Gene expression profiling to identify new prognostic markers in glioma.

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e14054 Background: As glioma are heterogeneous tumors, it therefore appears increasingly necessary to associate with the histological examination molecular markers to improve diagnosis and targeted therapy glimpse of glioma. The aim of this study was to characterize a new signature in glioma. Methods: Glioma samples, histologically verified and graded according to WHO classification 2007, were obtained from 81 adult patients who underwent surgery at Limoges and Montpellier University Hospitals from 1993 to 2013. Gene expression profiling by TaqMan Low Density Array and hierarchical clustering were performed on 96 selected genes. IDH mutation and ARTX loss were achieved by immunohistochemical staining on tissue microarray. Our expression dataset was validated on independent cohort (n = 671), composed of RNA-seq expression data retrieved from glioblastoma (GBM) and lower grade glioma (The Cancer Genome Atlas (TCGA) project (http://www.xenabrowser.net/). Results: To have a homogenous cohort, we studied only 64 patients (26 women, 38 men, median age: 47 years, range: 22–81) with primary brain tumors obtained from resected surgical specimens and naive from radiotherapy and/or chemotherapy. Tumors were diagnosed as grade II oligo-astrocytoma (n = 9), grade III oligo-astrocytoma (n = 10), grade III astrocytoma (n = 8), GBM (n = 17), grade II oligodendroglioma (n = 10) and grade III oligodendroglioma (n = 10). IDH1 (R132) mutations were detected in 20 of 53 tumors. Thanks to two methods, we put in evidence a set of 28 genes, highly associated to gene expression patterns that classify tumors into two prognostic groups: a poor prognosis group with a median survival of 26.0 ± 4.5 months, and a good pronostic group with a median survival of 118.0 ± 0.8 months (p < 0.001). The hierarchical clustering analysis of TCGA cohort based on our selection of 28 genes showed similar results (p < 0.001). Furthermore, gene expression profiling was associated to IDH mutation to define good prognostic group. Conclusions: Based on 28 genes, we identified new biomarkers, which have not yet much explored, for differential diagnosis and prognosis in glioma.

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