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Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling

Oncogene volume 24, pages 7902–7912 (2005)Cite this article

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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Authors and Affiliations

  1. Department of Pediatric Oncology and Hematology, University Hospital of Essen, Hufelandstr 55, Essen, 45122, Germany

    Alexander Schramm, Johannes H Schulte, Werner Havers & Angelika Eggert

  2. Institute for Cell Biology, University Hospital of Essen, Essen, Germany

    Ludger Klein-Hitpass

  3. Department of Pediatric Oncology, University Children's Hospital, Heidelberg, Germany

    Hauke Sieverts

  4. Department of Hematology, University Children's Hospital, Heidelberg, Germany

    Hauke Sieverts

  5. University Children's Hospital, Marburg, Germany

    Bernd Berwanger & Holger Christiansen

  6. Division of Intelligent Bioinformatics Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany

    Patrick Warnat, Benedikt Brors, Jürgen Eils & Roland Eils

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  1. Alexander Schramm
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Correspondence to Angelika Eggert.

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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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