Dataset Information

Genetic and Lineage Classification of Glioma-Initiating Cells Identifies a Clinically Relevant Glioblastoma Model.

ABSTRACT: The Cancer Genome Atlas (TCGA) project described a robust gene expression-based molecular classification of glioblastoma (GBM), but the functional and biological significance of the subclasses has not been determined. The present comprehensive analysis of 25 glioma-initiating cell (GIC) lines classifies GIC lines into four subtypes (classical, mesenchymal, proneural, and neural) that are closely related to the TCGA GBM subclasses and display distinct lineage characteristics and differentiation behavior that recapitulate neural development. More importantly, the GIC subtypes exhibit distinct biological phenotypes in relation to self-renewal capacity, proliferation, invasiveness, and angiogenic potential in vitro and in vivo. In addition, the GIC subtypes exhibit divergent patterns of signaling pathway activation and deactivation of the Wnt, Notch, and TGF-β pathways. These results will improve drug discovery targeting certain genetic mutation in glioblastoma and improve the development of precision medicine.

SUBMITTER: Saito N

PROVIDER: S-EPMC6826962 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Genetic and Lineage Classification of Glioma-Initiating Cells Identifies a Clinically Relevant Glioblastoma Model.

Saito Norihiko N Hirai Nozomi N Aoki Kazuya K Sato Sho S Suzuki Ryo R Hiramoto Yu Y Fujita Satoshi S Nakayama Haruo H Hayashi Morito M Sakurai Takatoshi T Iwabuchi Satoshi S

Cancers 20191015 10

The Cancer Genome Atlas (TCGA) project described a robust gene expression-based molecular classification of glioblastoma (GBM), but the functional and biological significance of the subclasses has not been determined. The present comprehensive analysis of 25 glioma-initiating cell (GIC) lines classifies GIC lines into four subtypes (classical, mesenchymal, proneural, and neural) that are closely related to the TCGA GBM subclasses and display distinct lineage characteristics and differentiation b ...[more]

PMID: 31618934

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Project description:The outcome of patients with anaplastic gliomas varies considerably depending on histology and single molecular markers such as codeletion of 1p/19q and mutations of the isocitrate dehydrogenase (IDH) gene. Whether a molecularly-based classification of anaplastic gliomas based on large scale genomic or epigenomic analyses is superior to histopathology, may reflect distinct biological subtypes, predict outcome and guide therapy decisions had yet to be determined. Epigenome-wide DNA methylation analysis, which also allows for the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering demonstrated two main groups based on IDH mutation status: CpG island methylator phenotype (CIMP) positive (77.5%) or negative (22.5%). CIMP+ (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q, but not based on histopathology. CIMP- (IDH wild type) tumors on the other hand showed hallmark copy-number alterations of glioblastomas. These tumors clustered together with CIMP- glioblastomas without forming separate groups based on WHO grade. There was no Tumor classification based on CIMP and 1p/19q status was significantly associated with survival allowing a better prediction of outcome than the current histopathological classification alone: Patients with CIMP+ tumors with 1p/19q codeletion had the best prognosis, followed by patients with CIMP+ but intact 1p/19q status. Patients with CIMP- anaplastic gliomas had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped into three molecular subtypes with clear association to underlying biology and clinical outcome based on IDH and 1p/19q status. The data do not provide a molecular basis for the diagnosis of anaplastic oligoastrocytoma. We investigated a subset of 228 anaplastic gliomas using the Illumina 450k methylation array.

Dataset Information

Genetic and Lineage Classification of Glioma-Initiating Cells Identifies a Clinically Relevant Glioblastoma Model.

Publications

Genetic and Lineage Classification of Glioma-Initiating Cells Identifies a Clinically Relevant Glioblastoma Model.

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