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Genom Data. 2015 Sep 1;5:333-336.

Gene expression profiling distinguishes proneural glioma stem cells from mesenchymal glioma stem cells.

Author information

1
Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
2
Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA ; Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
3
Department of Neurological Surgery, The Ohio State University, Columbus, OH 43210, USA ; Department of Neurosurgery, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
4
Department of Neurological Surgery, The Ohio State University, Columbus, OH 43210, USA.
5
Department of Pharmacology & Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15216, USA ; University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, PA 15213-1863, USA ; University of South Alabama Mitchell Cancer Institute, Mobile, AL 36604, USA.
6
Department of Neurosurgery, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
7
Department of Neurology & Northwestern Brain Tumor Institute, Center for Genetic Medicine, Robert Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
8
Department of Neurological Surgery, The Ohio State University, Columbus, OH 43210, USA ; James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.
9
Department of Pharmacology & Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15216, USA ; University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, PA 15213-1863, USA ; Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA 15216, USA ; University of South Alabama Mitchell Cancer Institute, Mobile, AL 36604, USA.

Abstract

Tumor heterogeneity of high-grade glioma (HGG) is recognized by four clinically relevant subtypes based on core gene signatures. However, molecular signaling in glioma stem cells (GSCs) in individual HGG subtypes is poorly characterized. Previously we identified and characterized two mutually exclusive GSC subtypes with distinct activated signaling pathways and biological phenotypes. One GSC subtype presented with a gene signature resembling Proneural (PN) HGG, whereas the other was similar to Mesenchymal (Mes) HGG. Classical HGG-derived GSCs were sub-classified as either one of these two subtypes. Differential mRNA expression analysis of PN and Mes GSCs identified 5,796 differentially expressed genes, revealing a pronounced correlation with the corresponding PN or Mes HGGs. Mes GSCs displayed more aggressive phenotypes in vitro and as intracranial xenografts in mice. Further, Mes GSCs were markedly resistant to radiation compared with PN GSCs. Expression of ALDH1A3 - one of the most up-regulated Mes representative genes and a universal cancer stem cell marker in non-brain cancers - was associated with self-renewal and a multi-potent stem cell population in Mes but not PN samples. Moreover, inhibition of ALDH1A3 attenuated the growth of Mes but not PN GSCs in vitro. Lastly, radiation treatment of PN GSCs up-regulated Mes-associated markers and down-regulated PN-associated markers, whereas inhibition of ALDH1A3 attenuated an irradiation-induced gain of Mes identity in PN GSCs in vitro. Taken together, our data suggest that two subtypes of GSCs, harboring distinct metabolic signaling pathways, represent intertumoral glioma heterogeneity and highlight previously unidentified roles of ALDH1A3-associated signaling that promotes aberrant proliferation of Mes HGGs and GSCs. Inhibition of ALDH1A3-mediated pathways therefore might provide a promising therapeutic approach for a subset of HGGs with the Mes signature. Here, we describe the gene expression analysis, including pre-processing methods for the data published by Mao and colleagues in PNAS [1], integration of microarray data from this study with The Cancer Genome Atlas (TCGA) glioblastoma data and also with another published study.

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