scholarly journals IMMU-17. SINGLE-CELL RNA-SEQ REVEALS HIGH-GRADE GLIOMA ASSOCIATED MICROGLIA WITH PROINFLAMMATORY AND STEM-LIKE FEATURES SUPPORT TUMOR PROGRESSION

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii108-ii108
Author(s):  
Hailong Liu ◽  
Yongqiang Liu ◽  
Janusz Franco-Barraza ◽  
Xinguang Yu ◽  
Shiyu Feng
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Poor Response ◽  
High Grade Glioma ◽  
High Grade ◽  
Rna Seq ◽  
Wild Type ◽  
Current Therapies ◽  
Tgf Β1

Abstract Poor response of human glioblastoma to current therapies are influenced by tumor microenvironment. Although glioblastoma is recognized by large enrichment of microglia, characterization of diverse cell subsets and their functions remain challenging because of high heterogenicity. Here, we analyzed single-cell transcriptomics to comprehensively map the cell populations and determine the roles of microglia in IDH1/2 wild-type (IDH-wt) glioblastoma progression. Besides finding microglia were significantly enriched in IDH-wt glioblastoma compared to IDH1/2 mutant (IDH-mut) gliomas, we identified a unique high-grade glioma microglia (HGAM) subtype characterized by proinflammatory and stem-like features. In particular, HGAM’s pro-tumoral IL1β secretion is mediated via ApoE-induced activation of NLRP1 inflammasome. HGAM phagocytosed OPC-like malignant cells forming the neoplastic microglia, which presented the stem-like potential giving rise to activated microglia. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation. Additionally, an intricated evaluation of glioma patients revealed that SETD2 mutation/low-expression correlated with adverse prognosis. Further analysis showed that SETD2 -dificient tumor cells presented hypersensitivity to HGAM-derived IL1β via epigenetic dysregulation of PHF6. Also, SETD2 -deficient tumor cells produced TGF-β1 contributing to microglia activation. Finally, targeting the TGF-β1/TβRI signaling impaired HGAM activation and tumor growth. Our studies identify a unique neoplastic microglia subpopulation and establish cellular basis of interactions with tumor cells important for disease progression.

scholarly journals PO-334 Identification of shared lineage programs across high-grade glioma subtypes by single-cell RNA-seq

2018 ◽  
Author(s):  
S Muller ◽  
E Di Lullo ◽  
A Bhaduri ◽  
M Aghi ◽  
AR Kriegstein ◽  
...  
Keyword(s):  
Single Cell ◽  
High Grade Glioma ◽  
High Grade ◽  
Rna Seq

scholarly journals HGG-57. WHOLE-GENOME SEQUENCING, METHYLATION ANALYSIS, AND SINGLE-CELL RNA-SEQ DEFINE UNIQUE CHARACTERISTICS OF PEDIATRIC TREATMENT-INDUCED HIGH-GRADE GLIOMA AND SUGGEST ONCOGENIC MECHANISMS

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii354-iii354
Author(s):  
John Lucas ◽  
John DeSisto ◽  
Ke Xu ◽  
Andrew Donson ◽  
Tong Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
High Grade Glioma ◽  
Whole Genome ◽  
High Grade ◽  
Rna Seq ◽  
Mutational Signatures ◽  
Pediatric Treatment

Abstract BACKGROUND Pediatric treatment-induced high-grade glioma (TIHGG) is among the most severe late effects observed in childhood cancer survivors and is uniformly fatal. We previously showed that TIHGG are divergent from de novo pediatric high-grade glioma (pHGG) and cluster into two gene expression subgroups, one stemlike and the other inflammatory. Here we systematically compared TIHGG molecular profiles to pHGG and evaluated expression and single cell sequencing profiles in order to identify oncogenic mechanisms and the cellular basis for the observed TIHGG gene expression subgroups. MATERIALS/ METHODS 450/850K methylation and mutational signature analysis was conducted in 36 TIHGG samples. Resultant data were analyzed for the presence of chromothripsis, distinct molecular alterations, and mutational signatures in a subset of 10 samples with whole genome sequencing data. Five TIHGGs underwent single-cell RNA-Seq analysis (scRNAseq). RESULTS 26/36 TIHGG clustered with the pedRTK1 methylation class. TIHGG were characterized by an increased frequency of chromothripsis relative to pHGG (67% vs. 31%, p=0.036). FISH and WGS revealed frequent PDGFRA amplification secondary to enrichment in ecDNA. TIHGG were enriched for COSMIC mutational signatures 5 and 19 (p=0.0003) relative to pHGG. scRNAseq data showed that TIHGG tumors are composed of stem-like, neuronal, and inflammatory cell populations which may contribute to the previously described dominant expression profiles. CONCLUSIONS TIHGG represents a distinct molecular subtype of pHGG. Chromothripsis, leading to enriched expression of genes in extrachromosomal DNA, likely contribute to TIHGG oncogenesis. The dominant cell type (stem-like vs. inflammatory) may define the expression subgroup derived from bulk RNA-seq in heterogeneous tumors.

Comprehensive Bulk and Single Cell Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2906-2906 ◽  
Author(s):  
Jean Fan ◽  
Lili Wang ◽  
Angela N Brooks ◽  
Youzhong Wan ◽  
Donna S Neuberg ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Single Cells ◽  
Lymphocytic Leukemia ◽  
Rna Seq ◽  
Wild Type ◽  
Mutation Status ◽  
Total Rna ◽  
Gene Sets

Abstract Large-scale sequencing efforts have identified SF3B1 as arecurrently mutated gene in chronic lymphocytic leukemia (CLL). While SF3B1 mutations have been associated with adverse clinical outcome in CLL, mechanistic understanding of its role in the oncogenic phenotype remains lacking. We therefore undertook a comprehensive transcriptomic characterization of CLL in relation to SF3B1 mutation status at both bulk and single cell levels. We first profiled bulk mature poly-A selected RNA by sequencing (RNA-seq) from 37 CLLs (13 SF3B1 wild-type, 24 mutated). After identifying and classifying splice alterations using the tool JuncBASE, we found SF3B1 mutation to be associated with increased alternative splicing, with the most pervasive changes in 3' splice site selection. 304 alternatively spliced events were significantly associated with SF3B1 mutation, 4 of which we validated by qRT-PCR in 20 independent CLL samples with known SF3B1 mutation status. We further identified 1963 differentially expressed genes (q < 0.2) associated with SF3B1 mutation. By gene set enrichment analysis, SF3B1 mutation appeared to impact a variety of cancer and CLL-associated gene pathways, including DNA damage response, apoptosis regulation, chromatin remodeling, RNA processing, and Notch activation (q < 0.01). ~20% of these gene sets were also found to be significantly enriched for genes exhibiting alternative splicing in association with SF3B1 mutation. As SF3B1 acts at the level of pre-mRNA, we also performed bulk RNA-seq with total RNA libraries generated from 5 CLLs (2 SF3B1 wild-type, 3 with the common K700E mutation). We again observed an enrichment of 3' splice site changes, along with ~30% overlap of differentially expressed genes, and ~16% overlap of enriched gene sets with the aforementioned poly-A data analysis. One differentially over-expressed gene associated with SF3B1 mutation unique to this total RNA data analysis and validated by total RNA qPCR of independent CLL samples was TERC, an essential RNA component of telomerase that serves as a replication template during telomeric elongation. TERC is a non-polyadenylated transcript and thus was undetected by our previous poly-A selected RNA-seq and by targeted qRT-PCR of oligo dT-generated cDNA. Recent reports have highlighted the involvement of the spliceosome in telomerase RNA processing, and shorter telomere length of CLLs with SF3B1 mutation. Thus, although further investigation will be needed, our analyses suggest a potential mechanism by which SF3B1 mutation contributes to aberrant regulation of telomerase activity. Since SF3B1 is commonly found as a subclonal mutation in CLL, and because signals obtained from bulk analyses reflect only the average characteristics of the population, we assessed the transcriptomic effects of SF3B1 mutation in single cells within a subset of CLL cases. We developed a novel and sensitive microfluidic approach that performs multiplexed targeted amplification of RNA to simultaneously detect somatic mutation status, gene expression (96 targets), and alternative splicing (45 targets) within the same individual cell for 96 to 288 cells from 5 patients with different SF3B1 mutations. From the same patient sample, single cells with SF3B1 mutation generally exhibited increased alternative splicing for events identified from the bulk analysis, thus confirming the association of SF3B1 mutation with altered splicing at the single cell level. Different SF3B1 hotspot mutations within the HEAT repeat domains exhibited similar patterns of alternative splicing while a mutation outside of the repeat domain did not. Furthermore, we confirmed significant changes in gene expression between SF3B1 wild-type and mutant cells of target genes involved in the Notch pathway (NCOR2), cell cycle (CDKN2A, CCND1) and apoptosis (TXNIP). Consistent with these analyses, functional studies with overexpression of full-length mutated SF3B1 in a hematopoietic cell lines confirmed the modulation of these pathways by this putative CLL driver. Our high-resolution single cell analysis further uncovered 2 transcription factors strongly associated with SF3B1 mutation but not previously appreciated (KLF3 and KLF8). Our comprehensive transcriptomic analysis thus highlights SF3B1 mutation as an efficient mechanism by which a complex of changes relevant to CLL biology are generated that can contribute to disease progression. Disclosures Kipps: Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Li:Fluidigm: Employment. Livak:Fluidigm: Employment.

scholarly journals STEM-05. SINGLE CELL SEQUENCING CHARACTERIZES SPATIAL AND TEMPORAL RELATIONSHIPS OF ENHANCING AND NON-ENHANCING REGIONS IN HIGH-GRADE GLIOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii197-ii197
Author(s):  
Kunal Patel ◽  
Riki Kawaguchi ◽  
Alvaro Alvarado ◽  
Deepthi Muthukrishnan ◽  
Richard Everson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Cell ◽  
Single Cell ◽  
Tumor Cells ◽  
High Grade Glioma ◽  
Cell Types ◽  
Magnetic Resonance Images ◽  
Stem Cell Markers ◽  
High Grade ◽  
Single Cell Sequencing

Abstract INTRODUCTION Treatments of high grade glioma focus on the contrast enhancing (CE) portion of the tumor. However, given the invasive nature of glioma, residual tumor cells responsible for recurrence likely exist in the non-enhancing (NE) region. METHODS In 3 patients undergoing surgery for malignant glioma, we used pre-operative magnetic resonance images to prospectively identify biopsy targets in the CE region and locations 0.5-2.0cm beyond the CE edge. We carried out single cell sequencing on image guided biopsy specimens to generate 12,528 RNA profiles. RESULTS In all samples, tumor cells clustered into three predominant groups: tumor cells with astrocyte markers (ASC-like), tumor cells with oligodendrocyte markers (ODC-like), and tumor cells with neither marker. This last group consisted of a small proportion of tumor cells and expressed putative stem cell markers (PROM1, NES, SLC1A3, A2B5, ID1). A trajectory analysis consistently positioned this group as branching off into either ASC-like or ODC-like cells. CE regions had different cellular compositions than NE regions, with higher proportions of tumor, endothelial cells, T-cells, and NK cells. Using location and cell density data, we modeled expected tumor burden, predicting tumor cells up to 1.5cm beyond the CE region of the tumor. There were significant differences in gene expression between CE and NE tumor cells, with increased inflammation and hypoxia in the CE region versus increased proliferative markers in the NE region. Tumor cells in the NE region were characterized by increased proliferation, markers of invasion, and markers of self-renewal. CONCLUSIONS Single cell sequencing illustrates multiple glioma cell types and suggests a hierarchical relationship between tumor cell types. CE and NE regions exhibit different tumor and non-tumor cell populations as well as different gene expression profiles within individual cell types. There remains a significant tumor cell burden in the NE portion of tumor, including actively proliferating cells.

