title: Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling.
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.
authors.affiliation: Department of Pediatric Oncology and Hematology, University Hospital of Essen, Hufelandstr 55, Essen 45122, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Schramm
authors.forename: Johannes H
authors.initials: JH
authors.lastname: Schulte
authors.forename: Ludger
authors.initials: L
authors.lastname: Klein-Hitpass
authors.forename: Werner
authors.initials: W
authors.lastname: Havers
authors.forename: Hauke
authors.initials: H
authors.lastname: Sieverts
authors.forename: Bernd
authors.initials: B
authors.lastname: Berwanger
authors.forename: Holger
authors.initials: H
authors.lastname: Christiansen
authors.forename: Patrick
authors.initials: P
authors.lastname: Warnat
authors.forename: Benedikt
authors.initials: B
authors.lastname: Brors
authors.forename: Jürgen
authors.initials: J
authors.lastname: Eils
authors.forename: Roland
authors.initials: R
authors.lastname: Eils
authors.forename: Angelika
authors.initials: A
authors.lastname: Eggert
mesh_terms: D000465:Algorithms; D015331:Cohort Studies; D003663:Decision Trees; D005784:Gene Amplification; D020869:Gene Expression Profiling; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D000071447:N-Myc Proto-Oncogene Protein; D009367:Neoplasm Staging; D009447:Neuroblastoma / Q000235:genetics* / Q000473:pathology*; D009687:Nuclear Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D015513:Oncogene Proteins / Q000235:genetics*; D011379:Prognosis; D012333:RNA, Messenger / Q000032:analysis; D020917:Receptor, trkA / Q000235:genetics*; D018570:Risk Assessment; D016019:Survival Analysis
chemical_list: C459801:MYCN protein, human; D000071447:N-Myc Proto-Oncogene Protein; D009687:Nuclear Proteins; D015513:Oncogene Proteins; D012333:RNA, Messenger; D020917:Receptor, trkA