scholarly journals The Study of Angptl4-Modulated Podocyte Injury in IgA Nephropathy

2021 ◽  
Vol 11 ◽  
Author(s):  
Sha Jia ◽  
Xiaofeng Peng ◽  
Ludan Liang ◽  
Ying Zhang ◽  
Meng Li ◽  
...  
Keyword(s):  
Iga Nephropathy ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Healthy Controls ◽  
Podocyte Injury ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Significant Difference ◽  
Limma Package

BackgroundIncreasing evidence shows that Angptl4 affects proteinuria in podocytes injured kidney disease, however, whether there is a relationship between Angptl4 and IgA nephropathy (IgAN) has not been studied yet.MethodsPlasma and urine samples were obtained from 71 patients with IgAN and 61 healthy controls. Glomeruli from six renal biopsy specimens (three IgAN patients and three healthy controls) were separated by RNA-Seq. Differentially expressed genes (DEGs) related to podocytes and Angptl4 between IgAN patients and healthy controls were performed using the Limma package. Gene set enrichment analysis was used to determine whether there was a statistically significant difference between the two groups. STRING was used to create a protein-protein interaction network of DEGs. Association analysis between Angptl4 levels and clinical features of IgAN was performed.ResultsThirty-three podocyte-related and twenty-three Angpt4-related DEGs were found between IgAN patients and healthy controls. By overlapping the genes, FOS and G6PC were found to be upregulated in IgAN patients, while MMP9 was downregulated in IgAN patients. Plasma and urine Angptl4 levels were closely related to the degree of podocyte injury and urine protein, but not to the protein-creatine ratio.ConclusionOur findings show that Angptl4 levels in plasma and urine are related to podocyte damage and, therefore, may be a promising tool for assessing the severity of IgAN patients to identify and reverse the progression to ESRD.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals MiR-574-5P, miR-1827, And miR-4429 As Potential Biomarkers For Schizophrenia

2021 ◽  
Author(s):  
Omran Davarinejad ◽  
Sajad Najafi ◽  
Hossein Zhaleh ◽  
Farzaneh Golmohammadi ◽  
Farnaz Radmehr ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Meta Analysis ◽  
Interaction Network ◽  
Receiver Operating Curve ◽  
Healthy Controls ◽  
Protein Protein Interaction ◽  
Mirna Array ◽  
Expression Arrays ◽  
Limma Package ◽  
Novel Biomarkers

Abstract Schizophrenia is a severe chronic debilitating disorder with millions of affected individuals. Lack of a reliable mollecular diagnostic invokes the identification of novel biomarkers. To elucidate the molecular basis of the disease, two mRNA expression arrays including GSE93987 and GSE38485, and one miRNA array, GSE54914, were downloaded from GEO, and meta-analysis was performed for mRNA expression arrays by employment of metaDE package. By WGCNA package, we performed network analysis for both mRNA expression arrays separately. Then, we made protein-protein interaction network for significant modules. Limma package was employed to analyze the miRNA array and dysregulated miRNAs (DEMs) were identified. Using genes of significant modules and DEMs, a mRNA-miRNA network was constructed and hub genes and miRNAs were identified. To confirm the dysregulation of genes, expression values were evaluated by available datasets including GEO series GSE62333, GSE93987, and GSE38485. The ability of the detected hub miRNAs to discriminate Schizophrenia from healthy controls was evaluated by assessing the receiver-operating curve. Finally, by performing Real-Time PCR, the expression level of genes and miRNAs were evaluated in 40 Schizophrenia patients compared with healthy controls. The results confirmed dysregulation of hsa-miR-574-5P, hsa-miR-1827, hsa-miR-4429, CREBRF, ARPP19, TGFBR2, and YWHAZ in blood samples of schizophrenia patients.

scholarly journals Identification of Potential Prognostic Biomarker for Predicting Survival in Multiple Myeloma Using Bioinformatics Analysis and Experiments

2021 ◽  
Vol 12 ◽  
Author(s):  
Jian Zhou ◽  
Menghui Zhang ◽  
Yan Zhang ◽  
Xi Shi ◽  
Linlin Liu ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Plasma Cells ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
New Biomarkers ◽  
Protein Protein Interaction Network

Multiple myeloma (MM) is a malignant disease of plasma cells, which remains incurable because of its unclear mechanism and drug resistance. Herein, we aimed to explore new biomarkers and therapeutic targets in MM. After screening differentially expressed genes (DEGs) in GSE6477 and GSE13591 dataset, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs using DAVID online database. The results indicated that the downregulated DEGs were mainly enriched in the immune-associated biological process. The protein–protein interaction network was constructed by STRING database, on which we performed module analysis and identified key genes. Gene set enrichment analysis (GSEA) and Kaplan–Meier analysis showed that RRM2 could be a novel biomarker in MM diagnosis. We further confirmed that novel RRM2 inhibitor osalmid inhibited MM cell proliferation and triggered cell cycle S phase arrest. Targeting RRM2 was expected to develop new therapeutic strategies for malignant MM.

Identification of IL-6 as a potential mediator of the myocardial fibrosis that occurs in response to surgery with cardiopulmonary bypass in children with Tetralogy of Fallot

2021 ◽  
pp. 1-7
Author(s):  
Hongtao Liu ◽  
Yun Zhang ◽  
Zhenhai Wu ◽  
Liangqing Zhang
Keyword(s):  
Heart Failure ◽  
Network Analysis ◽  
Myocardial Fibrosis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Gene Correlation ◽  
Cell Expression

Abstract Background: Tetralogy of Fallot is a common CHD. Studies have shown a close link between heart failure and myocardial fibrosis. Interleukin-6 has been suggested to be a post-independent factor of heart failure. This study aimed to explore the relationship between IL-6 and myocardial fibrosis during cardiopulmonary bypass. Material and Methods: We downloaded the expression profile dataset GSE132176 from Gene Expression Omnibus. After normalising the raw data, Gene Set Enrichment Analysis and differential gene expression analysis were performed using R. Further, a weighted gene correlation network analysis and a protein–protein interaction network analysis were used to identify HUB genes. Finally, we downloaded single-cell expression data for HUB genes using PanglaoDB. Results: There were 119 differentially expressed genes in right atrium tissues comparing the post-CPB group with the pre-CPB group. IL-6 was found to be significantly up-regulated in the post-CPB group. Six genes (JUN, FOS, ATF3, EGR1, IL-6, and PTGS2) were identified as HUB genes by a weighted gene correlation network analysis and a protein–protein interaction network analysis. Gene Set Enrichment Analysis showed that IL-6 affects the myocardium during CPB mainly through the JAK/STAT signalling pathway. Finally, we used PanglaoDB data to analyse the single-cell expression of the HUB genes. Conclusion: Our findings suggest that high expression of IL-6 and the activation of the JAK/STAT signalling pathway during CPB maybe the potential mechanism of myocardial fibrosis. We speculate that the high expression of IL-6 might be an important factor leading to heart failure after ToF surgery. We expect that these findings will provide a basis for the development of targeted drugs.

scholarly journals Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingni Wu ◽  
Xiaomeng Xia ◽  
Ye Hu ◽  
Xiaoling Fang ◽  
Sandra Orsulic
Keyword(s):  
Network Analysis ◽  
Topological Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Messenger Rnas ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Highly Correlated

Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.

scholarly journals Feature selection with the Fisher score followed by the Maximal Clique Centrality algorithm can accurately identify the hub genes of hepatocellular carcinoma

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chengzhang Li ◽  
Jiucheng Xu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Random Forest ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Maximal Clique ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Fisher Score ◽  
Protein Protein Interaction ◽  
Kaplan Meier

AbstractThis study aimed to select the feature genes of hepatocellular carcinoma (HCC) with the Fisher score algorithm and to identify hub genes with the Maximal Clique Centrality (MCC) algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to examine the enrichment of terms. Gene set enrichment analysis (GSEA) was used to identify the classes of genes that are overrepresented. Following the construction of a protein-protein interaction network with the feature genes, hub genes were identified with the MCC algorithm. The Kaplan–Meier plotter was utilized to assess the prognosis of patients based on expression of the hub genes. The feature genes were closely associated with cancer and the cell cycle, as revealed by GO, KEGG and GSEA enrichment analyses. Survival analysis showed that the overexpression of the Fisher score–selected hub genes was associated with decreased survival time (P < 0.05). Weighted gene co-expression network analysis (WGCNA), Lasso, ReliefF and random forest were used for comparison with the Fisher score algorithm. The comparison among these approaches showed that the Fisher score algorithm is superior to the Lasso and ReliefF algorithms in terms of hub gene identification and has similar performance to the WGCNA and random forest algorithms. Our results demonstrated that the Fisher score followed by the application of the MCC algorithm can accurately identify hub genes in HCC.

scholarly journals EMS1/DLL4-Notch Signaling Axis Augments Cell Cycle-Mediated Tumorigenesis and Progress in Human Adrenocortical Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yu-Gang Huang ◽  
Ya Wang ◽  
Rui-Juan Zhu ◽  
Kai Tang ◽  
Xian-Bin Tang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Notch Signaling ◽  
Signaling Pathway ◽  
Adrenocortical Carcinoma ◽  
Malignant Neoplasm ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Significant Difference

Adrenocortical carcinoma (ACC) is a rare malignant neoplasm that is prone to local invasion and metastasis. Meanwhile, overexpressed endothelial cell-specific molecule 1 (ESM1) is closely related to tumorigenesis of multitudinous tumors. However, the prognosis value and biological function of ESM1 in ACC remains undefined. In the current essay, the assessment in human ACC samples and multiple public cancer databases suggested that ESM1 was significantly overexpressed in ACC patients. The abnormal expression of ESM1 was evidently correlated with dismal overall survival (OS) in ACC patients. Then, the gene-set enrichment analysis (GSEA) was applied to unravel that ESM1 was mostly involved in cell cycle and Notch4 signaling pathway. Furthermore, in vitro experiment, RNA interference of ESM1 was carried out to state that ESM1 augments CDK1 and p21-mediated G2/M-phase transition of mitosis, cell proliferation via DLL4-Notch signaling pathway in human ACC cell line, SW13 cells. Additionally, two possible or available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored. Immune infiltration analysis highlighted that no significant difference was found in ACC patients between EMS1high and EMS1low group for immune checkpoint-related genes. In addition, the overexpression of ESM1 might trigger the accumulation of tumor mutation burden (TMB) during the cell cycle of DNA replication in ACC. The gene-drug interaction network then indicated that ESM1 inhibitors, such as cisplatin, might serve as potential drugs for the therapy of ACC. Collectively, the results asserted that ESM1 and related regulators might act as underlying prognostic biomarkers or novel therapeutic targets for ACC.

scholarly journals Insights into the SARS-CoV-2-Mediated Alteration in the Stress Granule Protein Regulatory Networks in Humans

Pathogens ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1459
Author(s):  
Kartikay Prasad ◽  
Abdullah F. Alasmari ◽  
Nemat Ali ◽  
Rehan Khan ◽  
Adel Alghamdi ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Translation Inhibition ◽  
Protein Protein Interaction ◽  
Innate Immune Signaling ◽  
Efficient Viral Replication ◽  
Severe Lung Disease

The rapidly and constantly evolving coronavirus, SARS-CoV-2, imposes a great threat to human health causing severe lung disease and significant mortality. Cytoplasmic stress granules (SGs) exert anti-viral activities due to their involvement in translation inhibition and innate immune signaling. SARS-CoV-2 sequesters important SG nucleator proteins and impairs SG formation, thus evading the host response for efficient viral replication. However, the significance of SGs in COVID-19 infection remains elusive. In this study, we utilize a protein-protein interaction network approach to systematically dissect the crosstalk of human post-translational regulatory networks governed by SG proteins due to SARS-CoV-2 infection. We uncovered that 116 human SG proteins directly interact with SARS-CoV-2 proteins and are involved in 430 different brain disorders including COVID-19. Further, we performed gene set enrichment analysis to identify the drugs against three important key SG proteins (DYNC1H1, DCTN1, and LMNA) and also looked for potential microRNAs (miRNAs) targeting these proteins. We identified bexarotene as a potential drug molecule and miRNAs, hsa-miR-615-3p, hsa-miR-221-3p, and hsa-miR-124-3p as potential candidates for the treatment of COVID-19 and associated manifestations.

scholarly journals Evaluation of the TRIP13 level in breast cancer and insights into potential molecular pathways

2020 ◽  
Author(s):  
Jin Lan ◽  
Jingzhan Huang ◽  
Yuan Gao ◽  
Jingbo Sun ◽  
Longshan Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Therapeutic Target ◽  
Cancer Metastasis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Breast Cancer Metastasis ◽  
Gene Set Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Kaplan Meier

Abstract Background: TRIP13 is a member belonging to a large AAA+ ATPases protein super family. Emerging evidences had shown that TRIP13 may serve as an oncogene However, the function of TRIP13 in BC has not yet been elucidated. Methods: By utilizing the multiple database across BC, we presented the expression of TRIP13 in BC tissue and normal control. We then verified the expression of TRIP13 in patients with BC by immunohistochemical (IHC) staining. Kaplan-Meier plots were used to perform the survival analysis. Further, gene ontology (GO) analysis, gene set enrichment analysis (GSEA), and PPI (protein-protein interaction) network were performed to explore the biological function and potential regular pathway of TRIP13 in BC. Results: The multiple database and immunohistochemical (IHC) showed that higher TRIP13 expression in BC tissue compared to normal tissue. TRIP13 was highly exprssed in lung metastasis lesion compared with primary tumor in our BALB/C mice 4T1 BC models. Kaplan-Meier plots also revealed that high TRIP13 expression correlated to poor survival in patients with BC. Moreover, GSEA analysis revealed that TRIP13 was primarily enriched in the processes of cell division and proliferation. Finally 10 hub genes with a high score of connectivity were filtered from the PPI network, including MAD2L1, CDC20, CDC5L, CDK1, CCNA2, BUB1B, RAD51, SPO11, KIF11 and AURKB. Conclusion: High TRIP13 expression predicted poor prognosis and contributed tumor growth and metastasis in the BC. Thus, ARL3 may be a prognostic marker and therapeutic target for glioma. TRIP13 may be a favorable biomarker and effective therapeutic target for BC. Keywords: TRIP13; breast cancer; metastasis; bioinformatic analysis, prognosis

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