Relevance of a TCGA-derived Glioblastoma Subtype Gene-Classifier among Patient Populations

Abstract

Glioblastomamultiforme (GBM), a deadly cancer, is the most lethal and common malignant brain tumor, and the leading cause of death in adult brain tumors. While genomic data continues to rocket, clinical application and translation topatientcare are lagging behind. Big data now deposited in the TCGA network offers a window to generate novel clinical hypotheses. We hypothesized that aTCGA-derivedgene-classifiercan be applied across different gene profiling platforms and population groups. Thisgene-classifiervalidated three robust GBM-subtypes across six different platforms, among Caucasian, Korean and Chinesepopulations: Three Caucasian-predominant TCGA-cohorts (Affymetrix U133A = 548, Agilent Custom-Array = 588, RNA-seq = 168), and three Asian-cohorts (Affymetrix Human Gene 1.0ST-Array = 61, Illumina = 52, Agilent 4 × 44 K = 60). To understandsubtype-relevanceinpatienttherapy, we investigated retrospective TCGApatientclinical sets.Subtype-specificpatientsurvival outcome was similarly poor and reflected the net result of a mixture of treatment regimens with/without surgical resection. As a proof-of-concept, insubtype-specificpatient-derived orthotopic xenograft (PDOX) mice, Classical-subtypedemonstrated no survival difference comparing radiation-therapy versus temozolomide monotherapies. Though preliminary, a PDOX model of Proneural/Neural-subtypedemonstrated significantly improved survival with temozolomide compared to radiation-therapy. A larger scale study using thisgene-classifiermay be useful in clinical outcome prediction andpatientselection for trials based on subtyping.