Abstract 2008: An investigation of the regulation of cellular processes in glioblastoma multiforme via integrated analysis of paired microRNA and gene expression profiles

Abstract

Abstract Glioblastoma multiforme (GBM) is the most common and malignant brain cancer in adults. Expression patterns of both protein-coding genes and microRNAs are frequently altered in GBM. MicroRNAs are able to modulate the expression of protein-coding genes mostly through downregulation by binding to the 3’-untranslated region of the targeted mRNAs. We have developed a computational data analysis method that allows one to associate microRNAs with pre-defined sets of genes that constitute important cellular pathways using expression data. We first acquired paired microRNA expression and gene expression data from 272 GBM samples available in The Cancer Genome Atlas (TCGA). The gene expression data from each sample were used separately to compute pathway enrichment p-values for 200 pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG) using gene set enrichment analysis (GSEA). We obtained p-values for associations between microRNAs and pathways by correlating the paired microRNA expression levels with pathway enrichment p-values throughout the 272 samples for each pathway-microRNA combination. The p-value corresponding to this correlation serves as an association score for each microRNA-pathway pair. A small p-value corresponds to a probable connection between the microRNA and the genes in the pathway, and therefore also between the microRNA and the cellular function in which these genes are involved. These analyses led to the identification of several previously known and unknown associations between microRNAs and cancer-related cellular processes. For example, we identified the known associations between miR-21 with p53 signaling, cell adhesion, and apoptotic pathways while also uncovering new possible regulatory pathways that might be linked to miR-21, such as VEGF and MAPK signaling pathways (correlation p-value < 1e-7 in the TCGA set). We also performed our analysis using an independent set of paired gene expression and microRNA expression profiling data from 15 GBM samples. In the case of miR-21, significant association with the apoptotic and cell adhesion pathways were also found in this validation set (p-value < 0.05). In addition to miR-21, cell adhesion was significantly associated with GBM linked microRNAs 7, 128a, 128b, 124a, 137, 139, and 218 in TCGA and the validation set. A significant association between known GBM associated microRNAs 21, 181b, 128a, 128b, 139 and the EGFR/AKT pathway, an important signaling pathway for developing of primary glioblastoma, was also discovered. Whereas we used our method in the context of microRNAs and cellular processes in this study, the flexibility of the method allows us to associate any high-throughput genomic data, such as gene copy number and gene methylation, with arbitrary gene sets, such as transcription binding site data and different sets of pathways. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2008.