scholarly journals Cell Heterogeneity Analysis in Single-Cell RNA-seq Data Using Mixture Exponential Graph and Markov Random Field Model

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yishu Wang ◽  
Xuehan Tian ◽  
Dongmei Ai
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Markov Random Field ◽  
Field Model ◽  
Cell Heterogeneity ◽  
Rna Seq ◽  
Markov Random Field Model ◽  
Markov Random ◽  
Single Cell Profiling

Advanced single-cell profiling technologies promote exploration of cell heterogeneity, and clustering of single-cell RNA (scRNA-seq) data enables discovery of coexpression genes and network relationships between genes. In particular, single-cell profiling of circulating tumor cells (CTCs) can provide unique insights into tumor heterogeneity (including in triple-negative breast cancer (TNBC)), while scRNA-seq leads to better understanding of subclonal architecture and biological function. Despite numerous reports suggesting a direct correlation between circulating tumor cells (CTCs) and poor clinical outcomes, few studies have provided a thorough heterogeneity characterization of CTCs. In addition, TNBC is a disease with not only intertumor but also intratumor heterogeneity and represents various biological distinct subgroups that may have relationships with immune functions that are not clearly established yet. In this article, we introduce a new scheme for detecting genotypic characterization of single-cell heterogeneities and apply it to CTC and TNBC single-cell RNA-seq data. First, we use an existing mixture exponential family graph model to partition the cell-cell network; then, with the Markov random field model, we obtain more flexible network rewiring. Finally, we find the cell heterogeneity and network relationships according to different high coexpression gene modules in different cell subsets. Our results demonstrate that this scheme provides a reasonable and effective way to model different cell clusters and different biological enrichment gene clusters. Thus, using different internal coexpression genes of different cell clusters, we can infer the differences in tumor composition and diversity.

scholarly journals HGG-53. PROJECT HOPE: “PEDIATRIC AND AYA HIGH-GRADE GLIOMA OMICS PROJECT”- A LONGITUDINAL MOLECULAR LANDSCAPE OF HIGH-GRADE GLIOMAS RESOLVED AT SINGLE-CELL LEVEL

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii353-iii353
Author(s):  
Olivia A Hack ◽  
Husam Babikir ◽  
Li Jiang ◽  
Karin Shamardani ◽  
Ilon Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Evolutionary Dynamics ◽  
Age Groups ◽  
Treatment Resistance ◽  
High Grade Glioma ◽  
Adolescent And Young Adult ◽  
High Grade ◽  
Older Children ◽  
High Grade Gliomas

Abstract High-grade gliomas (HGG) are among the most prevalent and fatal cancers in pediatric, adolescent, and young adult (AYA) patients. Especially understudied are older children and young adults, aged 16–39 years. Previously, we profiled primary pediatric HGGs through single-cell transcriptomics and identified the genetic, epigenetic and developmental programs that drive their malignant progression. However, the questions of how these programs compare to those in older HGG patients, what the mechanisms are by which these tumors ultimately evolve to drive recurrence and treatment resistance, and how distinct tumor cell subpopulations bidirectionally communicate with their microenvironment remain to be elucidated. Here, we use single-nucleus RNA sequencing to compare 11 paired, matched high-grade gliomas at diagnosis and recurrence and 15 additional H3K27M primary and recurrent DMG samples in pediatric and AYA patients. In all tumors, we find both undifferentiated and differentiated tumor cells recapitulating distinct glial lineages, as well as diverse microenvironmental cell populations. When longitudinally comparing this tumor architecture within matched pairs, we find substantial differences in transcriptional program expressions. Diagnostic samples include more differentiated, astrocyte-like tumor cells, while cells from recurrent samples more highly express ribosomal and heat-shock protein genes, suggesting tumor progression- and treatment-related shifts. Ongoing sequencing and analysis will allow for unprecedented insight into the evolutionary dynamics of pediatric and AYA high-grade gliomas as well as delineate differences in the biology of DMGs occurring in different age groups. This multi-institutional project was funded by the National Institute of Health.

scholarly journals Single-cell characterization of macrophages in glioblastoma reveals MARCO as a mesenchymal pro-tumor marker

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew X. Chen ◽  
Robyn D. Gartrell ◽  
Junfei Zhao ◽  
Pavan S. Upadhyayula ◽  
Wenting Zhao ◽  
...  
Keyword(s):  
Single Cell ◽  
Checkpoint Inhibitors ◽  
Single Cells ◽  
Scavenger Receptor ◽  
Dependent Manner ◽  
Rna Seq ◽  
Wild Type ◽  
Small Cell Lung ◽  
Worse Prognosis

Abstract Background Macrophages are the most common infiltrating immune cells in gliomas and play a wide variety of pro-tumor and anti-tumor roles. However, the different subpopulations of macrophages and their effects on the tumor microenvironment remain poorly understood. Methods We combined new and previously published single-cell RNA-seq data from 98,015 single cells from a total of 66 gliomas to profile 19,331 individual macrophages. Results Unsupervised clustering revealed a pro-tumor subpopulation of bone marrow-derived macrophages characterized by the scavenger receptor MARCO, which is almost exclusively found in IDH1-wild-type glioblastomas. Previous studies have implicated MARCO as an unfavorable marker in melanoma and non-small cell lung cancer; here, we find that bulk MARCO expression is associated with worse prognosis and mesenchymal subtype. Furthermore, MARCO expression is significantly altered over the course of treatment with anti-PD1 checkpoint inhibitors in a response-dependent manner, which we validate with immunofluorescence imaging. Conclusions These findings illustrate a novel macrophage subpopulation that drives tumor progression in glioblastomas and suggest potential therapeutic targets to prevent their recruitment.

750 Malat1 lncRNA controls metastatic reactivation of dormant breast cancer by immune evasion

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A799-A799
Author(s):  
Dhiraj Kumar ◽  
Sreeharsha Gurrapu ◽  
Hyunho Han ◽  
Yan Wang ◽  
Seongyeon Bae ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Single Cell ◽  
Cancer Cells ◽  
Tumor Cells ◽  
Immune Evasion ◽  
Breast Cancer Cells ◽  
Metastatic Potential ◽  
Rna Seq

BackgroundLong non-coding RNAs (lncRNAs) are involved in various biological processes and diseases. Malat1 (metastasis-associated lung adenocarcinoma transcript 1), also known as Neat2, is one of the most abundant and highly conserved nuclear lncRNAs. Several studies have shown that the expression of lncRNA Malat1 is associated with metastasis and serving as a predictive marker for various tumor progression. Metastatic relapse often develops years after primary tumor removal as a result of disseminated tumor cells undergoing a period of latency in the target organ.1–4 However, the correlation of tumor intrinsic lncRNA in regulation of tumor dormancy and immune evasion is largely unknown.MethodsUsing an in vivo screening platform for the isolation of genetic entities involved in either dormancy or reactivation of breast cancer tumor cells, we have identified Malat1 as a positive mediator of metastatic reactivation. To functionally uncover the role of Malat1 in metastatic reactivation, we have developed a knock out (KO) model by using paired gRNA CRISPR-Cas9 deletion approach in metastatic breast and other cancer types, including lung, colon and melanoma. As proof of concept we also used inducible knockdown system under in vivo models. To delineate the immune micro-environment, we have used 10X genomics single cell RNA-seq, ChIRP-seq, multi-color flowcytometry, RNA-FISH and immunofluorescence.ResultsOur results reveal that the deletion of Malat1 abrogates the tumorigenic and metastatic potential of these tumors and supports long-term survival without affecting their ploidy, proliferation, and nuclear speckles formation. In contrast, overexpression of Malat1 leads to metastatic reactivation of dormant breast cancer cells. Moreover, the loss of Malat1 in metastatic cells induces dormancy features and inhibits cancer stemness. Our RNA-seq and ChIRP-seq data indicate that Malat1 KO downregulates several immune evasion and stemness associated genes. Strikingly, Malat1 KO cells exhibit metastatic outgrowth when injected in T cells defective mice. Our single-cell RNA-seq cluster analysis and multi-color flow cytometry data show a greater proportion of T cells and reduce Neutrophils infiltration in KO mice which indicate that the immune microenvironment playing an important role in Malat1-dependent immune evasion. Mechanistically, loss of Malat1 is associated with reduced expression of Serpinb6b, which protects the tumor cells from cytotoxic killing by the T cells. Indeed, overexpression of Serpinb6b rescued the metastatic potential of Malat1 KO cells by protecting against cytotoxic T cells.ConclusionsCollectively, our data indicate that targeting this novel cancer-cell-initiated domino effect within the immune system represents a new strategy to inhibit tumor metastatic reactivation.Trial RegistrationN/AEthics ApprovalFor all the animal studies in the present study, the study protocols were approved by the Institutional Animal Care and Use Committee(IACUC) of UT MD Anderson Cancer Center.ConsentN/AReferencesArun G, Diermeier S, Akerman M, et al., Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes Dev 2016 Jan 1;30(1):34–51.Filippo G. Giancotti, mechanisms governing metastatic dormancy and reactivation. Cell 2013 Nov 7;155(4):750–764.Gao H, Chakraborty G, Lee-Lim AP, et al., The BMP inhibitor Coco reactivates breast cancer cells at lung metastatic sites. Cell 2012b;150:764–779.Gao H, Chakraborty G, Lee-Lim AP, et al., Forward genetic screens in mice uncover mediators and suppressors of metastatic reactivation. Proc Natl Acad Sci U S A 2014 Nov 18; 111(46): 16532–16537.

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

scholarly journals Single-Cell Transcriptomic Analysis Revealed a Critical Role of SPP1/CD44-Mediated Crosstalk Between Macrophages and Cancer Cells in Glioma

2021 ◽  
Vol 9 ◽  
Author(s):  
Cong He ◽  
Luoyan Sheng ◽  
Deshen Pan ◽  
Shuai Jiang ◽  
Li Ding ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Heterogeneity ◽  
Molecular Mechanisms ◽  
Critical Role ◽  
Cell Communication ◽  
High Grade Glioma ◽  
Sequencing Analysis ◽  
High Grade ◽  
Cellular Components

High-grade glioma is one of the most lethal human cancers characterized by extensive tumor heterogeneity. In order to identify cellular and molecular mechanisms that drive tumor heterogeneity of this lethal disease, we performed single-cell RNA sequencing analysis of one high-grade glioma. Accordingly, we analyzed the individual cellular components in the ecosystem of this tumor. We found that tumor-associated macrophages are predominant in the immune microenvironment. Furthermore, we identified five distinct subpopulations of tumor cells, including one cycling, two OPC/NPC-like and two MES-like cell subpopulations. Moreover, we revealed the evolutionary transition from the cycling to OPC/NPC-like and MES-like cells by trajectory analysis. Importantly, we found that SPP1/CD44 interaction plays a critical role in macrophage-mediated activation of MES-like cells by exploring the cell-cell communication among all cellular components in the tumor ecosystem. Finally, we showed that high expression levels of both SPP1 and CD44 correlate with an increased infiltration of macrophages and poor prognosis of glioma patients. Taken together, this study provided a single-cell atlas of one high-grade glioma and revealed a critical role of macrophage-mediated SPP1/CD44 signaling in glioma progression, indicating that the SPP1/CD44 axis is a potential target for glioma treatment.

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