Identification of alternative exon usage in cancer survival using hierarchical modeling

Alternative Splicing (AS);Alternative Exon Usage (AEU);Glioblastoma (GBM)

Sadeque, Ahmed ; Rodriguez-Zas ; Sandra L.

关键词: Alternative Splicing (AS);    Alternative Exon Usage (AEU);    Glioblastoma (GBM);   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/34549/Sadeque_Ahmed.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

BackgroundAlternative exon usage (AEU) is an important component of gene expression regulation. Exon expression platforms allow the detection of associations between AEU and phenotypes such as cancer. Numerous studies have identified associations between gene expression and the brain cancer glioblastoma multiforme (GBM). The few consistent gene expression biomarkers of GBM that have been reported may be due to the limited consideration of AEU and the analytical approaches used. The objectives of this study were to develop a model that accounts for thevariations in expression present between the exons within a gene and to identify AEU biomarkers of GBM survival.MethodsThe expression of exons corresponding to 25,403 genes was related to the survival of 250individuals diagnosed with GBM in a training data set. Genes exhibiting AEU in the trainingdata set were confirmed in an independent validation data set of 78 patients. A hierarchicalmodel allows the consideration of covariation between exons within a gene and of the effect ofthe epidemiological characteristics of the patients was developed to identify associationsbetween exon expression and patient survival. The same model serves multi-exon models withand without AEU and single-exon models.ResultsAEU associated with GBM survival was identified on 2477 genes (P-value < 5.0E-04 (FDR adjusted P-value < 5.0E-04). G-protein coupled receptor 98 (Gpr98) and epidermal growth factor (Egf) were among the genes exhibiting AEU with 30 and 9 exons associated with GBM survival, respectively. Pathways enriched among the AEU genes included focal adhesion, ECM-receptor interaction, ABC transporters and pathways in cancer. In addition, 24 multi-exon genes without AEU and 8 single-exon genes were associated with GBM survival (P-value < 0.0005).ConclusionsThe inferred patterns of AEU were consistent with in silico AS models. The hierarchical model used offered a flexible and simple way to interpret and identify associations between survival that accommodates multi-exon genes with or without AEU and single exon genes.