A multigene predictor of outcome in glioblastoma

Howard Colman, Li Zhang, Erik P Sulman, J Matthew McDonald, Nasrin Latif Shooshtari, Andreana Rivera, Sonya Popoff, Catherine L Nutt, David N Louis, J Gregory Cairncross, Mark R Gilbert, Heidi S Phillips, Minesh P Mehta, Arnab Chakravarti, Christopher E Pelloski, Krishna Bhat, Burt G Feuerstein, Robert B Jenkins, Ken Aldape

Only a subset of patients with newly diagnosed glioblastoma (GBM) exhibit a response to standard therapy. To date, a biomarker panel with predictive power to distinguish treatment sensitive from treatment refractory GBM tumors does not exist. An analysis was performed using GBM microarray data from 4 independent data sets. An examination of the genes consistently associated with patient outcome, revealed a consensus 38-gene survival set. Worse outcome was associated with increased expression of genes associated with mesenchymal differentiation and angiogenesis. Application to formalin fixed-paraffin embedded (FFPE) samples using real-time reverse-transcriptase polymerase chain reaction assays resulted in a 9-gene subset which appeared robust in these samples. This 9-gene set was then validated in an additional independent sample set. Multivariate analysis confirmed that the 9-gene set was an independent predictor of outcome after adjusting for clinical factors and methylation of the methyl-guanine methyltransferase promoter. The 9-gene profile was also positively associated with markers of glioma stem-like cells, including CD133 and nestin. In sum, a multigene predictor of outcome in glioblastoma was identified which appears applicable to routinely processed FFPE samples. The profile has potential clinical application both for optimization of therapy in GBM and for the identification of novel therapies targeting tumors refractory to standard therapy.