Protein-protein interaction network analysis and gene set enrichment analysis in epilepsy patients with brain cancer

Abstract

Many patients with brain cancer experience seizures or epilepsy and tumor-associated epilepsy (TAE) significantly decreases their quality of life. This study aimed to achieve a better understanding of the mechanisms of TAE. The differentially expressed genes (DEG) between epilepsy patients with or without brain tumor were firstly screened using the Linear Models for Microarray Data package using GSE4290 datasets from the USA National Center for Biotechnology Information Gene Expression Omnibus database. Then the protein-protein interaction (PPI) network, using data from the Human Protein Reference Database and the Biological General Repository for Interaction Datasets, was constructed. For further analysis, the PPI network structure and clusters in this PPI network were identified by ClusterOne. Meanwhile, gene set enrichment analysis was performed to illuminate the biological pathways and processes which generally affect patients with TAE. A total of 5113 DEG were identified and a PPI network, which contained 114 DEG and 21 normal genes, was established. Proteins, which mainly belonged to the mini chromosome maintenance and collagen families, were discovered to be enriched in the three identified clusters in the PPI network. Finally, several biological pathways (including cell cycle, DNA replication and transforming growth factor β1 signaling pathways) and processes (such as nucleocytoplasmic transport, nuclear transport and regulation of phosphorylation) were identified. Proteins in these three clusters may become new targets for TAE treatment. Our results provide some potential underlying biomarkers for understanding the pathogenesis of epilepsy in patients with brain tumor.

Keywords: Differentially expressed genes; Gene set enrichment analysis; Protein-protein interaction network; Tumor-associated epilepsy.