scholarly journals The Immune Cell Landscape in Different Anatomical Structures of Knee in Osteoarthritis: A Gene Expression-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Ziming Chen ◽  
Yuanchen Ma ◽  
Xuerui Li ◽  
Zhantao Deng ◽  
Minghao Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dendritic Cells ◽  
Mast Cells ◽  
Subchondral Bone ◽  
Immune Cells ◽  
Immune Cell ◽  
M2 Macrophages ◽  
Anatomical Structures ◽  
Normal Tissues ◽  
Immunological Mechanisms

Background. Immunological mechanisms play a vital role in the pathogenesis of knee osteoarthritis (KOA). Moreover, the immune phenotype is a relevant prognostic factor in various immune-related diseases. In this study, we used CIBERSORT for deconvolution of global gene expression data to define the immune cell landscape of different structures of knee in osteoarthritis. Methods and Findings. By applying CIBERSORT, we assessed the relative proportions of immune cells in 76 samples of knee cartilage, 146 samples of knee synovial tissue, 40 samples of meniscus, and 50 samples of knee subchondral bone. Enumeration and activation status of 22 immune cell subtypes were provided by the obtained immune cell profiles. In synovial tissues, the differences in proportions of plasma cells, M1 macrophages, M2 macrophages, activated dendritic cells, resting mast cells, and eosinophils between normal tissues and osteoarthritic tissues were statistically significant (P<0.05). The area under the curve was relatively large in resting mast cells, dendritic cells, and M2 macrophages in receiver operating characteristic analyses. In subchondral bones, the differences in proportions of resting master cells and neutrophils between normal tissues and osteoarthritic tissues were statistically significant (P<0.05). In subchondral bones, the proportions of immune cells, from the principle component analyses, displayed distinct group-bias clustering. Resting mast cells and T cell CD8 were the major component of first component. Moreover, we revealed the potential interaction between immune cells. There was almost no infiltration of immune cells in the meniscus and cartilage of the knee joint. Conclusions. The immune cell composition in KOA differed substantially from that of healthy joint tissue, while it also differed in different anatomical structures of the knee. Meanwhile, activated mast cells were mainly associated with high immune cell infiltration in OA. Furthermore, we speculate M2 macrophages in synovium and mast cells in subchondral bone may play an important role in the pathogenesis of OA.

scholarly journals GJA1 Expression and Its Prognostic Value in Cervical Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Silu Meng ◽  
Xinran Fan ◽  
Jianwei Zhang ◽  
Ran An ◽  
Shuang Li
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Logistic Regression ◽  
Gap Junction ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Immune Cell ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Chi Squared

Gap Junction Protein Alpha 1 (GJA1) belongs to the gap junction family and has been widely studied in cancers. We evaluated the role of GJA1 in cervical cancer (CC) using public data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. The difference of GJA1 expression level between CC and normal tissues was analyzed by the Gene Expression Profiling Interactive Analysis (GEPIA), six GEO datasets, and the Human Protein Atlas (HPA). The relationship between clinicopathological features and GJA1 expression was analyzed by the chi-squared test and the logistic regression. Kaplan–Meier survival analysis and Cox proportional hazard regression analysis were used to assessing the effect of GJA1 expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways regulated by GJA1. Immune Cell Abundance Identifier (ImmuCellAI) was chosen to analyze the immune cells affected by GJA1. The expression of GJA1 in CC was significantly lower than that in normal tissues based on the GEPIA, GEO datasets, and HPA. Both the chi-squared test and the logistic regression showed that high-GJA1 expression was significantly correlated with keratinization, hormone use, tumor size, and FIGO stage. The Kaplan–Meier curves suggested that high-GJA1 expression could indicate poor prognosis ( p = 0.0058 ). Multivariate analysis showed that high-GJA1 expression was an independent predictor of poor overall survival (HR, 4.084; 95% CI, 1.354-12.320; p = 0.013 ). GSEA showed many cancer-related pathways, such as the p53 signaling pathway and the Wnt signaling pathway, were enriched in the high-GJA1-expression group. Immune cell abundance analysis revealed that the abundance of CD8 naive, DC, and neutrophil was significantly increased in the high-GJA1-expression group. In conclusion, GJA1 can be regarded as a potential prognostic marker of poor survival and therapeutic target in CC. Moreover, many cancer-related pathways may be the critical pathways regulated by GJA1. Furthermore, GJA1 can affect the abundance of immune cells.

scholarly journals Innate Immune Cells in Pressure Overload-Induced Cardiac Hypertrophy and Remodeling

2021 ◽  
Vol 9 ◽  
Author(s):  
Xin Liu ◽  
Guo-Ping Shi ◽  
Junli Guo
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Mast Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Pressure Overload ◽  
Natural Killer T Cells ◽  
Innate Immune ◽  
Innate Immune Cells ◽  
Killer T Cells

Pressure overload and heart failure are among the leading causes of cardiovascular morbidity and mortality. Accumulating evidence suggests that inflammatory cell activation and release of inflammatory mediators are of vital importance during the pathogenesis of these cardiac diseases. Yet, the roles of innate immune cells and subsequent inflammatory events in these processes remain poorly understood. Here, we outline the possible underlying mechanisms of innate immune cell participation, including mast cells, macrophages, monocytes, neutrophils, dendritic cells, eosinophils, and natural killer T cells in these pathological processes. Although these cells accumulate in the atrium or ventricles at different time points after pressure overload, their cardioprotective or cardiodestructive activities differ from each other. Among them, mast cells, neutrophils, and dendritic cells exert detrimental function in experimental models, whereas eosinophils and natural killer T cells display cardioprotective activities. Depending on their subsets, macrophages and monocytes may exacerbate cardiodysfunction or negatively regulate cardiac hypertrophy and remodeling. Pressure overload stimulates the secretion of cytokines, chemokines, and growth factors from innate immune cells and even resident cardiomyocytes that together assist innate immune cell infiltration into injured heart. These infiltrates are involved in pro-hypertrophic events and cardiac fibroblast activation. Immune regulation of cardiac innate immune cells becomes a promising therapeutic approach in experimental cardiac disease treatment, highlighting the significance of their clinical evaluation in humans.

scholarly journals Multiomic analysis of the function of SPOCK1 across cancers: an integrated bioinformatics approach

2021 ◽  
Vol 49 (6) ◽  
pp. 030006052096265
Author(s):  
Jie Han ◽  
Yihui Rong ◽  
Xudong Gao
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Immune Cells ◽  
Immune Cell ◽  
Cancer Cell Line ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Normal Tissues

Objective To investigate SPARC (osteonectin), cwcv and kazal like domains proteoglycan 1 ( SPOCK1) gene expression across The Cancer Genome Atlas (TCGA) cancers, both in cancer versus normal tissues and in different stages across the cancer types. Methods This integrated bioinformatics study used data from several bioinformatics databases (Cancer Cell Line Encyclopedia, Genotype-Tissue Expression, TCGA, Tumor Immune Estimation Resource [TIMER]) to define the expression pattern of the SPOCK1 gene. A survival analysis was undertaken across the cancers. The search tool for retrieval of interacting genes (STRING) database was used to identify proteins that interacted with SPOCK1. Gene Set Enrichment Analysis was conducted to determine pathway enrichment. The TIMER database was used to explore the correlation between SPOCK1 and immune cell infiltration. Results This multiomic analysis showed that the SPOCK1 gene was expressed differently between normal tissues and tumours in several cancers and that it was involved in cancer progression. The overexpression of the SPOCK1 gene was associated with poor clinical outcomes. Analysis of gene expression and tumour-infiltrating immune cells showed that SPOCK1 correlated with several immune cells across cancers. Conclusions This research showed that SPOCK1 might serve as a new target for several cancer therapies in the future.

scholarly journals Elucidating the immune infiltration in acne and its comparison with rosacea by integrated bioinformatics analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248650
Author(s):  
Lu Yang ◽  
Yan-Hong Shou ◽  
Yong-Sheng Yang ◽  
Jin-Hua Xu
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Mast Cells ◽  
Immune Cells ◽  
Plasma Cells ◽  
Immune Cell ◽  
Healthy Individuals ◽  
Lesional Skin ◽  
Immune Infiltration ◽  
Acne Rosacea

Background Acne vulgaris and rosacea are common inflammatory complications of the skin, both characterized by abnormal infiltration of immune cells. The two diseases can be differentiated based on characteristic profile of the immune cell infiltrates at the periphery of disease lesions. In addition, dysregulated infiltration of immune cells not only occur in the acne lesions but also in non-lesional areas of patients with the disease, thus characterizing the immune infiltration in these sites can further enhance our understanding on the pathogenesis of acne. Methods Five microarray data-sets (GSE108110, GSE53795, GSE65914, GSE14905 and GSE78097) were downloaded from Gene Expression Omnibus. After removing the batch effects and normalizing the data, we applied the CIBERSORT algorithm combined with signature matrix LM22, to describe 22 types of immune cells’ infiltration in acne less than 48 hour (H) old, in comparation with non-lesional skin of acne patients, healthy skin and rosacea (including erythematotelangiectatic rosacea, papulopustular rosacea and phymatous rosacea) and we compared gene expression of Th1 and Th17-related molecules in acne, rosacea and healthy control. Results Compared with the non-lesional skin of acne patients, healthy individuals and rosacea patients, there is a significant increase in infiltration of neutrophils, monocytes and activated mast cells around the acne lesions, less than 48 H after their development. Contrarily, few naive CD4+ T cells, plasma cells, memory B cells and resting mast cells infiltrate acne sites compared to the aforementioned groups of individuals. Moreover, the infiltration of Regulatory T cells (Tregs) in acne lesions is substantially lower, relative to non-lesional sites of acne patients and skin of healthy individuals. In addition, non-lesional sites of acne patients exhibit lower infiltration of activated memory CD4+ T cells, plasma cells, memory B cells, M0 macrophages, neutrophils, resting mast cells but higher infiltration of Tregs and resting dendritic cells relative to skin of healthy individuals. Intriguingly, we found that among the 3 rosacea subtypes, the immune infiltration profile of papulopustular rosacea is the closest to that of acne lesions. In addition, through gene expression analysis of acne, rosacea and skin tissues of healthy individuals, we found a higher infiltration of Th1 and Th17 cells in acne lesions, relative to non-lesional skin areas of acne patients. Conclusions Our study provides new insights into the inflammatory pathogenesis of acne, and the difference between acne and rosacea, which helps in differentiating the two diseases. Our findings also guide on appropriate target therapy of the immune cell infiltrates in the two disease conditions.

scholarly journals Patterns of Immune Infiltration in Endometriosis and Their Relationship to r-AFS Stages

2021 ◽  
Vol 12 ◽  
Author(s):  
Qiyu Zhong ◽  
Fan Yang ◽  
Xiaochuan Chen ◽  
Jinbo Li ◽  
Cailing Zhong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cells ◽  
Plasma Cells ◽  
Immune Cell ◽  
M2 Macrophages ◽  
Expression Data ◽  
Gene Expression Microarray Data ◽  
And Function ◽  
Ovarian Endometriomas ◽  
Activation Status

Background: Endometriosis (EMS) is an estrogen-dependent disease in which endometrial glands and stroma arise outside the uterus. Current studies have suggested that the number and function of immune cells are abnormal in the abdominal fluid and ectopic lesion tissues of patients with EMS. The developed CIBERSORT method allows immune cell profiling by the deconvolution of gene expression microarray data.Methods: By applying CIBERSORT, we assessed the relative proportions of immune cells in 68 normal endometrial tissues (NO), 112 eutopic endometrial tissues (EU) and 24 ectopic endometrial tissues (EC). The obtained immune cell profiles provided enumeration and activation status of 22 immune cell subtypes. We obtained associations between the immune cell environment and EMS r-AFS stages. Macrophages were evaluated by immunohistochemistry (IHC) in 60 patients with ovarian endometriomas.Results: Total natural killer (NK) cells were significantly decreased in EC, while plasma cells and resting CD4 memory T cells were increased in EC. Total macrophages in EC were significantly increased compared to those of EU and NO, and M2 macrophages were the primary macrophages in EC. Compared to those of EC from patients with r-AFS stage I ~ II, M2 macrophages in EC from patients with stage III ~ IV were significantly increased. IHC experiments showed that total macrophages were increased in EC, with M2 macrophages being the primary subtype.Conclusions: Our data demonstrate that deconvolution of gene expression data by CIBERSORT provides valuable information about immune cell composition in EMS.

scholarly journals Using Tumor-Infiltrating Immune Cells and a ceRNA Network Model to Construct a Prognostic Analysis Model of Thyroid Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Fan Zhang ◽  
Xiaohui Yu ◽  
Zheyu Lin ◽  
Xichang Wang ◽  
Tiantian Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dendritic Cells ◽  
Thyroid Carcinoma ◽  
Gene Expression Profiling ◽  
Immune Cells ◽  
Expression Profiling ◽  
Immune Cell ◽  
Critical Role ◽  
The Cancer Genome Atlas ◽  
Cerna Network

Thyroid carcinoma is a solid malignant tumor that has had a fast-growing incidence in recent years. Our research used thyroid carcinoma gene expression profiling from TCGA (The Cancer Genome Atlas) database to identify differentially expressed ceRNAs. Using the gene expression profiling from 502 carcinoma thyroid tissues and 58 normal thyroid tissues from the TCGA database, we established the thyroid carcinoma-specific competitive endogenous RNA (ceRNA) network and found nine overall survival (OS)-associated genes (PRDM1, TGFBR3, E2F1, FGF1, ADAM12, ALPL, RET, AL928654.2, AC128688.2). We quantified the proportions of immune cells using the algorithm “CIBERSORT”, found three OS-associated immune cells (memory B cells, M0 macrophages, and activated dendritic cells), and established a thyroid carcinoma-specific immune cell network based on that. The good reliabilities AUC (area under the curve) of 10-year survival (0.955, 0.944, respectively) were accessed from the nomograms of genes and immune cells. Subsequently, by conducting co-expression analyses, we found a potential regulation network among ceRNAs and immune cells. Besides, we found that ALPL (alkaline phosphatase) and hsa-miR-204-5p were significantly correlated and that ALPL was related to activated dendritic cells. We took advantage of multi-dimensional databases to verify our discovery. Besides, immunohistochemistry (IHC) assays were conducted to detect the expression of a dendritic cell marker (CD11c) and ALPL in thyroid carcinoma (TC) and paracancerous tissues. In summary, our study found a potential mechanism in which hsa-miR-204-5p regulated ALPL in activated dendritic cells, which may allow them to play a critical role in thyroid carcinoma. These findings provide potential prognostic biomarkers and therapeutic targets for thyroid carcinoma.

scholarly journals The Toolbox for Untangling Chromosome Architecture in Immune Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuai Liu ◽  
Keji Zhao
Keyword(s):  
Gene Expression ◽  
Immune Cells ◽  
Spatial Organization ◽  
Chromosome Structure ◽  
Immune Cell ◽  
Genome Structure ◽  
Chromosome Architecture ◽  
The Past ◽  
Important Player ◽  
The Way

The code of life is not only encrypted in the sequence of DNA but also in the way it is organized into chromosomes. Chromosome architecture is gradually being recognized as an important player in regulating cell activities (e.g., controlling spatiotemporal gene expression). In the past decade, the toolbox for elucidating genome structure has been expanding, providing an opportunity to explore this under charted territory. In this review, we will introduce the recent advancements in approaches for mapping spatial organization of the genome, emphasizing applications of these techniques to immune cells, and trying to bridge chromosome structure with immune cell activities.

scholarly journals Updates on Immunotherapy and Immune Landscape in Renal Clear Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5856
Author(s):  
Myung-Chul Kim ◽  
Zeng Jin ◽  
Ryan Kolb ◽  
Nicholas Borcherding ◽  
Jonathan Alexander Chatzkel ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Single Cell Analysis ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Cellular Mechanisms ◽  
T Cell Infiltration ◽  
Immunological Mechanisms

Several clinicopathological features of clear cell renal cell carcinomas (ccRCC) contribute to make an “atypical” cancer, including resistance to chemotherapy, sensitivity to anti-angiogenesis therapy and ICIs despite a low mutational burden, and CD8+ T cell infiltration being the predictor for poor prognosis–normally CD8+ T cell infiltration is a good prognostic factor in cancer patients. These “atypical” features have brought researchers to investigate the molecular and immunological mechanisms that lead to the increased T cell infiltrates despite relatively low molecular burdens, as well as to decipher the immune landscape that leads to better response to ICIs. In the present study, we summarize the past and ongoing pivotal clinical trials of immunotherapies for ccRCC, emphasizing the potential molecular and cellular mechanisms that lead to the success or failure of ICI therapy. Single-cell analysis of ccRCC has provided a more thorough and detailed understanding of the tumor immune microenvironment and has facilitated the discovery of molecular biomarkers from the tumor-infiltrating immune cells. We herein will focus on the discussion of some major immune cells, including T cells and tumor-associated macrophages (TAM) in ccRCC. We will further provide some perspectives of using molecular and cellular biomarkers derived from these immune cell types to potentially improve the response rate to ICIs in ccRCC patients.

scholarly journals CXC Chemokines as Therapeutic Targets and Prognostic Biomarkers in Skin Cutaneous Melanoma Microenvironment

2021 ◽  
Vol 11 ◽  
Author(s):  
Xuezhi Zhou ◽  
Manjuan Peng ◽  
Ye He ◽  
Jingjie Peng ◽  
Xuan Zhang ◽  
...  
Keyword(s):  
Immune Cells ◽  
Cutaneous Melanoma ◽  
Immune Cell ◽  
Gene Activation ◽  
Skin Tumor ◽  
Pathological Stage ◽  
Normal Tissues ◽  
The World ◽  
Cxc Chemokine ◽  
The Relationship

BackgroundSkin Cutaneous Melanoma (SKCM) is a tumor of the epidermal melanocytes induced by gene activation or mutation. It is the result of the interaction between genetic, constitutional, and environmental factors. SKCM is highly aggressive and is the most threatening skin tumor. The incidence of the disease is increasing year by year, and it is the main cause of death in skin tumors around the world. CXC chemokines in the tumor microenvironment can regulate the transport of immune cells and the activity of tumor cells, thus playing an anti-tumor immunological role and affecting the prognosis of patients. However, the expression level of CXC chemokine in SKCM and its effect on prognosis are still unclear.MethodOncomine, UALCAN, GEPIA, STRING, GeneMANIA, cBioPortal, TIMER, TRRUST, DAVID 6.8, and Metascape were applied in our research.ResultThe transcription of CXCL1, CXCL5, CXCL8, CXCL9, CXCL10, and CXCL13 in SKCM tissues were significantly higher than those in normal tissues. The pathological stage of SKCM patients is closely related to the expression of CXCL4, CXCL9, CXCL10, CXCL11, CXCL12, and CXCL13. The prognosis of SKCM patients with low transcription levels of CXCL4, CXCL9, CXCL10, CXCL11, and CXCL13 is better. The differential expression of CXC chemokines is mainly associated with inflammatory response, immune response, and cytokine mediated signaling pathways. Our data indicate that the key transcription factors of CXC chemokines are RELA, NF-κB1 and SP1. The targets of CXC chemokines are mainly LCK, LYN, SYK, MAPK2, MAPK12, and ART. The relationship between CXC chemokine expression and immune cell infiltration in SKCM was closed.ConclusionsOur research provides a basis for screening SKCM biomarkers, predicting prognosis, and choosing immunotherapy.

scholarly journals Immune Cell Landscape in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yang Yang ◽  
Wei He ◽  
Zi-rui Wang ◽  
Yu-jiao Wang ◽  
Lan-lan Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
B Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Univariate Analysis ◽  
Molecular Therapy ◽  
Expression Level ◽  
Regulatory Factors ◽  
Normal Tissues ◽  
The Relationship

Background. The tumor-infiltrating immune cells are closely associated with the prognosis of gastric cancer (GC). This article is aimed at determining the composition change of immune cells and immune regulatory factors in GC and normal tissues, depicting their prognosis value in GC, and revealing the relationship between them and GC clinical parameters. Methods. We used CIBERSORT to calculate the proportion of 22 immune cells in the GC or normal tissues; a t -test was applied to assess the expression difference of immune cells and immune regulatory factors in normal and GC tissues. The relationship of the immune cells, immune regulatory factors, and GC patients’ clinical characteristics was assessed by univariate analysis. Results. In this study, we found that the proportion of macrophages increased, while plasma cells and monocytes decreased in GC tissues. In these immune fractions, Tregs and naïve B cells were found to be correlated with GC patients’ prognosis. Interestingly, the expression of immune regulatory factors was ambiguous with their classical function in GC tissues. For example, TIM-3, FOXP3, and CMTM6 were overexpressed, while CD27 and PD-1 were underexpressed in GC tissues. We also found that IDO1, PD-1, TIGIT, and TIM-3 were highly expressed in high-grade GC tissues, the HERC2 expression level was related to patients’ gender, and the TIGIT expression level was sensitive to targeted therapy. Furthermore, our results suggested that the infiltration of Tregs and naive B cells was strongly correlated with the T stage, radiation therapy, targeted molecular therapy, and the expression levels of TIM-3 and FOXP3 in GC. Conclusion. The expression pattern of tumor-infiltrating immune cells and immune regulatory factors was systematically depicted in the GC tumor microenvironment, indicating that individualized treatment based on the tumor-infiltrating immune cells and immune regulatory factors may be beneficial to GC patients.

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