Abstract 3936: Identifying molecular subgroups of gliomas in formalin fixed paraffin embedded material

Abstract

Abstract Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Histological classification, combined with the patients’ prognostic features, often guides treatment decisions. Unfortunately, differences in histology are subtle and therefore, diagnosis is subject to a large interobserver variability. To improve classification, we did expression profiling on fresh frozen tumor material of 276 glioma samples of all histological subtypes. This resulted in seven molecular subgroups, which correlated significantly better with survival than histology. When validated in prospective studies these molecular clusters could contribute to clinical decision making. However, there is a lack of fresh frozen glioma material, and until now clinical studies have been performed on formalin fixed paraffin embedded (FFPE) material. Therefore, we would like to see whether our molecular clusters are reproducible in FFPE material. Expression profiling was performed on 57 paired snap-frozen/FFPE glioma samples of all histological and molecular subtypes and three non-diseased brain samples. We collected FFPE material from the same patients that were included in our previous study (Gravendeel et al. Cancer Res 2009). FFPE expression profiling was performed using Hu_Ex_1.0_st “exon” arrays (Affymetrix) in combination with Nugen WT-Ovation technology (FFPE V2 and Exon modules). FFPE expression profiles were assigned to a molecular cluster based on its nearest centroid using the 20.000 most variably expressed exons. Preliminary analysis indicates that approximately 75% of all samples were assigned to the correct molecular cluster. Survival data confirmed that the molecular clusters identified using FFPE material retained significant prognostic value, similar to those obtained using fresh frozen material (p=0.0016). Our data indicate that exon arrays in combination with Nugen WT technology are a suitable platform to perform expression profiling on FFPE samples. We are currently expanding our dataset to include FFPE samples from a large phase III European trial. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3936. doi:10.1158/1538-7445.AM2011-3936