scholarly journals Construction of a Novel Ferroptosis-Related Gene Signature of Atherosclerosis

Author(s):  
Tucheng Huang ◽  
Kangjie Wang ◽  
Yuewei Li ◽  
Yanchen Ye ◽  
Yangxin Chen ◽  
...  

Atheroclerosis refers to a chronic inflammatory disease featured by the accumulation of fibrofatty lesions in the intima of arteries. Cardiovasular events associated with atherosclerosis remain the major causes of mortality worldwide. Recent studies have indicated that ferroptosis, a novel programmed cell death, might participate in the process of atherosclerosis. However, the ferroptosis landscape is still not clear. In this study, 59 genes associated with ferroptosis were ultimately identified in atherosclerosis in the intima. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for functional annotation. Through the construction of protein–protein interaction (PPI) network, five hub genes (TP53, MAPK1, STAT3, HMOX1, and PTGS2) were then validated histologically. The competing endogenous RNA (ceRNA) network of hub genes was ultimately constructed to explore the regulatory mechanism between lncRNAs, miRNAs, and hub genes. The findings provide more insights into the ferroptosis landscape and, potentially, the therapeutic targets of atherosclerosis.

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Anbang Wang ◽  
Ming Chen ◽  
Hui Wang ◽  
Jinming Huang ◽  
Yi Bao ◽  
...  

Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system. The study aimed to identify genetic characteristics and reveal the underlying mechanisms in RCC. GSE53757, GSE46699, and TCGA KIRC database (n = 897) were analyzed to screen differentially expressed genes (DEGs) in RCC. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by the analysis of the protein-protein interaction (PPI) network of the DEGs by Cytoscape software. In all, 834 DEGs were identified in RCC, including 416 upregulated genes and 418 downregulated genes. The top 10 hub genes, VEGFA, EGFR, EGF, CD44, CD86, FN1, ITGAM, ITGB2, TLR2, and PTPRC, were identified from the PPI network according to the core degree. The following subnetwork revealed that these significant modules were enriched in positive regulation of response to external stimulus, regulation of leukocyte-mediated immunity, and regulation of exocytosis. The expressions of these hub genes were also validated using qRT-PCR and IHC in Changzheng RCC database (n = 160). We especially found that half of the top ten hub genes were cell adhesion-related molecules, which were associated with RCC progression and poor prognosis. In conclusion, these hub genes, particularly cell adhesion-related molecules, could be used as prognostic biomarkers and potential therapeutic targets for RCC.


2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Weiwei Liang ◽  
FangFang Sun

Abstract This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein–protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.


2020 ◽  
Author(s):  
Fu Jun Liao ◽  
Peng-Fei Zheng ◽  
Yao-Zong Guan ◽  
Wei Li

Abstract Background: The purpose of this study was to explore the potential molecular targets of hyperlipidaemia and the related molecular mechanisms.Methods: The microarray data set of GSE66676 obtained from patients with hyperlipidaemia was downloaded. The weighted gene co‑expression network (WGCNA) analysis was used to analyze the gene expression profile and royalblue module was considered as the highest correlation. Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and genomes (KEGG) pathway enrichment analyses were implemented for the identification of genes in the royalblue module using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8; http://david.abcc.ncifcrf.gov). A protein-protein interaction (PPI) network was established by using the online STRING tool. Then, several hub genes were identified by the MCODE and cytoHubba plug-ins in Cytoscape software.Results: The significant module (royalblue) identified was associated with TC, TG and Non-HDL-C. GO and KEGG enrichment analyses revealed that the genes in the royalblue module were associated with carbon metabolism, steroid biosynthesis, fatty acid metabolism and biosynthesis of unsaturated fatty acids pathways. SQLE (degree = 17) was revealed as key molecules that associated with hypercholesterolemia (HCH) and SCD was revealed as key molecules that associated with hypertriglyceridemia (HTG). Meanwhile, RT-qPCR analysis also confirmed the above results based on our HCH/HTG samples.Conclusions: SQLE and SCD are related to hyperlipidaemia, SQLE/SCD may be new targets for cholesterol-lowering or triglyceride-lowering therapy, respectively.


2020 ◽  
Author(s):  
Lili Li ◽  
Jian Lv ◽  
Yuan He ◽  
Zhihua Wang

Abstract Background: Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear. Methods: This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment. Results: Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy. Conclusions: Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs.


2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110295
Author(s):  
Yunfei Zhang ◽  
Yue Huang ◽  
Wen-xia Chen ◽  
Zheng-min Xu

Objective This study aimed to explore the potential molecular mechanism of allergic rhinitis (AR) and identify gene signatures by analyzing microarray data using bioinformatics methods. Methods The dataset GSE19187 was used to screen differentially expressed genes (DEGs) between samples from patients with AR and healthy controls. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied for the DEGs. Subsequently, a protein–protein interaction (PPI) network was constructed to identify hub genes. GSE44037 and GSE43523 datasets were screened to validate critical genes. Results A total of 156 DEGs were identified. GO analysis verified that the DEGs were enriched in antigen processing and presentation, the immune response, and antigen binding. KEGG analysis demonstrated that the DEGs were enriched in Staphylococcus aureus infection, rheumatoid arthritis, and allograft rejection. PPI network and module analysis predicted seven hub genes, of which six ( CD44, HLA-DPA1, HLA-DRB1, HLA-DRB5, MUC5B, and CD274) were identified in the validation dataset. Conclusions Our findings suggest that hub genes play important roles in the development of AR.


2020 ◽  
Author(s):  
Lili Li ◽  
Jian Lv ◽  
Yuan He ◽  
Zhihua Wang

Abstract Background: Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear. Methods: This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment. Results: Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy. Conclusions: Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs.


Author(s):  
Xitong Yang ◽  
Pengyu Wang ◽  
Shanquan Yan ◽  
Guangming Wang

AbstractStroke is a sudden cerebrovascular circulatory disorder with high morbidity, disability, mortality, and recurrence rate, but its pathogenesis and key genes are still unclear. In this study, bioinformatics was used to deeply analyze the pathogenesis of stroke and related key genes, so as to study the potential pathogenesis of stroke and provide guidance for clinical treatment. Gene Expression profiles of GSE58294 and GSE16561 were obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IS and normal control group. The different expression genes (DEGs) between IS and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), the function and pathway enrichment analysis of DEGS were performed. Then, a protein–protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. A total of 85 DEGs were screened out in this study, including 65 upward genes and 20 downward genes. In addition, 3 KEGG pathways, cytokine − cytokine receptor interaction, hematopoietic cell lineage, B cell receptor signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the PPI network and CytoHubba, 10 hub genes including CEACAM8, CD19, MMP9, ARG1, CKAP4, CCR7, MGAM, CD79A, CD79B, and CLEC4D were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including hsa-mir-146a-5p, hsa-mir-7-5p, hsa-mir-335-5p, and hsa-mir-27a- 3p, were predicted as possibly the key miRNAs. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of ischemic stroke, and provide a new strategy for clinical therapy.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.


2022 ◽  
Vol 12 (3) ◽  
pp. 523-532
Author(s):  
Xin Yan ◽  
Chunfeng Liang ◽  
Xinghuan Liang ◽  
Li Li ◽  
Zhenxing Huang ◽  
...  

<sec> <title>Objective:</title> This study aimed to identify the potential key genes associated with the progression and prognosis of adrenocortical carcinoma (ACC). </sec> <sec> <title>Methods:</title> Differentially expressed genes (DEGs) in ACC cells and normal adrenocortical cells were assessed by microarray from the Gene Expression Omnibus database. The biological functions of the classified DEGs were examined by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein–protein interaction (PPI) network was mapped using Cytoscape software. MCODE software was also used for the module analysis and then 4 algorithms of cytohubba software were used to screen hub genes. The overall survival (OS) examination of the hub genes was then performed by the ualcan online tool. </sec> <sec> <title>Results:</title> Two GSEs (GSE12368, GSE33371) were downloaded from GEO including 18 and 43 cases, respectively. One hundred and sixty-nine DEGs were identified, including 57 upregulated genes and 112 downregulated genes. The Gene Ontology (GO) analyses showed that the upregulated genes were significantly enriched in the mitotic cytokines is, nucleus and ATP binding, while the downregulated genes were involved in the positive regulation of cardiac muscle contraction, extracellular space, and heparin-binding (P < 0.05). The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway examination showed significant pathways including the cell cycle and the complement and coagulation cascades. The protein– protein interaction (PPI) network consisted of 162 nodes and 847 edges, including mitotic nuclear division, cytoplasmic, protein kinase binding, and cell cycle. All 4 identified hub genes (FOXM1, UBE2C, KIF11, and NDC80) were associated with the prognosis of adrenocortical carcinoma (ACC) by survival analysis. </sec> <sec> <title>Conclusions:</title> The present study offered insights into the molecular mechanism of adrenocortical carcinoma (ACC) that may be beneficial in further analyses. </sec>


2020 ◽  
Author(s):  
Zhiqiang Liu ◽  
Bolong Wang

Abstract Background: Jianghuang (JH) is a popular ingredient in blood-regulating traditional Chinese Medicine (TCM) that could be effective for the treatment of various diseases. We demonstrate the compatibility laws and system pharmacological mechanisms of the key formula containing JH by leveraging data mining of bioinformatics databases.Material/Methods: The compatibility laws of blood-regulating formulae containing JH from the Chinese Traditional Medicine Formula Dictionary were analyzed using a generalized rule induction (GRI) algorithm implemented. The putative target gene and miRNA were retrieved via a combination of the Arrowsmith knowledge discovery tool and FunRich 3.1.3. System pharmacological mechanisms are traced by their protein-protein interaction (PPI) network, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted using Uniprot, the Human Protein Atlas (HPA), STRING 11.0, and KOBAS 3.0.Results: We found that the JH-CX-DG formula (Ligusticum chuanxiong-Angelica sinensis) could represent a key formula containing JH in blood-regulating TCM formulae. The JH-CX-DG formula was observed to directly target AKT, TLR4, caspase-3, PI3K, mTOR, p38 MAPK, VEGF, iNOS, Nrf2, BDNF, NF-κB, Bcl-2, and Bax 13 targets and regulate targets through 13 miRNA. The PPI network and KEGG pathway enrichment analysis showed that the JH-CX-DG formula possess potential pharmacological effects including anti-inflammatory, improving microcirculation, and anti-tumor through the regulation of multiple pathways including PI3K/Akt, MAPK, Toll-like receptor, T cell receptor, EGFR, VEGFR, Apoptosis, HIF-1 (p < 0.05).Conclusion: The JH-CX-DG formula can exert beneficial pharmacological effects through multi-target and multi-pathway interactions. It can be effectively administered for the treatment of inflammatory diseases, microcirculation disorders, cardiovascular disease, and cancer. We found a new effective drug formula through analyzing the compatibility law and systemic pharmacological mechanism of JH. Our study provides a theoretical basis and directions for subsequent research on the JH-CX-DG formula.


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