title: IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival.
abstract: BACKGROUND
  Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period.
  
  
  METHODS
  The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations.
  
  
  RESULTS
  Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05).
  
  
  CONCLUSIONS
  By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.
authors: Department of Biomedicine, University Hospital of Basel, Spitalstrasse 21, CH-4031 Basel, Switzerland.
authors: Severina
authors: S
authors: Leu
authors: Stefanie
authors: S
authors: von Felten
authors: Stephan
authors: S
authors: Frank
authors: Erik
authors: E
authors: Vassella
authors: Istvan
authors: I
authors: Vajtai
authors: Elisabeth
authors: E
authors: Taylor
authors: Marianne
authors: M
authors: Schulz
authors: Gregor
authors: G
authors: Hutter
authors: Jürgen
authors: J
authors: Hench
authors: Philippe
authors: P
authors: Schucht
authors: Jean-Louis
authors: JL
authors: Boulay
authors: Luigi
authors: L
authors: Mariani
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D001932:Brain Neoplasms / Q000145:classification / Q000235:genetics / Q000401:mortality; D002467:Cell Nucleus / Q000378:metabolism; D003131:Combined Modality Therapy; D019175:DNA Methylation; D015254:DNA Modification Methylases / Q000235:genetics*; D045643:DNA Repair Enzymes / Q000235:genetics*; D004273:DNA, Neoplasm / Q000235:genetics; D005260:Female; D005500:Follow-Up Studies; D005909:Glioblastoma / Q000145:classification / Q000235:genetics / Q000401:mortality*; D006801:Humans; D007124:Immunoenzyme Techniques; D007521:Isocitrate Dehydrogenase / Q000235:genetics*; D019656:Loss of Heterozygosity; D008297:Male; D008875:Middle Aged; D009154:Mutation / Q000235:genetics*; D009367:Neoplasm Staging; D011379:Prognosis; D011401:Promoter Regions, Genetic / Q000235:genetics; D060888:Real-Time Polymerase Chain Reaction; D015996:Survival Rate; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism*; D025521:Tumor Suppressor Proteins / Q000235:genetics*; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm; C495901:TP53 protein, human; D016159:Tumor Suppressor Protein p53; D025521:Tumor Suppressor Proteins; C538784:IDH2 protein, human; D007521:Isocitrate Dehydrogenase; C543588:IDH1 protein, human; D015254:DNA Modification Methylases; C515491:MGMT protein, human; D045643:DNA Repair Enzymes