KS01.6.A Comparative analysis of the immune compartment in human glioblastoma and IDH-mutant WHO grade 4 astrocytoma reveals profound differences in microglia phenotypes

2021 ◽  
Vol 23 (Supplement_2) ◽  
pp. ii4-ii4
Author(s):  
R Sankowski ◽  
M Friedrich ◽  
L Bunse ◽  
H H Heiland ◽  
M Platten ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Therapeutic Options ◽  
High Dimensional ◽  
Normal Brain ◽  
Who Grade ◽  
Idh Mutations ◽  
Single Cell Rna Sequencing ◽  
Human Gbm

Abstract BACKGROUND Glioblastoma (GBM) are the most common primary brain tumors. If untreated the average survival is around 12–18 months. Unfortunately, despite extensive research efforts, the therapeutic options remain limited. One major aspect complicating therapeutic development is an immunosuppressive tumor microenvironment. Isocitrate dehydrogenase (IDH)-mutant, WHO grade 4 astrocytomas appear histologically indistinguishable from GBM, but show significantly longer survival times. IDH mutations lead to changes in the tumor microenvironment with accrual of the neometabolite R-2-hydroxyglutarate. Previous studies on bulk transcriptomes have shown differences in the immune compartment of both tumor entities that were linked to the differences in clinical behavior. MATERIAL AND METHODS We have conducted high-dimensional comparative analyses of the myeloid compartment in surgically resected human GBM and IDH-mutant WHO grade 4 astrocytomas using single-cell RNA-Sequencing and immunohistochemistry. Histologically normal brain regions from epilepsy patients were used as controls. For analysis, whole-cell suspensions were prepared from freshly resected tumors or controls. Fluorescence activated cell sorting was used for myeloid cell enrichment. Samples were processed using the high-sensitivity single-cell RNA sequencing protocol CEL-Seq2. Seurat and StemID2 algorithms were used for clustering, differential gene expression and pseudotime analysis. Protein validation was achieved using immunohistochemistry. RESULTS We identified profound transcriptional changes of glioma-associated microglia in GBM with respect to control brain samples. Namely, we observed a global upregulation of major histocompatibility complex associated genes in GBM across all clusters. Additionally, we identified distinct myeloid subsets with phagocytic, hypoxia-associated and chemotactic transcriptomic signatures. Pseudotime analysis finely resolved transitional cell states. These changes were dramatically attenuated in IDH-mutant WHO grade 4 astrocytomas. The myeloid cells in these tumors resembled homeostatic microglia and showed an increased expression of cytokine and chemokine genes. CONCLUSION Here, we present a high-dimensional transcriptomic atlas of the myeloid compartment in human GBM and IDH-mutant WHO grade 4 astrocytomas. The identified differences point towards targeted therapeutic options via the modulation of the tumor microenvironment.

scholarly journals Evaluation of UMAP as an alternative to t-SNE for single-cell data

2018 ◽  
Author(s):  
Etienne Becht ◽  
Charles-Antoine Dutertre ◽  
Immanuel W. H. Kwok ◽  
Lai Guan Ng ◽  
Florent Ginhoux ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Single Cell ◽  
Rna Sequencing ◽  
Reduction Technique ◽  
High Dimensional ◽  
The Past ◽  
Dimensionality Reduction Technique ◽  
Single Cell Rna Sequencing ◽  
Linear Dimensionality Reduction ◽  
Cell Data

AbstractUniform Manifold Approximation and Projection (UMAP) is a recently-published non-linear dimensionality reduction technique. Another such algorithm, t-SNE, has been the default method for such task in the past years. Herein we comment on the usefulness of UMAP high-dimensional cytometry and single-cell RNA sequencing, notably highlighting faster runtime and consistency, meaningful organization of cell clusters and preservation of continuums in UMAP compared to t-SNE.

scholarly journals Computational Methods for Single-Cell RNA Sequencing

2020 ◽  
Vol 3 (1) ◽  
pp. 339-364 ◽  
Author(s):  
Brian Hie ◽  
Joshua Peters ◽  
Sarah K. Nyquist ◽  
Alex K. Shalek ◽  
Bonnie Berger ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Computational Methods ◽  
Analytical Methods ◽  
High Dimensional ◽  
Computational Tools ◽  
Single Cell Rna Sequencing ◽  
Selection Of

Single-cell RNA sequencing (scRNA-seq) has provided a high-dimensional catalog of millions of cells across species and diseases. These data have spurred the development of hundreds of computational tools to derive novel biological insights. Here, we outline the components of scRNA-seq analytical pipelines and the computational methods that underlie these steps. We describe available methods, highlight well-executed benchmarking studies, and identify opportunities for additional benchmarking studies and computational methods. As the biochemical approaches for single-cell omics advance, we propose coupled development of robust analytical pipelines suited for the challenges that new data present and principled selection of analytical methods that are suited for the biological questions to be addressed.

TAMI-32. CORRELATION BETWEEN RADIOSENSITIVITY INDEX AND M2 MACROPHAGE PROPORTION IN TUMOR MICROENVIRONMENT OF GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi204-vi205
Author(s):  
Bum-Sup Jang ◽  
In Ah Kim
Keyword(s):  
Overall Survival ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Rna Sequencing ◽  
The Cancer Genome Atlas ◽  
M2 Macrophage ◽  
M2 Macrophages ◽  
M1 Macrophage ◽  
Single Cell Rna Sequencing ◽  
Genome Atlas

Abstract BACKGROUND Tumor-associated macrophages (TAMs) Macrophage are predominant in glioblastoma tumor microenvironment (TME), supporting for neoplastic cell expansion and invasion. We investigated the relationship between radiosensitivity of glioblastoma and M1/M2 macrophage profiles in bulk and single cell RNA sequencing datasets. METHODS We used radiosensitivity index (RSI) gene signature and estimated RSI score based on the ranking of genes by expression level. Two large glioma datasets – The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) – were employed to identify whether RSI is clinically predictive of overall survival following radiation therapy. To analyze the association between M1/M2 macrophages and RSI within spatial context, the Ivy Glioblastoma Atlas Project dataset was investigated and single cell RNA sequencing dataset (GSE84465) was analyzed as well. Macrophages were profiled using a deconvolution algorithm, CIBERSORTx. RESULTS The RSI-high group having radioresistant tumors showed worse overall survival than the RSI-low group in both the TCGA (HR=1.87, 95% CI=1.06-3.29, P=0.031) and the CGGA (HR=1.61, 95% CI=1.04-2.50, P=0.031) glioblastoma population. In the Ivy Glioblastoma Atlas Project dataset, radiosensitive tumor having lower RSI was significantly more found in more vascular region including hyperplastic and microvascular region (coefficient=-0.07, P=0.001), meanwhile, radioresistant tumor was significantly clustered in necrotic region including perinecrotic and pseudopalisading regions (coefficient=0.07, P< 0.001). The proportion of M1/M2 macrophage and RSI score showed an inverse relationship (coefficient=-0.23, P=0.015), indicating that radioresistant glioblastomas are related with TME having more M2 than M1 macrophage. In single cell RNA sequencing dataset composed of immune and tumor cells collected from four patients, mean RSI of neoplastic cells was positively correlated with high proportion of M2 macrophages. CONCLUSION RSI can predict radiation response in terms of overall survival in glioblastoma patients. High proportion of M2 macrophage may play an important role in TME of radioresistant glioblastoma.

scholarly journals Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

Oncogene ◽  
2021 ◽  
Author(s):  
Philip Bischoff ◽  
Alexandra Trinks ◽  
Benedikt Obermayer ◽  
Jan Patrick Pett ◽  
Jennifer Wiederspahn ◽  
...  
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Single Cell ◽  
Rna Sequencing ◽  
Histological Grade ◽  
Cell Populations ◽  
Marker Genes ◽  
Single Cell Rna Sequencing

AbstractRecent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP²E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N³MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches.

scholarly journals Single-Cell RNA Sequencing Reveals Multiple Pathways and the Tumor Microenvironment Could Lead to Chemotherapy Resistance in Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Meijia Gu ◽  
Ti He ◽  
Yuncong Yuan ◽  
Suling Duan ◽  
Xin Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cancer Biology ◽  
Chemotherapy Resistance ◽  
Cell Types ◽  
Functional Enrichment ◽  
Single Cell Rna Sequencing

BackgroundCervical cancer is one of the most common gynecological cancers worldwide. The tumor microenvironment significantly influences the therapeutic response and clinical outcome. However, the complex tumor microenvironment of cervical cancer and the molecular mechanisms underlying chemotherapy resistance are not well studied. This study aimed to comprehensively analyze cells from pretreated and chemoresistant cervical cancer tissues to generate a molecular census of cell populations.MethodsBiopsy tissues collected from patients with cervical squamous cell carcinoma, cervical adenocarcinoma, and chronic cervicitis were subjected to single-cell RNA sequencing using the 10× Genomics platform. Unsupervised clustering analysis of cells was performed to identify the main cell types, and important cell clusters were reclustered into subpopulations. Gene expression profiles and functional enrichment analysis were used to explore gene expression and functional differences between cell subpopulations in cervicitis and cervical cancer samples and between chemoresistant and chemosensitive samples.ResultsA total of 24,371 cells were clustered into nine separate cell types, including immune and non-immune cells. Differentially expressed genes between chemoresistant and chemosensitive patients enriched in the phosphoinositide 3-kinase (PI3K)/AKT pathway were involved in tumor development, progression, and apoptosis, which might lead to chemotherapy resistance.ConclusionsOur study provides a comprehensive overview of the cancer microenvironment landscape and characterizes its gene expression and functional difference in chemotherapy resistance. Consequently, our study deepens the insights into cervical cancer biology through the identification of gene markers for diagnosis, prognosis, and therapy.

scholarly journals Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

2020 ◽  
Author(s):  
Philip Bischoff ◽  
Alexandra Trinks ◽  
Benedikt Obermayer ◽  
Jan Patrick Pett ◽  
Annika Lehmann ◽  
...  
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Histological Grade ◽  
Myeloid Dendritic Cells ◽  
Oncogenic Pathways ◽  
Single Cell Rna Sequencing ◽  
Cell Gene Expression

Recent developments in immuno-oncology demonstrate that not only cancer cells, but also features of the tumor microenvironment guide precision medicine. Still, the relationship between tumor and microenvironment remains poorly understood. To overcome this limitation and identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to lung adenocarcinomas. While the highly heterogeneous carcinoma cell transcriptomes reflected histological grade and activity of relevant oncogenic pathways, our analysis revealed two distinct microenvironmental patterns. We identified a prognostically unfavorable group of tumors with a microenvironment composed of cancer-associated myofibroblasts, exhausted CD8+ T cells, proinflammatory monocyte-derived macrophages and plasmacytoid dendritic cells (CEP2 pattern) and a prognostically favorable group characterized by myeloid dendritic cells, anti-inflammatory monocyte-derived macrophages, normal-like myofibroblasts, NK cells and conventional T cells (MAN2C pattern). Our results show that single-cell gene expression profiling allows to identify patient subgroups based on the tumor microenvironment beyond cancer cell-centric profiling.

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