scholarly journals Identification of Potential ceRNA Network and Patterns of Immune Cell Infiltration in Systemic Sclerosis-Associated Interstitial Lung Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Qiuhong Wu ◽  
Yang Liu ◽  
Yan Xie ◽  
Shixiong Wei ◽  
Yi Liu
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Immune Cells ◽  
Regulatory Network ◽  
Target Genes ◽  
Immune Cell ◽  
Differentially Expressed ◽  
Immune Cell Infiltration ◽  
Overlapping Genes

PurposeSystemic sclerosis-associated interstitial lung disease (SSc-ILD) is one of the most severe complications of systemic sclerosis (SSc) and is the leading cause of SSc-related deaths. However, the precise pathogenesis of pulmonary fibrosis in SSc-ILD remains unknown. This study aimed to evaluate the competing endogenous RNA (ceRNA) regulatory network and immune cell infiltration patterns in SSc-ILD.MethodsOne microRNA (miRNA) and three messenger RNA (mRNA) microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. Then, the differentially expressed miRNAs (DEmiRs) and mRNAs (DEMs) between SSc-ILD patients and normal controls were identified, respectively, followed by the prediction of the target genes and target lncRNAs of DEmiRs. The overlapping genes between DEmiRs target genes and DEMs were identified as core mRNAs to construct the ceRNA network. In addition, the “Cell Type Identification by Estimating Relative Subsets of Known RNA Transcripts (CIBERSORT)” algorithm was used to analyze the composition of infiltrating immune cells in lung tissues of SSc-ILD patients and controls, and differentially expressed immune cells were recognized. The correlation between immune cells and core mRNAs was evaluated by Pearson correlation analysis.ResultsTotally, 42 SSc-ILD lung tissues and 18 normal lung tissues were included in this study. We identified 35 DEmiRs and 142 DEMs and predicted 1,265 target genes of DEmiRs. Then, 9 core mRNAs related to SSc-ILD were recognized, which were the overlapping genes between DEmiRs target genes and DEMs. Meanwhile, 9 DEmiRs related to core mRNAs were identified reversely, and their target lncRNAs were predicted. In total, 9 DEmiRs, 9 core mRNAs, and 51 predicted lncRNAs were integrated to construct the ceRNA regulatory network of SSc-ILD. In addition, 9 types of immune cells were differentially expressed in lung tissues between SSc-ILD patients and controls. Some core mRNAs, such as COL1A1, FOS, and EDN1, were positively or negatively correlated with the number of infiltrating immune cells.ConclusionThis is the first comprehensive study to construct the potential ceRNA regulatory network and analyze the composition of infiltrating immune cells in lung tissues of SSc-ILD patients, which improves our understanding of the pathogenesis of SSc-ILD.

scholarly journals The Downregulation of PTGS2 Mediated by ncRNAs is Tightly Correlated with Systemic Sclerosis-Interstitial Lung Disease

2022 ◽  
Vol 12 ◽  
Author(s):  
Zhixiao Xu ◽  
Chengshui Chen
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Immune Cell ◽  
Gene Expression Omnibus ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Hub Genes ◽  
Cd20 Expression ◽  
Key Genes

Background: Interstitial lung disease in systemic sclerosis (SSc-ILD) is one of the most severe complications of systemic sclerosis (SSc) and is the main cause of mortality. In this study, we aimed to explore the key genes in SSc-ILD and analyze the relationship between key genes and immune cell infiltration as well as the key genes relevant to the hallmarks of cancer.Methods: Weighted gene co-expression network analysis (WGCNA) algorithm was implemented to explore hub genes in SSc-ILD samples from the Gene Expression Omnibus (GEO) database. Logistic regression analysis was performed to screen and verify the key gene related to SSc-ILD. CIBERSORT algorithms were utilized to analyze immune cell infiltration. Moreover, the correlation between the key genes and genes relevant to cancer was also evaluated. Furthermore, non-coding RNAs (ncRNAs) linking to PTGS2 were also explored.Results: In this study, we first performed WGCNA analysis for three GEO databases to find the potential hub genes in SSc-ILD. Subsequently, we determined PTGS2 was the key gene in SSC-ILD. Furthermore, in CIBERSORT analyses, PTGS2 were tightly correlated with immune cells such as regulatory T cells (Tregs) and was negatively correlated with CD20 expression. Moreover, PTGS2 was associated with tumor growth. Then, MALAT1, NEAT1, NORAD, XIST identified might be the most potential upstream lncRNAs, and LIMS1 and RANBP2 might be the two most potential upstream circRNAs.Conclusion: Collectively, our findings elucidated that ncRNAs-mediated downregulation of PTGS2, as a key gene in SSc-ILD, was positively related to the occurrence of SSc-ILD and abnormal immunocyte infiltration. It could be a promising factor for SSc-ILD progression to malignancy.

scholarly journals Plasma-Derived Exosomal hsa-miR-4488 and hsa-miR-1228-5p: Novel Biomarkers for Dermatomyositis-Associated Interstitial Lung Disease with Anti-Melanoma Differentiation-Associated Protein 5 Antibody-Positive Subset

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Danli Zhong ◽  
Chanyuan Wu ◽  
Dong Xu ◽  
Jingjing Bai ◽  
Qian Wang ◽  
...  
Keyword(s):  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Target Genes ◽  
Homo Sapiens ◽  
Differentially Expressed ◽  
Transmission Electron ◽  
Exosomal Mirnas ◽  
Differentially Expressed Mirnas ◽  
Novel Biomarkers ◽  
And Gender

The present study is aimed at profiling circulating exosome-derived microRNAs (miRNAs/miRs) from patients with dermatomyositis (DM), in particular those complicated with interstitial lung disease (ILD) with anti-melanoma differentiation-associated protein 5 (MDA5) antibody-positive. Fifteen participants were enrolled, including five patients with DM complicated with ILDs prior to treatment with circulating anti-MDA5 antibody-positive status [DM-ILD-MDA5 Ab(+)], five DM patients without ILDs who were negative for 16 detectable myositis-specific antibodies [DM-nonILD-MSA16(-)], and five age- and gender-matched healthy donor controls (HCs). The characteristics of the exosomes extracted by Ribo™ Exosome Isolation Reagent were identified using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and flow cytometry. Differentially expressed miRNAs, determined by next-generation deep sequencing, were identified through the criteria of ∣ log 2   fold   change ∣ ≥ 1 and P < 0.01 . A total of 38 miRNAs were significantly upregulated in exosomes from patients with DM-ILD-MDA5 Ab(+) compared to those from HC, while 21 miRNAs were significantly downregulated. Compared to exosomes derived from patients with DM-nonILD-MSA16(-), 51 miRNAs were significantly upregulated and 33 miRNAs were significantly downregulated from patients with DM-ILD-MDA5 Ab(+). A total of 73 exosomal miRNAs were significantly differentially expressed between DM-nonILD-MSA16(-) and HC. In particular, two miRNAs, Homo sapiens- (hsa-) miR-4488 and hsa-miR-1228-5p, were common differentially expressed miRNAs among three comparisons. GO and KEGG analyses suggested that several pathways may contribute the pathogenesis of DM-ILD-MDA5 Ab(+) and DM-nonILD-MSA16(-), while PPI network analysis of hsa-miR-4488 and hsa-miR-1228-5p indicated that their predicted target genes, DExD-box helicase 39B and MDM2, may be involved in the mechanisms of DM-ILD-MDA5 Ab(+).

scholarly journals Identification of miRNA-mRNA network and immune-related gene signatures in IgA nephropathy by integrated bioinformatics analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shi-Yao Wei ◽  
Shuang Guo ◽  
Bei Feng ◽  
Shang-Wei Ning ◽  
Xuan-Yi Du
Keyword(s):  
T Cells ◽  
Iga Nephropathy ◽  
Immune Cells ◽  
Regulatory Network ◽  
Target Genes ◽  
Immune Cell ◽  
Expression Profiles ◽  
Specific Treatment ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis worldwide, and its diagnosis depends mainly on renal biopsy. However, there is no specific treatment for IgAN. Moreover, its causes and underlying molecular events require further exploration. Methods The expression profiles of GSE64306 and GSE93798 were downloaded from the Gene Expression Omnibus (GEO) database and used to identify the differential expression of miRNAs and genes, respectively. The StarBase and TransmiR databases were employed to predict target genes and transcription factors of the differentially expressed miRNAs (DE-miRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to predict biological functions. A comprehensive analysis of the miRNA-mRNA regulatory network was constructed, and protein–protein interaction (PPI) networks and hub genes were identified. CIBERSORT was used to examine the immune cells in IgAN, and correlation analyses were performed between the hub genes and infiltrating immune cells. Results Four downregulated miRNAs and 16 upregulated miRNAs were identified. Forty-five and twelve target genes were identified for the upregulated and downregulated DE-miRNAs, respectively. CDKN1A, CDC23, EGR1, HIF1A, and TRIM28 were the hub genes with the highest degrees of connectivity. CIBERSORT revealed increases in the numbers of activated NK cells, M1 and M2 macrophages, CD4 naive T cells, and regulatory T cells in IgAN. Additionally, HIF1A, CDC23, TRIM28, and CDKN1A in IgAN patients were associated with immune cell infiltration. Conclusions A potential miRNA-mRNA regulatory network contributing to IgAN onset and progression was successfully established. The results of the present study may facilitate the diagnosis and treatment of IgAN by targeting established miRNA-mRNA interaction networks. Infiltrating immune cells may play significant roles in IgAN pathogenesis. Future studies on these immune cells may help guide immunotherapy for IgAN patients.

scholarly journals Identification of the Key Serum Biomarkers to Diagnose and Predict Metastasis of Osteosarcoma Based on the Analysis of Immune Cell Infiltration Characteristics

2021 ◽  
Author(s):  
Zhihao Chen ◽  
Liubing Li ◽  
Ziyuan Li ◽  
Xi Wang ◽  
Mingxiao Han ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Serum Biomarkers ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Diagnostic Model ◽  
Immune Cell Infiltration ◽  
Differentially Expressed Mirnas

Abstract Background: The potential functions of circular RNAs (circRNAs) and micro RNAs (miRNAs) in osteosarcoma (OS) have not been fully elucidated. Especially, the behavior and mechanism of immune responses in OS development and progression have not been fully demonstrated. It was reported that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. This study aimed to identify novel key serum biomarkers to diagnose and predict metastasis of OS based on the analysis of immune cell infiltration characteristics.Methods: The differentially-expressed circRNAs (DEcircRNAs), differentially-expressed miRNAs (DEmiRNAs),and differentially-expressed mRNAs (DEmRNAs) of human OS were investigated based on the microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Then, we analyzed immune characteristics pattern of tumor-infiltrating immune cells in OS. On this basis, we identified statistically-significant transcription factors and performed pathway enrichment analysis. Subsequently, we constructed protein-protein interaction (PPI) and competitive endogenous RNA (ceRNA) networks. Moreover, the biological characteristic of targets in ceRNA networks was proposed. Finally, the expression and diagnostic capability of these potential biomarkers from ceRNA network were confirmed by RT-qPCR in patients’ serum.Results: Seven differentially-expressed circRNAs (DEcircRNAs), 166 differentially-expressed miRNAs (DEmiRNAs) and 175 differentially-expressed mRNAs (DEmRNAs) were identified in total. The highest level of infiltration in OS patients were M0 macrophages, M2 macrophages and CD8+ T cells. Further, M0 macrophages and CD8+ T cells were showed the largest negative correlation coefficients. These significant immune characteristics pattern of tumor-infiltrating immune cells were revealed by the principal component analysis in OS. Moreover, we found 185 statistically-significant transcription factors in which the main significant molecules show the potential in immunotherapy of OS. Hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A from ceRNA networks associated with immune cell infiltration were confirmed as the potential novel biomarkers for OS diagnosis, of which FAM98A could distinguish and predict metastasis. Most importantly, a novel diagnostic model consisting of the four promising biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was highlighted with 0.928 AUC value.Conclusions: In summary, the potenial serum biomarkers to diagnose and predict metastasis of OS based on the analysis of immune cell infiltration characteristics were found, and a novel diagnostic model consisting of four promising serum biomarkers was proposed firstly. These results provided a new perspective for the immunotherapy of OS.

scholarly journals Comprehensive Analysis of Tumor Microenvironment Identified Prognostic Immune-Related Gene Signature in Ovarian Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Na Li ◽  
Biao Li ◽  
Xianquan Zhan
Keyword(s):  
Ovarian Cancer ◽  
Immune Cells ◽  
Prognostic Model ◽  
Immune Cell ◽  
Gene Signature ◽  
Differentially Expressed ◽  
Immune Cell Infiltration ◽  
Related Gene ◽  
Immune Related Gene ◽  
Immune Related Genes

BackgroundAccumulating evidence demonstrated that tumor microenvironmental cells played important roles in predicting clinical outcomes and therapeutic efficacy. We aimed to develop a reliable immune-related gene signature for predicting the prognosis of ovarian cancer (OC).MethodsSingle sample gene-set enrichment analysis (ssGSEA) of immune gene-sets was used to quantify the relative abundance of immune cell infiltration and develop high- and low-abundance immune subtypes of 308 OC samples. The presence of infiltrating stromal/immune cells in OC tissues was calculated as an estimate score. We estimated the correlation coefficients among the immune subtype, clinicopathological feature, immune score, distribution of immune cells, and tumor mutation burden (TMB). The differentially expressed immune-related genes between high- and low-abundance immune subtypes were further used to construct a gene signature of a prognostic model in OC with lasso regression analysis.ResultsThe ssGSEA analysis divided OC samples into high- and low-abundance immune subtypes based on the abundance of immune cell infiltration, which was significantly related to the estimate score and clinical characteristics. The distribution of immune cells was also significantly different between high- and low-abundance immune subtypes. The correlation analysis showed the close relationship between TMB and the estimate score. The differentially expressed immune-related genes between high- and low-abundance immune subtypes were enriched in multiple immune-related pathways. Some immune checkpoints (PDL1, PD1, and CTLA-4) were overexpressed in the high-abundance immune subtype. Furthermore, the five-immune-related-gene-signature prognostic model (CCL18, CXCL13, HLA-DOB, HLA-DPB2, and TNFRSF17)-based high-risk and low-risk groups were significantly related to OC overall survival.ConclusionImmune-related genes were the promising predictors of prognosis and survival, and the comprehensive landscape of tumor microenvironmental cells of OC has potential for therapeutic schedule monitoring.

scholarly journals Construction of miRNA-mRNA regulatory network and prognostic signature in endometrial cancer

2020 ◽  
Author(s):  
Jinhui Liu ◽  
Rui Sun ◽  
Sipei Nie ◽  
Jing Yang ◽  
Siyue Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Regulatory Network ◽  
Target Genes ◽  
Immune Cell ◽  
Cox Proportional Hazards ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Prognostic Signature ◽  
Hub Genes ◽  
Qrt Pcr

Abstract Background: Many studies have well supported the close relationship between miRNA and endometrial cancer (EC). This bioinformatic study, compared with other similar studies, confirmed a new miRNA-mRNA regulatory network to investigate the miRNA-mRNA regulatory network and the prognostic biomarkers in EC. Methods: We downloaded RNA-seq and miRNA-seq data of endometrial cancer from the TCGA database, and then we used EdegR package to screen differentially expressed miRNAs and mRNAs (DE-miRNAs and DE-mRNAs). The differentially expressed genes (DEGs) were identified and their functions were predicted using the functional and pathway enrichment analysis. Protein–protein interaction (PPI) network was established using STRING database, and the hub genes were verified by Gene Expression Profiling Interactive Analysis (GEPIA). Then, we constructed a regulatory network of EC-associated miRNAs and hub genes by Cytoscape, and determined the expression of unexplored miRNAs in EC tissues and normal adjacent tissues by quantitative Real-Time PCR (qRT-PCR). A prognostic signature model and a predictive nomogram were constructed. Finally, we explored the association between the prognostic model and the immune cell infiltration. Results: 11531 DE-mRNAs and 236 DE-miRNAs, as well as 275 and 118 candidate DEGs for upregulated and downregulated DE-miRNAs were screened out. These DEGs were significantly concentrated in FOXO signaling pathway, cell cycle and Focal adhesion. Among the 20 hub genes identified, 17 exhibited significantly different expression compared with normal tissues. The miRNA-mRNA network included 5 downregulated and 13 upregulated DE-miRNAs . qRT-PCR proved that the expression levels of miRNA-18a-5p, miRNA-18b-5p, miRNA-449c-5p and miRNA-1224-5p and their target genes, NR3C1, CTGF, MYC, and TNS1 were consistent with our predictions. Univariate and multivariate Cox proportional hazards regression analyses of the hub genes revealed that NR3C1, EZH2, and GATA4 showed a significant prognostic value. We identified the three-gene signature as an independent prognostic indicator for EC ( p =0.022，HR=1.321, 95% CI: 1.041-1.675) and these genes were closely related to eight types of immune infiltration cells. Conclusion: Our study revealed the mechanisms of the carcinogenesis and progression of EC.

scholarly journals Developing a risk scoring system based on immune-related lncRNAs for patients with gastric cancer

2020 ◽  
Author(s):  
Yuzhi Wang ◽  
Yu Zou ◽  
Yi Zhang ◽  
Chengwen Li
Keyword(s):  
Gastric Cancer ◽  
Immune Cells ◽  
Scoring System ◽  
Immune Cell ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Risk Scoring ◽  
Risk Scoring System

The immune system and the tumor interact closely during tumor development. Aberrantly-expressed long non-coding RNAs (lncRNAs) may be potentially applied as diagnostic and prognostic markers for gastric cancer (GC). At present, the diagnosis and treatment of GC patients remain a formidable clinical challenge. This study aimed to build a risk scoring system to improve the prognosis of GC patients. In this study, ssGSEA was used to evaluate the infiltration of immune cells in GC tumor tissue samples, and the samples were split into a high immune cell infiltration group and a low immune cell infiltration group. 1262 differentially expressed lncRNAs between the high immune cell infiltration group and the low immune cell infiltration group. 3204 differentially expressed lncRNAs between GC tumor tissues and paracancerous tissues were identified. Then, 621 immune-related lncRNAs were screened using a Venn analysis based on the above results, and 85 prognostic lncRNAs were identified using a univariate Cox analysis. We constructed a prognostic signature using LASSO analysis and evaluated the predictive performance of the signature using ROC analysis. GO and KEGG enrichment analyses were performed on the lncRNAs using the R package, “clusterProfiler.” The TIMER online database was used to analyze correlations between the risk score and the abundances of the six types of immune cells. In conclusion, our study found that specific immune-related lncRNAs were clinically significant. These lncRNAs were used to construct a reliable prognostic signature and analyzed immune infiltrates, which may assist clinicians in developing individualized treatment strategies for GC patients.

scholarly journals Immune cell infiltration characteristics and related core genes of bioinformatic analysis in multiple sclerosis

2021 ◽  
Author(s):  
jingyu zhao ◽  
Jianyong Zheng ◽  
Qun Wang ◽  
Qian Li ◽  
Nan zhang
Keyword(s):  
Multiple Sclerosis ◽  
Immune Cells ◽  
Immune Cell ◽  
Clinical Information ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Systematic Understanding ◽  
Core Genes

Abstract Background Introduction Multiple sclerosis(MS) is a common complication of uncontrolled or excessive neuroinflammation and autoimmunity disease. Advances in high-throughput technologies and available bioinformatics tools make it possible to evaluate different expressions in the whole genome instead of focusing on a limited number of genes. MethodsMaterials and methods Two public available databases GSE81279 and GSE21942 of multiple sclerosis samples were downloaded analyzed by CIBERSORT. Gene Ontology (GO) and KEGG pathway analysis based on GSEA was performed by cluster profile software to reveal the regulatory relations among genes and provided a systematic understanding of the functional differentially expressed genes at the transcriptional level.GSE81279 was used to validate the association between core genes and clinical information. ResultsFor immune cells, T-cell gamma delta and monocyte showed a trend toward reduction. The connection between the most prominent GO terms showed HBB, GATA2, NAA35, TCL1A, SECISBP2L, CLC, AGPAT5, CCR3, LTF, MALAT1, MS4A3 were significantly differentially expressed in MS. Gene set enrichment result was presented CDKN1A, DDB2, MME HMGN1, XPC, RELA for subsequent analysis.GSE81279 showed five types of immune cells revealed important links with MS. GSEA and layered KEGG analyses revealed that enrichment of immune response-related in primary immunodeficiency, it also consistent with previous studies. We got 10 genes, including HLA-DR, IL7R, HBB, TNFRSF1A, CYP27B1, NR1H3, IL2RA, TNFR1, BAFF, and CYP2R1 had close connections to clinical features. ConclusionsOur study identifies immune cell infiltration with microarray data of the plasma in MS by using CIBERSORT analysis, we also provide novel information for further study of genes of multiple sclerosis.

scholarly journals Transcription Factors That Regulate the Pathogenesis of Ulcerative Colitis

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Bing Zhang ◽  
Tao Sun
Keyword(s):  
Ulcerative Colitis ◽  
Transcription Factors ◽  
Immune Cells ◽  
Target Genes ◽  
Immune Cell ◽  
Adaptive Immune Response ◽  
Differentially Expressed ◽  
Estrogen Signaling ◽  
Functional Roles ◽  
Bowel Diseases

Ulcerative colitis (UC) is one of the inflammatory bowel diseases (IBD) characterized by occurrence in the rectum and sigmoid colon of young adults. However, the functional roles of transcription factors (TFs) and their regulating target genes and pathways are not fully known in ulcerative colitis (UC). In this study, we collected gene expression data to identify differentially expressed TFs (DETFs). We found that differentially expressed genes (DEGs) were significantly enriched in the target genes of HOXA2, IKZF1, KLF2, XBP1, EGR2, ETV7, BACH2, CBFA2T3, HLF, and NFE2. TFs including BACH2, CBFA2T3, EGR2, ETV7, NFE2, and XBP1, and their target genes were significantly enriched in signaling by interleukins. BACH2 target genes were enriched in estrogen receptor- (ESR-) mediated signaling and nongenomic estrogen signaling. Furthermore, to clarify the functional roles of immune cells on the UC pathogenesis, we estimated the immune cell proportions in all the samples. The accumulated effector CD8 and reduced proportion of naïve CD4 might be responsible for the adaptive immune response in UC. The accumulation of plasma in UC might be associated with increased gut permeability. In summary, we present a systematic study of the TFs by analyzing the DETFs, their regulating target genes and pathways, and immune cells. These findings might improve our understanding of the TFs in the pathogenesis of UC.

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