scholarly journals Relation between IDH1 status, histologic grade, immune-cell infiltration and expression of immune-related genes in patients with gliomas

2018 ◽  
Vol 29 ◽  
pp. x5
Author(s):  
S. Cabezas-Camarero ◽  
R. Pérez-Alfayate ◽  
I. Casado Fariñas ◽  
M. Sáiz-Pardo Sanz ◽  
I. Subhi-Issa ◽  
...  
Keyword(s):  
Immune Cell ◽  
Histologic Grade ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Related Genes

scholarly journals Development of an Immune-Related Gene Signature for Prognosis in Melanoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Jia-An Zhang ◽  
Xu-Yue Zhou ◽  
Dan Huang ◽  
Chao Luan ◽  
Heng Gu ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cell ◽  
Treatment Method ◽  
Gene Signature ◽  
Cell Infiltration ◽  
Venn Diagram ◽  
Immune Cell Infiltration ◽  
Tumor Purity ◽  
New Treatment ◽  
Immune Related Genes

Melanoma remains a potentially deadly malignant tumor. The incidence of melanoma continues to rise. Immunotherapy has become a new treatment method and is widely used in a variety of tumors. Original melanoma data were downloaded from TCGA. ssGSEA was performed to classify them. GSVA software and the "hclust" package were used to analyze the data. The ESTIMATE algorithm screened DEGs. The edgeR package and Venn diagram identified valid immune-related genes. Univariate, LASSO and multivariate analyses were used to explore the hub genes. The "rms" package established the nomogram and calibrated the curve. Immune infiltration data were obtained from the TIMER database. Compared with that of samples in the high immune cell infiltration cluster, we found that the tumor purity of samples in the low immune cell infiltration cluster was higher. The immune score, ESTIMATE score and stromal score in the low immune cell infiltration cluster were lower. In the high immune cell infiltration cluster, the immune components were more abundant, while the tumor purity was lower. The expression levels of TIGIT, PDCD1, LAG3, HAVCR2, CTLA4 and the HLA family were also higher in the high immune cell infiltration cluster. Survival analysis showed that patients in the high immune cell infiltration cluster had shorter OS than patients in the low immune cell infiltration cluster. IGHV1-18, CXCL11, LTF, and HLA-DQB1 were identified as immune cell infiltration-related DEGs. The prognosis of melanoma was significantly negatively correlated with the infiltration of CD4+ T cells, CD8+ T cells, dendritic cells, neutrophils and macrophages. In this study, we identified immune-related melanoma core genes and relevant immune cell subtypes, which may be used in targeted therapy and immunotherapy of melanoma.

Identification and Validation of Immune-Related Genes and Immune Cell Infiltration in Preeclampsia

2021 ◽  
Author(s):  
Rongxin Chen ◽  
Qing Han ◽  
Huale Zhang ◽  
Jianying Yan
Keyword(s):  
Immune Cell ◽  
Risk Model ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Receptor Interaction ◽  
Immune Cell Infiltration ◽  
Multisystem Disease ◽  
Predicting Model ◽  
Immune Related Genes ◽  
Maternal Fetal Interface

Abstract Background Preeclampsia (PE) is a complex multisystem disease and its etiology remains unclear. The aim of this study was to identify potential immune-related diagnostic genes for PE, analyze the role of immune cell infiltration in PE, and explore the mechanism underlying PE-induced disruption of immune tolerance at the maternal-fetal interface. Methods We used the PE dataset GES25906 from Gene Expression Omnibus and immune-related genes from ImmPort database. The differentially expressed genes (DEGs) were identified using the “limma” package, and the differentially expressed immune-related genes (DEIGs) were extracted from the DEGs and immune-related genes using Venn diagrams. The potential functions of DEIGs were determined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the protein–protein interaction network was obtained from the STRING database, and it was visualized using Cytoscape software. Least absolute shrinkage and selection operator logistic regression was used to verify the diagnostic markers of PE and build a predicting model. The model was validated using datasets GSE66273 and GSE75010. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in PE tissues. Results Six genes (ACTG1, ENG, IFNGR1, ITGB2, NOD1, and SPP1) enriched in Th17 cell differentiation, cytokine-cytokine receptor interaction, innate immune response, and positive regulation of MAPK cascade pathways were identified, and a predicting model was built. Datasets GSE66273 and GSE75010 were used to validate the model, and the area under the curve was 0.8333 and 0.8107, respectively. Immune cell infiltration analysis revealed an increase in plasma cells and gamma delta T cells and a decrease in resting natural killer cells in the high score group according to the predictive model risk values. Conclusions We developed a risk model to predict PE and proved that immune imbalance at the maternal-fetal interface plays a key role in the pathogenesis of PE.

Profiles of immune‐related genes and immune cell infiltration in the tumor microenvironment of diffuse lower‐grade gliomas

2020 ◽  
Vol 235 (10) ◽  
pp. 7321-7331 ◽  
Author(s):  
Xiangyang Deng ◽  
Dongdong Lin ◽  
Xiaojia Zhang ◽  
Xuchao Shen ◽  
Zelin Yang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Lower Grade ◽  
Immune Cell Infiltration ◽  
Immune Related Genes

Identification of an Immune-Related Prognostic Signature Associated with Immune Infiltration in Melanoma

2020 ◽  
Author(s):  
Nian Liu ◽  
Zijian Liu ◽  
Xinxin Liu ◽  
Xiaoru Duan ◽  
Yuqiong Huang ◽  
...  
Keyword(s):  
Immune Cell ◽  
Underlying Mechanism ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Immune Infiltration ◽  
Mutation Burden ◽  
Melanoma Prognosis ◽  
Melanoma Patients ◽  
Immune Related Genes

Abstract Background: Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related genes (IRGs) signature for melanoma prognosis. Methods: Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. Results: With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. Conclusions: This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

scholarly journals Identification of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Glioblastomas

2020 ◽  
Vol 11 ◽  
Author(s):  
Sicong Huang ◽  
Zijun Song ◽  
Tiesong Zhang ◽  
Xuyan He ◽  
Kaiyuan Huang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Related Genes

scholarly journals Effects of 1p/19q Codeletion on Immune Phenotype in Low Grade Glioma

2021 ◽  
Vol 15 ◽  
Author(s):  
Lei Lv ◽  
Yuliu Zhang ◽  
Yujia Zhao ◽  
Qinqin Wei ◽  
Ye Zhao ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Low Grade ◽  
Immune Cell Infiltration ◽  
Biological Processes ◽  
Chromosome 1P ◽  
Tumor Immune Microenvironment ◽  
Immune Related Genes ◽  
Checkpoint Genes

Background: Chromosome 1p/19q codeletion is one of the most important genetic alterations for low grade gliomas (LGGs), and patients with 1p/19q codeletion have significantly prolonged survival compared to those without the codeletion. And the tumor immune microenvironment also plays a vital role in the tumor progression and prognosis. However, the effect of 1p/19q codeletion on the tumor immune microenvironment in LGGs is unclear.Methods: Immune cell infiltration of 281 LGGs from The Cancer Genome Atlas (TCGA) and 543 LGGs from the Chinese Glioma Genome Atlas (CGGA) were analyzed for immune cell infiltration through three bioinformatics tools: ESTIMATE algorithm, TIMER, and xCell. The infiltrating level of immune cells and expression of immune checkpoint genes were compared between different groups classified by 1p/19q codeletion and IDH (isocitrate dehydrogenase) mutation status. The differential biological processes and signaling pathways were evaluated through Gene Set Enrichment Analysis (GSEA). Correlations were analyzed using Spearman correlation.Results: 1p/19q codeletion was associated with immune-related biological processes in LGGs. The infiltrating level of multiple kinds of immune cells and expression of immune checkpoint genes were significantly lower in 1p/19q codeletion LGGs compared to 1p/19q non-codeletion cohorts. There are 127 immune-related genes on chromosome 1p or 19q, such as TGFB1, JAK1, and CSF1. The mRNA expression of these genes was positively correlated with their DNA copy number. These genes are distributed in multiple immune categories, such as chemokines/cytokines, TGF-β family members, and TNF family members, regulating immune cell infiltration and expression of the immune checkpoint genes in tumors.Conclusion: Our results indicated that 1p/19q codeletion status is closely associated with the immunosuppressive microenvironment in LGGs. LGGs with 1p/19q codeletion display less immune cell infiltration and lower expression of immune checkpoint genes than 1p/19q non-codeletion cases. Mechanistically, this may be, at least in part, due to the deletion of copy number of immune-related genes in LGGs with 1p/19q codeletion. Our findings may be relevant to investigate immune evasion in LGGs and contribute to the design of immunotherapeutic strategies for patients with LGGs.

Crosstalk between the MSI status and tumor microenvironment in colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15236-e15236
Author(s):  
Peng Luo ◽  
Anqi Lin ◽  
Jian Zhang
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Microsatellite Instability ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Microenvironment ◽  
Mutation Data ◽  
Immune Related Genes

e15236 Background: In recent years, cancer immunotherapy has been extensively studied, and colorectal cancer (CRC) patients have also derived clinical benefits from immunotherapy, especially CRC patients with mismatch repair deficiency (dMMR)/microsatellite instability-high (MSI-H), whose sensitivity to immune checkpoint inhibitors (ICIs) is significantly higher than that of patients with microsatellite-stable (MSS)/microsatellite instability-low (MSI-L) disease. This study suggests that patients with MSI-H CRC have a higher mutational burden and more immune cell infiltration than those with MSS/MSI-L disease. However, most studies have not systematically evaluated the immune characteristics and immune microenvironments of MSI-H and MSS/MSI-L CRC. Methods: A published CRC cohort with mutation and immunotherapy-related prognostic data was collected. We analyzed the relationship between the MSI status and prognosis of ICI treatment in an immunotherapy cohort. We then further used mutation data for the immunotherapy and The Cancer Genome Atlas (TCGA)-CRC (colon adenocarcinoma (COAD) + rectum adenocarcinoma (READ) cohorts. For mRNA expression, mutation data analysis of the immune microenvironment and immunogenicity under different MSI status was performed. Results: Compared with MSS/MSI-L CRC patients, patients with MSI-H CRC significantly benefited from ICI treatment. We found that MSI-H CRC had more immune cell infiltration, higher expression of immune-related genes and higher immunogenicity than MSS/MSI-L disease. The MANTIS score used to predict the MSI status was positively correlated with immune cells, immune-related genes, and immunogenicity. In addition, subtype analysis showed that COAD and READ might have different tumor immune microenvironments. Conclusions: MSI-H CRC may have an inflammatory tumor microenvironment and increased sensitivity to ICIs. Unlike those of MSI-H READ, the immune characteristics of MSI-H COAD may be consistent with those of MSI-H CRC. Furthermore, the possible mechanism underlying the prognostic differences among CRC patients receiving ICIs in relation to the immune microenvironment were elucidated to provide theoretical guidance for further improving the curative effect of ICIs treatment on MSI-H CRC patients in the future and solve the problems underlying why MSS/MSI-L CRC patients do not benefit from ICIs treatment.

scholarly journals Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wen-Hua Yuan ◽  
Qi-Qi Xie ◽  
Ke-Ping Wang ◽  
Wei Shen ◽  
Xiao-Fei Feng ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Immune Cell ◽  
Diagnostic Markers ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Support Vector ◽  
Immune Cell Infiltration ◽  
M1 Macrophage ◽  
Immune Related Genes

AbstractOsteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.

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