scholarly journals RNA-seq co-expression network analysis reveals anxiolytic behavior of mice with Efnb2 knockout in parvalbumin+ neurons

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ying Sun ◽  
Le Ma ◽  
Jianhua Chen ◽  
Weidi Wang ◽  
Shiyu Peng ◽  
...  
Keyword(s):  
Network Analysis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Cell Voltage ◽  
Synaptic Function ◽  
Ras Signaling ◽  
Knock Out ◽  
Eph Receptor ◽  
Defensive Responses ◽  
Fear And Anxiety

AbstractAnxiety disorders are the most common psychiatric disorders, and the change in the activity of the prefrontal cortex (PFC) is considered as the underlying pathological mechanism. Parvalbumin-expressing (PV+) inhibition contributes to the overall activity of the PFC. However, the molecular mechanism underlying the excitation-inhibition imbalance of PV+ neurons in the PFC is unknown. Efnb2 is a membrane-bound molecule that plays an important role in the nervous system through binding the Eph receptor. To investigate whether the loss of Efnb2 in PV+ affects anxiety, we examined the behavior of wild type and Efnb2 in PV+ neurons knockout (KO) mice. We monitored the defensive responses to aversive stimuli of elevated plus maze (EPM) and found that KO mice exhibited obvious fearless and anxiolytic behaviors. To further investigate the underlying regulatory mechanism, we performed RNA sequencing, analyzed the differentially expressed genes (DEGs), and constructed the weighted gene co-expression network analysis (WGCNA). The WGCNA identified 12 characteristic modules. Among them, the MEgreen module showed the most significant correlation with KO mice of EPM stimuli. The Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that this was related to the distal axon, Ras signaling pathway and insulin signaling pathway. Furthermore, the whole-cell voltage clamp recordings also proved that Efnb2 gene knock-out could affect synaptic function. Together with the transcriptomic analysis of mice with Efnb2 knockout on PV+ neurons, our findings suggest that Efnb2 gene in the PV+ neuron of PFC may be a crucial factor for fear and anxiety, which provide an insight into anxiety pathophysiology.

scholarly journals MicroRNA expression profiling involved in Borax-induced anti-tumor effect using gene-chip analysis

2020 ◽  
Author(s):  
Lun Wu ◽  
Ying Wei ◽  
Wen-Bo Zhou ◽  
Jiao Zhou ◽  
Li-Hua Yang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Enrichment Analysis ◽  
Gene Chip ◽  
Differentially Expressed ◽  
Control Group ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Therapeutic Benefits ◽  
Differentially Expressed Mirnas

Abstract Background Borax, a boron compound, which is becoming widely recognized for its biological effects, including antioxidant activity, cytotoxicity, and potential therapeutic benefits. However, the specific molecular mechanisms underlying borax-induced anti-tumor effect still remain to be to further elucidated. MicroRNAs (miRNAs) may play key roles in cellular processes including tumor progression, cell apoptosis and cytotoxicity. Thus, this study aimed to investigate, whether miRNAs were involved in the borax-mediated anti-tumor effect using miRNA profiling of a human liver cancer cell line (HepG2) using gene-chip analysis.Methods Total RNA was extracted and purified from HepG2 cells that were treated with 4 mM borax for either 2 or 24 h. The samples underwent microarray analysis using an Agilent Human miRNA Array. Differentially expressed miRNAs were analysed by volcano plot and heatmap, and were validated using real-time fluorescent quantitative PCR (qPCR).ResultsAmong this, 2- or 24-h exposure to borax significantly altered the expression level of miRNAs in HepG2 cells, 4 or 14 were upregulated and 3 were downregulated compared with the control group, respectively (≥2-fold; P<0.05). GO enrichment analysis and KEGG pathway enrichment analysis revealed that target genes of differentially expressed miRNAs in HepG2 cells predominantly participated in MAPK signaling pathway, TGF-beta signaling pathway, NF-kappa B signaling pathway, etc; in 2-h borax treatment group, while Ras signaling pathway, FoxO signaling pathway, Cellular senescence, etc; involved in 24-h treatment group.Conclusions Result indicates that borax-induced anti-tumor effect may be associated with alterations in miRNAs.

scholarly journals Blood Gene Expression Profile Study Revealed the Activation of Apoptosis and p53 Signaling Pathway May Be the Potential Molecular Mechanisms of Ionizing Radiation Damage and Radiation-Induced Bystander Effects

Dose-Response ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 155932582091418
Author(s):  
Guangyao He ◽  
Anzhou Tang ◽  
Mao Xie ◽  
Wei Xia ◽  
Pengcheng Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Ionizing Radiation ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
P53 Signaling ◽  
Gene Correlation ◽  
Radiation Induced ◽  
P53 Signaling Pathway

Radiotherapy is an effective treatment for local solid tumors, but the mechanism of damage to human body caused by radiation therapy needs further study. In this study, gene expression profiles of human peripheral blood samples exposed to different doses and rates of ionizing radiation (IR) were used for bioinformatics analysis to investigate the mechanism of IR damage and radiation-induced bystander effect (RIBE). Differentially expressed genes analysis, weighted gene correlation network analysis, functional enrichment analysis, hypergeometric test, gene set enrichment analysis, and gene set variation analysis were applied to analyze the data. Moreover, receiver operating characteristic curve analysis was performed to identify core genes of IR damage. Weighted gene correlation network analysis identified 3 modules associated with IR damage, 2 were positively correlated and 1 was negatively correlated. The analysis showed that the positively correlated modules were significantly involved in apoptosis and p53 signaling pathway, and ESR1, ATM, and MYC were potential transcription factors regulating these modules. Thus, the study suggested that apoptosis and p53 signaling pathway may be the potential molecular mechanisms of IR damage and RIBE, which could be driven by ESR1, ATM, and MYC.

scholarly journals Network Pharmacology-Based Approach to Investigate the Mechanisms ofHedyotis diffusaWilld. in the Treatment of Gastric Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xinkui Liu ◽  
Jiarui Wu ◽  
Dan Zhang ◽  
Kaihuan Wang ◽  
Xiaojiao Duan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Cycle ◽  
Signaling Pathway ◽  
Excision Repair ◽  
Enrichment Analysis ◽  
Cyclin B1 ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Ras Signaling ◽  
Therapeutic Effects

Background.Hedyotis diffusaWilld. (HDW) is one of the renowned herbs often used in the treatment of gastric cancer (GC). However, its curative mechanism has not been fully elucidated.Objective. To systematically investigate the mechanisms of HDW in GC.Methods. A network pharmacology approach mainly comprising target prediction, network construction, and module analysis was adopted in this study.Results. A total of 353 targets of the 32 bioactive compounds in HDW were obtained. The network analysis showed that CA isoenzymes, p53, PIK3CA, CDK2,P27Kip1, cyclin D1, cyclin B1, cyclin A2, AKT1, BCL2, MAPK1, and VEGFA were identified as key targets of HDW in the treatment of GC. The functional enrichment analysis indicated that HDW probably produced the therapeutic effects against GC by synergistically regulating many biological pathways, such as nucleotide excision repair, apoptosis, cell cycle, PI3K/AKT/mTOR signaling pathway, VEGF signaling pathway, and Ras signaling pathway.Conclusions. This study holistically illuminates the fact that the pharmacological mechanisms of HDW in GC might be strongly associated with its synergic modulation of apoptosis, cell cycle, differentiation, proliferation, migration, invasion, and angiogenesis.

Bufalin: A Systematic Review of Research Hotspots and Antitumor Mechanisms by Text Mining and Bioinformatics

2020 ◽  
Vol 48 (07) ◽  
pp. 1633-1650
Author(s):  
Xian Zhang ◽  
Xiaoxuan Zhao ◽  
Kaili Liu ◽  
Yuxuan Che ◽  
Xun Qiu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Mesh Terms ◽  
Go Enrichment ◽  
Pubmed Database ◽  
Pathways Analysis

Bufalin is an anticancer drug extract from traditional Chinese medicine. Several articles about bufalin have been published. However, the literature on bufalin has not yet been systematically studied. This study aimed to identify the study status and knowledge structures of bufalin and to summarize the antitumor mechanism. Data were retrieved and downloaded from the PubMed database. The softwares of BICOMB, gCLUTO, Ucinet 6.0, and NetDraw2.084 were used to analyze these publications. The bufalin related genes were recognized and tagged by ABNER software. Then these BF-related genes were performed by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, and protein-protein interaction (PPI) network analysis. A total of 474 papers met the search criteria from 2000 to 2019. By biclustering clustering analysis, the 50 high-frequency main MeSH terms/subheadings were classified into 5 clusters. The clusters of drug therapy and the mechanism of bufalin were hotspot topics. A total of 50 genes were identified as BF-related genes. PPI network analysis showed that inducing apoptosis was the main effect of bufalin, and apoptosis-related gene Caspase 3 was the most reported by people. Bufalin could inhibit the proliferation, invasion, and metastasis of cancer cells through multiple signaling pathways, such as PI3K/AKT, Hedgehog, MAPK/JNK, Wnt/[Formula: see text]-catenin, TGF-[Formula: see text]/Smad, Integrin signaling pathway, and NF-KB signaling pathway via KEGG analysis. Through the quantitative analysis of bufalin literature, we revealed the research status and hot spots in this field and provided some guidance for further research.

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 &lt; 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 Protein Network Analysis to Prioritize Key Genes and Pathway for Stress-Mediated Neurodegeneration

2018 ◽  
Vol 11 (1) ◽  
pp. 240-251 ◽  
Author(s):  
Neha Srivastava ◽  
Bhartendu Nath Mishra ◽  
Prachi Srivastava
Keyword(s):  
Oxidative Stress ◽  
Gene Ontology ◽  
Transcription Factor ◽  
Network Analysis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Node Degree ◽  
Key Genes

Background:Oxidative Stress (OS) has been implicated in the pathophysiology of many neurodegenerative diseases. OS can cause cellular damage that results in cell death due to overproduction of reactive oxygen species (ROS) that may play the crucial role in the disease progression. An impaired mechanism in correlation with reduced expression of antioxidant proteins is the very common feature among most of the age-related disorders. Variousin-vitroandin-vivostudies suggest the major contribution of oxidative stress in neurodegeneration. Role of Nrf2 gene is well established as a neuroprotective gene especially in concern with stress-mediated neurodegeneration. Nrf2 is a bZIP transcription factor that forms the heterodimer with small Maf protein and transcription factor AP1 that regulates transcription by binding to ARE which coordinates the transcription of genes involved in phase II detoxification and an antioxidant defense that is used to protect the cell from oxidative stress.Aim:The currentinsilicostudy was attempted to prioritize key genes and pathway in stress-mediated neurodegeneration through network-based analysis.Methods:Protein-protein interaction network was constructed and analyzed using 63 Nrf2 regulating candidate genes obtained from NCBI database based on literature studies usingSTRING 10.0database andCytoscape v 3.6.0software plug-inNetwork Analyzer.Further, the functional enrichment analysis of identified gene was done usingPANTHER GENE ONTOLOGYsoftware and DAVID tool.Results:Based on network topological parameter, TP53, JUN, MYC, NFE2L2, AKT1, PIK3CA & UBC were identified as the key gene in the network. Among them, TP53 gene was obtained as a super hub gene with the highest Betweenness Centrality (BC) and node degree. The functional enrichment analysis was done usingPANTHER GENE ONTOLOGYsoftware and DAVID tool reveals their significant role in neurotrophin signaling pathway, MAPK signaling pathway, cellular response to stress & in the regulation of stress.Conclusion:The network analysis will help in prioritizing genes in the pathway that helps in understanding the underlying mechanism of disease. Thus, further study on these genes and their biological mechanism and pathway may, therefore, provide a potential target for the treatment of stress-mediated neurodegeneration.

scholarly journals Weighted gene correlation network analysis reveals novel biomarkers associated with mesenchymal stromal cell differentiation in early phase

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8907 ◽  
Author(s):  
Bin Xiao ◽  
Guozhu Wang ◽  
Weiwei Li
Keyword(s):  
Bone Marrow ◽  
Network Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Ras Signaling ◽  
High Morbidity ◽  
Hub Genes ◽  
Data Set ◽  
Regulatory Pathways ◽  
Gene Modules

Osteoporosis is a major public health problem that is associated with high morbidity and mortality, and its prevalence is increasing as the world’s population ages. Therefore, understanding the molecular basis of the disease is becoming a high priority. In this regard, studies have shown that an imbalance in adipogenic and osteogenic differentiation of bone marrow mesenchymal stem cells (MSCs) is associated with osteoporosis. In this study, we conducted a Weighted Gene Co-Expression Network Analysis to identify gene modules associated with the differentiation of bone marrow MSCs. Gene Ontology and Kyoto Encyclopedia of Genes and Genome enrichment analysis showed that the most significant module, the brown module, was enriched with genes involved in cell cycle regulation, which is in line with the initial results published using these data. In addition, the Cytoscape platform was used to identify important hub genes and lncRNAs correlated with the gene modules. Furthermore, differential gene expression analysis identified 157 and 40 genes that were upregulated and downregulated, respectively, after 3 h of MSCs differentiation. Interestingly, regulatory network analysis, and comparison of the differentially expressed genes with those in the brown module identified potential novel biomarker genes, including two transcription factors (ZNF740, FOS) and two hub genes (FOXQ1, SGK1), which were further validated for differential expression in another data set of differentiation of MSCs. Finally, Gene Set Enrichment Analysis suggested that the two most important candidate hub genes are involved in regulatory pathways, such as the JAK-STAT and RAS signaling pathways. In summary, we have revealed new molecular mechanisms of MSCs differentiation and identified novel genes that could be used as potential therapeutic targets for the treatment of osteoporosis.

scholarly journals Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection

2021 ◽  
Vol 10 (16) ◽  
pp. 3567
Author(s):  
Hassan Karami ◽  
Afshin Derakhshani ◽  
Mohammad Ghasemigol ◽  
Mohammad Fereidouni ◽  
Ebrahim Miri-Moghaddam ◽  
...  
Keyword(s):  
Network Analysis ◽  
Signaling Pathway ◽  
Drug Targets ◽  
Experimental Studies ◽  
A549 Cells ◽  
Enrichment Analysis ◽  
Type I ◽  
Hub Genes

The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHEL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug–target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.

A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Zuogui Yin in the Treatment of Male Infertility

2020 ◽  
Vol 23 ◽  
Author(s):  
Qi Zhao ◽  
Hengheng Dai ◽  
Jisheng Wang ◽  
Fei Yan ◽  
Guejin Jang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Alternative Therapy ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Complementary And Alternative Therapy

Background and Aim: Traditional Chinese medicine (TCM), as a complementary and alternative therapy, has played increasingly important roles in clinical treatment and disease prevention. Zuogui Yin (ZGY) is one of the well-known TCM prescription used for the treatment of male infertility. To fully reveal the potential mechanisms underlying the therapeutic effects of ZGY on male infertility, a network pharmacology approach was conducted at the molecular level. Methods: Network pharmacology approach was used in this study, which mainly included active compound screening, target prediction, gene enrichment analysis and network analysis. Results: The network analysis successfully identified 148 potential active ingredients of ZGY and 155 predicted targets that were associated with male infertility. ZGY might play a role in the treatment of male infertility by regulating ten hub targets (VEGFA, CASP3 , TNF, AKT1, EGF, EGFR, IL-6, MAPK1, TP53 and PTGS2) and six pathways (TNF signaling pathway, PI3K-Akt signaling pathway, FoxO signaling pathway, Toll-like receptor signaling pathway, VEGF signaling pathway and MAPK signaling pathway). Conclusion: This study explored the pharmacological activity and molecular mechanisms of ZGY against male infertility from a holistic perspective. The underlying molecular mechanisms were closely related to the intervention of oxidative stress and apoptosis with CASP3, TP53, AKT1 and MAPK1 being possible targets.

scholarly journals Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics

2021 ◽  
Vol 12 ◽  
Author(s):  
Yijun Shi ◽  
Yaowei Ding ◽  
Guoge Li ◽  
Lijuan Wang ◽  
Rasha Alsamani Osman ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Growth Factor ◽  
Signaling Pathway ◽  
Protein Modification ◽  
Enrichment Analysis ◽  
Roc Curves ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Insulin Like Growth Factor ◽  
Diagnostic Potential

ObjectiveHere, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.MethodsTandem mass tag (TMT) quantitative proteomic analysis was performed to determine the differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples collected from 10 patients with MS and 10 non-inflammatory neurological controls (NINCs). The DEPs were analyzed using bioinformatics tools, and the candidate proteins were validated using the ELISA method in another cohort comprising 160 samples (paired CSF and plasma of 40 patients with MS, CSF of 40 NINCs, and plasma of 40 healthy individuals). Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method.ResultsCompared to NINCs, we identified 83 CSF-specific DEPs out of a total of 343 proteins in MS patients. Gene ontology (GO) enrichment analysis revealed that these DEPs are mainly involved in platelet degranulation, negative regulation of proteolysis, and post-translational protein modification. Pathway enrichment analysis revealed that the complement and coagulation cascades, Ras signaling pathway, and PI3K-Akt signaling pathway are the main components. Insulin-like growth factor-binding protein 7 (IGFBP7), insulin-like growth factor 2 (IGF2), and somatostatin (SST) were identified as the potential proteins with high scores, degree, and centrality in the protein-protein interaction (PPI) network. We validated the expression of these three proteins using ELISA. Compared to NINCs, the level of CSF IGFBP7 was significantly upregulated, and the level of CSF SST was significantly downregulated in the MS group.ConclusionOur results suggest that SST and IGFBP7 might be associated with the pathogenesis of MS and would be helpful in diagnosing MS. Since IGFBP7 was used to classify relapsing remitting MS (RRMS) and secondary progressive MS (SPMS) patients, therefore, it may act as a potential key marker and therapeutic target in MS.

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