Comprehensive Bioinformatics Analysis Identifies POLR2I as a Key Gene in the Pathogenesis of Hypertensive Nephropathy.
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SUBMITTER: You S
PROVIDER: S-EPMC8375388 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Intracerebral hemorrhage (ICH) is a dangerous neurological disease. The mechanism of ferroptosis in ICH remains unclear. Using bioinformatics analysis, we aimed to identify the key molecules involved in ferroptosis and provide treatment targets for ICH to further explore the mechanism of ferroptosis in ICH. GSE24265 was downloaded from the Gene Expression Omnibus (GEO) dataset and intersected with ferroptosis genes. A total of 45 differentially expressed genes (DEGs) were selected, most of which were involved in the TNF signaling pathway and oxidative stress response. Key modules constructed by the protein-protein interaction (PPI) network analysis and screening of genes related to the TNF signaling pathway led to the confirmation of the following genes of interest: MAPK1, MAPK8, TNFAIP3, ATF4, and SLC2A1. Moreover, MAPK1 was one of the key genes related to TNF signaling and oxidative stress, and it may play an important role in ferroptosis after cerebral hemorrhage. The MAPK1-related molecules included hsa-miR-15b-5P, hsa-miR-93-5P, miR-20b-5p, SNHG16, XIST, AC084219.4, RP11-379K17.11, CTC-444N24.11, GS1-358P8.4, CTB-89H12.4, RP4-773N10.5, and FGD5-AS1. We also generated a hemorrhage rat model, which was used to conduct exercise intervention in ICH rats, and qRT-PCR was used to assess the expression levels of our genes of interest. The mRNA levels after cerebral hemorrhage showed that MAPK1, ATF4, SLC2A1, and TNFAIP3 were upregulated, whereas MAPK8 was downregulated. Treadmill training increased the expression of anti-inflammatory molecules TNFAIP3 and SLC2A1 and reduced the expression of MAPK1, ATF4, and MAPK8, indicating that treadmill training may be utilized as antioxidant therapy to decrease neuronal ferroptosis. The results of this study indicated that the MAPK1-related mRNA-miRNA-lncRNA interaction chain could be potentially employed as a biomarker of the inception and progression of ferroptosis after cerebral hemorrhage.
| S-EPMC8215678 | biostudies-literature
Project description:Objective: Ferroptosis has an important role in developing pulmonary fibrosis. The present project aimed to identify and validate the potential ferroptosis-related genes in pulmonary fibrosis by bioinformatics analyses and experiments. Methods: First, the pulmonary fibrosis tissue sequencing data were obtained from Gene Expression Omnibus (GEO) and FerrDb databases. Bioinformatics methods were used to analyze the differentially expressed genes (DEGs) between the normal control group and the pulmonary fibrosis group and extract ferroptosis-related DEGs. Hub genes were screened by enrichment analysis, protein-protein interaction (PPI) analysis, and random forest algorithm. Finally, mouse pulmonary fibrosis model was made for performing an exercise intervention and the hub genes' expression was verified through qRT-PCR. Results: 13 up-regulated genes and 7 down-regulated genes were identified as ferroptosis-related DEGs by comparing 103 lung tissues with idiopathic pulmonary fibrosis (IPF) and 103 normal lung tissues. PPI results indicated the interactions among these ferroptosis-related genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment and Genome-Ontology (GO) enrichment analyses showed that these ferroptosis-related genes involved in the organic anion transport, response to hypoxia, response to decrease oxygen level, HIF-1 signaling pathway, renal cell carcinoma, and arachidonic acid metabolism signaling pathway. The confirmed genes using PPI analysis and random forest algorithm included CAV1, NOS2, GDF15, HNF4A, and CDKN2A. qRT-PCR of the fibrotic lung tissues from the mouse model showed that the mRNA levels of NOS2 and GDF15 were up-regulated, while CAV1 and CDKN2A were down-regulated. Also, treadmill training led to an increased expression of CAV1 and CDKN2A and a decrease in the expression of NOS2 and GDF15. Conclusion: Using bioinformatics analysis, 20 potential genes were identified to be associated with ferroptosis in pulmonary fibrosis. CAV1, NOS2, GDF15, and CDKN2A were demonstrated to be influencing the development of pulmonary fibrosis by regulating ferroptosis. These findings suggested that, as an aerobic exercise treatment, treadmill training reduced ferroptosis in the pulmonary fibrosis tissues, and thus, reduces inflammation in the lungs. Aerobic exercise training initiate concomitantly with induction of pulmonary fibrosis reduces ferroptosis in lung. These results may develop our knowledge about pulmonary fibrosis and may contribute to its treatment.
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Project description:BACKGROUND:Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. METHOD:We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. RESULTS:The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. CONCLUSIONS:We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.
| S-EPMC7312768 | biostudies-literature
Project description:In order to further elucidate the potential correlations and treatments of IgA nephropathy (IgAN) and hypertensive nephropathy (HT), bioinformatics analysis of IgAN and HT was performed. The mRNA expression profiles of human renal biopsy samples from patients with IgAN, patients with HT and pre?transplant healthy living controls (LD) were downloaded from the Gene Expression Omnibus database. Then, the differentially expressed genes (DEGs) were identified and functions of DEGs were analyzed. Finally, the regulatory networks containing DEGs and related?transcription factors (TFs) were constructed using Cytoscape software. When compared with the LD group, 134 and 188 DEGs were obtained in the IgAN and HT groups, respectively. A total of 39 genes were altered in the HT group when compared with the IgAN group. In addition, 66 genes were shared in the IgAN and HT groups when compared with the LD group, 6 of which [early growth response 1, activating transcription factor 3, nuclear receptor subfamily 4 group A member 2 (NR4A2), NR4A1, v?maf avian musculoaponeurotic fibrosarcoma oncogene homolog F and Kruppel like factor 6] were identified as TFs. In addition, DEGs including interleukin (IL) 1 receptor antagonist, collagen type 4 ?2 chain, IL8, FBJ murine osteosarcoma viral oncogene homolog and somatostatin were enriched in a number of inflammation?associated biological processes, and DEGs including structural maintenance of chromosomes protein 3, v?crk avian sarcoma virus CT10 oncogene homolog and myosin 6 were enriched in non?inflammation?associated biological processes. Therefore, the differentially expressed TF genes and the genes associated with inflammation may be effective as potential therapeutic targets for IgAN and HT.
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Project description:BackgroundIslet β cells dysfunction (IBCD) is a cortical component in pathogenesis of type 2 diabetic mellitus (T2DM). However, the relationship of ferroptosis and IBCD remains unknown. This study was aimed to screen potential ferroptosis key genes to reveal latent physiological and pathological process of IBCD in T2DM.MethodsFirstly, T2DM key genes were screened by combining with differentially expressed genes (DEGs) analysis and WGCNA. Then, ferroptosis-related genes (FRGs) in IBCD of T2DM were identified by taking the intersection between T2DM key genes and FRGs. Finally, T2DM-FRGs were validated in another T2DM dataset as well as islet single-cell RNA sequencing dataset and the miRNA regulated T2DM-FRG was predicted by using four miRNA databases.Results89 T2DM key genes were identified between DEGs and WGCNA. Then, 3 T2DM-FRGs were screened by taking the intersection of T2DM key genes and FRGs, namely ITGA6, MGST1 and ENO2. At last, MGST1 were validated as the T2DM-FRG in another T2DM islet issues dataset and islet single-cell RNA sequencing dataset.ConclusionMGST1 may be the potential ferroptosis key gene of IBCD in T2DM.
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Project description:AIMS/INTRODUCTION:The aim of the present study was to identify candidate differentially expressed genes (DEGs) and pathways using bioinformatics analysis, and to improve our understanding of the cause and potential molecular events of diabetic nephropathy. MATERIALS AND METHODS:Two cohort profile datasets (GSE30528 and GSE33744) were integrated and used for deep analysis. We sorted DEGs and analyzed differential pathway enrichment. DEG-associated ingenuity pathway analysis was carried out. The screened gene expression feature was verified in the db/db mouse kidney cortex. Then, rat mesangial cells cultured with high-concentration glucose were used for verification. The target genes of transcriptional factor E26 transformation-specific-1 (ETS1) were predicted with online tools and validated using chromatin immunoprecipitation assay quantitative polymerase chain reaction. RESULTS:The two GSE datasets identified 89 shared DEGs; 51 were upregulated; and 38 were downregulated. Most of the DEGs were significantly enriched in cell adhesion, the plasma membrane, the extracellular matrix and the extracellular region. Quantitative reverse transcription polymerase chain reaction analysis validated the upregulated expression of Itgb2, Cd44, Sell, Fn1, Tgfbi and Il7r, and the downregulated expression of Igfbp2 and Cd55 in the db/db mouse kidney cortex. Chromatin immunoprecipitation assay quantitative polymerase chain reaction showed that Itgb2 was the target gene of transcription factor Ets1. ETS1 knockdown in rat mesangial cells decreased integrin subunit beta 2 expression. CONCLUSION:We found that EST1 functioned as an important transcription factor in diabetic nephropathy development through the promotion of integrin subunit beta 2 expression. EST1 might be a drug target for diabetic nephropathy treatment.
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Project description:Melanoma is the deadliest skin tumor and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma. We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553, and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein-protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples. Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL), and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL, and EGFR were identified in the TCGA database and melanoma tissues. The results suggested that FLG, DSG1, DSG3, IVL, and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma. These hub genes might well have clinical significance as diagnostic markers.
| S-EPMC7596746 | biostudies-literature
Project description:PURPOSE:Performing bioinformatics analyses using trabecular meshwork (TM) gene expression data in order to further elucidate the molecular pathogenesis of primary open-angle glaucoma (POAG), and to identify candidate target genes. METHODS:A systematic search in Gene Expression Omnibus and ArrayExpress was conducted, and quality control and preprocessing of the data was performed with ArrayAnalysis.org. Molecular pathway overrepresentation analysis was performed with PathVisio using pathway content from three pathway databases: WikiPathways, KEGG and Reactome. In addition, Gene Ontology (GO) analysis was performed on the gene expression data. The significantly changed pathways were clustered into functional categories which were combined into a network of connected genes. RESULTS:Ninety-two significantly changed pathways were clustered into five functional categories: extracellular matrix (ECM), inflammation, complement activation, senescence and Rho GTPase signalling. ECM included pathways involved in collagen, actin and cell-matrix interactions. Inflammation included pathways entailing NF-?B and arachidonic acid. The network analysis showed that several genes overlap between the inflammation cluster on the one hand, and the ECM, complement activation and senescence clusters on the other hand. GO analysis, identified additional clusters, related to development and corticosteroids. CONCLUSION:This study provides an overview of the processes involved in the molecular pathogenesis of POAG in the TM. The results show good face validity and confirm findings from histological, biochemical, genome-wide association and transcriptomics studies. The identification of known points of action for drugs, such as Rho GTPase, arachidonic acid, NF-?B, prostaglandins and corticosteroid clusters, supports the value of this approach to identify potential drug targets.
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Project description:Passive Heymann nephritis (PHN), the best characterized animal model of experimental membranous nephropathy, is characterized by subepithelial immune deposits, podocyte foot processes effacement and massive proteinuria beginning 4 days following disease induction. Although single genes involved in PHN have been studied, no whole genome-wide expression analysis of kidney tissue has been performed.Microarray analysis was performed to identify gene expression changes in PHN rat kidneys during the onset of proteinuria.Our results showed that 234 transcripts were differentially expressed in diseased animals compared to controls. Genes exclusively upregulated in diseased animals were mainly required for cell structure and motility, immunity and defense, cell cycle, and developmental processes. The single most increased gene was transgelin (Tagln) showing a 70-fold upregulation in animals with PHN. Protein-protein interaction analysis revealed the following four processes of major relevance in disease manifestation: (i) DNA damage and repair; (ii) changes in the extracellular matrix; (iii) deregulation of cytokines and growth factors, as well as (iv) rearrangements of the cytoskeleton.We show for the first time the complex interplay between multiple different genes in experimental membranous nephropathy, supporting a role for genomic approaches to better understanding and defining specific disease processes.
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Project description:BACKGROUND:Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism. METHODS:Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein-protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN. RESULTS:In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN. CONCLUSIONS:We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.
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