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.
Highlights
Despite advances in our understanding of the molecular aspects of glioblastoma (GBM), the prognosis for glioblastoma remains dismal [1,2,3,4]
To identify potential glioma-initiating cell (GIC) subtypes, we performed cluster analysis of gene expression data (Affymetrix U133A2) from 25 GIC cell lines generated from fresh GBM tissues (Table S1)
Our results show that unsupervised clustering of GIC gene expression analysis matched perfectly with that from a supervised clustering using 840 genes previously used to separate GBM tumors into four subtypes
Summary
Despite advances in our understanding of the molecular aspects of glioblastoma (GBM), the prognosis for glioblastoma remains dismal [1,2,3,4]. Recent studies indicate that some neoplastic cells within human glioblastoma are capable of self-renewal and multilineage differentiation—properties associated with normal neural stem cells [5,6,7]. These stem-like tumor cells, known as glioma-initiating cells (GICs), are responsible for tumor initiation and recurrence after therapy, which makes them attractive targets for novel GBM therapies [8,9,10]. Other studies indicate that GICs retain relevant molecular features of human GBM and may enable development of better preclinical models for evaluating tumor biology and therapeutics [11]. More recent work from Lottaz et al [14] divided 17 GICs into two groups, one expressing a “proneural” gene signature resembling normal fetal brain stem cells and the other
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