TMIC-60. COMPREHENSIVE SPATIAL CHARACTERIZATION OF IMMUNE CELLS IN THE CNS BRAIN TUMOR MICROENVIRONMENT

Abstract Previous immune profiling in brain tumors has mostly focused on the high-density tumor areas, and as such, little is known about the nature and types of immunological responses that occur across the tumor landscape, including at the tumor-central nervous system (CNS) interface. En bloc resections of glioblastomas (n=10) and CNS lung metastases (n=10) were oriented on slides as whole mount wedges spanning three anatomical areas including the invasive edge, tumor region, and necrotic core. Tumor segmentation was performed and regional differences were immunologically analyzed for 770 immune genes using the NanoString nCounter System with CIBERSORT analysis to delineate immune gene signatures. The analysis was validated using multiplex immunohistochemistry (IHC). The top upregulated immune genes in the GBM necrotic core were associated with macrophages, including the CD163 lineage marker, chemotactic factors (such as CCL18 and SAA1), and the phagocytosis stimulatory factors (such as IL-8 and MARCO). The necrotic core downregulates GBM antigens (such as IL13RA2 and MAGEB2), markers of dendritic cells (such as LILRA4), and immune stimulatory processes including MHC, IFN, IL-12, TNF, and ICOS expression. In direct contrast, the infiltrating edge of the GBM relative to the tumor is enriched with stimulators for NK cytotoxicity (i.e., CD244, the fractalkine receptor for immune cells), chemokines for thymocytes and dendritic cells, and immune stimulatory IL-12 receptors. Glioblastoma has rare focal isolated areas of CD3 T-cell reactivity within the tumor. Similar to GBM, the necrotic center of lung metastases is enriched in immune suppressive macrophages, as reflected by CD163 IHC staining and arginase expression; however, they are more frequently infiltrated with M1 macrophages. Yet the majority of lung cancers are more diffusely infiltrated with CD3 T cells, especially at the infiltrating edge. In general, we noted distinct inter- and intratumoral immune gene signatures, with macrophages dominating the brain tumors, especially the necrotic core.

Download Full-text

Identification the prognostic value of immune gene signature and infiltrating immune cells of esophageal cancer patients

10.21203/rs.3.rs-20941/v1 ◽

2020 ◽

Author(s):

Lin Wang ◽

Qian Wei ◽

Ming Zhang ◽

Lianze Chen ◽

Zinan Li ◽

...

Keyword(s):

T Cells ◽

Esophageal Cancer ◽

Signaling Pathway ◽

Immune Cells ◽

Roc Curves ◽

Survival Outcome ◽

Immune Gene ◽

Prognostic Signature ◽

Immune Genes ◽

Validation Set

Abstract Background Esophageal cancer (ESCA) is one of the deadliest solid malignancies with worse survival in the world. The poor prognosis of ESCA is not only related to malignant cells, but also affected by the microenvironment. We aimed to establish prognostic signature consisting of immune genes to predict the survival outcome of patients and estimate the prognosis value of infiltrating immune cells in tumor microenvironment (TME). Methods Based on integrated analysis of gene expression profiling and immune gene database, differentially immune-related genes were filtered out. Then, stepwise Cox regression analysis was applied to identify survival related immune genes and construct prognosis signature. Functional enrichment analysis was performed to explore biology function. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were performed to validate the predictive effect of predictive signature. We also verified the clinical value of prognostic signature under the influence of different clinical parameters. For deeper analysis, we evaluated the correlation between prognosis signature and infiltrating immune cells by Tumor Immune Estimation Resource (TIMER) and CIBERSORT. Results Finally, we identified 303 differentially immune genes as candidate and constructed immune prognosis signature composed of six immune genes. Furthermore, we observed that the prognosis signature was enriched in cytokine-mediated signaling pathway, lymphocyte activation, immune effector process, cancer pathway, NF-kappa B signaling pathway. K-M survival curves showed that the prognosis signature indeed have good predictive ability in entire ESCA set ( P =0.003), validation set 1 ( P =0.008) and validation set 2 ( P =0.036). The area under the curve (AUC) of ROC curves validated the predictive accuracy of immune signature in three cohorts (AUC=0.757, 0.800 and 0.701), respectively. In addition, we identified the prognosis value of infiltrating-immune cells including activated memory CD4 T cells, T cells follicular helper cells and monocytes and provided a landscape of TME. Conclusions The results indicated that immune prognosis signature can be a novel biomarker to predict survival outcome, which can provide new targets for immunotherapy and individualized therapies in ESCA and open up a new prospect for improving the prognosis of ESCA patients in the era of immunotherapy.

Download Full-text

Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405616666210104111218 ◽

2021 ◽

Vol 16 ◽

Author(s):

Ghazanfar Latif ◽

Jaafar Alghazo ◽

Fadi N. Sibai ◽

D.N.F. Awang Iskandar ◽

Adil H. Khan

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Brain Mri ◽

Tumor Segmentation ◽

Brain Anatomy ◽

Mri Segmentation ◽

Brain Tumor Segmentation ◽

Brain Images ◽

Low Contrast ◽

Fuzzy C Means

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

Download Full-text

Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽

10.1186/s12885-021-08041-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lin Chen ◽

Yuxiang Dong ◽

Yitong Pan ◽

Yuhan Zhang ◽

Ping Liu ◽

...

Keyword(s):

Breast Cancer ◽

Regression Analysis ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

Risk Scores ◽

Validation Dataset ◽

Immune Gene ◽

Cox Regression Analysis ◽

Immune Genes ◽

Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

Download Full-text

IMMU-45. CUSTOMIZED LIPID NANOPARTICLES DELIVER NUCLEIC ACIDS TO IMMUNE CELLS IN BRAIN TUMORS

Neuro-Oncology ◽

10.1093/neuonc/noaa215.475 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii114-ii114

Author(s):

Adam Grippin ◽

Brandon Wummer ◽

Hector Mendez-Gomez ◽

Tyler Wildes ◽

Kyle Dyson ◽

...

Keyword(s):

Brain Tumors ◽

Nucleic Acids ◽

Immune Cells ◽

White Blood Cells ◽

Lipid Nanoparticles ◽

Intracranial Tumor ◽

Innate Immune ◽

Checkpoint Blockade ◽

Normal Brain ◽

Innate Immune Cells

Abstract BACKGROUND Brain tumors are notoriously difficult to treat in part due to their isolation behind the blood brain barrier and their power to suppress antitumor immune responses. We have previously reported cationic liposome formulations capable of delivering immune modulatory nucleic acids to immune cells in various peripheral organs, but there is currently no reliable method to deliver nucleic acids into brain tumors without direct injection into the tumor site. OBJECTIVE Here, we report the development of a customized lipid nanoparticle to deliver immune modulatory nucleic acids to immune cells in brain tumors. APPROACH Cationic liposomes composed of varying lipid combinations were evaluated for their ability to deliver functional mRNA and siRNA to innate immune cells in vitro and in intracranial tumor models. Nucleic acids were labelled with Cy3 to monitor particle distribution in vivo. RESULTS Lipids composed of DOTAP and cholesterol selectively delivered mRNA and siRNA to intracranial GL261 and KR158b tumors. Interestingly, these particles selectively delivered these nucleic acids to CD45+ white blood cells with minimal delivery to CD45- tumor cells or normal brain tissue. Encapsulation of siRNA blocking programmed death ligand 1 (PDL1) significantly reduced PDL1 expression on innate immune cells in brain tumors, with the greatest effects on tumor-associated macrophages. Co-administration of systemic checkpoint blockade with intravenous administration of these lipid nanoparticles bearing PDL1 siRNA enabled systemic and intratumoral checkpoint blockade, leading to 37% long term survivorship in an otherwise fatal intracranial tumor model. CONCLUSIONS Our customized lipid nanoparticles enable potent intratumoral immune modulation via delivery of nucleic acids to immune cells in brain tumors.

Download Full-text

Cell subtypes and immune dysfunction in peritoneal fluid of endometriosis revealed by single-cell RNA-sequencing

Cell & Bioscience ◽

10.1186/s13578-021-00613-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gen Zou ◽

Jianzhang Wang ◽

Xinxin Xu ◽

Ping Xu ◽

Libo Zhu ◽

...

Keyword(s):

Dendritic Cells ◽

Single Cell ◽

Natural Killer ◽

Rna Sequencing ◽

Peritoneal Cavity ◽

Immune Cells ◽

Peritoneal Fluid ◽

Control Sample ◽

Immune Dysfunction ◽

Single Cell Rna Sequencing

Abstract Background Endometriosis is a refractory and recurrent disease and it affects nearly 10% of reproductive-aged women and 40% of infertile patients. The commonly accepted theory for endometriosis is retrograde menstruation where endometrial tissues invade into peritoneal cavity and fail to be cleared due to immune dysfunction. Therefore, the comprehensive understanding of immunologic microenvironment of peritoneal cavity deserves further investigation for the previous studies mainly focus on one or several immune cells. Results High-quality transcriptomes were from peritoneal fluid samples of patients with endometriosis and control, and firstly subjected to 10 × genomics single-cell RNA-sequencing. We acquired the single-cell transcriptomes of 10,280 cells from endometriosis sample and 7250 cells from control sample with an average of approximately 63,000 reads per cell. A comprehensive map of overall cells in peritoneal fluid was first exhibited. We unveiled the heterogeneity of immune cells and discovered new cell subtypes including T cell receptor positive (TCR+) macrophages, proliferating macrophages and natural killer dendritic cells in peritoneal fluid, which was further verified by double immunofluorescence staining and flow cytometry. Pseudo-time analysis showed that the response of macrophages to the menstrual debris might follow the certain differentiation trajectory after endometrial tissues invaded into the peritoneal cavity, that is, from antigen presentation to pro-inflammation, then to chemotaxis and phagocytosis. Our analyses also mirrored the dysfunctions of immune cells including decreased phagocytosis and cytotoxic activity and elevated pro-inflammatory and chemotactic effects in endometriosis. Conclusion TCR+ macrophages, proliferating macrophages and natural killer dendritic cells are firstly reported in human peritoneal fluid. Our results also revealed that immune dysfunction happens in peritoneal fluid of endometriosis, which may be responsible for the residues of invaded menstrual debris. It provided a large-scale and high-dimensional characterization of peritoneal microenvironment and offered a useful resource for future development of immunotherapy.

Download Full-text

Mesenchymal stem cells induce mature dendritic cells into a novel Jagged-2–dependent regulatory dendritic cell population

Blood ◽

10.1182/blood-2008-04-154138 ◽

2009 ◽

Vol 113 (1) ◽

pp. 46-57 ◽

Cited By ~ 199

Author(s):

Bin Zhang ◽

Rui Liu ◽

Dan Shi ◽

Xingxia Liu ◽

Yuan Chen ◽

...

Keyword(s):

Stem Cells ◽

Mesenchymal Stem Cells ◽

Dendritic Cells ◽

Immune Cells ◽

Cell Contact ◽

Multilineage Differentiation ◽

Immunomodulatory Effects ◽

Cd11b Expression ◽

Dendritic Cell Population

Abstract Mesenchymal stem cells (MSCs), in addition to their multilineage differentiation, exert immunomodulatory effects on immune cells, even dendritic cells (DCs). However, whether they influence the destiny of full mature DCs (maDCs) remains controversial. Here we report that MSCs vigorously promote proliferation of maDCs, significantly reduce their expression of Ia, CD11c, CD80, CD86, and CD40 while increasing CD11b expression. Interestingly, though these phenotypes clearly suggest their skew to immature status, bacterial lipopolysaccharide (LPS) stimulation could not reverse this trend. Moreover, high endocytosic capacity, low immunogenicity, and strong immunoregulatory function of MSC-treated maDCs (MSC-DCs) were also observed. Furthermore we found that MSCs, partly via cell-cell contact, drive maDCs to differentiate into a novel Jagged-2–dependent regulatory DC population and escape their apoptotic fate. These results further support the role of MSCs in preventing rejection in organ transplantation and treatment of autoimmune disease.

Download Full-text

IBRDM: An Intelligent Framework for Brain Tumor Classification Using Radiomics- and DWT-based Fusion of MRI Sequences

ACM Transactions on Internet Technology ◽

10.1145/3434775 ◽

2022 ◽

Vol 22 (1) ◽

pp. 1-30

Author(s):

Rahul Kumar ◽

Ankur Gupta ◽

Harkirat Singh Arora ◽

Balasubramanian Raman

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Performance Metrics ◽

Tumor Classification ◽

Training Dataset ◽

Tumor Segmentation ◽

Discrete Wavelet ◽

Low Grade ◽

Brain Tumor Segmentation ◽

Mri Sequences

Brain tumors are one of the critical malignant neurological cancers with the highest number of deaths and injuries worldwide. They are categorized into two major classes, high-grade glioma (HGG) and low-grade glioma (LGG), with HGG being more aggressive and malignant, whereas LGG tumors are less aggressive, but if left untreated, they get converted to HGG. Thus, the classification of brain tumors into the corresponding grade is a crucial task, especially for making decisions related to treatment. Motivated by the importance of such critical threats to humans, we propose a novel framework for brain tumor classification using discrete wavelet transform-based fusion of MRI sequences and Radiomics feature extraction. We utilized the Brain Tumor Segmentation 2018 challenge training dataset for the performance evaluation of our approach, and we extract features from three regions of interest derived using a combination of several tumor regions. We used wrapper method-based feature selection techniques for selecting a significant set of features and utilize various machine learning classifiers, Random Forest, Decision Tree, and Extra Randomized Tree for training the model. For proper validation of our approach, we adopt the five-fold cross-validation technique. We achieved state-of-the-art performance considering several performance metrics, 〈 Acc , Sens , Spec , F1-score , MCC , AUC 〉 ≡ 〈 98.60%, 99.05%, 97.33%, 99.05%, 96.42%, 98.19% 〉, where Acc , Sens , Spec , F1-score , MCC , and AUC represents the accuracy, sensitivity, specificity, F1-score, Matthews correlation coefficient, and area-under-the-curve, respectively. We believe our proposed approach will play a crucial role in the planning of clinical treatment and guidelines before surgery.

Download Full-text

Recent insights into the implications of metabolism in plasmacytoid dendritic cell innate functions: Potential ways to control these functions

F1000Research ◽

10.12688/f1000research.11332.1 ◽

2017 ◽

Vol 6 ◽

pp. 456 ◽

Cited By ~ 9

Author(s):

Philippe Saas ◽

Alexis Varin ◽

Sylvain Perruche ◽

Adam Ceroi

Keyword(s):

Dendritic Cells ◽

Lipid Metabolism ◽

Nuclear Receptors ◽

Immune Cells ◽

Transforming Growth Factor ◽

Plasmacytoid Dendritic Cell ◽

Innate Immune ◽

Type I ◽

Innate Immune Cells ◽

Immune Functions

There are more and more data concerning the role of cellular metabolism in innate immune cells, such as macrophages or conventional dendritic cells. However, few data are available currently concerning plasmacytoid dendritic cells (PDC), another type of innate immune cells. These cells are the main type I interferon (IFN) producing cells, but they also secrete other pro-inflammatory cytokines (e.g., tumor necrosis factor or interleukin [IL]-6) or immunomodulatory factors (e.g., IL-10 or transforming growth factor-β). Through these functions, PDC participate in antimicrobial responses or maintenance of immune tolerance, and have been implicated in the pathophysiology of several autoimmune diseases. Recent data support the idea that the glycolytic pathway (or glycolysis), as well as lipid metabolism (including both cholesterol and fatty acid metabolism) may impact some innate immune functions of PDC or may be involved in these functions after Toll-like receptor (TLR) 7/9 triggering. Some differences may be related to the origin of PDC (human versus mouse PDC or blood-sorted versus FLT3 ligand stimulated-bone marrow-sorted PDC). The kinetics of glycolysis may differ between human and murine PDC. In mouse PDC, metabolism changes promoted by TLR7/9 activation may depend on an autocrine/paracrine loop, implicating type I IFN and its receptor IFNAR, explaining a delayed glycolysis. Moreover, PDC functions can be modulated by the metabolism of cholesterol and fatty acids. This may occur via the production of lipid ligands that activate nuclear receptors (e.g., liver X receptor [LXR]) in PDC or through limiting intracellular cholesterol pool size (by statins or LXR agonists) in these cells. Finally, lipid-activated nuclear receptors (i.e., LXR or peroxisome proliferator activated receptor) may also directly interact with pro-inflammatory transcription factors, such as NF-κB. Here, we discuss how glycolysis and lipid metabolism may modulate PDC functions and how this may be harnessed in pathological situations where PDC play a detrimental role.

Download Full-text

The Differential Anti-HIV Effect of a New Humic Substance-Derived Preparation in Diverse Cells of the Immune System

Acta Naturae ◽

10.32607/20758251-2019-11-2-68-76 ◽

2019 ◽

Vol 11 (2) ◽

pp. 68-76

Author(s):

G. V. Kornilaeva ◽

A. E. Siniavin ◽

A. Schultz ◽

A. Germann ◽

C. Moog ◽

...

Keyword(s):

Dendritic Cells ◽

T Lymphocytes ◽

Humic Substance ◽

Immune Cells ◽

Cell Types ◽

Inhibitory Effect ◽

Infection Inhibition ◽

Toxic Concentrations ◽

Anti Hiv ◽

Hiv 1

The anti-HIV activity of a new humic substance-derived preparation has been studied in individual pools of immune cells (CD4+ T lymphocytes, macrophages, dendritic cells). Near-complete inhibition of the HIV infection (by more than 90%) was achieved by treating each of the abovementioned cell types with non-toxic concentrations of the preparation. The inhibitory effect demonstrates the possibility of preventing the depletion of a significant portion of functionally important immune cells. A comparative study of infection inhibition in individual cell pools has allowed us to reveal the differences in the preparations effectiveness in each of the cell populations. A R5-tropic HIV-1 infection in macrophages exhibited maximum sensitivity to the preparation: 90% and 50% inhibition of the infection were observed in the presence of concentrations as low as 1.4 and 0.35 g/ml, respectively. A 15- and 19-fold higher concentration was required to achieve the same extent of inhibition in dendritic cells infected with the same strain. The effectiveness of the drug in CD4 + T lymphocytes is quite comparable to its effectiveness in macrophages. The drug is universally effective for both the T- and M-tropic variants of HIV-1.

Download Full-text

ILDR1 Is a Prognostic Biomarker and Associated With Immune Inﬁltration in Gastric Cancer

10.21203/rs.3.rs-944596/v1 ◽

2021 ◽

Author(s):

Yanling Ma ◽

WenBo Qi ◽

BaoHong Gu ◽

XueMei Li ◽

ZhenYu Yin ◽

...

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Dendritic Cells ◽

Cancer Patients ◽

Cd8 T Cells ◽

Immune Cells ◽

Copy Number ◽

Sequencing Data ◽

Number Variation ◽

Gastric Cancer Patients

Abstract Objective: To investigate the association between ILDR1 and prognosis and immune infiltration in gastric cancer. Methods: We analyzed the RNA sequencing data of 9736 tumor tissues and 8587 normal tissues in the TCGA and GTEx databases through the GEPIA2 platform. The expression of ILDR1 in gastric cancer and normal gastric mucosa tissues with GEPIA and TIMER. Clinical subgroup analysis was made through Kaplan-Meier analysis. Analyzed the correlation between ILDR1 and VEGFA expression in gastric cancer, through the gene sequencing data of gastric cancer in TCGA. Explored the relationship between ILDR1 methylation and the prognosis of gastric cancer patients through the MethSurv database. The correlation between ILDR1 and immune cells and the correlation of copy number variation were explored through the TIMER database. Results: ILDR1-high GC patients had a lower PFS and OS. High ILDR1 expression was significantly correlated with tumor grade. There was a negative correlation between the ILDR1 expression and the abundances of CD8+ T, Macrophages and DC and etc. The methylation level of ILDR1 is associated with a good prognosis of gastric cancer. ILDR1 copy number variation was correlated with immune cells, IDLR1 arm-loss was associated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells, and arm-duplication was associated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells. Conclusion: The increased expression of ILDR1 is associated with poor prognosis in patients with gastric cancer. ILDR1 can be used as a novel predictive biomarker to provide a new therapeutic target for gastric cancer patients.

Download Full-text