Differential Gene Expression in MRI-classified Glioblastoma

Abstract

Previous characterization of the genome and transcriptome of glioblastoma (GBM) has revealed molecular alterations that potentially drive GBM pathogenesis and heterogeneity 1-6. These open-resources are evolving, such as The Cancer Genome Atlas (TCGA) and The Cancer Imaging Atlas (TCIA) at the National Institute of Health comprising a large cohort of molecular and MRI data. Yet, no report deciphers the link between molecular signatures and MRI-classified GBM. The necessity to re-form molecular and imaging data motivated our computational approach to integrate TCIA and TCGA datasets derived from GBM. We uncovered common and distinct molecular signatures across GBM patients and specific to tumor locations, respectively. Despite heterogeneity in GBM, the top 12 genes from our analysis highlights that the dysregulation of a subset of neurotransmitter receptor or transporter and synaptic activity is common across GBM patients. The coherent layer of imaging and molecular information would help us stratify precision neuro-oncology and treatment options in ways that are not possible through MRI or genomic data alone. Our findings provide molecular targets in the disrupted neurocircuit of GBM, suggesting imbalanced excitation and inhibition. Given the fact that GBM patients exhibit similar symptoms resembling patients with neurodegenerative diseases and seizures, our results supported the hypothesis-GBM in the context of neurological disorders beyond a solely cancerous disease.