The multi-omics and Mendelian randomization analyses unveiled potential marker genes in the progression of glioblastoma.

ABSTRACT: In glioma research, identifying key molecules for predicting patient prognosis is challenging due to high heterogeneity. This study explores the correlation between alternative splicing (AS) and glioma prognosis, aiming to identify molecular markers for potential treatments. Retrieve transcriptomic and clinical data of glioma samples from the cancer genome atlas, eQTLGen database, and GWAS Catalog database. Build a predictive model for patient prognosis using the lasso-cox method. Machine learning is employed to identify the most diagnostically and predictively valuable biomarkers or features. Mendelian randomization analysis is employed to evaluate the causal relationship between genes and diseases. gene ontology, Kyoto encyclopedia of genes and genomes are utilized to explore the potenti

SUBMITTER: Hai J 

PROVIDER: S-EPMC12851673 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature