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Identification of potential biomarkers and therapeutic targets for human IgA nephropathy and hypertensive nephropathy by bioinformatics analysis.

ABSTRACT: 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.

SUBMITTER: Cui Y

PROVIDER: S-EPMC5547965 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Identification of potential biomarkers and therapeutic targets for human IgA nephropathy and hypertensive nephropathy by bioinformatics analysis.

Cui Yingchun Y Liu Shengmao S Cui Wenpeng W Gao Dan D Zhou Wenhua W Luo Ping P

Molecular medicine reports 20170715 3

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. Fina ...[more]

PMID: 28713898

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Project description:BackgroundIgA nephropathy (IgAN) has become the leading cause of end-stage renal disease in young adults. Nevertheless, the current diagnosis exclusively relies on invasive renal biopsy, and specific treatment is deficient. Thus, our study aims to identify potential crucial genes, thereby providing novel biomarkers for the diagnosis and therapy of IgAN.MethodsThree microarray datasets were downloaded from GEO official website. Differentially expressed genes (DEGs) were identified by limma package. GO and KEGG analysis were conducted. Tissue/organ-specific DEGs were distinguished via BioGPS. GSEA was utilized to elucidate the predominant enrichment pathways. The PPI network of DEGs was established, and hub genes were mined through Cytoscape. The CTD database was employed to determine the association between hub genes and IgAN. Infiltrating immune cells and their relationship to hub genes were evaluated based on CIBERSORT. Furthermore, the diagnostic effectiveness of hub markers was subsequently predicted using the ROC curves. The CMap database was applied to investigate potential therapeutic drugs. The expression level and diagnostic accuracy of TYROBP was validated in the cell model of IgAN and different renal pathologies.ResultsA total of 113 DEGs were screened, which were mostly enriched in peptidase regulator activity, regulation of cytokine production, and collagen-containing extracellular matrix. Among these DEGs, 67 genes manifested pronounced tissue and organ specificity. GSEA analysis revealed that the most significant enriched gene sets were involved in proteasome pathway. Ten hub genes (KNG1, FN1, ALB, PLG, IGF1, EGF, HRG, TYROBP, CSF1R, and ITGB2) were recognized. CTD showed a close connection between ALB, IGF, FN1 and IgAN. Immune infiltration analysis elucidated that IGF1, EGF, HRG, FN1, ITGB2, and TYROBP were closely associated with infiltrating immune cells. ROC curves reflected that all hub genes, especially TYROBP, exhibited a good diagnostic value for IgAN. Verteporfin, moxonidine, and procaine were the most significant three therapeutic drugs. Further exploration proved that TYROBP was not only highly expressed in IgAN, but exhibited high specificity for the diagnosis of IgAN.ConclusionsThis study may offer novel insights into the mechanisms involved in IgAN occurrence and progression and the selection of diagnostic markers and therapeutic targets for IgAN.

Project description:BackgroundIgA nephropathy (IgAN) is the most common primary glomerular disease and the leading cause of the end-stage renal disease in the world. The pathogenesis of IgAN has not been well elucidated, and yet treatment is limited. High-throughput microarray has been applied for elucidating molecular biomarkers and potential mechanisms involved in IgAN. This study aimed to identify the potential key genes and therapeutics associated with IgAN using integrative bioinformatics and transcriptome-based computational drug repurposing approach.MethodsThree datasets of mRNA expression profile were obtained from the gene expression omnibus database and differentially expressed genes (DEGs) between IgAN glomeruli and normal tissue were identified by integrated analysis. Gene ontology and pathway enrichment analyses of the DEGs were performed by R software, and protein-protein interaction networks were constructed using the STRING online search tool. External dataset and immunohistochemical assessment of kidney biopsy specimens were used for hub gene validation. Potential compounds for IgAN therapy were obtained by Connectivity Map (CMap) analysis and preliminarily verified in vitro. Stimulated human mesangial cells were collected for cell proliferation and cell cycle analysis using cell counting kit 8 and flow cytometry, respectively.Results134 DEGs genes were differentially expressed across kidney transcriptomic data from IgAN patients and healthy living donors. Enrichment analysis showed that the glomerular compartments underwent a wide range of interesting pathological changes during kidney injury, focused on anion transmembrane transporter activity and protein digestion and absorption mostly. Hub genes (ITGB2, FCER1G, CSF1R) were identified and verified to be significantly upregulated in IgAN patients, and associated with severity of renal lesions. Computational drug repurposing with the CMap identified tetrandrine as a candidate treatment to reverse IgAN hub gene expression. Tetrandrine administration significantly reversed mesangial cell proliferation and cell cycle transition.ConclusionThe identification of DEGs and related therapeutic strategies of IgAN through this integrated bioinformatics analysis provides a valuable resource of therapeutic targets and agents of IgAN. Especially, our findings suggest that tetrandrine might be beneficial for IgAN, which deserves future research.

Project description:Gliomas are primary tumors that originate in the brain or spinal cord and develop from supportive glial cells. The present study aimed to identify potential candidate molecular markers for the treatment of gliomas, and to explore the underlying mechanisms of this disease. The gene expression profile data GSE50021, which consisted of 10 specimens of normal brain tissues and 35 specimens of glioma tissues, was downloaded from Gene Expression Omnibus (GEO). The methylation microarray data GSE50022, consisting of 28 glioma specimens, was also downloaded from GEO. Differentially expressed genes (DEGs) between patients with glioma and normal individuals were identified, and key methylation sites were screened. Transcriptional regulatory networks were constructed, and target genes were selected. Survival analysis of key methylation sites and risk analysis of sub-pathways were performed, from which key genes and pathways were selected. A total of 79 DEGs and 179 key methylation sites were identified, of which 20 target genes and 36 transcription factors were included in the transcriptional regulatory network. Glutamate metabotropic receptor 2 (GRM2) was regulated by 8 transcription factors. Inositol-trisphosphate 3-kinase A (ITPKA) was a significantly enriched DEG, associated with the inositol phosphate metabolism pathway, Survival analysis revealed that the survival time of patients with lower methylation levels in cg00157228 was longer than patients with higher methylation levels. ITPKA was the closest located gene to cg00157228. In conclusion, GRM2 and enriched ITPKA, associated with the inositol phosphate metabolism pathway, may be key mechanisms in the development and progression of gliomas. Furthermore, the present study provided evidence for an additional mechanism of methylation-induced gliomas, in which methylation results in the dysregulation of specific transcripts. The results of the present study may provide a research direction for studying the mechanisms underlying the development and progression of gliomas.

Project description:The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I ?2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.

Project description:Background: Immunoglobulin A nephropathy (IgAN) is the most common type of primary glomerulonephritis worldwide and a frequent cause of end-stage renal disease. The inflammation cascade due to the infiltration and activation of immune cells in glomeruli plays an essential role in the progression of IgAN. In this study, we aimed to identify hub genes involved in immune infiltration and explore potential prognostic biomarkers and therapeutic targets in IgAN. Methods: We combined the single-cell and bulk transcriptome profiles of IgAN patients and controls with clinical data. Through single-cell analysis and weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) enrichment analysis, and differentially expressed gene (DEG) analysis in the bulk profile, we identified cell-type-specific potential hub genes in IgAN. Real hub genes were extracted via validation analysis and clinical significance analysis of the correlation between the expression levels of genes and the estimated glomerular filtration rate (eGFR) in the external dataset. Gene set enrichment analysis was performed to predict the probable roles of the real hub genes in IgAN. Results: A total of eleven cell clusters were classified via single-cell analysis, among which macrophages showed a variable proportion between the IgAN and normal control samples. We recognized six functional co-expression gene modules through WGCNA, among which the black module was deemed an IgAN-related and immune-involving module via GO enrichment analysis. DEG analysis identified 45 potential hub genes from genes enriched in GO terms. A total of twenty-three potential hub genes were specifically expressed in macrophages. Furthermore, we validated the differential expression of the 23 potential hub genes in the external dataset and identified nine genes with prognostic significance as real hub genes, viz., CSF1R, CYBB, FPR3, GPR65, HCLS1, IL10RA, PLA2G7, TYROBP, and VSIG4. The real hub gens are thought to contribute to immune cell regulation, immunoreaction, and regulation of oxidative stress, cell proliferation, and material metabolism. Conclusion: In this study, we demonstrated that macrophages infiltrated the glomeruli and contributed to the inflammatory response in IgAN. Based on integrated bioinformatics analyses of single-cell and bulk transcriptome data, we highlighted nine genes as novel prognostic biomarkers, which may enable the development of innovative prognostic and therapeutic strategies for IgAN.

Project description:BackgroundHeart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.MethodsWe searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.ResultsA total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).ConclusionsThis discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Dataset Information

Identification of potential biomarkers and therapeutic targets for human IgA nephropathy and hypertensive nephropathy by bioinformatics analysis.

Publications

Identification of potential biomarkers and therapeutic targets for human IgA nephropathy and hypertensive nephropathy by bioinformatics analysis.

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