Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma.

ABSTRACT: Background: Glioma is the most common type of primary central nervous system tumors. However, the relationship between gene mutations and transcriptome is unclear in diffuse glioma, and there are no systemic analyses with regard to the genotype-phenotype association currently. Methods: We performed the multi-omics analysis in large glioblastoma multiforme (GBM, n=126) and low-grade glioma (LGG, n=481) cohorts obtained from The Cancer Genome Atlas (TCGA) database. We used multivariate linear models to evaluate associations between driver gene mutations and global gene expression. We developed generalized linear models to evaluate associations between genetic/expression factors with clinicopathologic features. Multivariate Cox proportional hazards models were used to predict th

SUBMITTER: Yang Q 

PROVIDER: S-EPMC7171505 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature