title: Development of robust discriminant equations for assessing subtypes of glioblastoma biopsies.
abstract: BACKGROUND
  In the preceding decade, various studies on glioblastoma (Gb) demonstrated that signatures obtained from gene expression microarrays correlate better with survival than with histopathological classification. However, there is not a universal consensus formula to predict patient survival.
  
  
  METHODS
  We developed a gene signature using the expression profile of 47 Gbs through an unsupervised procedure and two groups were obtained. Subsequent to a training procedure through leave-one-out cross-validation, we fitted a discriminant (linear discriminant analysis (LDA)) equation using the four most discriminant probesets. This was repeated for two other published signatures and the performance of LDA equations was evaluated on an independent test set, which contained status of IDH1 mutation, EGFR amplification, MGMT methylation and gene VEGF expression, among other clinical and molecular information.
  
  
  RESULTS
  The unsupervised local signature was composed of 69 probesets and clearly defined two Gb groups, which would agree with primary and secondary Gbs. This hypothesis was confirmed by predicting cases from the independent data set using the equations developed by us. The high survival group predicted by equations based on our local and one of the published signatures contained a significantly higher percentage of cases displaying IDH1 mutation and non-amplification of EGFR. In contrast, only the equation based on the published signature showed in the poor survival group a significant high percentage of cases displaying a hypothesised methylation of MGMT gene promoter and overexpression of gene VEGF.
  
  
  CONCLUSIONS
  We have produced a robust equation to confidently discriminate Gb subtypes based in the normalised expression level of only four genes.
authors.affiliation: Servei de Genòmica, Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
authors.forename: X
authors.initials: X
authors.lastname: Castells
authors.forename: J J
authors.initials: JJ
authors.lastname: Acebes
authors.forename: C
authors.initials: C
authors.lastname: Majós
authors.forename: S
authors.initials: S
authors.lastname: Boluda
authors.forename: M
authors.initials: M
authors.lastname: Julià-Sapé
authors.forename: A P
authors.initials: AP
authors.lastname: Candiota
authors.forename: J
authors.initials: J
authors.lastname: Ariño
authors.forename: A
authors.initials: A
authors.lastname: Barceló
authors.forename: C
authors.initials: C
authors.lastname: Arús
mesh_terms: D000465:Algorithms; D001706:Biopsy; D001932:Brain Neoplasms / Q000145:classification / Q000235:genetics* / Q000401:mortality; D019175:DNA Methylation; D015254:DNA Modification Methylases / Q000235:genetics; D045643:DNA Repair Enzymes / Q000235:genetics; D016002:Discriminant Analysis; D005784:Gene Amplification; D020869:Gene Expression Profiling / Q000379:methods*; D018773:Genes, erbB-1; D005909:Glioblastoma / Q000145:classification / Q000235:genetics* / Q000401:mortality; D006801:Humans; D007521:Isocitrate Dehydrogenase / Q000235:genetics; D053208:Kaplan-Meier Estimate; D009154:Mutation; D020411:Oligonucleotide Array Sequence Analysis; D016016:Proportional Hazards Models; D060888:Real-Time Polymerase Chain Reaction; D020133:Reverse Transcriptase Polymerase Chain Reaction; D025521:Tumor Suppressor Proteins / Q000235:genetics; D042461:Vascular Endothelial Growth Factor A / Q000096:biosynthesis
chemical_list: D025521:Tumor Suppressor Proteins; D042461:Vascular Endothelial Growth Factor A; D007521:Isocitrate Dehydrogenase; C543588:IDH1 protein, human; D015254:DNA Modification Methylases; C515491:MGMT protein, human; D045643:DNA Repair Enzymes