scholarly journals Identification of the Key MicroRNAs and the miRNA-mRNA Regulatory Pathways in Prostate Cancer by Bioinformatics Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Dongyang Li ◽  
Xuanyu Hao ◽  
Yongsheng Song
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Signaling Pathway ◽  
Regulatory Networks ◽  
Experimental Studies ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Tgf Beta ◽  
Regulatory Pathways ◽  
Ppi Networks

Objective. To identify key microRNAs (miRNAs) and their regulatory networks in prostate cancer.Methods. Four miRNA and three gene expression microarray datasets were downloaded for analysis from Gene Expression Omnibus database. The differentially expressed miRNA and genes were accessed by a GEO2R. Functional and pathway enrichment analyses were performed using the DAVID program. Protein-protein interaction (PPI) and miRNA-mRNA regulatory networks were constructed using the STRING and Cytoscape tool. Moreover, the results and clinical significance were validated in TCGA data.Results. We identified 26 significant DEMs, 633 upregulated DEGs, and 261 downregulated DEGs. Functional enrichment analysis indicated that significant DEGs were related to TGF-beta signaling pathway and TNF signaling pathway in PCa. Key DEGs such as HSPA8, PPP2R1A, CTNNB1, ADCY5, ANXA1, and COL9A2 were found as hub genes in PPI networks. TCGA data supported our results and the miRNAs were correlated with clinical stages and overall survival.Conclusions. We identified 26 miRNAs that may take part in key pathways like TGF-beta and TNF pathways in prostate cancer regulatory networks. MicroRNAs like miR-23b, miR-95, miR-143, and miR-183 can be utilized in assisting the diagnosis and prognosis of prostate cancer as biomarkers. Further experimental studies are required to validate our results.

scholarly journals Identification of Key Genes and miRNA-mRNA Regulatory Pathways in Bronchopulmonary Dysplasia in Preterm Infants by Bioinformatics Methods

2020 ◽  
Author(s):  
Tong Sun ◽  
Haiyang Yu ◽  
Jianhua Fu
Keyword(s):  
Gene Expression ◽  
Preterm Infants ◽  
Bronchopulmonary Dysplasia ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Regulatory Pathways ◽  
Ppi Networks ◽  
Key Genes

Abstract Background: Bronchopulmonary dysplasia (BPD) remains a severe respiratory complication of preterm infants in neonatal intensive care units (NICUs). However, its pathogenesis has been unclear. Bioinformatics analysis, which can help us explore genetic alternations and recognize latent diagnostic biomarkers, has recently promoted the comprehension of the molecular mechanisms underlying disease occurrence and development. Methods: In this study, we identified key genes and miRNA-mRNA regulatory networks in BPD in preterm infants to elucidate the pathogenesis of BPD. We downloaded and analyzed miRNA and gene expression microarray datasets from the Gene Expression Omnibus database (GEO). Differentially expressed miRNA (DEMs) and differentially expressed genes (DEGs) were obtained through NetworkAnalyst. We performed pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery program (DAVID), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then we used the STRING to establish protein–protein interactions and the Cytoscape tool to establish miRNA–mRNA regulatory networks. Results: We identified 19 significant DEMs and 140 and 33 significantly upregulated and downregulated DEGs, respectively. Functional enrichment analysis indicated that significant DEGs were associated with the antigen processing and presentation, and B-cell receptor signaling pathways in BPD. Key DEGs, such as CD19, CD79B, MS4A1, and FCGR2B were selected as hub genes in PPI networks. Conclusions: In this study, we screened out 19 DEMs that might play important roles in the regulatory networks of BPD. Higher expression of miRNAs such as miR-15b-5p, hsa-miR-32-5p, miR-3613-3p, and miR-33a-5p and lower expression of miRNAs such as miR-3960, miR-425-5p, and miR-3202 might be correlated with the process of BPD.

scholarly journals Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaowen Tan ◽  
Xiting Zhang ◽  
Lanlan Pan ◽  
Xiaoxuan Tian ◽  
Pengzhi Dong
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Atherosclerotic Plaque ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Carotid Atherosclerotic Plaque ◽  
Ppi Networks ◽  
Coronary Artery Atherosclerosis

Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human.Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO), including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs) were analyzed.Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI) networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton.Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.

scholarly journals The Mechanism Study of Xiao-Xian-Xiong Decoction in the Treatment of Atherosclerosis with Network Pharmacology

2020 ◽  
Author(s):  
Liucheng Xiao ◽  
Zonghuan Li ◽  
Chongyuan Fan ◽  
Chenggong Zhu ◽  
Xingyu Ma ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Signaling Pathway ◽  
Mapk Pathway ◽  
Enrichment Analysis ◽  
Foam Cells ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Mechanism Study ◽  
Ppi Networks

Abstract Background: Xiao-Xian-Xiong decoction is a useful formula in the treatment of atherosclerosis in traditional Chinese medicine. In this study, we aimed to investigate the function of Xiao-Xian-Xiong decoction in the treatment of atherosclerosis. Methods: In this study, we conducted the method of network pharmacology and molecular docking to discover the mechanism of Xiao-Xian-Xiong decoction against atherosclerosis. Then, we validated the function of Xiao-Xian-Xiong decoction in atherosclerosis in vitro. We investigated the function and mechanism of Xiao-Xian-Xiong decoction in RAW264.7 macrophage-derived foam cells.Results: We identified 213 targets of Xiao-Xian-Xiong decoction and 331 targets of atherosclerosis. The PPI networks of Xiao-Xian-Xiong decoction and atherosclerosis were constructed. Furthermore, the two PPI networks were merged and the core PPI network was obtained. Then, functional enrichment analysis was conducted with GO and KEGG signaling pathway analysis. KEGG analysis indicated Xiao-Xian-Xiong decoction was correlated with ubiquitin mediated proteolysis pathway, PI3K-AKT pathway, MAPK pathway, Notch signaling pathway, and TGF-β signaling pathway. At last, we validated the function of Xiao-Xian-Xiong decoction with atherosclerosis in vitro. Xiao-Xian-Xiong decoction reduced lipid accumulation and promoted the outflow of cholesterol in RAW264.7-derived foam cells. Xiao-Xian-Xiong decoction increased the expression of ABCA1 and ABCG1 protein in foam cells. ABCA1 and ABCG1 were related with regulation of the inflammatory pathway and cell proliferation in atherosclerosis.Conclusions: Combined the mechanism of available treatments of atherosclerosis, we inferred Xiao-Xian-Xiong decoction could alleviate atherosclerosis by inhibiting inflammatory response and cell proliferation.

scholarly journals Demethylation alters transcriptome profiling of buds and leaves in ‘Kyoho’ grape

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Haoran Jia ◽  
Zibo Zhang ◽  
Ehsan Sadeghnezhad ◽  
Qianqian Pang ◽  
Shangyun Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Epigenetic Modification ◽  
Deep Understanding ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Glutathione Metabolism ◽  
Endogenous Factors

Abstract Background Grape buds and leaves are directly associated with the physiology and metabolic activities of the plant, which is monitored by epigenetic modifications induced by environment and endogenous factors. Methylation is one of the epigenetic regulators that could be involved in DNA levels and affect gene expression in response to stimuli. Therefore, changes of gene expression profile in leaves and bud through inhibitors of DNA methylation provide a deep understanding of epigenetic effects in regulatory networks. Results In this study, we carried out a transcriptome analysis of ‘Kyoho’ buds and leaves under 5-azacytidine (5-azaC) exposure and screened a large number of differentially expressed genes (DEGs). GO and KEGG annotations showed that they are mainly involved in photosynthesis, flavonoid synthesis, glutathione metabolism, and other metabolic processes. Functional enrichment analysis also provided a holistic perspective on the transcriptome profile when 5-azaC bound to methyltransferase and induced demethylation. Enrichment analysis of transcription factors (TFs) also showed that the MYB, C2H2, and bHLH families are involved in the regulation of responsive genes under epigenetic changes. Furthermore, hormone-related genes have also undergone significant changes, especially gibberellin (GA) and abscisic acid (ABA)-related genes that responded to bud germination. We also used protein-protein interaction network to determine hub proteins in response to demethylation. Conclusions These findings provide new insights into the establishment of molecular regulatory networks according to how methylation as an epigenetic modification alters transcriptome patterns in bud and leaves of grape.

scholarly journals Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

2021 ◽  
Vol 8 ◽  
Author(s):  
Ningyuan Chen ◽  
Liu Miao ◽  
Wei Lin ◽  
Donghua Zou ◽  
Ling Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Functional Enrichment Analysis ◽  
Normal Subjects ◽  
Functional Enrichment ◽  
Differentially Methylated Genes

Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects. (2) Functional enrichment analysis and construction of differential methylation gene regulatory networks were performed. (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray dataset. (4) Correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNAs matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes—s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interesting different expression positions [differentially methylated positions (DMPs)] and their corresponding gene expression, we found that methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expressions in obese subjects were validated in a separate microarray dataset.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

scholarly journals Deciphering The Molecular Pathogenesis Behind Neurological Manifestations of SARS-CoV-2 And Drug Repurposing, A Systems Biology Approach

2021 ◽  
Author(s):  
maryam mozafar ◽  
Seyed Amir Mirmotalebisohi ◽  
Marzieh Sameni ◽  
Zeinab Dehghan ◽  
Yalda Khazaei-Poul ◽  
...  
Keyword(s):  
Systems Biology ◽  
Regulatory Networks ◽  
Target Genes ◽  
Viral Infections ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Neurological Complications ◽  
Functional Enrichment ◽  
Neurological Manifestations ◽  
Ppi Networks

Abstract Introduction: As the COVID-19 pandemic spreads worldwide, reports about the neurological complications of SARS-CoV-2 are excessively increasing. However, there is still insufficient high-throughput data on neuronal cells infected with SARS-CoV-2 to help predict its neural pathogenesis. HCoV-OC43 is another member of the beta coronavirus family that has confirmed neuro-invasive effects and has available neural omics data. This study predicts the critical genes, biological processes, and pathways mediating in SARS-CoV-2 neurological manifestations using a systems biology approach.Method: We retrieved raw data related to SARS-CoV-2 and HCoV-OC43 infections from gene expression omnibus datasets (GSE147507 and GSE13879 respectively). We constructed gene regulatory networks for both infections, detected significant regulatory motifs by FANMOD software, and created their subnetworks. We also constructed PPI networks and identified the MCODE clusters. In the intersection of merged subnetworks of two viruses, the most critical genes were verified in GRN & PPI networks. We drug-repurposed for the selected target genes and performed the functional enrichment analysis using DAVID and String databases.Results: Some of the top KEGG pathway results included NF-kappa B, Toll-like receptor, NOD-like receptor, MAPK, and Neurotrophin signaling pathways. The most essential identified genes included IL6, TNF, HOXA5, POU2F2, ITGB3, STAT1, YY1, E2F6, ESR1, FOXO3, FOXO1, MEF2A, ATF3, ATF4, DDIT3, TCF4, BCL2L2, and BMP4. These genes were also involved in mechanisms of other viral infections of the nervous system. This study repurposes nine medicines with effects on COVID-19 neurological complications. Some of the repurposed drugs were previously registered in clinical trials for COVID-19 treatment.Conclusion: We recommended some identified crucial genes and medications to investigate further their potential role in treating COVID-19 neurological complications.

scholarly journals Identification of crucial genes and pathways associated with prostate cancer in multiple databases

2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110166
Author(s):  
Hanxu Guo ◽  
Zhichao Zhang ◽  
Yuhang Wang ◽  
Sheng Xue
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Expression Profiles ◽  
Malignant Neoplasm ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Core ◽  
Ppi Networks ◽  
Core Genes

Objective Prostate cancer (PCa) is a malignant neoplasm of the urinary system. This study aimed to use bioinformatics to screen for core genes and biological pathways related to PCa. Methods The GSE5957 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were constructed by R language. Furthermore, protein–protein interaction (PPI) networks were generated to predict core genes. The expression levels of core genes were examined in the Tumor Immune Estimation Resource (TIMER) and Oncomine databases. The cBioPortal tool was used to study the co-expression and prognostic factors of the core genes. Finally, the core genes of signaling pathways were determined using gene set enrichment analysis (GSEA). Results Overall, 874 DEGs were identified. Hierarchical clustering analysis revealed that these 24 core genes have significant association with carcinogenesis and development . LONRF1, CDK1, RPS18, GNB2L1 ( RACK1), RPL30, and SEC61A1 directly related to the recurrence and prognosis of PCa. Conclusions This study identified the core genes and pathways in PCa and provides candidate targets for diagnosis, prognosis, and treatment.

scholarly journals Bioinformatics Analysis of Gene Expression Profiles of Immune-mediated Necrotizing Myopathy

2021 ◽  
Author(s):  
Jiaying Shi ◽  
Shule Wang ◽  
Jingfei Zhang ◽  
Xueli Chang ◽  
Juan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Hub Genes ◽  
Necrotizing Myopathy ◽  
Ppi Networks ◽  
Immune Mediated ◽  
Potential Biomarkers

Abstract Background: Immune-mediated necrotizing myopathy (IMNM) is a type of autoimmune myopathy with limited therapeutic measures. This study aims to elucidate the potential biomarkers and investigate the underlying mechanisms in IMNM. Materials and Methods: Microarray datasets in GSE128470 and GSE39454 were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were filtrated by limma package in R statistical software. Functional enrichment analyses were performed using DAVID online tools. STRING database was used to construct protein‑protein interaction (PPI) networks. The module analysis and hub genes validation were performed using Cytoscape software. Results: Integrated analysis of two databases revealed 160 co-expressed DEGs in IMNM, including 80 downregulated genes and 80 upregulated genes. GO enrichment analysis revealed that sarcomere is the most significantly enriched GO term within the DEGs. KEGG pathway enrichment analysis revealed significant enrichment pathways in cancer. A PPI network consisting of 115 nodes and 205 edges were constructed and top 20 hub genes were identified. Two key modules from the network were identified. Eight hub genes in module 1 (MYH3, MYH7B, MYH8, MYL5, MYBPH, ACTC1, YNNT 2 and MYOG) are tightly associated with skeletal muscle construction. Seven hub genes in module 2 (C1QA, TYROBP, MS4A6A, RNASE6, FCGR2A, FCER1G and LAPTM5) mainly take part in immune response. Conclusions: Our research indicated that cancer-related pathways, skeletal muscle construction pathways and immune-mediated pathways might participate in the development of IMNM. Identified hub genes may serve as potential biomarkers or targets for early diagnosis.

scholarly journals Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Shenghua Pan ◽  
Tingting Tang ◽  
Yanke Wu ◽  
Liang Zhang ◽  
Zekai Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Colon Adenocarcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Kaplan Meier

The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan–Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein–protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients’ overall survival (log rank p < 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan–Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.

scholarly journals Immune-Related Genes: Potential Regulators and Drug Therapeutic Targets in Hypertrophic Cardiomyopathy

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wei Liu ◽  
Ju Ye ◽  
Jinqiang Cai ◽  
Feng Xie ◽  
Mengjie Tang ◽  
...  
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
Signaling Pathway ◽  
Regulatory Network ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Regulatory Pathways ◽  
Smad Protein ◽  
Immune Related Genes

Background. Accumulating evidence shows that the innate immune system is a key player in cardiovascular repair and regeneration, but little is known about the role of immune-related genes (IRGs) in hypertrophic cardiomyopathy (HCM). Methods. The differential mRNA expression profiles of HCM samples were downloaded from the Gene Expression Omnibus (GEO) dataset (GSE89714), and the IRG expression profile was obtained from the ImmPort database. The regulatory pathways of IRGs in HCM were screened out through discrepantly expressive genes (DEGs) analysis, enrichment of gene function/pathway analysis, and protein-protein interaction (PPI) network. Besides, hub IRGs in the PPI network were selected for drug prediction. Results. A total of 854 genes were differentially expressed in HCM, of which 88 were IRGs. Functional enrichment analysis revealed that 88 IRGs were mainly involved in the biological processes (BP) of SMAD protein pathway, smooth muscle cell proliferation, protein serine/threonine kinase, and mitogen-activated protein kinase (MAPK) cascade. Cytokine-cytokine receptor interaction, TGFβ signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway were enriched in the pathway enrichment analysis of these 88 IRGs. Furthermore, the PPI regulatory network of IRGs was constructed, and 10 hub IRGs were screened out to construct a regulatory network for HCM. 4 transcription factors (TFs) were the major regulator of 10 hub IRGs. Finally, these 10 hub IRGs were entered into the pharmacogenomics database for prediction, and the relevant drugs were obtained. Conclusions. In this study, 10 hub IRGs were coexpressed with 4 TFs to construct a regulatory network for HCM. Drug prediction of these 10 hub IRGs proposed potential therapeutic agents that could be used in HCM. These results indicate that IRGs are potential regulators and drug therapeutic targets in HCM.

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