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Master regulators, regulatory networks, and pathways of glioblastoma subtypes.

Bozdag S, Li A, Baysan M, Fine HA - Cancer Inform (2014)

Bottom Line: Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing.We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways.Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

View Article: PubMed Central - PubMed

Affiliation: Neuro-Oncology Branch, National Cancer Institute, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA. ; Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, Wisconsin, USA.

ABSTRACT
Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

No MeSH data available.


Related in: MedlinePlus

IPA network built from genes in gene regulatory network of the mesenchymal subtype. Colored nodes are the genes in the mesenchymal gene regulatory network (Red: upregulated, Green: downregulated).
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Related In: Results  -  Collection


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f6-cin-suppl.3-2014-033: IPA network built from genes in gene regulatory network of the mesenchymal subtype. Colored nodes are the genes in the mesenchymal gene regulatory network (Red: upregulated, Green: downregulated).

Mentions: To further annotate these genes, we also uploaded them into IPA and examined networks with similar functions as found by GO terms. The network for the mesenchymal subtype is shown in Figure 6 and other networks are shown in Supplementary Figure 9.


Master regulators, regulatory networks, and pathways of glioblastoma subtypes.

Bozdag S, Li A, Baysan M, Fine HA - Cancer Inform (2014)

IPA network built from genes in gene regulatory network of the mesenchymal subtype. Colored nodes are the genes in the mesenchymal gene regulatory network (Red: upregulated, Green: downregulated).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4214595&req=5

f6-cin-suppl.3-2014-033: IPA network built from genes in gene regulatory network of the mesenchymal subtype. Colored nodes are the genes in the mesenchymal gene regulatory network (Red: upregulated, Green: downregulated).
Mentions: To further annotate these genes, we also uploaded them into IPA and examined networks with similar functions as found by GO terms. The network for the mesenchymal subtype is shown in Figure 6 and other networks are shown in Supplementary Figure 9.

Bottom Line: Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing.We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways.Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

View Article: PubMed Central - PubMed

Affiliation: Neuro-Oncology Branch, National Cancer Institute, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA. ; Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, Wisconsin, USA.

ABSTRACT
Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

No MeSH data available.


Related in: MedlinePlus