Characterization of aging cancer-associated fibroblasts draws implications in prognosis and immunotherapy response in low-grade gliomas.

ABSTRACT: Background: Due to the highly variable prognosis of low-grade gliomas (LGGs), it is important to find robust biomarkers for predicting clinical outcomes. Aging cancer-associated fibroblasts (CAFs) within the senescent stroma of a tumor microenvironment (TME) have been recently reported to play a key role in tumor development. However, there are few studies focusing on this topic in gliomas. Methods and Results: Based on the transcriptome data from TCGA and CGGA databases, we identified aging CAF-related genes (ACAFRGs) in LGGs by the weighted gene co-expression network analysis (WGCNA) method, followed by which LGG samples were classified into two aging CAF-related gene clusters with distinct prognosis and characteristics of the TME. Machine learning algorithms were used to s

SUBMITTER: Zhou Z 

PROVIDER: S-EPMC9449154 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature