Integrated pathway analysis identifies prognostically relevant subtypes of glioblastoma characterized by abnormalities in multi-omics.

ABSTRACT:

Background

Gene expression-based molecular subtypes in glioblastoma from The Cancer Genome Atlas Network (TCGA-GBM) unraveled the pathological origins by identifying tumour cell driver genes. However, the causal inference between molecular subtype origins and their therapeutic efficacy remains obscure.

Methods

We integrated TCGA-GBM multi-omics (DNA, mRNA, and protein profiles) using correlation analysis to identify cis-regulation. We analyzed the exposure-mediated base substitution-level mutations and their potential triggers. Importantly, we performed Consensus Clustering based on the MSigDB database with Silhouette-correction to identify prognostically relevant pathway-based MSig subtypes. The tumour driver mutations (co-occurrence mutation pattern), aberrant pathways (tu

SUBMITTER: Zhang P 

PROVIDER: S-EPMC12647366 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature