ArticleFrontiers in genetics2022
Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Emerging Oncogenic and Immunoregulatory Roles of BST2 in Human Cancers.Biomedicines · 2026Review
- Pan-Cancer Analysis of BST2 Expression, Prognostic Significance, and Immune Correlations.Cancer management and research · 2025Article
- BST2 Drives Epithelial Ovarian Cancer Progression via Macrophage M2 Polarization, Neural Remodeling, and Immunosuppressive Microenvironment Formation.Human mutation · 2025Article
- Beneficial mechanisms of dimethyl fumarate in autoimmune uveitis: insights from single-cell RNA sequencing.Journal of neuroinflammation · 2024Article
- Bone marrow stromal cell antigen 2: Tumor biology, signaling pathway and therapeutic targeting (Review).Oncology reports · 2024Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rigorous molecular analysis of the immune cell environment and immune response of human tumors has led to immune checkpoint inhibitors as one of the most promising strategies for the treatment of human cancer. However, in human glioblastoma multiforme (GBM) which develops in part by attracting immune cell types intrinsic to the human brain (microglia), standard immunotherapy has yielded inconsistent results in experimental models and patients. Here, we analyzed publicly available expression datasets to identify molecules possibly associated with immune response originating from or influencing the tumor microenvironment in primary tumor samples. Using three glioma datasets (GSE16011, Rembrandt-glioma and TCGA-glioma), we first analyzed the data to distinguish between GBMs of high and low tumor cell purity, a reflection of the cellular composition of the tumor microenvironment, and second, to identify differentially expressed genes (DEGs) between these two groups using GSEA and other analyses. Tumor purity was negatively correlated with patient prognosis. The interferon gamma-related gene
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Registered trials
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