Abstract
Background: The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Here, weighted correlation network analysis (WGCNA) was performed on publicly available datasets to identify immune-related molecules that may contribute to the progression of GBM and thus be exploited as potential therapeutic targets.Methods: WGCNA was used to identify highly correlated gene clusters in Chinese Glioma Genome Atlas glioma dataset. Immune-related genes in significant modules were subsequently validated in the Cancer Genome Atlas (TCGA) and Rembrandt databases, and impact on GBM development was examined in migration and vascular mimicry assays in vitro and in an orthotopic xenograft model (GL261 luciferase-GFP cells) in mice.Results: WGCNA yielded 14 significant modules, one of which (black) contained genes involved in immune response and extracellular matrix formation. The intersection of these genes with a GO immune-related gene set yielded 47 immune-related genes, five of which exhibited increased expression and association with worse prognosis in GBM. One of these genes, TREM1, was highly expressed in areas of pseudopalisading cells around necrosis and associated with other proteins induced in angiogenesis/hypoxia. In macrophages induced from THP1 cells, TREM1 expression levels were increased under hypoxic conditions and associated with markers of macrophage M2 polarization. TREM1 siRNA knockdown in induced macrophages reduced their ability to promote migration and vascular mimicry in GBM cells in vitro, and treatment of mice with LP-17 peptide, which blocks TREM1, inhibited growth of GL261 orthotopic xenografts. Finally, blocking the cytokine receptor for CSF1 in induced macrophages also impeded their potential to promote tumor migration and vascular mimicry in GBM cells.Conclusions: Our results demonstrated that TREM1 could be used as a novel immunotherapy target for glioma patients.
Highlights
Glioblastoma (GBM) is one of the most deadly types of malignant solid tumor
To find the key modules associated with GBM clinical traits, we performed weighted correlation network analysis (WGCNA) on the Chinese Glioma Genome Atlas (CGGA) glioma dataset
To validate TREM1 as a gene associated with prognosis, we examined molecular features of the gene in samples in the Rembrandt, The Cancer Genome Atlas (TCGA), and CGGA databases
Summary
Glioblastoma (GBM) is one of the most deadly types of malignant solid tumor. Despite considerable effort toward the molecular understanding and treatment of the disease, the patient survival rate remains dismally low. The 5-year survival rate of 6.8% is especially low for GBM relative to all tumor types [1]. A compounding problem for the incidence of GBM is the increasing longevity of the human population worldwide. In the United States, the incidence of GBM is estimated to be 3.22 per 100,000 individuals [1]. The development of effective treatment strategies to prevent the progression of GBM and improve the quality of life for patients is urgently needed. The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Weighted correlation network analysis (WGCNA) was performed on publicly available datasets to identify immune-related molecules that may contribute to the progression of GBM and be exploited as potential therapeutic targets
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