GBM microglia
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE65868 | GEO | 2019/02/27
REPOSITORIES: GEO
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Project description:Little is known about the immune performance and interactions of CNS microglia/macrophages in glioma patients. Microglia/macrophages were found to be the predominant immune cell infiltrating gliomas (approximately 1% of total cells); others identified are myeloid dendritic cells (DCs), plasmacytoid DCs, and T cells. Using a procedure enriching for CD11b/c+CD45+ glioma-infiltrating microglia/macrophages (GIMs) from postoperative tissue specimens of glioma patients (Hussain et al. Neuro Oncol. 2006 J;8(3):261-79) gene expression profiles were obtained form paired samples. The expression profiles are used to identify expression signatures contributed by GIMs in glioblastoma data sets (Murat et al, submitted).
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Project description:Low grade gliomas (LGG) account for about two-thirds of all glioma diagnoses in adolescents and young adults (AYA) and malignant progression of these patients leads to dismal outcomes. Recent studies have shown the importance of the dynamic tumor microenvironment in high-grade gliomas (HGG), yet its role is still poorly understood in low-grade glioma malignant progression. Here, we investigated the heterogeneity of the immune microenvironment using a platelet-derived growth factor (PDGF)-driven RCAS (replication-competent ASLV long terminal repeat with a splice acceptor) glioma model that recapitulates the malignant progression of low to high-grade glioma in humans and also provides a model system to characterize immune cell trafficking and evolution. To illuminate changes in the immune cell landscape during tumor progression, we performed single-cell RNA sequencing on immune cells isolated from animals bearing no tumor (NT), LGG and HGG, with a particular focus on the myeloid cell compartment, which is known to mediate glioma immunosuppression. LGGs demonstrated significantly increased infiltrating T cells, CD4 T cells, CD8 T cells, B cells, and natural killer cells in the tumor microenvironment, whereas HGGs significantly abrogated this infiltration. Our study identified two distinct macrophage clusters in the tumor microenvironment; one cluster appeared to be bone marrow-derived while another was defined by overexpression of Trem2, a known anti-tumor immunity marker in myeloid cell subpopulations. Our data demonstrates that these two distinct macrophage clusters show an immune-activated phenotype (Stat1, Tnf, Cxcl9 and Cxcl10) in LGG which evolves to an immunosuppressive state (Lgals3, Apoc1 and Id2) in HGG that restricts T cell recruitment and activation. We identified CD74 and macrophage migration inhibition factor (MIF) as potential targets for these distinct macrophage populations. Interestingly, these results were mirrored by our analysis of the TCGA dataset, which demonstrated a statistically significant association between CD74 overexpression and decreased overall survival in AYA patients with grade II LGGs. Targeting immunosuppressive myeloid cells and intra-tumoral macrophages within this therapeutic window may ameliorate mechanisms associated with immunosuppression before and during malignant progression.
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Project description:The different phases of tumor immunoediting in vivo were dissected thanks to a murine model of glioma induced by PDGF-B overexpression. We show that low-grade gliomas are highly immunostimulatory and that the adaptive immune system prevents the development of secondary tumor in syngeneic mice. During tumor progression, glioma cells downregulate immunostimulatory genes and the immune infiltrate becomes pro-tumorigenic. We showed that glioma cells are able to progress towards a high-grade phenotype even in immunodeficient mice, albeit more slowly and this progression invariably requires a downregulation of immunostimulatory genes.
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Project description:Ribba2012 - Low-grade gliomas, tumour growth inhibition model
Using longitudinal mean tumour diameter (MTD) data, this model describe the size evolution of low-grade glioma (LGG) in patients treated with chemotherapy or radiotherapy.
This model is described in the article:
A tumour growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy
Ribba B, Kaloshi G, Peyre M, Ricard D, Calvez V, Tod M, Cajavec-Bernard B, Idbaih A, Psimaras D, Dainese L, Pallud J, Cartalat-Carel S, Delattre JY, Honnorat J, Grenier E, Ducray F.
Clin. Cancer Res. 2012 Sep; 18(18): 5071-5080
Abstract:
PURPOSE: To develop a tumor growth inhibition model for adult diffuse low-grade gliomas (LGG) able to describe tumor size evolution in patients treated with chemotherapy or radiotherapy.
EXPERIMENTAL DESIGN: Using longitudinal mean tumor diameter (MTD) data from 21 patients treated with first-line procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine (PCV) chemotherapy, we formulated a model consisting of a system of differential equations, incorporating tumor-specific and treatment-related parameters that reflect the response of proliferative and quiescent tumor tissue to treatment. The model was then applied to the analysis of longitudinal tumor size data in 24 patients treated with first-line temozolomide (TMZ) chemotherapy and in 25 patients treated with first-line radiotherapy.
RESULTS: The model successfully described the MTD dynamics of LGG before, during, and after PCV chemotherapy. Using the same model structure, we were also able to successfully describe the MTD dynamics in LGG patients treated with TMZ chemotherapy or radiotherapy. Tumor-specific parameters were found to be consistent across the three treatment modalities. The model is robust to sensitivity analysis, and preliminary results suggest that it can predict treatment response on the basis of pretreatment tumor size data.
CONCLUSIONS: Using MTD data, we propose a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model might be used to predict treatment efficacy in LGG patients and could constitute a rational tool to conceive more effective chemotherapy schedules.
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2024-09-02 | BIOMD0000000521 | BioModels
Project description:We used whole genome microarray expression profiling as a discovery platform to identify high grade diffuse glioma associated differently expressed genes comparing with low grade diffuse glioma.
2021-03-01 | GSE106784 | GEO
Project description:Genomic evolution of low and high grade glioma
| PRJNA634165 | ENA
Project description:Genomic evolution of low and high grade glioma
| PRJNA634166 | ENA