Identifying Novel Glioma Associated Pathways Based On Ntegrating Omics Data

Gliomas are the most common type of primary brain tumor in adults. The occurrenceand development of glioma is a complex process with different steps, phases and polygene.Gene expression by microarray technology contains the high information and high densitycharacteristic and it has been widely applied in the study of molecular pathogenesis of cancer.However, most of the analyses focused on detecting the differentially expressed genesin cancer not in the pathway or network level. In order to find important pathwaysassociated with glioma, we integrated omics datas on glioma, such as gene expressionmicroarray, MicroRNA and Chip-Seq datasets. In this work, we verified the hypothesis thatthe significant signatures of different datasets are more similar at pathway level than atgene level. We also identified some putative novel pathways related with glioma, such asRegulation of epithelial-to-mesenchymal transition (EMT), TGF-beta-dependent inductionof EMT via SMADs and so on. The identified novel glioma related pathways need furtherexperimental testing and will provide essential information for clinical research,personalized therapy and molecular mechanism in glioma. During identifing the interestedgenes procedures, we used a novel method called Cancer Outlier Profiling Analysis(COPA), and used GeneGO database, which is manually curated database,to do thepathway enrichment analysis.