scholarly journals The Immune Cell Landscape in Renal Allografts

2021 ◽  
Vol 30 ◽  
pp. 096368972199545
Author(s):  
Jun Lu ◽  
Yi Zhang ◽  
Jingjing Sun ◽  
Shulin Huang ◽  
Weizhen Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Infiltration ◽  
M1 Macrophages ◽  
Deconvolution Analysis ◽  
Renal Allografts ◽  
Antibody Mediated Rejection

Immune cell infiltration plays an important role in the pathophysiology of kidney grafts, but the composition of immune cells is ill-defined. Here, we aimed at evaluating the levels and composition of infiltrating immune cells in kidney grafts. We used CIBERSORT, an established algorithm, to estimate the proportions of 22 immune cell types based on gene expression profiles. We found that non-rejecting kidney grafts were characteristic with high rates of M2 macrophages and resting mast cells. The proportion of M1 macrophages and activated NK cells were increased in antibody-mediated rejection (ABMR). In T cell-mediated rejection (TCMR), a significant increase in CD8 T cell and γδT cell infiltration was observed. CD8 positive T cells were dramatically increased in mixed-ABMR/TCMR. Then, the function of ABMR and TCMR prognostic molecular biomarkers were identified. Finally, we described the gene expression of molecular markers for ABMR diagnosis was elevated and related to the ratio of monocytes and M1 macrophages in ABMR biopsies, while the expression of TCMR diagnosis markers was increased too and positively correlated with γδT cells and activated CD4 memory T cells in TCMR biopsies. Our data suggest that CIBERSORT’s deconvolution analysis of gene expression data provides valuable information on the composition of immune cells in renal allografts.

scholarly journals Identifying Immune Cell Infiltration and Effective Diagnostic Biomarkers in Rheumatoid Arthritis by Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Sheng Zhou ◽  
Hongcheng Lu ◽  
Min Xiong
Keyword(s):  
Rheumatoid Arthritis ◽  
T Cells ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
M1 Macrophages ◽  
Tfh Cells

BackgroundRheumatoid arthritis (RA) is a chronic systemic autoimmune disorder characterized by inflammatory cell infiltration, leading to persistent synovitis and joint destruction. The pathogenesis of RA remains unclear. This study aims to explore the immune molecular mechanism of RA through bioinformatics analysis.MethodsFive microarray datasets and a high throughput sequencing dataset were downloaded. CIBERSORT algorithm was performed to evaluate immune cell infiltration in synovial tissues between RA and healthy control (HC). Wilcoxon test and Least Absolute Shrinkage and Selection Operator (LASSO) regression were conducted to identify the significantly different infiltrates of immune cells. Differentially expressed genes (DEGs) were screened by “Batch correction” and “RobustRankAggreg” methods. Functional correlation of DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Candidate biomarkers were identified by cytoHubba of Cytoscape, and their diagnostic effectiveness was predicted by Receiver Operator Characteristic Curve (ROC) analysis. The association of the identified biomarkers with infiltrating immune cells was explored using Spearman’s rank correlation analysis in R software.ResultsTen significantly different types of immune cells between RA and HC were identified. A total of 202 DEGs were obtained by intersection of DEGs screened by two methods. The function of DEGs were significantly associated with immune cells. Five hub genes (CXCR4, CCL5, CD8A, CD247, and GZMA) were screened by R package “UpSet”. CCL5+CXCR4 and GZMA+CD8A were verified to have the capability to diagnose RA and early RA with the most excellent specificity and sensitivity, respectively. The correlation between immune cells and biomarkers showed that CCL5 was positively correlated with M1 macrophages, CXCR4 was positively correlated with memory activated CD4+ T cells and follicular helper T (Tfh) cells, and GZMA was positively correlated with Tfh cells.ConclusionsCCL5, CXCR4, GZMA, and CD8A can be used as diagnostic biomarker for RA. GZMA-Tfh cells, CCL5-M1 macrophages, and CXCR4- memory activated CD4+ T cells/Tfh cells may participate in the occurrence and development of RA, especially GZMA-Tfh cells for the early pathogenesis of RA.

scholarly journals Enhanced CD4+ and CD8+ T cell infiltrate within convex hull defined pancreatic islet borders as autoimmune diabetes progresses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexander J. Dwyer ◽  
Jacob M. Ritz ◽  
Jason S. Mitchell ◽  
Tijana Martinov ◽  
Mohannad Alkhatib ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Convex Hull ◽  
Pancreatic Islets ◽  
Immune Cell ◽  
Nod Mice ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Analytical Strategy ◽  
Islet Mass

AbstractThe notion that T cell insulitis increases as type 1 diabetes (T1D) develops is unsurprising, however, the quantitative analysis of CD4+ and CD8+ T cells within the islet mass is complex and limited with standard approaches. Optical microscopy is an important and widely used method to evaluate immune cell infiltration into pancreatic islets of Langerhans for the study of disease progression or therapeutic efficacy in murine T1D. However, the accuracy of this approach is often limited by subjective and potentially biased qualitative assessment of immune cell subsets. In addition, attempts at quantitative measurements require significant time for manual analysis and often involve sophisticated and expensive imaging software. In this study, we developed and illustrate here a streamlined analytical strategy for the rapid, automated and unbiased investigation of islet area and immune cell infiltration within (insulitis) and around (peri-insulitis) pancreatic islets. To this end, we demonstrate swift and accurate detection of islet borders by modeling cross-sectional islet areas with convex polygons (convex hulls) surrounding islet-associated insulin-producing β cell and glucagon-producing α cell fluorescent signals. To accomplish this, we used a macro produced with the freeware software ImageJ equipped with the Fiji Is Just ImageJ (FIJI) image processing package. Our image analysis procedure allows for direct quantification and statistical determination of islet area and infiltration in a reproducible manner, with location-specific data that more accurately reflect islet areas as insulitis proceeds throughout T1D. Using this approach, we quantified the islet area infiltrated with CD4+ and CD8+ T cells allowing statistical comparison between different age groups of non-obese diabetic (NOD) mice progressing towards T1D. We found significantly more CD4+ and CD8+ T cells infiltrating the convex hull-defined islet mass of 13-week-old non-diabetic and 17-week-old diabetic NOD mice compared to 4-week-old NOD mice. We also determined a significant and measurable loss of islet mass in mice that developed T1D. This approach will be helpful for the location-dependent quantitative calculation of islet mass and cellular infiltration during T1D pathogenesis and can be combined with other markers of inflammation or activation in future studies.

Abstract 095: CD74 Deficient Mice are Resistant to Toll-Like Receptor-Induced Preeclampsia

Hypertension ◽  
2014 ◽  
Vol 64 (suppl_1) ◽  
Author(s):  
Mohamad Hatahet ◽  
Olga Y Gasheva ◽  
Valorie L Chiasson ◽  
Piyali Chatterjee ◽  
Kelsey R Bounds ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Endothelial Dysfunction ◽  
Mhc Class Ii ◽  
Immune Cells ◽  
Immune Cell ◽  
Class Ii ◽  
Poly I:C ◽  
Hypertensive Disorder ◽  
Toll Like Receptor

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder characterized by vascular endothelial dysfunction and excessive immunity and inflammation. Activation of the dsRNA receptor Toll-like receptor 3 (TLR3) or the ssRNA receptor TLR7 elicits a pregnancy-dependent PE-like syndrome in mice by inducing a pro-inflammatory immune response. CD74 (MHC Class II invariant chain) acts as a chaperone for MHC Class II surface expression on immune cells during antigen presentation and is cleaved into Class II-Associated Invariant Peptide (CLIP) following polyclonal activation of immune cell TLRs. The presence of CLIP in the groove of MHC Class II prevents T cell-dependent death leading to persistent immune cell activation. We hypothesized that genetic deletion of CD74 and subsequent depletion of CLIP on immune cells prevents TLR-induced immune responses and the development of PE in mice. Pregnant WT and CD74 KO mice were given i.p. injections of normal saline (P), poly I:C (TLR3 agonist; P-PIC), or R837 (TLR7 agonist; P-R837) on gestational days 13, 15, and 17 and euthanized on day 18. P-PIC and P-R837 WT mice had significantly increased splenic levels of pro-inflammatory CD3+/gd T cells and plasma levels of the gd T cell-derived cytokines IFNg, TNFa, and IL-17 compared to P WT mice whereas P-PIC and P-R837 CD74 KO mice had significantly increased anti-inflammatory CD3+/gd T cells and no significant increases in plasma IFNg, TNFa, and IL-17 levels. P-PIC and P-R837 CD74 KO mice did not develop the hypertension (gd17 SBP in mmHg: P WT=102±3, P CD74 KO=100±3, P-PIC WT=147±4*, P-PIC CD74 KO=95±3, P-R837 WT=133±2*, P-R837 CD74 KO=97±1; *p<0.05 vs. P WT), endothelial dysfunction, proteinuria, or placental necrosis seen in P-PIC and P-R837 WT mice. In conclusion, CD74 is crucial for the development of TLR-induced PE-like symptoms in mice and CD74/CLIP depletion may be a promising therapeutic target for women with PE.

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 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.

Immunohistochemical observation of local inflammatory cell infiltration in the host-tissue reaction site of human hydatid cysts

2018 ◽  
Vol 93 (3) ◽  
pp. 277-285 ◽  
Author(s):  
R. Jafari ◽  
B. Sanei ◽  
A. Baradaran ◽  
M. Kolahdouzan ◽  
B. Bagherpour ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Tissue Reaction ◽  
Distinct Pattern ◽  
Host Tissue ◽  
Cell Infiltration ◽  
Reaction Site ◽  
Hydatid Cysts ◽  
Ki 67

AbstractThe aim of this study was to evaluate the pattern of local immune cell infiltration in human cystic echinococcosis (CE) by identifying the subtypes of immune cells using immunohistochemistry (IHC). Fifty surgically removed hydatid cyst samples and surrounding tissues were collected from patients referred to Al-Zahra Hospital, Isfahan, Iran. IHC was performed on the surrounding host tissue of hydatid cysts using anti-human CD3, CD19, CD8, CD4, CD68, CD56, Ki-67 and Foxp3 (forkhead box P3) antibodies. The results were then compared to hepatocellular carcinoma and chronic hepatitis. In the host-tissue reaction site of liver hydatid cysts, a distinct pattern of local immune cell response, which outwardly consisted of a pack of the fibrous elements, a layer of palisading macrophages, an eosinophil-containing layer and a layer of accumulated lymphocytes, was observed. However, in some cases there were no positive cells for CD56+ natural killer cells and Foxp3+ regulatory T cells. The CD3+ T cells were the predominant inflammatory cells in all groups, followed by CD19+ B cells. It can be concluded that different immune cells are involved in the local response to human hydatid cysts.

scholarly journals Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Guohe Song ◽  
Yang Shi ◽  
Meiying Zhang ◽  
Shyamal Goswami ◽  
Saifullah Afridi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
T Cell Subsets ◽  
M2 Macrophage ◽  
Advanced Hcc ◽  
Immune Cell Subsets

AbstractDiverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) still remains limited. To assess the plasticity and phenotypes of immune cells within HBV/HCV-related HCC microenvironment at single-cell level, we performed single-cell RNA sequencing on 41,698 immune cells from seven pairs of HBV/HCV-related HCC tumors and non-tumor liver tissues. We combined bio-informatic analyses, flow cytometry, and multiplex immunohistochemistry to assess the heterogeneity of different immune cell subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune cell subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by diverse immune cell subsets that can transit among different states and mutually interact. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival rates. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes, and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study provides insight into the immune microenvironment in HBV/HCV-related HCC and highlights novel macrophage and T-cell subsets that could be further exploited in future immunotherapy.

Association between cetuximab response and differential immunologic gene expression signatures in colorectal cancer metastases.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 558-558 ◽  
Author(s):  
Michael Sangmin Lee ◽  
Benjamin Garrett Vincent ◽  
Autumn Jackson McRee ◽  
Hanna Kelly Sanoff
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
T Cells ◽  
T Cell ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Activated T Cells ◽  
Gene Sets

558 Background: Different immune cell infiltrates into colorectal cancer (CRC) tumors are associated with different prognoses. Tumor-associated macrophages contribute to immune evasion and accelerated tumor progression. Conversely, tumor infiltrating lymphocytes at the invasive margin of CRC liver metastases are associated with improved outcomes with chemotherapy. Cetuximab is an IgG1 monoclonal antibody against epidermal growth factor receptor (EGFR) and stimulates antibody-dependent cellular cytotoxicity (ADCC) in vitro. However, it is unclear in humans if response to cetuximab is modulated by the immune response. We hypothesized that different immune patterns detected in gene expression profiles of CRC metastases are associated with different responses to cetuximab. Methods: We retrieved gene expression data from biopsies of metastases from 80 refractory CRC patients treated with cetuximab monotherapy (GEO GSE5851). Samples were dichotomized by cetuximab response as having either disease control (DC) or progressive disease (PD). We performed gene set enrichment analysis (GSEA) with GenePattern 3.9.4 using gene sets of immunologic signatures obtained from the Molecular Signatures Database v5.0. Results: Among the 68 patients with response annotated, 25 had DC and 43 had PD. In the PD cohort, 59/1910 immunologic gene sets had false discovery rate (FDR) < 0.1. Notably, multiple gene sets upregulated in monocyte signatures were associated with PD. Also, gene sets consistent with PD1-ligated T cells compared to control activated T cells (FDR = 0.052) or IL4-treated CD4 T cells compared to controls (FDR = 0.087) were associated with PD. Conclusions: Cetuximab-resistant patients tended to have baseline increased expression of gene signatures reflective of monocytic infiltrates, consistent with also having increased expression of the IL4-treated T-cell signature. Cetuximab resistance was also associated with increased expression of the PD1-ligated T cell signature. These preliminary findings support further evaluation of the effect of differential immune infiltrates in prognosis of metastatic CRC treated with cetuximab.

scholarly journals Comprehensive Analysis of Cell Population Dynamics and Related Core Genes During Vitiligo Development

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingzhan Zhang ◽  
Shirong Yu ◽  
Wen Hu ◽  
Man Wang ◽  
Dilinuer Abudoureyimu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
T Cell ◽  
Peripheral Blood ◽  
Immune Cell ◽  
Cd8 T Cell ◽  
Cd4 T Cell ◽  
Healthy Controls ◽  
Cell Abundance

Vitiligo is a common immune-related depigmentation condition, and its pathogenesis remains unclear. This study used a combination of bioinformatics methods and expression analysis techniques to explore the relationship between immune cell infiltration and gene expression in vitiligo. Previously reported gene expression microarray data from the skin (GSE53146 and GSE75819) and peripheral blood (GSE80009 and GSE90880) of vitiligo patients and healthy controls was used in the analysis. R software was used to filter the differentially expressed genes (DEGs) in each dataset, and the KOBAS 2.0 server was used to perform functional enrichment analysis. Compared with healthy controls, the upregulated genes in skin lesions and peripheral blood leukocytes of vitiligo patents were highly enriched in immune response pathways and inflammatory response signaling pathways. Immunedeconv software and the EPIC method were used to analyze the expression levels of marker genes to obtain the immune cell population in the samples. In the lesional skin of vitiligo patients, the proportions of macrophages, B cells and NK cells were increased compared with healthy controls. In the peripheral blood of vitiligo patients, CD8+ T cells and macrophages were significantly increased. A coexpression analysis of the cell populations and DEGs showed that differentially expressed immune and inflammation response genes had a strong positive correlation with macrophages. The TLR4 receptor pathway, interferon gamma-mediated signaling pathway and lipopolysaccharide-related pathway were positively correlated with CD4+ T cells. Regarding immune response-related genes, the overexpression of IFITM2, TNFSF10, GZMA, ADAMDEC1, NCF2, ADAR, SIGLEC16, and WIPF2 were related to macrophage abundance, while the overexpression of ICOS, GPR183, RGS1, ILF2 and CD28 were related to CD4+ T cell abundance. GZMA and CXCL10 expression were associated with CD8+ T cell abundance. Regarding inflammatory response-related genes, the overexpression of CEBPB, ADAM8, CXCR3, and TNIP3 promoted macrophage infiltration. Only ADORA1 expression was associated with CD4+ T cell infiltration. ADAM8 and CXCL10 expression were associated with CD8+ T cell abundance. The overexpression of CCL18, CXCL10, FOS, NLRC4, LY96, HCK, MYD88, and KLRG1, which are related to inflammation and immune responses, were associated with macrophage abundance. We also found that immune cells infiltration in vitiligo was associated with antigen presentation-related genes expression. The genes and pathways identified in this study may point to new directions for vitiligo treatment.

scholarly journals Identification of new biomarkers and pathways associated with treatment and prognosis in melanoma patients

2020 ◽  
Author(s):  
Biao Huang ◽  
Wei Han ◽  
Zu-Feng Sheng ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Prognostic Value ◽  
Immune Cell ◽  
Gene Interaction ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Strong Positive Correlation ◽  
Hub Genes

Abstract Background Skin cutaneous melanoma (SKCM) is known as the most malignancy and treatment-resistant in human tumor, causing about 72% of deaths in skin carcinoma. However, the potential mechanism and new effective targets remain to be further elucidated. Available datasets such as Gene Expression Omnibus (GEO) can be utilized to search for novel therapeutic targets and prognostic biomarkers. Methods Three data sets were downloaded from GEO database . The differentially expressed genes (DEGs) were identified via Venn software. Protein‐protein interaction network of DEGs was developed and the module hub genes analysis was constructed by Cytoscape. Subsequently, multiple online tools and Kaplan-Meier survival curves were analyzed to detect underlying signaling pathways, gene expression, drug-gene interaction and prognostic value of hub genes. In addition, we explored the correlation between hub genes and immune cell infiltration. At last, the related miRNA, lncRNA networks were constructed by R software. Results A total of 308 DEGs and 12 hub genes were identified. Function and pathway enrichment results demonstrated a correlation between DEGs and the tumor microenvironment, immune response and melanoma tumorigenesis. Subsequently, we focused on assessing potential value of 12 hub genes. Seven hub genes ( CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 ) were identified with significant overall survival for prognosis. What’s more, five of these seven hub genes were found to be related to clinical stages (P values<0.05). In addition, the most important pathways of hub genes include interleukin-10 signaling, peptide ligand-binding receptors, which play important roles in tumor microenvironment for immune activation or immunosuppressive by regulating the infiltration of immune cells. Our results revealed a strong positive correlation between gene expression (CCL4, CCL5, CXCL9, CXCL10 and CXCL13) and immune cell infiltration (B-cell, CD8+ T cells, CD4+ T cells, macrophages, Neutrophils, Dendritic cells). Interestingly, 8 of 12 hub genes (CXCL10, CCL4, CCL5, IL6, CXCL2, PTGER3, GAL, NPY1R) were also found in the predicted drug-gene interaction. The related miRNA, lncRNA for diagnosis and prognosis were found in networks. Conclusion In conclusion, CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 were of high prognostic value and may be potential targets for the diagnosis and therapy of patients with melanoma.

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