Mining of Network Markers for Brain Tumor from Transcriptome and Interactome Data

Title:Mining of Network Markers for Brain Tumor from Transcriptome and Interactome Data

Volume: 8 Issue: 3

Author(s): Jongkwang Kim

Affiliation:

Keywords: Brain, cancer, GBM, gene, integration, pathway, PPI, protein, sub-network.

Abstract: Glioblastoma multiforme (GBM: grade IV astrocytoma) is the most common but lethal form of brain cancer. The median survival time of GBM patients is only 15 months. Only a few predictive markers have been reported for prognosis and treatment.

This study integrates gene expression and protein-protein interaction data to search for pathways that are differentially regulated between long-term and short-term survivors of GBM patients. A novel objective function for greedy search was introduced in search for 47 significantly and differentially expressed sub-networks (SDES) or pathways in a greedy fashion. The resultant putative pathways (involving 156 genes) were tested for enrichment of known GBM cancer genes as well as GO terms related to “biological process.” Integration of gene expression profiles of GBM patients with a PPI network improves the recall rate of known GBM driver genes and shows the better GO enrichment in comparison to the conventional gene-set approach that is based solely on the expression data.

Cite this article as:

Kim Jongkwang, Mining of Network Markers for Brain Tumor from Transcriptome and Interactome Data, Current Bioinformatics 2013; 8 (3) . https://dx.doi.org/10.2174/1574893611308030005