540 Transcriptionally defined immune landscape in human gliomas

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A576-A576
Author(s):  
Pravesh Gupta ◽  
Minghao Dang ◽  
Krishna Bojja ◽  
Huma Shehwana ◽  
Tuan Tran ◽  
...  

BackgroundBrain immunity is largely myeloid cell dominated rather than lymphoid cells in healthy and diseased state including malignancies of glial origins called as gliomas. Despite this skewed myeloid centric immune contexture, immune checkpoint and T cell based therapeutic modalities are generalizably pursued in gliomas ignoring the following facts i) T cells are sparse in tumor brain ii) glioma patients are lymphopenic iii) gliomas harbor abundant and highly complex myeloid cell repertoire. We recognized these paradoxes pertaining to fundamental understanding of constituent immune cells and their functional states in the tumor immune microenvironment (TIME) of gliomas, which remains elusive beyond a priori cell types and/or states.MethodsTo dissect the TIME in gliomas, we performed single-cell RNA-sequencing on ~123,000 tumor-derived sorted CD45+ leukocytes from fifteen genomically classified patients comprising IDH-mutant primary (IMP; n=4), IDH-mutant recurrent (IMR; n=4), IDH-wild type primary (IWP; n=3), or IDH-wild type recurrent (IWR; n=4) gliomas (hereafter referred as glioma subtypes) and two non-glioma brains (NGBs) as controls.ResultsUnsupervised clustering analyses delineated predominant 34-myeloid cell clusters (~75%) over 28-lymphoid cell clusters (~25%) reflecting enormous heterogeneity within and across glioma subtypes. The glioma immune diversity spanned functionally imprinted phagocytic, antigen-presenting, hypoxia, angiogenesis and, tumoricidal myeloid to classical cytotoxic lymphoid subpopulations. Specifically, IDH-mutant gliomas were predominantly enriched for brain-resident microglial subpopulations in contrast to enriched bone barrow-derived infiltrates in IDH-wild type especially in a recurrent setting. Microglia attrition in IWP and IWR gliomas were concomitant with invading monocyte-derived cells with semblance to dendritic cell and macrophage like transcriptomic features. Additionally, microglial functional diversification was noted with disease severity and mostly converged to inflammatory states in IWR gliomas. Beyond dendritic cells, multiple antigen-presenting cellular states expanded with glioma severity especially in IWP and IWR gliomas. Furthermore, we noted differential microglia and dendritic cell inherent antigen presentation axis viz, osteopontin, and classical HLAs in IDH subtypes and, glioma-wide non-PD1 checkpoints associations in T cells like Galectin9 and Tim-3. As a general utility, our immune cell deconvolution approach with single-cell-matched bulk RNA sequencing data faithfully resolved 58-cell states which provides glioma specific immune reference for digital cytometry application to genomics datasets.ConclusionsAltogether, we identified prognosticator immune cell-signatures from TCGA cohorts as one of many potential immune responsiveness applications of the curated signatures for basic and translational immune-genomics efforts. Thus, we not only provide an unprecedented insight of glioma TIME but also present an immune data resource that can be exploited for immunotherapy applications.Ethics ApprovalThe brain tumor/tissue samples were collected as per MD Anderson internal review board (IRB)-approved protocol numbers LAB03-0687 and, LAB04-0001. One non-tumor brain tissue sample was collected from patient undergoing neurosurgery for epilepsy as per Baylor College of Medicine IRB-approved protocol number H-13798. All experiments were compliant with the review board of MD Anderson Cancer Center, USA.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii112-ii112
Author(s):  
Pravesh Gupta ◽  
Minghao Dang ◽  
Krishna Bojja ◽  
Tuan Tran M ◽  
Huma Shehwana ◽  
...  

Abstract The brain tumor immune microenvironment (TIME) continuously evolves during glioma progression and a comprehensive understanding of the glioma-centric immune cell repertoire beyond a priori cell types and/or states is uncharted. Consequently, we performed single-cell RNA-sequencing on ~123,000 tumor-derived immune cells from 17-pathologically stratified, IDH (isocitrate dehydrogenase)-differential primary, recurrent human gliomas, and non-glioma brains. Our analysis delineated predominant 34-myeloid cell clusters (~75%) over 28-lymphoid cell clusters (~25%) reflecting enormous heterogeneity within and across gliomas. The glioma immune diversity spanned functionally imprinted phagocytic, antigen-presenting, hypoxia, angiogenesis and, tumoricidal myeloid to classical cytotoxic lymphoid subpopulations. Specifically, IDH-mutant gliomas were enriched for brain-resident microglial subpopulations in contrast to enhanced bone barrow-derived infiltrates in IDH-wild type, especially in a recurrent setting. Microglia attrition in IDH-wild type -primary and -recurrent gliomas were concomitant with invading monocyte-derived cells with semblance to dendritic cell and macrophage/microglia like transcriptomic features. Additionally, microglial functional diversification was noted with disease severity and mostly converged to inflammatory states in IDH-wild type recurrent gliomas. Beyond dendritic cells, multiple antigen-presenting cellular states expanded with glioma severity especially in IDH-wild type primary and recurrent- gliomas. Furthermore, we noted differential microglia and dendritic cell inherent antigen presentation axis viz, osteopontin, and classical HLAs in IDH subtypes and, glioma-wide non-PD1 checkpoints associations in T cells like Galectin9 and Tim-3. As a general utility, our immune cell deconvolution approach with single-cell-matched bulk RNA sequencing data faithfully resolved 58-cell states which provides glioma specific immune reference for digital cytometry application to genomics datasets. Resultantly, we identified prognosticator immune cell-signatures from TCGA cohorts as one of many potential immune responsiveness applications of the curated signatures for basic and translational immune-genomics efforts. Thus, we not only provide an unprecedented insight of glioma TIME but also present an immune data resource that can be exploited to guide pragmatic glioma immunotherapy designs.


2019 ◽  
Vol 5 (4) ◽  
pp. 199-208
Author(s):  
Xiaoyang Jin ◽  
Lingyuan Meng ◽  
Zhao Yin ◽  
Haisheng Yu ◽  
Linnan Zhang ◽  
...  

Abstract Dendritic cells (DCs) are professional antigen-presenting cells (APCs). The key functions of DCs include engulfing, processing and presenting antigens to T cells and regulating the activation of T cells. There are two major DC subtypes in human blood: plasmacytoid DCs (pDCs) and conventional DCs. To define the differences between the adult and infant immune systems, especially in terms of DC constitution, we enriched DCs from human cord blood and generated single-cell RNA sequencing data from about 7000 cells using the 10x Genomics Single Cell 3′ Solution. After incorporating the differential expression analysis method in our clustering process, we identified all the known dendritic cell subsets. Interestingly, we also found a group of DCs with gene expression that was a mix of megakaryocytes and pDCs. Further, we verified the expression of selected genes at both the RNA level by PCR and the protein level by flow cytometry. This study further demonstrates the power of single-cell RNA sequencing in dendritic cell research.


2021 ◽  
Author(s):  
Sakthi Rajendran ◽  
Clayton Peterson ◽  
Alessandro Canella ◽  
Yang Hu ◽  
Amy Gross ◽  
...  

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 marker of tumor associated macrophages. 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 gliomas. Targeting immunosuppressive myeloid cells and intra-tumoral macrophages within this therapeutic window may ameliorate mechanisms associated with immunosuppression before and during malignant progression.


2021 ◽  
Vol 129 (Suppl_1) ◽  
Author(s):  
Benjamin Kopecky ◽  
Junedh Amrute ◽  
Hao Dun ◽  
C. Corbin Frye ◽  
DANIEL KREISEL ◽  
...  

Heart transplant rejection is common and is associated with significant morbidity and mortality. Current immunosuppressive therapies primarily target recipient T-cells and have a multitude of untoward effects including infections, malignancies, and end-organ damage. Recent studies implicate the roles of antigen presenting cells towards pathogenesis of allograft rejection through recruitment and activation of T-cells. The importance of antigen presenting cell origin, identity, and functional importance remains unknown. Using complimentary imaging and single cell RNA sequencing techniques, we show that donor and recipient monocytes and macrophages co-exist after heart transplantation. These myeloid populations have diverse transcriptional signatures that evolve throughout ongoing rejection. Donor macrophages can be defined ontologically and based on their expression of C-C chemokine receptor 2 (CCR2) and expression of MHC-II. Donor CCR2+ and CCR2- populations can be further defined based on their gene expression profiles, highlighting the marked heterogeneity in the donor macrophage population. Selective depletion of CCR2+ macrophages result in prolonged allograft survival. We use longitudinal single cell RNA sequencing to show that donor CCR2+ and CCR2- macrophages have distinct activation mechanisms such that donor CCR2+ macrophages signal through MyD88/NF-kB. Conditional depletion of MyD88 in donor macrophages recapitulates the donor CCR2+ depletion phenotype. Further interrogation of MyD88 conditionally depleted allografts shows reduced T-cell alloreactivity, holding promise for a potential therapeutic target pathway. Together, we show the molecular identity, diversity, and evolution of donor and recipient monocytes and macrophages as well as the functional relevance and activation pathways of donor macrophages in cardiac allografts.


2020 ◽  
Vol 31 (9) ◽  
pp. 1977-1986 ◽  
Author(s):  
Andrew F. Malone ◽  
Haojia Wu ◽  
Catrina Fronick ◽  
Robert Fulton ◽  
Joseph P. Gaut ◽  
...  

BackgroundIn solid organ transplantation, donor-derived immune cells are assumed to decline with time after surgery. Whether donor leukocytes persist within kidney transplants or play any role in rejection is unknown, however, in part because of limited techniques for distinguishing recipient from donor cells.MethodsWhole-exome sequencing of donor and recipient DNA and single-cell RNA sequencing (scRNA-seq) of five human kidney transplant biopsy cores distinguished immune cell contributions from both participants. DNA-sequence comparisons used single nucleotide variants (SNVs) identified in the exome sequences across all samples.ResultsAnalysis of expressed SNVs in the scRNA-seq data set distinguished recipient versus donor origin for all 81,139 cells examined. The leukocyte donor/recipient ratio varied with rejection status for macrophages and with time post-transplant for lymphocytes. Recipient macrophages displayed inflammatory activation whereas donor macrophages demonstrated antigen presentation and complement signaling. Recipient-origin T cells expressed cytotoxic and proinflammatory genes consistent with an effector cell phenotype, whereas donor-origin T cells appeared quiescent, expressing oxidative phosphorylation genes. Finally, both donor and recipient T cell clones within the rejecting kidney suggested lymphoid aggregation. The results indicate that donor-origin macrophages and T cells have distinct transcriptional profiles compared with their recipient counterparts, and that donor macrophages can persist for years post-transplantation.ConclusionsAnalysis of single nucleotide variants and their expression in single cells provides a powerful novel approach to accurately define leukocyte chimerism in a complex organ such as a transplanted kidney, coupled with the ability to examine transcriptional profiles at single-cell resolution.PodcastThis article contains a podcast at https://www.asn-online.org/media/podcast/JASN/2020_08_07_JASN2020030326.mp3


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A885-A885
Author(s):  
Pravesh Gupta ◽  
Dapeng Hao ◽  
Krishna Bojja Bojja ◽  
Tuan Tran ◽  
Minghao Dang ◽  
...  

BackgroundGliomas are recalcitrant tumors of the central nervous system. The tumor immune microenvironment (TIME) in gliomas is considered immunosuppressive and making it difficult to treat these tumors with conventional immunotherapy approaches, therefore a better characterization of the immune cell repertoire is needed to fully understand the tumor immune contexture. While single-cell RNA-sequencing (scRNA-seq) approaches have revealed the transcriptional heterogeneity, the gene regulatory landscape at the chromatin level is quintessential for a deeper understanding of lineage and signal-dependent transcription factors (TFs) induced in the brain TIME.MethodsWe performed single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on ~90,000 tumor-associated and sorted CD45+ leukocytes from fourteen genomically classified patients comprising IDH-mutant primary (IMP; n=4), IDH-mutant recurrent (IMR; n=3), IDH-wild type primary (IWP; n=3), or IDH-wild type recurrent (IWR; n=4) gliomas (hereafter referred as glioma subtypes) and two non-glioma brains (NGBs) as controls. The resulting data were quality checked and processed using Cell Ranger ATAC-seq pipeline and trajectory analyses were performed using Monocle2.ResultsUsing scRNA-seq data from matched specimens and gene tagging approaches, we identified twenty-six clusters of myeloid and seventeen clusters of lymphoid populations across and within gliomas. In this study, we exclusively focused on myeloid subpopulations, which were resolved into microglia and non-microglia myeloid cell subsets. Concordant with our scRNA-seq data, we identified all cell types including monocytes, monocyte-derived cells (MDCs), and dendritic cells by using differential gene accessibility (DGE) analyses. Importantly, although MG from all samples clustered differently, NGB and IM subtypes exhibited concordance in DGE and were separate from IWP and IWR subtypes. Reconstruction of the cell trajectories demonstrated that enhancers for TFs related to mesenchymal transition in GBM such as NF-kB and CEBPB were accessible from normal to tumor-associated microglia. On the other hand, tissue-associated macrophages exhibited enhanced calcium-regulated NFAT TF accessibility. Tumor-associated IWP and IWR myeloid cells also showed a gain of DGE of apoptosis and a reduction of proliferation-related genes.ConclusionsOur studies demonstrate that in addition to the previous dogma of myeloid mediated immune suppression that contributes to tumor immune escape, epigenomic reprogramming in the brain TIME leads to unexpected activation of transcriptional pathways that can trigger transdifferentiation and cell death of myeloid cells further promoting tumor progression. In summary, we provide an unparalleled epigenomic landscape of glioma-associated myeloid cells that may have translational implications.AcknowledgementsThis study in Krishna Bhat’s laboratory was supported by the generous philanthropic contributions to The University of Texas (UT) MD Anderson Cancer Center (MDACC) Moon Shots Program™, Marnie Rose Foundation, NIH grants: R21 CA222992 and R01CA225963. This study was partly supported by the UT MDACC start-up research fund to Linghua Wang and CPRIT Single-Core grant RP180684 to Nicholas Navin.Trial RegistrationNAEthics ApprovalThe brain tumor/tissue samples were collected as per MD Anderson internal review board (IRB)-approved protocol numbers LAB03-0687 and, LAB04-0001. One non-tumor brain tissue sample was collected from a patient undergoing neurosurgery for epilepsy as per Baylor College of Medicine IRB-approved protocol number H-13798. All experiments were compliant with the review board of MD Anderson Cancer Center, USA.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 40-41
Author(s):  
Jovian Yu ◽  
Xiufen Chen ◽  
James Godfrey ◽  
Girish Venkataraman ◽  
Sonali M. Smith ◽  
...  

Introduction: Classical Hodgkin lymphoma (cHL) is characterized by a robust and complex immune cell infiltrate and the rare presence of malignant Hodgkin-Reed-Sternberg (HRS) cells. At the genetic level, HRS cells recurrently acquire alterations that lead to defective antigen presentation (β2 microglobulin mutations) and mediate T cell dysfunction (PD-L1 copy gains/amplifications) in order to subvert host immune surveillance. The clinical relevance of PD-L1 protein over-expression in cHL is clear, as response rates to PD-1 blockade therapy are extremely high among patients with relapsed/refractory (r/r) disease. Despite its remarkable efficacy, the cells that mediate response to anti-PD-1 therapy in cHL remain undefined. Recent analyses have highlighted a possible role for CD4+ T cells in mediating the clinical activity of anti-PD-1 therapy in cHL. CD4+ T cells significantly outnumber CD8+ T cells in cHL lesions and are more frequently juxtaposed to HRS cells in situ. Furthermore, HLA class II expression on HRS cells predicted higher complete response rates to PD-1 blockade therapy in r/r cHL patients. However, a candidate T cell population capable of specific reactivity to antigens expressed by HRS cells has yet to be identified. This information is critical as such T cells might be functionally reinvigorated to mediate HRS cell elimination following PD-1 blockade therapy. In order to address this key knowledge gap, we analyzed data at single cell (sc) resolution using paired RNA and T cell receptor (TCR) sequencing in 9 diagnostic cHL and 5 reactive lymph node (RLN) specimens. Methods: Sequencing was performed using the 10x Genomics Chromium Single Cell 5' Gene Expression and V(D)J workflows. B-cell depletion of each sample was achieved using CD19 microbeads and negative selection to enrich T cell populations. Reads were analyzed and aligned with CellRanger (v3.1.0) and Seurat (v3.2.0) was used to conduct clustering by a shared nearest neighbor (SNN) graph on scRNA data. TCR sequencing data was integrated using scRepertoire (v1.0.0). Results: A detailed map of the immune cell states in cHL was created using scRNA-seq (10X) data on 79,085 cells from 9 cHL (52,602 cells) and 5 RLN samples (26,484 cells) expressing a total of 21,421 genes (mean 5649 cells/sample; mean 2849 mRNA reads/cell). Dimensionality reduction and unsupervised graph-based clustering revealed 21 distinct cell type and activation state clusters, including T cells, NK cells, macrophages, and dendritic cells (Fig 1A-B). A cluster identifying HRS cells was not observed, consistent with a recently published report. Ten T cell clusters were identified (47,573 cells), including naive- and memory-like T cells, effector/cytotoxic CD8+ T cells, regulatory T cells, and T follicular helper cells. Unexpectedly, a putative exhausted T cell cluster was not clearly observed. The relative contributions of cHL and RLNs cases to these clusters are shown in Fig 1C. Paired TCR sequencing was available for 23,943 cells. Overall TCR diversity was lower among cHL samples compared to RLN specimens (Fig 1D). In cHL samples, modest clonal expansion within regulatory T cell and memory CD4+ T cell clusters was observed, but the most striking clonal expansion occurred among cells assigned to effector/cytotoxic CD8+ T cell clusters - a finding not observed in most RLN specimens (Fig 1E). Clonally-expanded effector/cytotoxic CD8+ T cells displayed high expression of granzymes (GZMA, GZMH, GZMK), cytokines (TNF, IFNG) and chemokines (CCL4/CCL5), and modest expression of exhaustion markers (PDCD1, ENTPD1, HAVCR2, ITGAE), contrasting with data from single-cell analyses of solid tumors. Clonal expansion of effector/cytotoxic CD8+ T cells was particularly robust in EBV-positive cHLs, likely due to recognition of viral-derived epitopes displayed on HRS cells (Fig 1F). Phenotypic and functional validation of key immune cell clusters in cHL specimens using spectral cytometry is underway and will be reported at the meeting. Conclusions: For the first time, our data have unveiled the nature of the T cell repertoire in cHL at single cell resolution. Our results reveal a recurrent pattern of clonal expansion within effector CD8+ cells, which may be the HRS antigen-specific T cells that mediate response to PD-1 blockade. This hypothesis requires confirmation through similar analyses of pre- and on-treatment biopsies of cHL patients receiving anti-PD-1 therapy. Disclosures Godfrey: Gilead: Research Funding; Merck: Research Funding; Verastem: Research Funding. Venkataraman:EUSA Pharma: Speakers Bureau. Smith:Janssen: Consultancy; BMS: Consultancy; TG Therapeutics: Consultancy, Research Funding; Genentech/Roche: Consultancy, Other: Support of parent study and funding of editorial support, Research Funding; Karyopharm: Consultancy, Research Funding; FortySeven: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding. Kline:Kite/Gilead: Speakers Bureau; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees, Research Funding.


2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii39-ii39
Author(s):  
Oleg Yegorov ◽  
Changlin Yang ◽  
Anjelika Dechkovskaia ◽  
Maryam Rahman ◽  
Ashley Ghiaseddin ◽  
...  

Abstract BACKGROUND The application of single cell sequencing as a novel immune monitoring platform can be used to identify the molecular mechanisms of immune response to dendritic cell- based vaccines, trace the cell types and states involved, and uncover novel biomarkers for immunotherapy. We applied single-cell RNA Seq analysis of longitudinal peripheral blood mononuclear cells (PBMCs) in patients with newly-diagnosed GBM enrolled on the ATTAC II clinical trial (FDA IND BB-16530; Clinicaltrials.gov # NCT02465268) who experienced a sustained radiographic response to autologous CMV pp65-LAMP RNA-pulsed DC vaccines plus GM-CSF and tetanus-diphtheria booster administered during adjuvant cycles of dose-intensified temozolomide. METHODS We constructed 5’ gene expression libraries and T cell receptor enriched libraries for 10x Genomics single-cell 5’ and VDJ sequencing, generated from PBMCs collected prior to and during patient immunization using dendritic cells loaded with messenger ribonucleic acid encoding the human cytomegalovirus (CMV) matrix protein pp65 conjugated with the lysosomal associated membrane protein (LAMP) sequence. RESULTS Overall, we sequenced a total of 189,808 single-cell transcriptomes from 5 patients. We leveraged these transcriptome-wide features to distinguish 15 peripheral immune cell subtypes in tested PBMCs. Analysis revealed dynamic changes in immune cell subsets over the course of first three vaccines, including increases in cytotoxic CD8 T cells, CD4 T cells, and NK cell subsets. Increased markers of T cell activation were observed during vaccination. Surprisingly, we observed a very high-level frequency of natural killer T (NKT) cells in the patient with a complete durable response compared to other patients. After three DC vaccines, the level of NKT cells in PBMC of this patient increased up to 10%. CONCLUSIONS These results emphasize the importance of subset specific profiling to achieve higher resolution in monitoring immune responses compared with bulk expression profiling in patients receiving immunotherapeutic treatment.


2021 ◽  
Vol 12 ◽  
Author(s):  
Qixia Shen ◽  
Yucheng Wang ◽  
Jiaoyi Chen ◽  
Lifeng Ma ◽  
Xiaoru Huang ◽  
...  

Allograft rejection is a common immunological feature in renal transplantation and is associated with reduced graft survival. A mouse renal allograft rejection model was induced and single-cell RNA sequencing (scRNA-seq) data of CD45+ leukocytes in kidney allografts on days 7 (D7) and 15 (D15) after operation was analyzed to reveal a full immunological profiling. We identified 20 immune cell types among 10,921 leukocytes. Macrophages and CD8+ T cells constituted the main populations on both timepoints. In the process from acute rejection (AR) towards chronic rejection (CR), the proportion of proliferating and naïve CD8+ T cells dropped significantly. Both B cells and neutrophils decreased by about 3 folds. On the contrary, the proportion of macrophages and dendritic cells (DCs) increased significantly, especially by about a 4.5-fold increase in Ly6cloMrc1+ macrophages and 2.6 folds increase in Ly6cloEar2+ macrophages. Moreover, myeloid cells harbored the richest ligand and receptor (LR) pairs with other cells, particularly for chemokine ligands such as Cxcl9, Cxcl10, Cxcl16 and Yars. However, macrophages with weak response to interferon gamma (IFNg) contributed to rejection chronicization. To conclude, reduction in CD8 T cells, B cells and neutrophils while increasing in Ly6cloMrc1+ macrophages and Ly6cloEar2+ macrophages, may contribute significantly to the progress from AR towards CR.


2021 ◽  
Author(s):  
He-zuo Lü ◽  
Xin-Yi Lyu ◽  
Jing-Lu Li ◽  
Shu-Qin Ding ◽  
Jian-Guo Hu

Abstract Background The myeloid cells play a vital role in health and disease of central nervous system (CNS). However, how to clearly distinguish them is still a knotty problem. At present, single-cell RNA Sequencing (scRNA-Seq) technology can sequence thousands of cells at the single-cell level, and then divide the cells into different clusters according to the similarity of gene expression, but it is still difficult to further identity these cell clusters. Generally, there are some specific marker genes for cell-type identities. However, it is difficult to distinguish a variety of myeloid cells in the CNS, because these cells often have the same or cross gene markers, and some markers will change significantly in different pathological states. Therefore, establishing a simple and practical method to distinguish these cell populations is of great significance for the analysis of scRNA-Seq data. Methods Referring to CellMarker (http://biocc.hrbmu.edu.cn/CellMarker/), PanglaoDB (https://panglaodb.se/) and Mouse Cell Atlas (http://bis.zju.edu.cn/MCA/gallery.html), combining with the recent literatures, a simple Excel template was designed, in which a panel of gene makers corresponding to the myeloid cells were included. The 83 cell clusters from several recently reported single-cell data were used to verify the accuracy of this template. Results This template could easily distinguish myeloid cell-subtypes and non-myeloid cells. Comparing with literatures, the overall consistency rate was 93.98%. There was no statistically significant difference between the two groups (Bowker’s test, P >0.05). Kappa symmetric measures showed that the Kappa value = 0.642 (P < 0.01). Conclusions The cell identities of scRNA-Seq cluster data could be performed using our simple Excel formulae, a panel of gene markers and ideal cell clustering data are the basis for accurate identification of CNS myeloid cell-subtypes.


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