Molecular Subtypes of Anaplastic Gliomas Identified with Somatic-Mutation and Pathway Based Gene Signature
Authors: Wardak Zabi , Park Sunho , Zhu Hong , Choe Kevin S. , Hwang Tae Hyun 
Published: May 2018

AbstractPurposeAnaplastic gliomas constitute heterogeneous population with variable outcomes and no consensus on therapeutic approach. Molecular profiling may provide prognostication beyond clinical and pathologic factors and help guide treatment decisions.Experimental DesignThe Cancer Genome Atlas (TCGA) was utilized to derive a 39-gene low grade glioma-specific gene signature. Consensus clustering based on expression of the signature identified subgroups for 176 patients with anaplastic glioma from TCGA. Overall survival (OS) was analyzed for each subgroup. A total of 68 patients from Repository for Molecular Brain Neoplasia Data (REMBRANDT) were used as an independent validation dataset.ResultsConsensus clustering separated the TCGA group into two distinct cohorts. The OS was significantly different between two subgroups, 20 vs. 67 months (p<0.001). On univariate analysis, the molecular subgroup, age, KPS, IDH1/2 mutation, 1p19q-co-deletion, chemotherapy, and use of both chemotherapy and radiation-therapy were significantly associated with OS. On multivariable analysis, the molecular subgroup remained significant with HR of 2.6 (p=.047, 95%CI [1.01-6.68]). In an independent validation with REMBRANDT, consensus clustering based on the signature successfully identified similarly poor prognostic subgroup with median survival of 14 months and concordance of expression patterns in 21 of the genes.ConclusionExpression patterns of the 39 gene stratified anaplastic gliomas into two distinct subgroups with substantially different OS. This molecular prognostication was validated in an external dataset. Utilization of molecular subgroup, in addition to known prognostic factors may help define those requiring aggressive therapeutic intervention. Characteristic genes within the poor prognostic group may represent potential targets for therapeutic intensification.Source code and dataset used in this work is available for reviewers at:https://www.taehyunlab.org/ntripathImportance of the studyDespite the revolution of tailored therapy, anaplastic gliomas represent a category of tumors without clear treatment recommendations. While current prognostic factors help guide therapy recommendations, further refinement with the addition of molecular markers can help physicians with treatment recommendations. In this study, we developed a 39 gene prognostic gene signature by utilizing Pan-Cancer TCGA mutation profiles of over 5,000 patients across 19 different TCGA cancer types to stratify patients with anaplastic gliomas. We performed consensus clustering based on gene expression profiles of our 39-gene signature without any consideration of clinical factors or outcomes to TCGA anaplastic gliomas patients as well as an independent dataset and successfully identified two molecular subgroups with distinct clinical outcome. We found that subgroups have remarkably different survivals with a clear poor prognostic group. Furthermore, the poor prognostic group showed significant benefits for aggressive multimodality therapy, justifying the use of intensive therapy based on molecular stratification.