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Integrated analysis of mutations, miRNA and mRNA expression in glioblastoma

DOI: 10.1186/1752-0509-4-163

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Abstract:

We identified association of somatic mutations in 14 genes with glioblastoma, of which 8 genes are newly identified, and association of loss of heterozygosity (LOH) is identified in 11 genes with glioblastoma, of which 9 genes are newly discovered. By gene coexpression network analysis, we indentified 15 genes essential to the function of the network, most of which are cancer related genes. We also constructed miRNA coexpression networks and found 19 important miRNAs of which 3 were significantly related to glioblastoma patients' survival. We identified 3,953 predicted miRNA-mRNA pairs, of which 14 were previously verified by experiments in other groups. Using pathway enrichment analysis we also found that the genes in the target network of the top 19 important miRNAs were mainly involved in cancer related signaling pathways, synaptic transmission and nervous systems processes. Finally, we developed new methods to decipher the pathway connecting mutations, expression information and glioblastoma. We indentified 4 cis-expression quantitative trait locus (eQTL): TP53, EGFR, NF1 and PIK3C2G; 262 trans eQTL and 26 trans miRNA eQTL for somatic mutation; 2 cis-eQTL: NRAP and EGFR; 409 trans- eQTL and 27 trans- miRNA eQTL for lost of heterozygosity (LOH) mutation.Our results demonstrate that integrated analysis of multi-dimensional data has the potential to unravel the mechanism of tumor initiation and progression.Glioblastoma (glioblastoma multiforme or GBM) is the most common and aggressive type of primary brain tumor in humans, involving glial cells and accounting for 52% of all parenchymal brain tumor cases and 20% of all intracranial tumors [1]. Glioblastoma is located preferentially in the cerebral hemispheres. In the past two decades, the molecular mechanisms, genetics and pathways to treat GBM have extensively been studied [2]. However, the precise mechanism of GBM is unknown and its median survival rate is very low [3]. The Cancer Genome Atlas (TCGA) generated lar

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