Machine learning algorithms for predicting glioma patient prognosis based on CD163+FPR3+ macrophage signature.

ABSTRACT: Tumor-associated macrophages (TAMs) play a vital role in glioma progression and are associated with poor outcomes in glioma patients. However, the specific roles of different subpopulations of TAMs remain poorly understood. Two distinct cell types, glioma and myeloid cells, were identified through single-cell sequencing analysis in gliomas. Within the TAMs-associated weighted gene co-expression network analysis (WGCNA) module, FPR3 emerged as a hub gene and was found to be expressed on CD163+ macrophages, while also being associated with clinical outcomes. Subsequently, a comprehensive assessment was undertaken to investigate the correlation between FPR3 expression and immune characteristics, revealing that FPR3 potentially plays a role in reshaping the glioma microenvironment. We identifi

SUBMITTER: Zhou Q 

PROVIDER: S-EPMC11399388 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature