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 Identification and validation of three core genes in p53 signaling pathway in hepatitis B virus-related hepatocellular carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Mingxue Yu ◽  
Wenli Xu ◽  
Yusheng Jie ◽  
Jiahui Pang ◽  
Siqi Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Validation Dataset ◽  
P53 Signaling ◽  
B Virus ◽  
P53 Signaling Pathway ◽  
Core Genes

Abstract Background Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus (HBV) infection. We aimed to identify some core genes and pathways for HBV-related HCC. Methods Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus (GEO). The GSE62232 and GSE121248 profiles were the analysis datasets and GSE94660 was the validation dataset. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes between HBV-related HCC tissues and normal tissues. Then, functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of these three core genes in tumor tissues and adjacent non-tumor liver tissues from 12 HBV related HCC patients, HBV-associated liver cancer cell lines and normal liver cell lines, and HepG2 with p53 knockdown or deletion, respectively. Results Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed that samples highly expressing three core genes were all enriched in the p53 signaling pathway in a validation dataset (P < 0.0001). The expression of these three core genes in tumor tissue samples was higher than that in relevant adjacent non-tumor liver tissues (P < 0.0001). Furthermore, we also found that the above genes were highly expressed in liver cancer cell lines compared with normal liver cells. In addition, we found that the expression of these three core genes in p53 knockdown or knockout HCC cell lines was lower than that in negative control HCC cell lines (P < 0.05). Conclusions CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

scholarly journals Identification of biological pathways and genes associated with neurogenic heterotopic ossification by text mining

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8276 ◽  
Author(s):  
Yichong Zhang ◽  
Yuanbo Zhan ◽  
Yuhui Kou ◽  
Xiaofeng Yin ◽  
Yanhua Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Text Mining ◽  
Heterotopic Ossification ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Egf Receptor ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Specific Gene ◽  
Cord Injury

Background Neurogenic heterotopic ossification is a disorder of aberrant bone formation affecting one in five patients sustaining a spinal cord injury or traumatic brain injury (SCI-TBI-HO). However, the underlying mechanisms of SCI-TBI-HO have proven difficult to elucidate. The aim of the present study is to identify the most promising candidate genes and biological pathways for SCI-TBI-HO. Methods In this study, we used text mining to generate potential explanations for SCI-TBI-HO. Moreover, we employed several additional datasets, including gene expression profile data, drug data and tissue-specific gene expression data, to explore promising genes that associated with SCI-TBI-HO. Results We identified four SCI-TBI-HO-associated genes, including GDF15, LDLR, CCL2, and CLU. Finally, using enrichment analysis, we identified several pathways, including integrin signaling, insulin pathway, internalization of ErbB1, urokinase-type plasminogen activator and uPAR-mediated signaling, PDGFR-beta signaling pathway, EGF receptor (ErbB1) signaling pathway, and class I PI3K signaling events, which may be associated with SCI-TBI-HO. Conclusions These results enhance our understanding of the molecular mechanisms of SCI-TBI-HO and offer new leads for researchers and innovative therapeutic strategies.

Identification of Four Key Biomarkers and Small Molecule Drugs Innasopharyngeal Carcinoma by Weighted Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Xi Pan ◽  
Jian-Hao Liu
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Therapeutic Goals ◽  
Small Molecule Drugs

Abstract Background Nasopharyngeal carcinoma (NPC) is a heterogeneous carcinoma that the underlying molecular mechanisms involved in the tumor initiation, progression, and migration are largely unclear. The purpose of the present study was to identify key biomarkers and small-molecule drugs for NPC screening, diagnosis, and therapy via gene expression profile analysis. Methods Raw microarray data of NPC were retrieved from the Gene Expression Omnibus (GEO) database and analyzed to screen out the potential differentially expressed genes (DEGs). The key modules associated with histology grade and tumor stage was identified by using weighted correlation network analysis (WGCNA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of genes in the key module were performed to identify potential mechanisms. Candidate hub genes were obtained, which based on the criteria of module membership (MM) and high connectivity. Then we used receiver operating characteristic (ROC) curve to evaluate the diagnostic value of hub genes. The Connectivity map database was further used to screen out small-molecule drugs of hub genes. Results A total of 430 DEGs were identified based on two GEO datasets. The green gene module was considered as key module for the tumor stage of NPC via WGCNA analysis. The results of functional enrichment analysis revealed that genes in the green module were enriched in regulation of cell cycle, p53 signaling pathway, cell part morphogenesis. Furthermore, four DEGs-related hub genes in the green module were considered as the final hub genes. Then ROC revealed that the final four hub genes presented with high areas under the curve, suggesting these hub genes may be diagnostic biomarkers for NPC. Meanwhile, we screened out several small-molecule drugs that have provided potentially therapeutic goals for NPC. Conclusions Our research identified four potential prognostic biomarkers and several candidate small-molecule drugs for NPC, which may contribute to the new insights for NPC therapy.

scholarly journals The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins

2019 ◽  
Author(s):  
Jarmila Nahálková
Keyword(s):  
Signaling Pathway ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Protein Protein Interaction ◽  
P53 Signaling ◽  
Age Related ◽  
P53 Signaling Pathway ◽  
Protein Protein Interaction Network

The protein-protein interaction network of seven pleiotropic proteins (PIN7) contains proteins with multiple functions in the aging and age-related diseases (TPPII, CDK2, MYBBP1A, p53, SIRT6, SIRT7, and BSG). At the present work, the pathway enrichment, the gene function prediction and the protein node prioritization analysis were applied for the examination of main molecular mechanisms driving PIN7 and the extended network. Seven proteins of PIN7 were used as an input for the analysis by GeneMania, a Cytoscape application, which constructs the protein interaction network. The software also extends it using the interactions retrieved from databases of experimental and predicted protein-protein and genetic interactions. The analysis identified the p53 signaling pathway as the most dominant mediator of PIN7. The extended PIN7 was also analyzed by Cytohubba application, which showed that the top-ranked protein nodes belong to the group of histone acetyltransferases and histone deacetylases. These enzymes are involved in the reverse epigenetic regulation mechanisms linked to the regulation of PTK2, NFκB, and p53 signaling interaction subnetworks of the extended PIN7. The analysis emphasized the role of PTK2 signaling, which functions upstream of the p53 signaling pathway and its interaction network includes all members of the sirtuin family. Further, the analysis suggested the involvement of molecular mechanisms related to metastatic cancer (prostate cancer, small cell lung cancer), hemostasis, the regulation of the thyroid hormones and the cell cycle G1/S checkpoint. The additional data-mining analysis showed that the small protein interaction network MYBBP1A-p53-TPPII-SIRT6-CD147 controls Warburg effect and MYBBP1A-p53-TPPII-SIRT7-BSG influences mTOR signaling and autophagy. Further investigations of the detail mechanisms of these interaction networks would be beneficial for the development of novel treatments for aging and age-related diseases.

scholarly journals Identification and Validation of Three Core Genes in p53 Signaling Pathway in Hepatitis B Virus-Related Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Mingxue Yu ◽  
Wenli Xu ◽  
Yusheng Jie ◽  
Jiahui Pang ◽  
Siqi Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Liver Cancer Cell ◽  
P53 Signaling ◽  
P53 Signaling Pathway ◽  
Core Genes

Abstract Background：Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus infection. We aimed to identify some core genes and pathways for HBV-related HCC. Methods: Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes. Then functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of gene expression in tumor tissues from HBV related HCC patients, HBV-related liver cell lines, and transfection si-p53 and knock-out p53 liver cancer cell lines. Finally, the prediction of the ceRNA network was constructed with R software. Results: Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed highly-expressed samples of three core genes were all enriched in the p53 signaling pathway in a validation dataset(P<0.0001). Expression of these three core genes were consistently higher in tumor tissue samples (P<0.0001) and liver cancer cell lines (P<0.05). However, transfection si-p53 and knock-out p53 liver cancer cell lines had lower expression (P<0.05). LncRNAs, including NEAT1, MALAT1, XIST, AC021078.1, and SNHG16, were identified by close interactions with core genes. Conclusions: CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

scholarly journals Exploring the Mechanism of Baicalin Intervention in Breast Cancer Based on MicroRNA Microarrays and Bioinformatics Strategies

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Anqi Ge ◽  
Lifang Liu ◽  
Xian’guang Deng ◽  
Jun Luo ◽  
Yanghua Xu
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Signaling Pathway ◽  
Breast Cancer Cells ◽  
Enrichment Analysis ◽  
Dependent Manner ◽  
P53 Signaling ◽  
Microrna Microarrays ◽  
P53 Signaling Pathway ◽  
Mcf 7

Objective. To explore the mechanism of baicalin intervention in breast cancer based on microRNA microarrays. Methods. The inhibitory rate of baicalin intervention in MCF-7 breast cancer cells was determined by MTT. Then, the miRNA microarrays were used to validate the key microRNAs. After that, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate microRNA, hsa-miR-15a, hsa-miR-100, hsa-miR-16, and hsa-miR-7t. Finally, the potential targets of these key microRNAs are predicted by miRWalk, and DAVID was utilized for gene ontology (GO) enrichment analysis and pathway enrichment analysis. Results. Baicalin may inhibit the proliferation of MCF-7 cells in a dose-dependent and time-dependent manner. The concentration of baicalin 150 μmol/L was determined for the subsequent miRNA chip research. A total of 92 upregulated microRNAs and 35 downregulated microRNAs were obtained. The upregulated miRNAs include hsa-miR-6799-5p, hsa-miR-6126, hsa-miR-4792, hsa-miR-6848-5p, hsa-miR-3197, hsa-miR-6779-5p, and hsa-miR -654-5p. The downregulated miRNAs include hsa-miR-3911, hsa-miR-504-5p, hsa-miR-30a-3p, hsa-miR-193b-3p, and hsa-miR-181b-5p. Then, differentially expressed miRNA was verified by qRT-PCR. The results showed that the expression of hsa-miR-15a, hsa-miR-100, hsa-miR-16, and hsa-let-7c was upregulated ( P < 0.05 ), which was consistent with the results of the miRNA microarray. The enrichment analysis showed that baicalin might regulate the DNA-templated proliferation, DNA-templated transcription, p53 signaling pathway, etc., of MCF-7 breast cancer cells through miRNA. Conclusion. Baicalin inhibits the proliferation of breast cancer cells. It may achieve antitumor effects through regulating microRNAs so as to affect the DNA replication (such as cellular response to DNA damage stimulus and DNA binding), RNA transcription (such as regulation of transcription, DNA-templated, transcription from RNA polymerase II promoter, and transcription factor binding), protein synthesis (such as mRNA binding, Golgi apparatus, and protein complex), endocytosis, pathways in cancer, p53 signaling pathway, and so on.

scholarly journals Identification of Molecular Mechanisms Underlying Sex-Associated Differences in the Chronic Obstructive Pulmonary Disease through Bioinformatics Analysis

2021 ◽  
Author(s):  
Fengshou Chen ◽  
Haijia Hou ◽  
Jie Han ◽  
Bing Tang
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Cholesterol Metabolism ◽  
Chronic Obstructive ◽  
Hub Genes ◽  
Obstructive Pulmonary Disease ◽  
P53 Signaling ◽  
Copd Patients ◽  
P53 Signaling Pathway

Abstract Background Accumulating evidence suggests the existence sex associated differences in the Chronic Obstructive Pulmonary Disease (COPD). However, limited knowledge exists on the molecular mechanisms underlying sex associated differences in COPD patients. Methods The GSE8581 dataset obtained from the GEO database was used to analyze differentially expressed genes (DEGs). Then enrichment analysis for DEGs were conducted through Metascape. PPI and the hub genes-pathway networks were constructed using the STRING database and Cytoscape software. Finally, the CTD was used to examine the relationships between the hub DEGs and COPD. Results The results revealed that different subsets of DEGs had different characteristics in GO functions and KEGG pathways. Different subsets of hub genes were obtained based on PPI network. The study then constructed the hub genes-pathway network for different subsets to explore the key signaling pathways and hub genes involved. The findings showed that NRAS and RAC1 functioned through “Rap1 signaling pathway” and “PI3K-Akt signaling pathway”, in male COPD patients. On the other hand, “Cholesterol metabolism” was among the important pathways in female COPD patients while the hub genes, APOE and APOC3 functioned through “Cholesterol metabolism”. Moreover, “Ubiquitin mediated proteolysis” and the “p53 signaling pathway” were shown to play more important roles in male COPD patients compared to their female counterparts. Furthermore, CDK2 and UBE2N were the hub genes involved in “p53 signaling pathway” and “Ubiquitin mediated proteolysis”, respectively. Finally the study identified the relationship between the hub genes and COPD in CTD. Conclusions The present study uncovered different molecular mechanisms in COPD patients based on sex. Additionally, distinct pathways and hub genes including NRAS, RAC1, APOE, APOC3, CDK2 and UBE2N were identified in the two genders of COPD patients. Further studies are needed to explore individualized treatment for COPD based on the findings.

scholarly journals Hub Genes of Stroke Identified by Weighted Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Junhong Li ◽  
Yang Zhai ◽  
Peng Wu ◽  
Yueqiang Hu ◽  
Wei Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Common Disease ◽  
Hub Genes ◽  
Neuron Death ◽  
Roc Curve Analysis

Abstract BACKGROUD: Microarray-based gene expression profiling is widely used in biomedical research. Weighted gene co-expression network analysis (WGCNA) links microarray data directly to clinical traits and identifies rules for predicting pathological stage and prognosis of disease.WGCNA is useful in understandingmany biological processes. Stroke is a common disease worldwide, however, molecular mechanisms of its pathogenesis are largely unknown. The aim of this study was to construct gene co-expression networks for identification of key modules and hub genes associated with stroke pathogenesis.METHODS: Gene microarray expression profiles of stroke samples were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package in R software. WGCNA was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify key modules and hub genes. Subsequently, functional enrichment analyses were performed. Further, receiver operating characteristic (ROC) curve analysis was carried out to validate expression of hub genes and literature validation was performed as well.RESULTS: A total of 11,747 most variant genes were used for co-expression network construction. Pink and yellow modules were significantly correlated to stroke pathogenesis. Functional enrichment analysis showed that the pink module was mainly involved in regulation of neuron regeneration, and repair of DNA damage.On the other hand, yellow module was mainly enriched in ion transport system dysfunction which was correlated with neuron death. A total of eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) were identified and validated at transcriptional levels and through existing literature.CONCLUSION: The eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) identified in the study are potentialbiomarkers and therapeutic targets for effective diagnosis and treatment of stroke.

scholarly journals Dynamical Regulation Analysis Identifies Molecular Mechanisms of Fuzheng-Huayu Formula against Hepatitis B-Caused Liver Cirrhosis

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qi-Long Chen ◽  
Yi-Yu Lu ◽  
Jing-Hua Peng ◽  
Shu Dong ◽  
Bin Wei ◽  
...  
Keyword(s):  
Liver Cirrhosis ◽  
Hepatitis B ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Critical Function ◽  
P53 Signaling ◽  
New Strategy ◽  
Target Network

Fuzheng-Huayu (FZHY) tablet was formulated based on Chinese medicine theory in treating liver fibrosis. A clinical trial has indicated that FZHY can against hepatitis B-caused liver cirrhosis (HBC), but the underlying mechanism of FZHY efficacy is unclear. Here, we report that miRNA expression levels are remarkably changed when FZHY formula was used in HBC patient’s treatment as a paradigm of trials. Then, we functionally characterize the significant impact of potential kernel miRNAs by miRNA-target network analysis. Enrichment analysis show that the FZHY formula dramatically effecting the molecular regulated module in HBC. Thus, we infer that FZHY plays a critical function in HBC treatment process and directly regulated many important pathways, including but not limited to cell cycle, p53 signaling pathway, and TGF-βsignaling pathway, suggesting a new strategy for investigating the molecular mechanism of FZHY treatment.

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