Abstract
Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.
Highlights
Glioblastoma (GBM) tumors, with an adult median survival time of 14.6 months after radiation and temozolomide therapy [1], are known for their heterogeneity, vascularization, and lethality
The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are hypo-methylated in glioblastoma relative to lower grade glioma tumors
These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network
Summary
Glioblastoma (GBM) tumors, with an adult median survival time of 14.6 months after radiation and temozolomide therapy [1], are known for their heterogeneity, vascularization, and lethality. Genes in the Brain Network were compared with those in the TCGA Network to investigate commonality in GBM co-expression. All 22 genes showed significantly upregulated expression (Student’s T Test; p < 0.001) in GBM relative to LGG (in the TCGA Network) and relative to normal brain (in the Brain Network).
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