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1.
West China Journal of Stomatology ; (6): 533-540, 2023.
Article in English | WPRIM | ID: wpr-1007936

ABSTRACT

OBJECTIVES@#To investigate possible cross-talk genes, associated pathways, and transcription factors between chronic periodontitis (CP) and chronic obstructive pulmonary disease (COPD).@*METHODS@#The gene expression profiles of CP (GSE10334 and GSE16134) and COPD (GSE76925) were downloaded from the GEO database. Differential expression and functional clustering analyses were performed. The protein‑protein interaction (PPI) network was constructed. The core cross-talk genes were filtered using four topological analysis algorithms and modular segmentation. Then, functional clustering analysis was performed again.@*RESULTS@#GSE10334 detected 164 differentially expressed genes (DEGs) (119 upregulated and 45 downregulated). GSE16134 identified 208 DEGs (154 upregulated and 54 downregulated). GSE76925 identified 1 408 DEGs (557 upregulated and 851 downregulated). The PPI network included 21 nodes and 20 edges. The final screening included seven cross-talk genes: CD79A, FCRLA, CD19, IRF4, CD27, SELL, and CXCL13. Relevant pathways included primary immunodeficiency, the B-cell receptor signaling pathway, and cytokine-cytokine receptor interaction.@*CONCLUSIONS@#This study indicates the probability of shared pathophysiology between CP and COPD, and their cross-talk genes, associated pathways, and transcription factors may offer novel concepts for future mechanistic investigations.


Subject(s)
Humans , Chronic Periodontitis/genetics , Gene Regulatory Networks , Gene Expression Profiling , Protein Interaction Maps/genetics , Pulmonary Disease, Chronic Obstructive/genetics
2.
Chinese Journal of Preventive Medicine ; (12): 1040-1046, 2023.
Article in Chinese | WPRIM | ID: wpr-985506

ABSTRACT

Objective: Using bioinformatics methods to analyze the core pathogenic genes and related pathways in elderly osteoporosis. Methods: From November 2020 and August 2021, eight elderly osteoporosis patients who received treatment and five healthy participants who underwent physical examinations in Beijing Jishuitan Hospital were selected as subjects. The expression level of RNA in the peripheral blood of eight elderly osteoporosis patients and five healthy participants was collected for high-throughput transcriptome sequencing and analysis. The gene ontology (GO) analysis Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING website and Cytoscape software, and the most significant modules and hub genes were screened out. Results: Among the eight elderly osteoporosis patients, there were seven females and one male, with an average age of 72.4 years (SD=4.2). Among the five healthy participants, there were four females and one male, with an average age of 68.2 years (SD=5.7). A total of 1 635 DEGs (847 up-regulated and 788 down-regulated) were identified. GO analysis revealed that the molecular functions of DEGs were mainly enriched in structural constituents of the ribosome, protein dimerization activity, and cellular components were mainly enriched in the nucleosome, DNA packaging complex, cytosolic part, protein-DNA complex and the cytosolic ribosome. KEGG pathway analysis showed that DEGs were mainly enriched in systemic lupus erythematosus and ribosome. Gene UBA52, UBB, RPS27A, RPS15, RPS12, RPL13A, RPL23A, RPL10A, RPS25 and RPS6 were selected and seven of them could encode ribosome proteins. Conclusion: The pathogenesis of elderly osteoporosis may be associated with ribosome-related genes and pathways.


Subject(s)
Female , Humans , Male , Aged , Gene Expression Profiling/methods , Transcriptome , Protein Interaction Maps/genetics , Computational Biology/methods , Osteoporosis/genetics
3.
Journal of Forensic Medicine ; (6): 433-440, 2023.
Article in English | WPRIM | ID: wpr-1009374

