Development and validation of an inflammatory response-related prognostic model and immune infiltration analysis in glioblastoma.

ABSTRACT:

Background

Despite receiving standard treatment, the prognosis of glioblastoma (GBM) patients is still poor. Considering the heterogeneity of each patient, it is imperative to identify reliable risk model that can effectively predict the prognosis of each GBM patient to guide the personalized treatment.

Methods

Transcriptomic gene expression profiles and corresponding clinical data of GBM patients were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Inflammatory response-related genes were extracted from Gene Set Enrichment Analysis (GSEA) website. Univariate Cox regression analysis was used for prognosis-related inflammatory genes (P<0.05). A polygenic prognostic risk model was constructed using least absolute shrinkage and s

SUBMITTER: Zhu W 

PROVIDER: S-EPMC9929762 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature