bank of the German competence network ‘Pediatric Oncology and Hematology’. This work was funded by a Grant from the Kind-Philipp Stiftung (to AE) and the German National Genome Network (BMBF/NGFN2) to AE and AS.
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Schramm, A., Schulte, J., Klein-Hitpass, L. et al. Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling. Oncogene 24, 7902–7912 (2005). https://doi.org/10.1038/sj.onc.1208936
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DOI: https://doi.org/10.1038/sj.onc.1208936
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