Prognostic impact of gene expression-based classification for neuroblastoma
|Authors:||Oberthuer A, Hero B, Berthold F, Juraeva D, Faldum A, Kahlert Y, Asgharzadeh S, Seeger R, Scaruffi P, Tonini GP, Janoueix-Lerosey I, Delattre O, Schleiermacher G, Vandesompele J, Vermeulen J, Speleman F, Noguera R, Piqueras M, Bénard J, Valent A, Avigad S, Yaniv I, Weber A, Christiansen H, Grundy RG, Schardt K, Schwab M, Eils R, Warnat P, Kaderali L, Simon T, Decarolis B, Theissen J, Westermann F, Brors B, Fischer M|
|CellNetworks People:||Eils Roland, Kaderali Lars|
|Journal:||J Clin Oncol. 2010 Jul 20;28(21):3506-15|
PURPOSE: To evaluate the impact of a predefined gene expression-based classifier for clinical risk estimation and cytotoxic treatment decision making in neuroblastoma patients.
PATIENTS AND METHODS: Gene expression profiles of 440 internationally collected neuroblastoma specimens were investigated by microarray analysis, 125 of which were examined prospectively. Patients were classified as either favorable or unfavorable by a 144-gene prediction analysis for microarrays (PAM) classifier established previously on a separate set of 77 patients. PAM classification results were compared with those of current prognostic markers and risk estimation strategies.
RESULTS: The PAM classifier reliably distinguished patients with contrasting clinical courses (favorable [n = 249] and unfavorable [n = 191]; 5-year event free survival [EFS] 0.84 +/- 0.03 v 0.38 +/- 0.04; 5-year overall survival [OS] 0.98 +/- 0.01 v 0.56 +/- 0.05, respectively; both P < .001). Moreover, patients with divergent outcome were robustly discriminated in both German and international cohorts and in prospectively analyzed samples (P
CONCLUSION: Gene expression-based classification using the 144-gene PAM predictor can contribute to improved treatment stratification of neuroblastoma patients.