, , and Status Predicts Prognosis in Glioma.

The aim of this study was to identify relevant biomarkers for the prognosis of glioma considering current molecular changes such as mutation and 1p19q deletion. Gene expression profiling was performed using the TaqMan Low Density Array and hierarchical clustering using 96 selected genes in 64 patients with newly diagnosed glioma. The expression dataset was validated on a large independent cohort from The Cancer Genome Atlas (TCGA) database. A differential expression panel of 26 genes discriminated two prognostic groups regardless of grade and molecular groups of tumors: Patients having a poor prognosis with a median overall survival (OS) of 23.0 ± 9.6 months (group A) and patients having a good prognosis with a median OS of 115.0 ± 6.6 months (group B) ( = 0.007). Hierarchical clustering of the glioma TCGA cohort supported the prognostic value of these 26 genes ( < 0.0001). Among these genes, and were identified as factors that can be associated with status and 1p/19q co-deletion to distinguish between prognostic groups of glioma from the TCGA cohort. Therefore, associated with seemed to be able to provide new information on glioma prognosis.