PMID: 26770395Jan 16, 2016Paper

Screening feature genes of astrocytoma using a combined method of microarray gene expression profiling and bioinformatics analysis

International Journal of Clinical and Experimental Medicine
Yong CaiJianguo Yang

Abstract

The aim of our study was to find feature genes associated with astrocytoma and correlative gene functions which can distinguish cancer tissue from adjacent non-tumor astrocyte tissues. Gene expression profile GSE15824 was downloaded from Gene Expression Omnibus database which included 8 astrocytoma tissues and 3 adjacent non-tumor astrocyte samples. The raw data were first transformed into probe-level data and the differentially expressed genes (DEGs) between tissues of patients with astrocytoma and normal specimen were identified using T-test in samr package of R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze the gene ontology (GO) enrichment on gene functions and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, corresponding protein-protein interaction (PPI) networks of DEGs was constructed using the Cytoscape based on the data collected from STRING online datasets. A total of 3072 genes, including 1799 up-regulated genes and 1273 down-regulated genes, were filtered as DEGs, and we learnt that the DEGs including AQP4, PMP2, SRARCL1 and SLC1A2CAMs etc and that AQP4 was most significantly related to cell osmotic pressure. Three feature genes in KEGG pathw...Continue Reading

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