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Transcriptomal Diversity of Long-Term Glioblastoma Survivors

ABSTRACT: Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression.

ORGANISM(S): Homo sapiens

PROVIDER: GSE54077 | GEO | 2014/05/02

SECONDARY ACCESSION(S): PRJNA235156

REPOSITORIES: GEO

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Project description:Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression. All tumors (n = 7) were obtained following surgical resection at the MSKCC as part of routine clinical care, and snap frozen. Tumors were obtained in accordance with Institutional Review Board policies at the MSKCC. Each sample was examined histologically by 3 independent neuropathologists and confirmed to be World Health Organization (WHO) grade IV glioma (GBM). Before analysis, tumors were sectioned and microdissected. Genomic DNA or RNA was extracted using the DNeasy kit (Qiagen) or RNeasy Lipid Tissue Mini Kit (Qiagen) as per the manufacturer’s instructions. Expression analysis of tumors was performed using the Affymetrics U133 2.0 microarray (Affymetrix). Affymetrix CEL files were imported into the Partek Genomics Suite (Partek). The TCGA gene expression data (HT-HG-U133A) was accessed from the TCGA data repositories (http://cancergenome.nih.gov, date of download 12/2013).

Project description:Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient's surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated. Gene expression profiling experiments were conducted for 25 patient-derived xenograft glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.

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Transcriptomal Diversity of Long-Term Glioblastoma Survivors

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