scholarly journals Integration of Genetic and Immune Infiltration Insights into Data Mining of Multiple Sclerosis Pathogenesis

2021 ◽  
Author(s):  
Xiaoyun Zhang ◽  
Ying Song ◽  
Xiao Chen ◽  
Xiaojia Zhuang ◽  
Zhiqiang Wei ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Correlation Analysis ◽  
Immune Cells ◽  
Genetic Basis ◽  
Demyelinating Disease ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Ms Pathogenesis ◽  
Brain Tissues

Abstract Background: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. MS pathogenesis is closely related to the environment, genetic, and immune system, but the underlying interactions have not been clearly elucidated. This study aims to unveil the genetic basis and immune landscape of MS pathogenesis with bioinformatics.Methods:Gene matrix wasretrieved from the gene expression database NCBI GEO. Then, bioinformatics was used to standardize the samples and obtain differentially expressed genes (DEGs). The protein-protein interaction network was constructed with DEGs on the STRING website. Cytohubbaplug-in and MCODE plug-in were used to mine hub genes. Meanwhile, the CIBERSORTX algorithm was used to explore the characteristics of immune cellinfiltration in MS brain tissues. Spearman correlation analysis was performed between genes and immune cells, and the correlation between genes and different types of brain tissues was also analyzed using the WGCNA method.Results:A total of 90 samples from 2 datasetswere included, and 882 DEGs and 10 hub genes closely related to MS were extracted. Functional enrichment analysis suggested the roleof immune response in MS. Besides,CIBERSORTX algorithm results showed that MS brain tissuescontained a variety of infiltrating immune cells. Correlation analysis suggested that the hub genes were highly relevant to chronic active white matter lesions.Certain hub genes played a role in the activation of immune cells such as macrophages and natural killer cells.Conclusions: Our study shall provideguidance for the further study of the genetic basis and immune infiltration mechanism of MS.

scholarly journals Integration of Genetic and Immune Infiltration Insights Into Data Mining of Multiple Sclerosis Pathogenesis

2021 ◽  
Author(s):  
Xiaoyun Zhang ◽  
Ying Song ◽  
Xiao Chen ◽  
Xiaojia Zhuang ◽  
Qizhi Xie ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Correlation Analysis ◽  
Immune Cells ◽  
Genetic Basis ◽  
Demyelinating Disease ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Multiple Sclerosis Pathogenesis ◽  
Brain Tissues

Abstract Background: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. Pathogenesis is closely related to environment, genetic and immune system, but the underlying interactions are still not clearly elucidated. Our study aims to uncover the genetic basis and immune landscape of multiple sclerosis pathogenesis with bioinformatics.Methods: In our study, gene matrix were retrieceed from gene expression database NCBI GEO. We then used bioinformatics to standardize the samples and obtain differential gene expressions (DEGs). We constructed a protein-protein interaction network with DEGs on the STRING website, and used Cytohubba plug-in and MCODE plug-in to to mine hub genes. Then we had a functional enrichment hub genes and DEGs. Meanwhile, we use CIBERSORTX algorithm to explore the characteristics of immune cells infiltration in brain tissues of multiple sclerosis, and did a Spearman correlation analysis between genes and immune cells. We also analyzed the correlation between genes and types of brain tissues with WGCNA method.Results: We included a total of 90 samples from 2 datasets in the study, extracted 882 differential genes and 10 hub genes closely related to multiple sclerosis. Functional enrichment analysis suggested roles of immune response in multiple sclerosis. Besides, with CIBERSORTX algorithm we found brain tissues of MS contain a variety of infiltrating immune cells. Correlation analysis suggested that hub genes are highly relevant to chronic active white matter lesions and certain hub genes in our study may play a role in the activation of immune cells such as macrophages and natural killer cells.Conclusions: Our study provides guidance for the study of genetic basis and immune infiltration mechanism of multiple sclerosis.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

scholarly journals Prognostic and immunological value of LTB4R in pan-cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 9336-9356
Author(s):  
Sidan Long ◽  
◽  
Shuangshuang Ji ◽  
Kunmin Xiao ◽  
Peng Xue ◽  
...  
Keyword(s):  
Immune Cells ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Negative Influence ◽  
Leukotriene B4 ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Significant Difference ◽  
Pan Cancer

<abstract> <sec><title>Background</title><p>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.</p> </sec> <sec><title>Methods</title><p>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies.</p> </sec> <sec><title>Results</title><p>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns.</p> </sec> <sec><title>Conclusion</title><p>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.</p> </sec> </abstract>

scholarly journals Identification of Biomarkers Related to Immune Cell Infiltration in Hepatocellular Carcinoma Using Gene Co-Expression Network

2021 ◽  
Vol 27 ◽  
Author(s):  
Wanbang Zhou ◽  
Yiyang Chen ◽  
Ruixing Luo ◽  
Zifan Li ◽  
Guanwei Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Network Analysis ◽  
Tumor Progression ◽  
Protein Interactions ◽  
Immune Cells ◽  
Immune Cell ◽  
Immune Microenvironment ◽  
Hub Genes ◽  
Expression Levels ◽  
Immune Infiltration

Hepatocellular carcinoma (HCC) is a common cancer with poor prognosis. Due to the lack of effective biomarkers and its complex immune microenvironment, the effects of current HCC therapies are not ideal. In this study, we used the GSE57957 microarray data from Gene Expression Omnibus database to construct a co-expression network. The weighted gene co-expression network analysis and CIBERSORT algorithm, which quantifies cellular composition of immune cells, were used to identify modules related to immune cells. Four hub genes (EFTUD2, GAPDH, NOP56, PA2G4) were identified by co-expression network and protein-protein interactions network analysis. We examined these genes in TCGA database, and found that the four hub genes were highly expressed in tumor tissues in multiple HCC groups, and the expression levels were significantly correlated with patient survival time, pathological stage and tumor progression. On the other hand, methylation analysis showed that the up-regulation of EFTUD2, GAPDH, NOP56 might be due to the hypomethylation status of their promoters. Next, we investigated the correlations between the expression levels of four hub genes and tumor immune infiltration using Tumor Immune Estimation Resource (TIMER). Gene set variation analysis suggested that the four hub genes were associated with numerous pathways that affect tumor progression or immune microenvironment. Overall, our results showed that the four hub genes were closely related to tumor prognosis, and may serve as targets for treatment and diagnosis of HCC. In addition, the associations between these genes and immune infiltration enhanced our understanding of tumor immune environment and provided new directions for the development of drugs and the monitoring of tumor immune status.

scholarly journals Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yang Shen ◽  
Li-rong Xu ◽  
Xiao Tang ◽  
Chang-po Lin ◽  
Dong Yan ◽  
...  
Keyword(s):  
Immune Cells ◽  
Plasma Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gamma Delta ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Bioinformatics Analyses ◽  
Immune Infiltration ◽  
Atheromatous Plaques

Abstract Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques. Conclusions Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

scholarly journals Identification of immune-infiltrated hub genes as potential biomarkers of Moyamoya disease by bioinformatics analysis

2021 ◽  
Author(s):  
Fa Jin ◽  
Chuanzhi Duan
Keyword(s):  
Moyamoya Disease ◽  
Expression Profiles ◽  
Molecular Transport ◽  
Neutrophil Infiltration ◽  
Negative Control Group ◽  
Negative Control ◽  
Functional Enrichment ◽  
Control Group ◽  
Hub Genes ◽  
Immune Infiltration

Abstract Background Moyamoya disease (MMD) is a unique chronic progressive cerebrovascular disease. The molecular mechanism behind pathophysiology is still elusive. This study aims to determine the key genes and their roles in the immune infiltration of MMD.Methods We download raw gene expression profiles (GSE157628, GSE141024) of cerebrovascular tissue from GEO database. Identify differentially expressed genes (DEGs) and perform functional enrichment analysis. The CIBERSORT deconvolution algorithm was used to analyze the proportion of immune cell infiltration between MMD and negative control group. We screened for neutrophil-associated DEGs, constructed a protein-protein interaction network (PPI) using STRING, and clarified hub genes using the Cytoscape plugin MCODE analysis. The receiver operating characteristic (ROC) curve is applied to test and filter the best gene signature.Results A total of 570 DEGs were detected, including 212 downregulated and 358 up-regulated genes. Reactome and KEGG enrichment revealed that DEGs are involved in the cell cycle, molecular transport, and metabolic pathways. The immune infiltration profile demonstrates that MMD cerebrovascular tissues contained a higher proportion of neutrophils, monocytes, and NK cells than negative control group. PPI network and MCODE cluster identified 9 DEGs (UNC13D, AZU1, PYCARD, ELANE, SDCBP, CCL11, CCL15, CCL20, and CXCL5) associated with neutrophil infiltration. ROC results showed that UNC13D has good specificity and sensitivity (AUC = 0.7846).Conclusions The characteristics of immune infiltration in the cerebrovascular tissues of MMD patients and abnormal expression of hub genes provide new insights for understanding MMD progression. UNC13D is promising to be one of the candidate molecules to determine neutrophil infiltration characteristics in MMD.

scholarly journals Identification of Key Biomarkers and Immune Infiltration in Sciatic Nerve of Diabetic Neuropathy BKS-db/db Mice by Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Yixuan Lin ◽  
Fanjing Wang ◽  
Lianzhi Cheng ◽  
Zhaohui Fang ◽  
Guoming Shen
Keyword(s):  
Diabetic Neuropathy ◽  
Signaling Pathway ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Data Set ◽  
Immune Infiltration ◽  
P53 Signaling ◽  
Ppi Networks ◽  
Key Genes ◽  
P53 Signaling Pathway

Diabetic neuropathy (DN) is one of the chronic complications of diabetes which can cause severe harm to patients. In order to determine the key genes and pathways related to the pathogenesis of DN, we downloaded the microarray data set GSE27382 from Gene Expression Omnibus (GEO) and adopted bioinformatics methods for comprehensive analysis, including functional enrichment, construction of PPI networks, central genes screening, TFs-target interaction analysis, and evaluation of immune infiltration characteristics. Finally, we examined quantitative real- time PCR (qPCR) to validate the expression of hub genes. A total of 318 differentially expressed genes (DEGs) were identified, among which 125 upregulated DEGs were enriched in the mitotic nuclear division, extracellular region, immunoglobulin receptor binding, and p53 signaling pathway, while 193 downregulated DEGs were enriched in ion transport, membrane, synapse, sodium channel activity, and retrograde endocannabinoid signaling. GSEA plots showed that condensed nuclear chromosome kinetochore were the most significant enriched gene set positively correlated with the DN group. Importantly, we identified five central genes (Birc5, Bub1, Cdk1, Ccnb2, and Ccnb1), and KEGG pathway analysis showed that the five hub genes were focused on progesterone-mediated oocyte maturation, cell cycle, and p53 signaling pathway. The proportion of immune cells from DN tissue and normal group showed significant individual differences. In DN samples, T cells CD4 memory resting and dendritic cells resting accounted for a higher proportion, and macrophage M2 accounted for a lower proportion. In addition, all five central genes showed consistent correlation with immune cell infiltration levels. qPCR showed the same expression trend of five central genes as in our analysis. Our research identified key genes related to differential genes and immune infiltration related to the pathogenesis of DN and provided new diagnostic and potential therapeutic targets for DN.

scholarly journals SCG2 is a Prognostic Biomarker Associated With Immune Infiltration and Macrophage Polarization in Colorectal Cancer

2022 ◽  
Vol 9 ◽  
Author(s):  
Hao Wang ◽  
Jinwen Yin ◽  
Yuntian Hong ◽  
Anli Ren ◽  
Haizhou Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Macrophage Polarization ◽  
Clinical Stage ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Secretory Proteins ◽  
Advanced Clinical Stage ◽  
Multiple Tumor ◽  
Immune Infiltration

Colorectal cancer (CRC) is the second most lethal malignancy around the world. Limited efficacy of immunotherapy creates an urgent need for development of novel treatment targets. Secretogranin II (SCG2) is a member of the chromogranin family of acidic secretory proteins, has a role in tumor microenvironment (TME) of lung adenocarcinoma and bladder cancer. Besides, SCG2 is a stroma-related gene in CRC, its potential function in regulating tumor immune infiltration of CRC needs to be fully elucidated. In this study, we used western blot, real-time PCR, immunofluorescence and public databases to evaluate SCG2 expression levels and distribution. Survival analysis and functional enrichment analysis were performed. We examined TME and tumor infiltrating immune cells using ESTIMATE and CIBERSORT algorithm. The results showed that SCG2 expression was significantly decreased in CRC tumor tissues, and differentially distributed between tumor and adjacent normal tissues. SCG2 was an independent prognostic predictor in CRC. High expression of SCG2 correlated with poor survival and advanced clinical stage in CRC patients. SCG2 might regulate multiple tumor- and immune-related pathways in CRC, influence tumor immunity by regulating infiltration of immune cells and macrophage polarization in CRC.

scholarly journals Potential Prognosis and Diagnostic Value of AKT3, LSM12, MEF2C, and RAB30 in Exosomes in Colorectal Cancer on Spark Framework

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jue Wang ◽  
Sheng Wu ◽  
Jiuwen Zhang ◽  
Jing Chen
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Cancer Metastasis ◽  
Diagnostic Value ◽  
Functional Enrichment ◽  
Expression Levels ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Proposed Model ◽  
Tcga Dataset

Colorectal cancer (CRC) is a common malignant tumor and one of the leading causes of cancer-related deaths worldwide. CRC progression is greatly affected by the local microenvironment. In the study, we proposed a deep computational-based model for the classification of mRNA, lncRNA, and circRNA in exosomes. We, first, analyzed mRNA expression levels in CRC tumors and normal tissues. Secondly, we used GO and KEGG to analyze their functional enrichment. Thirdly, we analyzed the composition of immune cells in all TCGA samples and then evaluated the prognostic value of tumor-infiltrating immune cells in CRC. Lastly, we combined the TCGA dataset, i.e., COADN = 449 and ROADN = 6, for analysis and found that the expression levels of AKT3, LSM12, MEF2C, and RAB30 in exosomes were significantly correlated with tumor immune infiltration levels. The performance evaluation has shown that the proposed model based on neural networks performs better as compared to the existing methods. The proposed model can be used as a potential tool for the immune infiltration level and their role in cancer metastasis and progression, which can help us to explore potential strategies for CRC diagnosis, therapy, and prognosis.

Mine TCGA Database for Tumor Microenvironment-Related Genes of Prognostic value in lung squamous cell carcinoma

2020 ◽  
Author(s):  
Xiao Chen ◽  
Rui Li ◽  
Yun-Hong Yin ◽  
Xiao Liu ◽  
Xi-Jia Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cells ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes

Abstract Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.

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