scholarly journals Whole Blood Transcriptome Analysis Reveals the Correlation between Specific Immune Cells and Septicemic Melioidosis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ke Xu ◽  
Dahua Xu ◽  
Hua Pei ◽  
Yunfan Quan ◽  
Jun Liu ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Expression Patterns ◽  
Multivariate Logistic Regression Analysis ◽  
Cell Types ◽  
Host Immune System ◽  
Resting Cells

Melioidosis is a serious infectious disease caused by the environmental Gram-negative bacillus Burkholderia pseudomallei. It has been shown that the host immune system, mainly comprising various types of immune cells, fights against the disease. The present study was to specify correlation between septicemic melioidosis and the levels of multiple immune cells. First, the genes with differential expression patterns between patients with septicemic melioidosis (B. pseudomallei) and health donors (control/healthy) were identified. These genes being related to cytokine binding, cell adhesion molecule binding, and MHC relevant proteins may influence immune response. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed 23 enriched immune response pathways. We further leveraged the microarray data to investigate the relationship between immune response and septicemic melioidosis, using the CIBERSORT analysis. Comparison of the percentages of 22 immune cell types in B. pseudomallei vs. control/healthy revealed that those of CD4 memory resting cells, CD8+ T cells, B memory cells, and CD4 memory activated cells were low, whereas those of M0 macrophages, neutrophils, and gamma delta T cells were high. The multivariate logistic regression analysis further revealed that CD8+ T cells, M0 macrophages, neutrophils, and naive CD4+ cells were strongly associated with the onset of septicemic melioidosis, and M2 macrophages and neutrophils were associated with the survival in septicemic melioidosis. Taken together, these data point to a complex role of immune cells on the development and progression of melioidosis.

scholarly journals Single-Cell Profiling of Kidney Transplant Recipients With Immunosuppressive Treatment Reveals the Dynamic Immune Characteristics

2021 ◽  
Vol 12 ◽  
Author(s):  
Yongguang Liu ◽  
Xiaoyou Liu ◽  
Song Zhou ◽  
Ruiquan Xu ◽  
Jianmin Hu ◽  
...  
Keyword(s):  
T Cells ◽  
Kidney Transplantation ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Peripheral Blood ◽  
Cd4 T Cells ◽  
Immune Cell ◽  
Immunosuppressive Agents ◽  
Cell Types ◽  
Before And After

Kidney transplantation is currently the first choice of treatment for various types of end-stage renal failure, but there are major limitations in the application of immunosuppressive protocols after kidney transplantation. When the dose of immunosuppressant is too low, graft rejection occurs easily, while a dose that is too high can lead to graft loss. Therefore, it is very important to explore the immune status of patients receiving immunosuppressive agents after kidney transplantation. To compare the immune status of the recipient’s whole peripheral blood before and after receipt of immunosuppressive agents, we used single-cell cytometry by time-of-flight (CyTOF) to detect the peripheral blood immune cells in five kidney transplant recipients (KTRs) from the Department of Organ Transplantation of Zhujiang Hospital of Southern Medical University before and after receiving immunosuppressive agents. Based on CyTOF analysis, we detected 363,342 live single immune cells. We found that the immune cell types of the KTRs before and after receipt of immunosuppressive agents were mainly divided into CD4+ T cells, CD8+ T cells, B cells, NK cells/γδ T cells, monocytes/macrophages, granulocytes, and dendritic cells (DCs). After further reclustering of the above cell types, it was found that the immune cell subclusters in the peripheral blood of patients underwent major changes after receipt of immunosuppressants. After receiving immunosuppressive therapy, the peripheral blood of KTRs had significantly increased levels of CD57+NK cells and significantly decreased levels of central memory CD4+ T cells, follicular helper CD4+ T cells, effector CD8+ T cells, effector memory CD8+ T cells and naive CD8+ T cells. This study used CyTOF to classify immune cells in the peripheral blood of KTRs before and after immunosuppressive treatment, further compared differences in the proportions of the main immune cell types and immune cell subgroups before and after receipt of immunosuppressants, and provided relatively accurate information for assessment and treatment strategies for KTRs.

