Identification of a prognostic signature consisting of three macrophage-related genes for glioblastoma based on bulk and single-cell transcriptomes analyses

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Abstract

Background: Tumor-associated macrophages have been implicated in the progression and treatment resistance of glioblastoma (GBM). This study aimed to identify macrophage-related genes associated with prognosis and therapeutic response in GBM. Materials and methods: Bulk RNA-seq data from 533 patients with GBM were downloaded from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Bioinformatic tools were used to detect the co-expression gene modules associated with the infiltration of immune cells, identify a prognostic macrophage-related gene signature, and explore their association with sensitivity to chemotherapeutic drugs and immune checkpoint blockade. Single-cell RNA-seq data and multiplexed immunofluorescence were used to validate ISG20 expression (a member of the identified gene signature) in macrophages. Results: We detected gene modules associated with macrophages and identified a signature consisting of three macrophage-related genes (ISG20, PARP12 and IFIT5) in the discovery set (TCGA–GBM, n = 159), and validated its prognostic value in the validation set (CGGA–GBM, n = 374). This gene signature demonstrated favorable accuracy in predicting prognosis and resistance of immuno- and chemo-therapy. The co-expression of ISG20 and PD-1 in macrophages was verified by single-cell RNA-seq data and multiplex immunofluorescence. Conclusions: This study presents a macrophage-related gene signature to predict prognosis and therapeutic response in GBM. ISG20, PARP12 and IFIT5 are interferon-stimulated genes, and further investigations may provide new insights into the interplay between macrophages and interferon signaling in GBM.

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Wu, Q., Chen, C., Li, L., Liu, H., Cui, L., Bai, Y., … Peng, Y. (2025). Identification of a prognostic signature consisting of three macrophage-related genes for glioblastoma based on bulk and single-cell transcriptomes analyses. Annals of Medicine, 57(1). https://doi.org/10.1080/07853890.2025.2546111

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