title: Exon-level expression analyses identify MYCN and NTRK1 as major determinants of alternative exon usage and robustly predict primary neuroblastoma outcome.
abstract: BACKGROUND
  Using mRNA expression-derived signatures as predictors of individual patient outcome has been a goal ever since the introduction of microarrays. Here, we addressed whether analyses of tumour mRNA at the exon level can improve on the predictive power and classification accuracy of gene-based expression profiles using neuroblastoma as a model.
  
  
  METHODS
  In a patient cohort comprising 113 primary neuroblastoma specimens expression profiling using exon-level analyses was performed to define predictive signatures using various machine-learning techniques. Alternative transcript use was calculated from relative exon expression. Validation of alternative transcripts was achieved using qPCR- and cell-based approaches.
  
  
  RESULTS
  Both predictors derived from the gene or the exon levels resulted in prediction accuracies >80% for both event-free and overall survival and proved as independent prognostic markers in multivariate analyses. Alternative transcript use was most prominently linked to the amplification status of the MYCN oncogene, expression of the TrkA/NTRK1 neurotrophin receptor and survival.
  
  
  CONCLUSIONS
  As exon level-based prediction yields comparable, but not significantly better, prediction accuracy than gene expression-based predictors, gene-based assays seem to be sufficiently precise for predicting outcome of neuroblastoma patients. However, exon-level analyses provide added knowledge by identifying alternative transcript use, which should deepen the understanding of neuroblastoma biology.
authors.affiliation: University Hospital Essen, Childrens Hospital, Department of Hematology/Oncology, Germany. alexander.schramm@uni-due.de
authors.forename: A
authors.initials: A
authors.lastname: Schramm
authors.forename: B
authors.initials: B
authors.lastname: Schowe
authors.forename: K
authors.initials: K
authors.lastname: Fielitz
authors.forename: M
authors.initials: M
authors.lastname: Heilmann
authors.forename: M
authors.initials: M
authors.lastname: Martin
authors.forename: T
authors.initials: T
authors.lastname: Marschall
authors.forename: J
authors.initials: J
authors.lastname: Köster
authors.forename: J
authors.initials: J
authors.lastname: Vandesompele
authors.forename: J
authors.initials: J
authors.lastname: Vermeulen
authors.forename: K
authors.initials: K
authors.lastname: de Preter
authors.forename: J
authors.initials: J
authors.lastname: Koster
authors.forename: R
authors.initials: R
authors.lastname: Versteeg
authors.forename: R
authors.initials: R
authors.lastname: Noguera
authors.forename: F
authors.initials: F
authors.lastname: Speleman
authors.forename: S
authors.initials: S
authors.lastname: Rahmann
authors.forename: A
authors.initials: A
authors.lastname: Eggert
authors.forename: K
authors.initials: K
authors.lastname: Morik
authors.forename: J H
authors.initials: JH
authors.lastname: Schulte
mesh_terms: D045744:Cell Line, Tumor; D002675:Child, Preschool; D005091:Exons / Q000235:genetics*; D020869:Gene Expression Profiling; D006801:Humans; D007223:Infant; D000071447:N-Myc Proto-Oncogene Protein; D009447:Neuroblastoma / Q000235:genetics* / Q000401:mortality; D009687:Nuclear Proteins / Q000235:genetics*; D015513:Oncogene Proteins / Q000235:genetics*; D011379:Prognosis; D012333:RNA, Messenger; D020917:Receptor, trkA / Q000235:genetics*; D012307:Risk Factors; 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