ABSTRACT

OBJECTIVES@#The common differentially expressed mRNAs in brain, heart and liver tissues of deceased sudden infant death syndrome (SIDS) and infectious sudden death in infancy (ISDI) confirmed by autopsy was screened by bioinformatics to explore the common molecular markers and pathogenesis of SIDS and ISDI.@*METHODS@#The datasets of GSE70422 and GSE136992 were downloaded, the limma of R software was used to screen differentially expressed mRNA in different tissue samples of SIDS and ISDI decedents for overlapping analysis. The clusterProfiler of R software was used to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The protein-protein interaction (PPI) network was constructed by STRING database, while the hub gene was screened by cytoHubba plug-in.@*RESULTS@#Compared with the control group, there were 19 significant differentially expressed genes in the tissue samples of SIDS and ISDI decedents, among which 16 in the heart tissue and 3 in the liver tissue, and the astrotactin 1 (ASTN1) gene expression difference in the heart tissue was most significant. The PPI network identified Ras homolog family member A (RHOA), integrin subunit alpha 1 (ITGA1), and H2B clustered histone 5 (H2BC5) were hub genes. The analysis of GO and KEGG showed that differentially expressed genes were enriched in the molecular pathways of actin cytoskeleton regulation, focal adhesion and response to mycophenolic acid.@*CONCLUSIONS@#ASTN1, RHOA and ITGA1 may participate in the development of SIDS and ISDI. The enrichment of differentially expressed genes in immune and inflammatory pathways suggests a common molecular regulatory mechanism between SIDS and ISDI. These findings are expected to provide new biomarkers for molecular anatomy and forensic identification of SIDS and ISDI.


Subject(s)
Humans , Infant , Gene Expression Profiling , Sudden Infant Death/genetics , Gene Regulatory Networks , Protein Interaction Maps/genetics , Computational Biology
4.
Journal of Experimental Hematology ; (6): 511-515, 2022.
Article in Chinese | WPRIM | ID: wpr-928745

ABSTRACT

OBJECTIVE@#To identify the key genes and explore mechanisms in the development of myelodysplastic syndrome (MDS) by bioinformatics analysis.@*METHODS@#Two cohorts profile datasets of MDS were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed gene (DEG) was screened by GEO2R, functional annotation of DEG was gained from GO database, gene ontology (GO) enrichment analysis was performed via Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and key genes were screened by Matthews correlation coefficient (MCC) based on STRING database.@*RESULTS@#There were 112 DEGs identified, including 85 up-regulated genes and 27 down-regulated genes. GO enrichment analysis showed that biological processes were mainly enriched in immune response, etc, cellular component in cell membrane, etc, and molecular function in protein binding, etc. KEGG signaling pathway analysis showed that main gene enrichment pathways were primary immunodeficiency, hematopoietic cell lineage, B cell receptor signaling pathway, Hippo signaling pathway, and asthma. Three significant modules were screened by Cytoscape software MCODE plug-in, while 10 key node genes (CD19, CD79A, CD79B, EBF1, VPREB1, IRF4, BLNK, RAG1, POU2AF1, IRF8) in protein-protein interaction (PPI) network were screened based on STRING database.@*CONCLUSION@#These screened key genes and signaling pathways are helpful to better understand molecular mechanism of MDS, and provide theoretical basis for clinical targeted therapy.


Subject(s)
Humans , Computational Biology , Gene Expression , Gene Expression Profiling , Microarray Analysis , Myelodysplastic Syndromes/genetics , Protein Interaction Maps
5.
Journal of Zhejiang University. Medical sciences ; (6): 62-72, 2022.
Article in English | WPRIM | ID: wpr-928657

ABSTRACT

To explore the mechanism of ovarian toxicity of Hook. F. (TwHF) by network pharmacology and molecular docking. The candidate toxic compounds and targets of TwHF were collected by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Comparative Toxicogenomics Database (CTD). Then, the potential ovarian toxic targets were obtained from CTD, and the target genes of ovarian toxicity of TwHF were analyzed using the STRING database. The protein-protein interaction (PPI) network was established by Cytoscape and analyzed by the cytoHubba plug-in to identify hub genes. Additionally, the target genes of ovarian toxicity of TwHF were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses by using the R software. Finally, Discovery Studio software was used for molecular docking verification of the core toxic compounds and the hub genes. Nine candidate toxic compounds of TwHF and 56 potential ovarian toxic targets were identified in this study. Further network analysis showed that the core ovarian toxic compounds of TwHF were triptolide, kaempferol and tripterine, and the hub ovarian toxic genes included , , , , , , , , and . Besides, the GO and KEGG analysis indicated that TwHF caused ovarian toxicity through oxidative stress, reproductive system development and function, regulation of cell cycle, response to endogenous hormones and exogenous stimuli, apoptosis regulation and aging. The docking studies suggested that 3 core ovarian toxic compounds of TwHF were able to fit in the binding pocket of the 10 hub genes. TwHF may cause ovarian toxicity by acting on 10 hub genes and 140 signaling pathways.


Subject(s)
Drugs, Chinese Herbal/toxicity , Medicine, Chinese Traditional , Molecular Docking Simulation , Network Pharmacology , Protein Interaction Maps
6.
Journal of Southern Medical University ; (12): 171-180, 2022.
Article in Chinese | WPRIM | ID: wpr-936299

ABSTRACT

OBJECTIVE@#To study the therapeutic mechanism of Longqi Fang (LQF) for diabetic kidney disease (DKD) based on GEO database and network pharmacology.@*METHODS@#LQF and DKD targets were obtained using the databases including GEO, TCMSP, CNKI, ChemDraw, and SwissTarget Prediction, and LQF-DKD intersection targets were obtained with VENNY. String was used for protein-protein interaction (PPI) analysis, and R package for KEGG and GO enrichment analysis. Cytoscape 3.7.2 software Network graphs were constructed. The results of network pharmacology analysis were verified in SD rat models of DKD by daily treatment of the rats with LQF at low (1 g/kg), medium (2 g/kg), and high (2 g/kg) doses, and kidney pathology was observed with HE staining and the changes in renal function were assessed. Western blotting was used to detect the expression levels of NF-κB and p-NF-κB proteins.@*RESULTS@#We identified 760 main targets of LQF, and obtained 1026 differential genes using GEO database and 61 LQF-DKD intersection targets using Venny database. The core targets obtained through PPI network analysis included Myc, EGF, CASP3, VEGFA, CCL2, SPP1, VCAM1 and ICAM1. Go analysis showed that LQF affects mainly nuclear receptor activity and ligand activated transcription factor activity. KEGG analysis showed that LQF affects inflammatory signaling pathways by interfering with NF-κB, TNF, and PI3K-AKT. In rat models of DKD, treatment with LQF resulted in significant improvements of the renal functions (P < 0.05) and glomerular and tubular structure and arrangement in a dose-dependent manner. Western blotting results showed that LQF dose-dependently downregulated NF-κB and p-NF-κB expressions in the rat models.@*CONCLUSION@#The therapeutic mechanism of LQF for DKD involves multiple components, targets and signal pathways that mediate an inhibitory effect on NF-κB signaling pathway to protect the renal function.


Subject(s)
Animals , Rats , Diabetes Mellitus , Diabetic Nephropathies/metabolism , Network Pharmacology , Phosphatidylinositol 3-Kinases/metabolism , Protein Interaction Maps , Rats, Sprague-Dawley
7.
Chinese Journal of Hepatology ; (12): 297-303, 2022.
Article in Chinese | WPRIM | ID: wpr-935941

ABSTRACT

Objective: To screen and analyze the key differentially expressed genes characteristics in nonalcoholic fatty liver disease (NAFLD) with bioinformatics method. Methods: NAFLD-related expression matrix GSE89632 was downloaded from the GEO database. Limma package was used to screen differentially expressed genes (DEGs) in healthy, steatosis (SS), and nonalcoholic steatohepatitis (NASH) samples. WGCNA was used to analyze the output gene module. The intersection of module genes and differential genes was used to determine the differential genes characteristic, and then GO function and KEGG signaling pathway enrichment analysis were performed. The protein-protein interaction network (PPI) was constructed using the online website STRING and Cytoscape software, and the key (Hub) genes were screened. Finally, R software was used to analyze the receiver operating characteristic curve (ROC) of the Hub gene. Results: 92 differentially expressed genes characteristic were obtained through screening, which were mainly enriched in inflammatory response-related functions of "lipopolysaccharide response and molecular response of bacterial origin", as well as cancer signaling pathways of "proteoglycan in cancer" and "T-cell leukemia virus infection-related". 10 hub genes (FOS, CXCL8, SERPINE1, CYR61, THBS1, FOSL1, CCL2, MYC, SOCS3 and ATF3) had good diagnostic value. Conclusion: The differentially expressed hub genes among the 10 NAFLD disease-related characteristics obtained with bioinformatics analysis may become a diagnostic and prognostic marker and potential therapeutic target for NAFLD. However, further basic and clinical studies are needed to validate.


Subject(s)
Humans , Computational Biology/methods , Gene Expression Profiling/methods , Gene Regulatory Networks , Non-alcoholic Fatty Liver Disease/genetics , Protein Interaction Maps/genetics
8.
Int. braz. j. urol ; 47(4): 843-855, Jul.-Aug. 2021. tab, graf
Article in English | LILACS | ID: biblio-1286781

ABSTRACT

ABSTRACT Objective: Interstitial cystitis (IC)/bladder pain syndrome (BPS) is a chronic inflammatory disease that can cause bladder pain and accompanying symptoms, such as long-term urinary frequency and urgency. IC/BPS can be ulcerative or non-ulcerative. The aim of this study was to explore the core genes involved in the pathogenesis of ulcerative IC, and thus the potential biomarkers for clinical treatment. Materials and Methods: First, the gene expression dataset GSE11783 was downloaded using the Gene Expression Omnibus (GEO) database and analyzed using the limma package in R to identify differentially expressed genes (DEGs). Then, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for Gene Ontology (GO) functional analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Finally, the protein-protein interaction (PPI) network was constructed, and key modules and hub genes were determined using the STRING and Cytoscape software. The resulting key modules were then analyzed for tissue-specific gene expression using BioGPS. Results: A total of 216 up-regulated DEGs and 267 down-regulated genes were identified, and three key modules and nine hub genes were obtained. Conclusion: The core genes (CXCL8, CXCL1, IL6) obtained in this study may be potential biomarkers of interstitial cystitis with guiding significance for clinical treatment.


Subject(s)
Humans , Cystitis, Interstitial/genetics , Software , Gene Expression Profiling , Protein Interaction Maps/genetics , Gene Ontology
9.
Journal of Central South University(Medical Sciences) ; (12): 1063-1070, 2021.
Article in English | WPRIM | ID: wpr-922585

ABSTRACT

OBJECTIVES@#The biomarkers targeting colorectal cancer (CRC) prognosis are short of high accuracy and sensitivity in clinic. Through bioinformatics analysis, we aim to identify and confirm a series of key genes referred to the diagnosis and prognosis of CRC.@*METHODS@#GSE31905, GSE35279, and GSE41657 were selected as complete RNA sequencing data sets of CRC and colorectal mucosa (CRM) tissues from the NCBI-GEO database, and the differentially expressed genes (DEGs) were analyzed. The common DEGs in these 3 data sets were obtained by Venn map, and enriched by STRING network system and Cytoscape software. The Kaplan-Meier plotter website was used to verify the correlation between the enriched genes and the prognosis of CRC.@*RESULTS@#For the whole RNA sequencing data sets of CRC and normal intestinal mucosa samples, the DEGs of CRC and CRM in the 3 data sets (|log@*CONCLUSIONS@#The above 11 genes verified by bioinformatics retrieval and analysis can predict the poor prognosis of CRC to a certain extent, and they provide a possible target for the diagnosis and treatment of CRC.


Subject(s)
Humans , Biomarkers, Tumor/metabolism , Colorectal Neoplasms/genetics , Computational Biology , Formins , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Glycoproteins , Intercellular Signaling Peptides and Proteins , Oncogenes , Prognosis , Protein Interaction Maps
10.
West China Journal of Stomatology ; (6): 633-641, 2021.
Article in English | WPRIM | ID: wpr-921385

ABSTRACT

OBJECTIVES@#To identify the differentially expressed genes (DEGs) during the pathogenesis of periodontitis by bioinformatics analysis.@*METHODS@#GEO2R was used to screen DEGs in GSE10334 and GSE16134. Then, the overlapped DEGs were used for further analysis. g:Profiler was used to perform Gene Ontology analysis and pathway analysis for upregulated and downregulated DEGs. The STRING database was used to construct the protein-protein interaction (PPI) network, which was further visua-lized and analyzed by Cytoscape software. Hub genes and key modules were identified by cytoHubba and MCODE plug-ins, respectively. Finally, transcription factors were predicted via iRegulon plug-in.@*RESULTS@#A total of 196 DEGs were identified, including 139 upregulated and 57 downregulated DEGs. Functional enrichment analysis showed that the upregulated DEGs were mainly enriched in immune-related pathways including immune system, viral protein interaction with cytokine and cytokine receptor, cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and chemokine receptors bind chemokines. On the contrary, the downregulated DEGs were mainly related to the formation of the cornified envelope and keratinization. The identified hub genes in the PPI network were CXCL8, CXCL1, CXCR4, SEL, CD19, and IKZF1. The top three modules were involved in chemokine response, B cell receptor signaling pathway, and interleukin response, respectively. iRegulon analysis revealed that IRF4 scored the highest.@*CONCLUSIONS@#The pathogenesis of periodontitis was closely associated with the expression levels of the identified hub genes including CXCL8, CXCL1, CXCR4, SELL, CD19, and IKZF1. IRF4, the predicted transcription factor, might serve as a dominant upstream regulator.


Subject(s)
Humans , Computational Biology , Gene Expression Profiling , Microarray Analysis , Periodontitis , Protein Interaction Maps
11.
China Journal of Chinese Materia Medica ; (24): 4522-4530, 2021.
Article in Chinese | WPRIM | ID: wpr-888154

ABSTRACT

Magnoliae Officinalis Cortex(Houpo) can treat peptic ulcer disease(PUD), the mechanism of which remains unclear. In this study, network pharmacology and molecular docking were employed to predict the mechanism of Houpo in the treatment of PUD. Through literature review and TCMSP screening, 15 main active ingredients were obtained. The SwissTargetPrediction database was used to predict the potential targets of the ingredients, and Therapeutic Target Database(TTD), DrugBank, and Human Phenotype Ontology(HPO) to screen the disease-related targets. A total of 49 potential targets were obtained by the intersection of active ingre-dients-related targets and disease-related targets. Cytoscape 3.6.1 was employed to construct the protein-protein interaction network for the targets with high confidence(score>0.700) screened out by STRING. The DAVID database was used for GO and KEGG pathway enrichment of potential targets. GO enrichment analysis showed that the treatment mechanism was mostly related to nuclear receptor activity, ligand-activated transcription factor activity, and G protein-coupled acetylcholine receptor activity. KEGG enrichment analysis found that Houpo could regulate material metabolism, endocrine system, p53 signaling pathway, and PPAR signaling pathway. Molecu-lar docking verified that all 15 ingredients had good binding activities with key targets(CHRM1, CHRM2, FABP1, mTOR, and STAT3). The results mean that Houpo can treat PUD by participating in cell metabolism, inhibiting inflammatory cytokines, and regulating cell proliferation and apoptosis.


Subject(s)
Humans , Drugs, Chinese Herbal , Molecular Docking Simulation , Peptic Ulcer , Protein Interaction Maps , Receptor, Muscarinic M1 , Signal Transduction
12.
China Journal of Chinese Materia Medica ; (24): 3970-3979, 2021.
Article in Chinese | WPRIM | ID: wpr-888123

ABSTRACT

The traditional Chinese medicines(TCM) for activating blood circulation and the TCM for regulating Qi are often used in combination in clinical practice. However, their mechanisms are still unclear. The activity spectrum of targets can fuse the active components, targets and intensity of action, which provides support for the discussion of efficacy targets. The chemical components of common TCM sets for activating blood circulation and regulating Qi, as well as the negative sets not for activating blood circulation and re-gulating Qi were obtained from the database of TCM. By the similarity analysis of chemical components in TCM for activating blood circulation and DrugBank database, the predicted targets of chemical components in TCM for activating blood circulation were obtained, and the similarity value of the two was taken as the activity value of the active components and predicted targets. Then, the component-target activity value was weighted. The activity values of herb acting on the same target were fused to construct activity spectra of targets of the herbs for activating blood circulation, herbs for regulating Qi and negative herbs. The targets whose activity values of activating blood circulation and regulating Qi were higher than those of negative herbs were selected as potential targets of efficacy. Protein-protein interaction networks were constructed for topological, GO and KEGG enrichment analysis to determine the key targets of efficacy of activating blood circulation and regulating Qi. The component-target activity information collected from DrugBank database contained 4 499 compounds, 627 targets and 11 295 action relationships. The activating blood function protein-protein interaction network contained 206 nodes and 1 728 edges, while the regulating Qi function protein-protein interaction network contained 230 nodes and 986 edges. The enrichment analysis of topology, GO and KEGG showed that TCM for activating blood circulation mainly exerted its anti-inflammatory, neuroprotective and angiogenic effects on signaling cascade pathway mediated by VEGF/VEGFR2, ERK signaling pathway, calcium signaling pathway and PI3 K-AKT signaling pathway, and the key targets included mitogen activated protein kinases 3(MAPK3), proto-oncogene tyrosine-protein kinase Src(SRC), mitogen activated protein kinases 1(MAPK1), epidermal growth factor receptor(EGFR), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform(PIK3 CA), peroxisome proliferators-activated receptor gamma(PPARG), nitric oxide synthase 3(NOS3), prostaglandin G/H synthetase 2(PTGS2), matrix metalloproteinase-9(MMP9), and vascular endothelial growth factor A(VEGFA). TCM for regulating Qi mainly exerted anti-inflammatory and neuroprotective effects by acting on MAPK signaling pathway and PI3 K-AKT signaling pathway, and the key targets included mitogen activated protein kinases 8(MAPK8), SRC, mitogen activated protein kinases 14(MAPK14), and RAC-alpha serine/threonine-protein kinase(AKT1), mitogen activated protein kinases 3(MAPK3). Based on the activity spectrum of targets, the targets of the TCM for activating blood and the targets of the TCM for regulating Qi were analyzed to provide reference for the study of efficacy targets of TCM, and also provide some scientific basis for clinical application.