scholarly journals Systemic Immune Response in Murine Bilateral Pheochromocytoma Model During Immunotherapy Based on a Combination of Mannan-BAM, TLR Ligands and Anti-CD40 Antibodies (MBTA Therapy)

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A1032-A1033
Author(s):  
Ondrej Uher ◽  
Thanh-Truc Huynh ◽  
Boqun Zhu ◽  
Lucas A Horn ◽  
Rogelio Medina ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Immune Memory ◽  
Effector Memory ◽  
Memory Cells ◽  
Macrophage Phenotype ◽  
Adaptive Immune Cells

Abstract Immunotherapy has become an essential component of cancer treatment, however, a majority of patients with solid metastatic cancers, such as pheochromocytoma (PHEO), do not respond to this type of therapy. Recently, we developed an intratumoral (i.t.) immunotherapy based on the unique combination of TLR ligands, anti-CD40 antibodies, and mannan, which is artificially bound to tumor cells via an anchor (MBTA therapy). This therapy resulted in the complete eradication of aggressive subcutaneous PHEO in 67% of mice and demonstrated a systemic antitumor immune response and regression of non-treated lesions in the metastatic model (1). To further evaluate this systemic effect generated during MBTA therapy, we established a murine bilateral PHEO model, where MBTA therapy was i.t. injected into one tumor, and the distant (non-treated) tumor was monitored for changes in size and immune cell infiltration. The growth of both MBTA-treated and distant tumors was reduced compared to that of the control. Interestingly, survival of the MBTA-treated mice was twice as long compared to the control mice. Moreover, we have made several unique observations during the experiments which were focused on the tumor microenvironment. Flow cytometry analysis revealed the ability of MBTA therapy to significantly increase the infiltration of innate immune cells (monocytes, DCs, macrophages, NK cells) not only in MBTA-treated tumors, but also in distal tumors, despite the fact that MBTA therapy was designed to elicit only local inflammation. An analysis of the macrophage phenotype revealed a switch from protumor M2 to antitumor M1 macrophages in both tumors during the entire MBTA therapy treatment. Analysis of splenic adaptive immune cells revealed that naïve CD4+ or CD8+ T cells differentiated into central memory cells and effector memory cells. CD4+ and CD8+ T cells were elevated in MBTA-treated and distant tumors with a significantly higher frequency of CD8+ effector memory T cells. Moreover, the adoptive transfer of CD4+ and CD8+ T cells revealed that immune memory, after tumor rechallenging, was driven by CD4+ T cells. Collectively, these results illustrate the ability of MBTA therapy to activate both parts of the immune system and render a systemic antitumor response against non-treated metastases. We believe that our results could lead to the use of MBTA therapy in patients with aggressive, metastatic lesions. Reference: Caisova et al., Cancers (Basel), 2019. 11(5).

scholarly journals TAMI-07. THE IMMUNE MICROENVIRONMENT IN LOWER GRADE GLIOMAS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii214-ii214
Author(s):  
Anupam Kumar ◽  
Katharine Chen ◽  
Claudia Petritsch ◽  
Theodore Nicolaides ◽  
Mariarita Santi-Vicini ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Cd8 T Cells ◽  
Molecular Mechanisms ◽  
T Regulatory Cells ◽  
Immune Cell ◽  
T Cell Response ◽  
Cytotoxic T Cell ◽  
Lower Grade ◽  
Functional Relationships

Abstract The determinants of the tumor-associated immune response in brain tumors are poorly understood. Using tumor samples from two molecularly distinct subtypes of lower grade glioma, MAPK-driven glioma with biallelic inactivation of CDKN2A (n=30) and IDH-mutant, 1p/19q-intact astrocytoma (n=29), we demonstrate qualitative and quantitative differences in the tumor-associated immune response and we investigate the molecular mechanisms involved. Histologically the MAPK-driven gliomas were comprised of pleomorphic xanthoastrocytoma (PXA) (n=11) and anaplastic PXA (n=19). Seven patients had paired samples from two sequential surgeries. Immune cell populations and their activity were determined by quantitative multiplex immunostaining and Digital Spatial Profiling and gene expression was analyzed by Nanostring. Functional studies were performed using established cell lines and two new patient-derived lines from MAPK-driven LGGs. MAPK-driven tumors exhibited an increased number of CD8+ T cells and tumor-associated microglial/macrophage (TAMs), including CD163+ TAMs, as compared to IDH-mutant astrocytoma. In contrast, IDH-mutant tumors had increased FOXP3+ immunosuppressive T regulatory cells. Transcriptional and protein level analyses in MAPK-driven tumors suggested an active cytotoxic T cell response with robust expression of granzyme B, present on 27% of CD8+ T cells, increased MHC class I expression, and altered cytokine profiles. Interestingly, MAPK-driven tumors also had increased expression of immunosuppressive molecules, including CXCR4, PD-L1, and VEGFA. Expression differences for cell surface and secreted proteins were confirmed in patient-derived tumor lines and functional relationships between altered chemokine expression and immune cell infiltration was investigated. Our data provide novel insights into the immune contexture of MAPK driven LGGs and suggest MAPK driven gliomas with biallelic inactivation of CDKN2A may be particularly vulnerable to immunotherapeutic modulation

Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 32-33
Author(s):  
Tomohiro Aoki ◽  
Lauren C. Chong ◽  
Katsuyoshi Takata ◽  
Katy Milne ◽  
Elizabeth Chavez ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Expression Patterns ◽  
The Other ◽  
Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

scholarly journals Identification of immune-based prostate cancer subtypes using mRNA expression

2020 ◽  
Author(s):  
Jukun Song ◽  
Song He ◽  
Wei Wang ◽  
Jiaming Su ◽  
Dongbo Yuan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Immune Response ◽  
Immune Cells ◽  
Immune Cell ◽  
Molecular Classification ◽  
Cell Types ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Cell Subpopulation ◽  
Immune Cell Infiltration

Abstract Background Immune infiltration of Prostate cancer (PCa) was highly related to clinical outcomes. However, previous works failed to elucidate the diversity of different immune cell types that make up the function of the immune response system. The aim of the study was to uncover the composition of TIICs in PCa utilizing the CIBERSORT algorithm and further reveal the molecular characteristics of PCa subtypes. Method In the present work, we employed the CIBERSORT method to evaluate the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We analyzed the correlation between immune cell infiltration and clinical information. The tumor-infiltrating immune cells of the TCGA PCa cohort were analyzed for the first time. The fractions of 22 immune cell types were imputed to determine the correlation between each immune cell subpopulation and clinical feature. Three types of molecular classification were identified via R-package of “CancerSubtypes”. The functional enrichment was analyzed in each subtype. The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen chemotherapeutic targets for the potential treatment of PCa. Results In current work, we utilized the CIBERSORT algorithm to assess the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We investigated the correlation between immune cell infiltration and clinical data. The tumor-infiltrating immune cells in the TCGA PCa cohort were analyzed. The 22 immune cells were also calculated to determine the correlation between each immune cell subpopulation and survival and response to chemotherapy. Three types of molecular classification were identified. Each subtype has specific molecular and clinical characteristics. Meanwhile, Cluster I is defined as advanced PCa, and is more likely to respond to immunotherapy. Conclusions Our results demonstrated that differences in immune response may be important drivers of PCa progression and response to treatment. The deconvolution algorithm of gene expression microarray data by CIBERSOFT provides useful information about the immune cell composition of PCa patients. In addition, we have found a subtype of immunopositive PCa subtype and will help to explore the reasons for the poor effect of PCa on immunotherapy, and it is expected that immunotherapy will be used to guide the individualized management and treatment of PCa patients.

scholarly journals Early Response of CD8+ T Cells in COVID-19 Patients

2021 ◽  
Vol 11 (12) ◽  
pp. 1291
Author(s):  
Deni Ramljak ◽  
Martina Vukoja ◽  
Marina Curlin ◽  
Katarina Vukojevic ◽  
Maja Barbaric ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Mrna Expression ◽  
Cd8 T Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Effector Memory ◽  
Healthy Controls ◽  
Ifn Γ

