Glioblastoma Prognosis and Therapeutic Response Predicted by a Cancer-Associated Fibroblasts Risk Score.

ABSTRACT:

Background

Cancer-associated fibroblasts (CAFs), as a key component of the tumor microenvironment, have not been systematically elucidated in glioblastoma (GBM). Our study aims to develop a prognostic model integrating CAFs-related features, with the goal of providing new insights for precise stratification and optimized treatment strategies for GBM patients.

Methods

Utilizing GBM-related data from reputable public databases, we utilized the Seurat package in R to analyze single-cell RNA sequencing (scRNA-seq) data for the characterization of CAFs in GBM. We identified CAFs phenotypes and screened for key CAFs-related genes significantly associated with patient prognosis. Using regression analysis, we constructed a CAFs-based risk score, which was subsequently validated in m

SUBMITTER: Zhou H 

PROVIDER: S-EPMC12767406 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature