scholarly journals Glucotoxicity Activation of IL6 and IL11 and Subsequent Induction of Fibrosis May Be Involved in the Pathogenesis of Islet Dysfunction

2021 ◽  
Vol 8 ◽  
Author(s):  
Liqin Lu ◽  
Lili Zhuang ◽  
Ximei Shen ◽  
Liyong Yang
Keyword(s):  
Extracellular Matrix ◽  
Enrichment Analysis ◽  
Gene Clusters ◽  
Validation Dataset ◽  
Receptor Interaction ◽  
Sprague Dawley ◽  
Hub Genes ◽  
Roc Curve Analysis ◽  
Sprague Dawley Rats ◽  
Islet Dysfunction

Background: Islet dysfunction is the main pathological process of type 2 diabetes mellitus (T2DM). Fibrosis causes islet dysfunction, but the current mechanism is still unclear. Here, bioinformatics analysis identified gene clusters closely related to T2DM and differentially expressed genes related to fibrosis, and animal models verified the roles of these genes.Methods: Human islet transcriptomic datasets were obtained from the Gene Expression Omnibus (GEO), and weighted gene coexpression network analysis (WGCNA) was applied to screen the key gene modules related to T2DM and analyze the correlations between the modules and clinical characteristics. Enrichment analysis was performed to identify the functions and pathways of the key module genes. WGCNA, protein-protein interaction (PPI) analysis and receiver operating characteristic (ROC) curve analysis were used to screen the hub genes. The hub genes were verified in another GEO dataset, the islets of high-fat diet (HFD)-fed Sprague-Dawley rats were observed by H&E and Masson’s trichrome staining, the fibrotic proteins were verified by immunofluorescence, and the hub genes were tested by immunohistochemistry.Results: The top 5,000 genes were selected according to the median absolute deviation, and 18 modules were analyzed. The yellow module was highly associated with T2DM, and its positive correlation with glycated hemoglobin (HbA1c) was significantly stronger than that with body mass index (BMI). Enrichment analysis revealed that extracellular matrix organization, the collagen-containing extracellular matrix and cytokine−cytokine receptor interaction might influence T2DM progression. The top three hub genes, interleukin 6 (IL6), IL11 and prostaglandin-endoperoxide synthase 2 (PTGS2), showed upregulated expression in T2DM. In the validation dataset, IL6, IL11, and PTGS2 levels were upregulated in T2DM, and IL6 and PTGS2 expression was positively correlated with HbA1c and BMI; however, IL11 was positively correlated only with HbA1c. In HFD-fed Sprague-Dawley rats, the positive of IL6 and IL11 in islets was stronger, but PTGS2 expression was not significantly altered. The extent of fibrosis, irregular cellular arrangement and positive actin alpha 2 (ACTA2) staining in islets was significantly greater in HFD-fed rats than in normal diet-fed rats.Conclusion: Glucotoxicity is a major factor leading to increased IL6 and IL11 expression, and IL6-and IL11-induced fibrosis might be involved in islet dysfunction.

scholarly journals Identification of Core Prognosis-Related Candidate Genes in Chinese Gastric Cancer Population Based on Integrated Bioinformatics

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Mengjun Li ◽  
Xinhai Wang ◽  
Jun Liu ◽  
Xiang Mao ◽  
Dongbing Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Extracellular Matrix ◽  
Focal Adhesion ◽  
Chinese Population ◽  
Enrichment Analysis ◽  
Population Based ◽  
Receptor Interaction ◽  
Akt Signaling Pathway ◽  
Hub Genes ◽  
Upregulated Genes

Background. Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. There are great geographical differences in the incidence of GC, and somatic mutation rates of driver genes are also different. The present study is aimed at screening core prognosis-related candidate genes in Chinese gastric cancer population based on integrated bioinformatics for the early diagnosis and prognosis of GC. Methods. In the present study, the differentially expressed genes (DEGs) in GC were identified using four microarray datasets from the Gene Expression Omnibus (GEO) database. The samples of these datasets were all from China. Functional enrichment analysis of DEGs was conducted to evaluate the underlying molecular mechanisms involved in GC. Protein-protein interaction (PPI) network and cytoHubba were performed to determine hub genes associated with GC. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the hub genes. Results. A total of 240 DEGs were obtained through the RRA method, including 80 upregulated genes and 160 downregulated genes. Upregulated genes were mainly enriched in extracellular matrix organization, extracellular matrix, and extracellular matrix structural constituent. The downregulated genes were mainly enriched in digestion, extracellular space, and oxidoreductase activity. The KEGG pathway enrichment analysis showed that the upregulated genes were mainly associated with ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. And downregulated genes were mainly associated with the metabolism of xenobiotics by cytochrome P450, metabolic pathways, and gastric acid secretion. The transcriptional and translational expression levels of the genes including COL1A1, COL5A2, COL12A1, and VCAN were higher in GC tissues than normal tissues. Conclusion. A total of four genes including COL1A1, COL5A2, COL12A1, and VCAN were considered potential GC biomarkers in the Chinese population. And ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway were revealed to be important mechanisms of GC. Our findings provide novel insights into the occurrence and progression of GC in the Chinese population.

scholarly journals Identification of key genes in calcific aortic valve disease via weighted gene co-expression network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jin-Yu Sun ◽  
Yang Hua ◽  
Hui Shen ◽  
Qiang Qu ◽  
Jun-Yan Kan ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Network Analysis ◽  
Aortic Valve ◽  
Aortic Valve Disease ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Valve Disease ◽  
Hub Genes ◽  
Calcific Aortic Valve Disease ◽  
Underlying Mechanisms

Abstract Background Calcific aortic valve disease (CAVD) is the most common subclass of valve heart disease in the elderly population and a primary cause of aortic valve stenosis. However, the underlying mechanisms remain unclear. Methods The gene expression profiles of GSE83453, GSE51472, and GSE12644 were analyzed by ‘limma’ and ‘weighted gene co-expression network analysis (WGCNA)’ package in R to identify differentially expressed genes (DEGs) and key modules associated with CAVD, respectively. Then, enrichment analysis was performed based on Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, DisGeNET, and TRRUST database. Protein–protein interaction network was constructed using the overlapped genes of DEGs and key modules, and we identified the top 5 hub genes by mixed character calculation. Results We identified the blue and yellow modules as the key modules. Enrichment analysis showed that leukocyte migration, extracellular matrix, and extracellular matrix structural constituent were significantly enriched. SPP1, TNC, SCG2, FAM20A, and CD52 were identified as hub genes, and their expression levels in calcified or normal aortic valve samples were illustrated, respectively. Conclusions This study suggested that SPP1, TNC, SCG2, FAM20A, and CD52 might be hub genes associated with CAVD. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.

scholarly journals Identification of Hub Genes And Pathways of Gastric Adenocarcinoma Using Bioinformatics Analysis

2021 ◽  
Author(s):  
Yu Di
Keyword(s):  
Gastric Cancer ◽  
Extracellular Matrix ◽  
Gastric Adenocarcinoma ◽  
Cellular Response ◽  
Receptor Interaction ◽  
Signal Pathways ◽  
Connectivity Map ◽  
Hub Genes ◽  
Matrix Organization ◽  
Catabolic Process

Abstract Object: Understanding hub genes associated with gastric adenocarcinoma (GC) development could lead to effective advances to diagnose and treat the diseases. In order to discover possible signal pathways and hub genes for the disease, we utilized the bioinformatics tools to analyze its mechanism.Method: The gene chip of GSE7997was download from the GEO Datasets. Expression data of gastric cancer and its adjacent normal tissues were compared and the DEGs were acquired. The clusterProfiler and KEGG.db R packages were used for the analysis of its gene ontology process and KEGG pathways. What’s more, the PPI network was constructed by the STRING website. The hub genes were acquired by the plugin of the Cytohubba in Cytoscape. Finally, these genes were examined by the TCGA datasets and potential drugs were explored by Connectivity map.Results: The up regulated DEGs was mainly associated with the process of an extracellular matrix organization, an extracellular matrix organization, Collagen catabolic process, and multicellular organismal catabolic process. The down regulated DEGs have mainly associated with the process of digestion， cellular response to zinc ion， digestive system process, and organic hydroxy compound metabolic process. The up regulated DEGs was mainly located on PI3K-AKTsignal pathways, human papillomavirus infection，Cytokine-cytokine receptor interaction, and focal adhesion process. The down regulated genes were mainly associated with protein digestion and absorption, mineral absorption, and the pancreatic secretion. Cytohubba had found hub genes of COL1A2, COL5A1, COL4A1, COL5A2, COL6A3, COL11A1, SERPINH1, FN1, and down-regulated COL2A1.These genes were associated with the process of transforming growth factor, extracellular matrix, cell adhesion, wound healing and so on. As examined by the TCGA datasets, these altered genes were associated with overall survivaland no disease progress time (P<0.05). Finally, we got the small molecule drugs of fenofibrate, benzbromarone, semustine, chloroquine, ondansetron, hydroxyachillin, megestrol, ciclopirox and monastrol for gastric cancer by Connectivity map (P<0.05).Conclusion: As mentioned above, we got 9 hub genes and tested by the TCGA datasets of gastric adenocarcinoma. They were associated with overall survival and disease free progressive time in gastric cancer patients. The bioinformatical analysis of the disease may enhance the understanding of the mechanism of disorders.

scholarly journals Identification of potential diagnostic and prognostic biomarkers for LUAD based on TCGA and GEO databases

2021 ◽  
Author(s):  
Qiangqiang Zheng ◽  
Shihui Min ◽  
Qinghua Zhou
Keyword(s):  
Signaling Pathway ◽  
Clinical Features ◽  
Enrichment Analysis ◽  
Expression Level ◽  
Normal Lung ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Viral Carcinogenesis ◽  
Relationship Of

Accumulating evidence has demonstrated that gene alterations play a crucial role in LUAD development, progression, and prognosis. The current study aimed to identify the hub genes associated with LUAD. In the present study, we used TCGA database to screen the hub genes. Then, we validated the results by GEO datasets. Finally, we used cBioPortal, UALCAN, qRT-PCR, HPA database, TCGA database, and Kaplan-Meier plotter database to estimate the gene mutation, gene transcription, protein expression, clinical features of hub genes in patients with LUAD. A total of 5,930 DEGs were screened out in TCGA database. Enrichment analysis revealed that DEGs were involved in the transcriptional misregulation in cancer, viral carcinogenesis, cAMP signaling pathway, calcium signaling pathway, and ECM-receptor interaction. The combining results of MCODE and CytoHubba showed that ADCY8, ADRB2, CALCA, GCG, GNGT1, and NPSR1 were hub genes. Then, we verified the above results by GSE118370, GSE136043, and GSE140797 datasets. Compared with normal lung tissues, the expression level of ADCY8 and ADRB2 were lower in LUAD tissues, but the expression level of CALCA, GCG, GNGT1, and NPSR1 were higher. In the prognosis analyses, the low expression of ADCY8 and ADRB2 and the high expression of CALCA, GCG, GNGT1, and NPSR1 were correlated with poor OS and poor PFS. The significant differences in the relationship of the expression of 6 hub genes and clinical features were observed. In conclusion, 6 hub genes will not only contribute to elucidating the pathogenesis of LUAD, and may be potential therapeutic targets for LUAD.

scholarly journals Screening and Identification of Key Biomarkers in Breast Cancer with Brain Metastasis: Evidence from Bioinformatic Analysis

2020 ◽  
Author(s):  
tao ming Shao ◽  
zhi yang Hu ◽  
wen wei Li ◽  
long yun Pan
Keyword(s):  
Breast Cancer ◽  
Protein Interactions ◽  
Poor Prognosis ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.

Abstract P628: Angiotensin 1-7 Mas Receptor and Dopamine D1 receptor Interaction as a Novel Natriuretic Mechanism in Rat Kidneys

Hypertension ◽  
2015 ◽  
Vol 66 (suppl_1) ◽  
Author(s):  
Andrea C Diaz Diaz ◽  
Mustafa F Lokhandwala ◽  
Faraz Jafri ◽  
Anees A Banday
Keyword(s):  
Blood Pressure ◽  
Sodium Excretion ◽  
Dopamine D1 Receptor ◽  
D1 Receptor ◽  
Receptor Interaction ◽  
Sprague Dawley ◽  
Positive Interaction ◽  
Mas Receptor ◽  
Sprague Dawley Rats ◽  
Renal Dopamine

Evidence to date suggests that a positive interaction between natriuretic factors promotes sodium excretion to maintain sodium homeostasis and blood pressure. Although the involvement of renal dopamine D1 receptor (D1R) in promoting sodium excretion is well established; the role of Angiotensin (Ang) 1-7 Mas receptor (MasR) is not clear. Here we provide evidence for a functional interaction between these two renal G protein-coupled receptors which suggests that natriuretic response to Ang 1-7 via MasR is dependent on D1R activation. Male Sprague Dawley rats of comparable weight and age were infused with Ang 1-7, MasR antagonist DPro, D1R agonist SKF38393 and D1R antagonist SCH23390. Blood pressure was monitored throughout the experimental procedure and none of the infused drugs affected the pressure. Animals infused with saline alone served as controls. Infusion of Ang1-7 caused significant natriuresis and robust diuresis compared to saline. SKF38393 infusion also induced significant natriuresis and diuresis when compared to saline infusion. Both natriuretic and diuretic response to Ang 1-7 was blocked by Dpro and SCH23390. However, Dpro failed to block SKF38393 response. Concomitant infusion of SKF38393 and Ang 1-7 did not show a cumulative natriuretic or diuretic effect when compared to SKF38393 or Ang 1-7 infusion alone. FENa (%), control (saline): 0.30 ± 0.09; Ang 1-7: 1.03 ± 0.21; Ang 1-7 plus Dpro: 0.49 ± 0.11; Ang 1-7 plus SCH23390: 0.36 ± 0.10; SKF38393: 0.83 ± 0.16; SKF38393 plus SCH23390: 0.41 ± 0.09; SKF38393 plus Dpro: 0.82 ± 0.17; Ang 1-7 plus SKF38393: 1.06 ± 0.21. These data suggest that Ang 1-7 via MasR causes natriuresis which is dependent on D1R activation. On the other hand, renal D1R-mediated sodium excretion is independent of MasR. This study is a paradigm shift as these data identify a novel functional unidirectional interaction between renal MasR and D1R which deviates from commonly known receptor-receptor interaction.

scholarly journals The Important Role of Perituberal Tissue in Epileptic Patients with Tuberous Sclerosis Complex by the Transcriptome Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shuqiang Li ◽  
Huijie Shao ◽  
Liansheng Chang
Keyword(s):  
Tuberous Sclerosis ◽  
Tuberous Sclerosis Complex ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes ◽  
R Language ◽  
Protein Protein Interaction

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.

17β-Estradiol supplementation reduces tubulointerstitial fibrosis by increasing MMP activity in the diabetic kidney

2007 ◽  
Vol 292 (2) ◽  
pp. R769-R777 ◽  
Author(s):  
Richard W. Mankhey ◽  
Corinne C. Wells ◽  
Faizah Bhatti ◽  
Christine Maric
Keyword(s):  
Extracellular Matrix ◽  
Diabetic Nephropathy ◽  
Tubulointerstitial Fibrosis ◽  
Relative Optical Density ◽  
Sprague Dawley ◽  
Type Iv ◽  
Sprague Dawley Rats ◽  
Ecm Degradation ◽  
17Β Estradiol ◽  
Renal Expression

We previously reported that supplementation with 17β-estradiol (E2) attenuates albuminuria, glomerulosclerosis, and tubulointerstitial fibrosis in diabetic nephropathy. The present study examined the mechanisms by which E2 regulates extracellular matrix (ECM) metabolism, a process that contributes to the development of glomerulosclerosis and tubulointerstitial fibrosis. The study was performed in female nondiabetic (ND), streptozotocin-induced diabetic (D), and diabetic with E2 supplementation (D+E2) Sprague-Dawley rats for 12 wk. Diabetes was associated with an increase in the renal expression of collagen α type IV [ND, 0.22 ± 0.02; D, 0.99 ± 0.09 relative optical density (ROD); P < 0.05] and fibronectin protein (ND, 0.36 ± 0.08; D, 1.47 ± 0.08 ROD; P < 0.05), as measured by Western blot analysis. E2 supplementation partially attenuated this increase in collagen α type IV (D+E2, 0.47 ± 0.10 ROD) and fibronectin (D+E2, 0.71 ± 0.16 ROD) protein expression associated with D. Diabetes was also associated with a decrease in the expression of matrix metalloproteinase (MMP) isoform MMP-2 (ND, 0.79 ± 0.01; D, 0.62 ± 0.06 ROD; P < 0.05) and MMP-9 protein (ND, 0.49 ± 0.02; D, 0.33 ± 0.03 ROD; P < 0.05). E2 supplementation restored MMP-2 and MMP-9 protein to levels similar or even greater than in the ND kidneys (MMP-2, 0.75 ± 0.06; MMP-9, 0.73 ± 0.01 ROD). The activities of MMP-2 (ND, 7.88 ± 0.44; D, 5.60 ± 0.54 ROD; P < 0.05) and MMP-9 (ND, 29.9 ± 1.8; D, 12.9 ± 2.3 ROD; P < 0.05), as measured by zymography, were also decreased with D. E2 supplementation restored MMP-2 and MMP-9 activity to levels similar to that in ND kidneys (MMP-2, 7.66 ± 0.35; MMP-9, 21.4 ± 2.9 ROD). We conclude that E2 supplementation is renoprotective by attenuating glomerulosclerosis and tubulointerstitial fibrosis by reducing ECM synthesis and increasing ECM degradation.

scholarly journals Identification of genes and pathways involved in malignant pleural mesothelioma using bioinformatics methods

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xingsheng Liu ◽  
Kun Qian ◽  
Gaojun Lu ◽  
Peng Chen ◽  
Yi Zhang
Keyword(s):  
Malignant Pleural Mesothelioma ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Pleural Mesothelioma ◽  
Hub Genes ◽  
Poor Overall Survival ◽  
Microarray Datasets ◽  
Functional Analyses

Abstract Background Malignant pleural mesothelioma (MPM) is a rare tumor in the pleura. This study was carried out to identify key genes and pathways that may be involved in MPM. Methods Microarray datasets GSE51024 and GSE2549 were analyzed for differentially expressed genes (DEGs) between normal and MPM tissues. The identified DEGs were subjected to functional analyses using bioinformatics tools. Results A total of 276 DEGs were identified, consisting of 187 downregulated and 79 upregulated genes. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis indicated that the DEGs were enriched in extracellular structure organization, extracellular matrix, and ECM−receptor interaction. Due to high degree of connectivity among 24 hub genes, EZH2 and HMMR are likely to play roles in the carcinogenesis and progression of MPM. The two genes were found over-expressed in MPM tissues. Patients with elevated EZH2 and HMMR expressions had poor overall survival. Conclusions EZH2 and HMMR are identified to be the hub genes for MPM and they may be further characterized to better understand the molecular mechanisms underlying the carcinogenesis of MPM.

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