Healthy and controlled immune response in COVID-19 is crucial for mild forms of the disease. Although CD8+ T cells play important role in this response, there is still a lack of studies showing the gene expression profiles in those cells at the beginning of the disease as potential predictors of more severe forms after the first week. We investigated a proportion of different subpopulations of CD8+ T cells and their gene expression patterns for cytotoxic proteins (perforin-1 (PRF1), granulysin (GNLY), granzyme B (GZMB), granzyme A (GZMA), granzyme K (GZMK)), cytokine interferon-γ (IFN-γ), and apoptotic protein Fas ligand (FASL) in CD8+ T cells from peripheral blood in first weeks of SARS-CoV-2 infection. Sixteen COVID-19 patients and nine healthy controls were included. The absolute counts of total lymphocytes (p = 0.007), CD3+ (p = 0.05), and CD8+ T cells (p = 0.01) in COVID-19 patients were significantly decreased compared to healthy controls. In COVID-19 patients in CD8+ T cell compartment, we observed lower frequency effector memory 1 (EM1) (p = 0.06) and effector memory 4 (EM4) (p < 0.001) CD8+ T cells. Higher mRNA expression of PRF1 (p = 0.05) and lower mRNA expression of FASL (p = 0.05) at the fifth day of the disease were found in COVID-19 patients compared to healthy controls. mRNA expression of PRF1 (p < 0.001) and IFN-γ (p < 0.001) was significantly downregulated in the first week of disease in COVID-19 patients who progressed to moderate and severe forms after the first week, compared to patients with mild symptoms during the entire disease course. GZMK (p < 0.01) and FASL (p < 0.01) mRNA expression was downregulated in all COVID-19 patients compared to healthy controls. Our results can lead to a better understanding of the inappropriate immune response of CD8+ T cells in SARS-CoV2 with the faster progression of the disease.

scholarly journals Analysis of the Intratumoral Adaptive Immune Response in Well Differentiated and Dedifferentiated Retroperitoneal Liposarcoma

Sarcoma ◽  
2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
William W. Tseng ◽  
Shruti Malu ◽  
Minying Zhang ◽  
Jieqing Chen ◽  
Geok Choo Sim ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Cd8 T Cells ◽  
Immune Checkpoint ◽  
Cd4 T Cells ◽  
Immune Cell ◽  
Adaptive Immune Response ◽  
Adaptive Immune ◽  
Retroperitoneal Liposarcoma ◽  
Well Differentiated

Treatment options are limited in well differentiated (WD) and dedifferentiated (DD) retroperitoneal liposarcoma. We sought to study the intratumoral adaptive immune response and explore the potential feasibility of immunotherapy in this disease. Tumor-infiltrating lymphocytes (TILs) were isolated from fresh surgical specimens and analyzed by flow cytometry for surface marker expression. Previously reported immune cell aggregates known as tertiary lymphoid structures (TLS) were further characterized by immunohistochemistry. In all fresh tumors, TILs were found. The majority of TILs were CD4 T cells; however cytotoxic CD8 T cells were also seen (average: 20% of CD3 T cells). Among CD8 T cells, 65% expressed the immune checkpoint molecule PD-1. Intratumoral TLS may be sites of antigen presentation as DC-LAMP positive, mature dendritic cells were found juxtaposed next to CD4 T cells. Clinicopathologic correlation, however, demonstrated that presence of TLS was associated with worse recurrence-free survival in WD disease and worse overall survival in DD disease. Our data suggest that an adaptive immune response is present in WD/DD retroperitoneal liposarcoma but may be hindered by TLS, among other possible microenvironmental factors; further investigation is needed. Immunotherapy, including immune checkpoint blockade, should be evaluated as a treatment option in this disease.

scholarly journals Landscape of glioblastoma niches reveals the prognostic effects of tumor-infiltrating cells

2021 ◽  
Author(s):  
Zixuan Xiao ◽  
Wei Zhang ◽  
Guanzhang Li ◽  
Wendong Li ◽  
Lin Li ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Tumor Cell ◽  
Cd8 T Cells ◽  
Plasma Cells ◽  
Cell Types ◽  
Enrichment Score ◽  
Large Gene ◽  
Mesenchymal Differentiation ◽  
Positive Immune Response

AbstractA comprehensive characterization of non-tumor cells in the niches of primary glioblastoma is not fully established yet. This study aims to present an overview of tumor-infiltrating non-malignant cells in the complex microenvironment of glioblastoma with detailed characterizations of their prognostic effects. We curate 540 gene signatures covering a total of 64 non-tumor cell types. Cell type-specific expression patterns are interrogated by normalized enrichment score (NES) across four large gene expression profiling cohorts of glioblastoma with a total number of 967 cases. The GBMs in each cohort are hierarchically clustered into negative or positive immune response classes with significantly different overall survival. Our results show that astrocytes, macrophages, monocytes, NKTs, preadipocytes, smooth muscle cells, and MSC are risk factors, while CD8 T cells, CD8+ T cells, and plasma cells are protective factors. Moreover, we find that the immune system and organogenesis are uniformly enriched in negative immune response clusters, in contrast to the enrichment of nervous system in positive immune response clusters. Mesenchymal differentiation is also observed in the negative immune response clusters. High enrichment status of macrophages in negative immune response clusters are independently validated by analyzing scRNA-seq data from eight high-grade gliomas, revealing that negative immune response samples comprised 46.63% to 55.12% of macrophages, whereas positive immune response samples comprised only 1.70% to 8.12%, with IHC staining of samples from six short-term and six long-term survivors of GBMs confirming the results.Simple SummaryThe landscape of infiltrating non-tumor cells in glioblastoma niches remains unclear. In this study, we explore the enrichment status of a total of 64 non-tumor cell types predicted by applying 540 gene signatures curated from literature and normalized enrichment score (NES) across four large gene expression profiling cohorts of glioblastoma with 967 cases. Based on non-tumor cell type-based enrichment status, GBMs in each cohort are classified into positive or negative immune response clusters, showing a statistically significant different overall survival. Astrocytes, macrophages, monocytes, NKTs, preadipocytes, smooth muscle cells, and MSC are identified as risk factors, as well as protector factors of CD8 T cells, CD8+ T cells, and plasma cells. Our results also find that immune system- and organogenesis-related GO terms are uniformly enriched in negative immune response clusters, whereas positive immune response clusters are enriched with GO terms concerning the nervous system. The mesenchymal differentiation is observed in the negative immune response clusters. Particularly, the high presence of macrophages in the negative immune response clusters is further validated using scRNA-seq analysis and IHC staining of GBMs from independent cohorts.

scholarly journals Crosstalk Between Tumor-Associated Microglia/Macrophages and CD8-Positive T Cells Plays a Key Role in Glioblastoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Sheng Tu ◽  
Xu Lin ◽  
Jili Qiu ◽  
Jiaqi Zhou ◽  
Hui Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Malignant Disease ◽  
Immune Therapy ◽  
Cell Types ◽  
Different Types ◽  
The Central Nervous System ◽  
And Function ◽  
The Relationship

Glioblastoma is considered to be the most malignant disease of the central nervous system, and it is often associated with poor survival. The immune microenvironment plays a key role in the development and treatment of glioblastoma. Among the different types of immune cells, tumor-associated microglia/macrophages (TAM/Ms) and CD8-positive (CD8+) T cells are the predominant immune cells, as well as the most active ones. Current studies have suggested that interaction between TAM/Ms and CD8+ T cells have numerous potential targets that will allow them to overcome malignancy in glioblastoma. In this review, we summarize the mechanism and function of TAM/Ms and CD8+ T cells involved in glioblastoma, as well as update on the relationship and crosstalk between these two cell types, to determine whether this association alters the immune status during glioblastoma development and affects optimal treatment. We focus on the molecular factors that are crucial to this interaction, and the role that this crosstalk plays in the biological processes underlying glioblastoma treatment, particularly with regard to immune therapy. We also discuss novel therapeutic targets that can aid in resolving reticular connections between TAM/Ms and CD8+ T cells, including depletion and reprogramming TAM/Ms and novel TAM/Ms-CD8+ T cell cofactors with potential translational usage. In addition, we highlight the challenges and discuss future perspectives of this crosstalk between TAM/Ms and CD8+ T cells.

scholarly journals Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data with ImmClassifier

2020 ◽  
Author(s):  
Xuan Liu ◽  
Sara J.C. Gosline ◽  
Lance T. Pflieger ◽  
Pierre Wallet ◽  
Archana Iyer ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Effector Memory ◽  
Immune Cell Population ◽  
Fine Grained ◽  
Knowledge Based ◽  
Comparable Performance

AbstractSingle-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.

Sign in / Sign up

Export Citation Format

Share Document