Subject(s)
Drugs, Chinese Herbal/pharmacology , Medicine, Chinese Traditional , Protein Interaction Maps , Qi , Vascular Endothelial Growth Factor A
13.
Acta Academiae Medicinae Sinicae ; (6): 371-381, 2021.
Article in Chinese | WPRIM | ID: wpr-887869

ABSTRACT

Objective To explore the function and mechanism of related genes in the occurrence and development of liver cancer, and the possibility of key genes as potential biomarkers and prognostic indicators for the treatment of liver cancer.Methods We selected 4 datasets(GSE57957, GSE121248, GSE36376 and GSE14520)from the GEO database.With


Subject(s)
Humans , Biomarkers, Tumor/genetics , Carrier Proteins , Computational Biology , Cytochrome P-450 CYP2E1 , Cytochrome P-450 CYP3A , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Glycoproteins , Liver Neoplasms/genetics , Prognosis , Protein Interaction Maps
14.
China Journal of Chinese Materia Medica ; (24): 2413-2423, 2021.
Article in Chinese | WPRIM | ID: wpr-879142

ABSTRACT

To probe the potential hepatotoxic components of Epimedii Folium and investigate its mechanism based on network toxicology and cell experimental validation. According to the previous results of component measurement and cytotoxicity evaluation, 11 active compounds related to hepatotoxicity in Epimedii Folium were chosen as research object in this study. Through SwissTargetPrediction database and GeneCards database, the potentially hepatotoxic targets of Epimedii Folium were obtained. Subsequently, the protein-target interaction network and active compounds-hepatotoxic targets network were established to analyze the core targets and screen the key hepatotoxic compounds in Epimedii Folium. Meanwhile, the signaling pathways and molecular mechanisms were inferred with GO functional enrichment analysis and KEGG pathway enrichment analysis on the core targets. At last, the effect of icaritin as the chief hepatotoxic compound on the indexes related to hepatotoxicity in HL-7702 cells and HepG2 cells was investigated to validate the hepatotoxicity mechanism of Epimedii Folium. Through the network toxicology analysis, 190 action targets and 991 hepatotoxic targets were collected, then 64 potentially hepatotoxic targets of Epimedii Folium including AKT1, EGFR, MAPK3, TNF and so on were obtained, and icaritin was screened as the key hepatotoxic compound. GO functional enrichment analysis indicated 160 biological process terms such as protein phosphorylation and negative regulation of apoptotic process, 41 molecular function terms such as protein binding and ATP binding, and 32 cellular component terms such as cytosol and cell surface. KEGG pathway enrichment analysis inferred 75 signaling pathways involving PI3 K-Akt and HIF-1. After comprehensive analysis, it was inferred that the hepatotoxicity mechanism of Epimedii Folium was related with regulating oxidative stress and apoptosis. The results of cell biology experiments showed that icaritin could significantly increase the level of aspartate aminotransferase and lactate dehydrogenase, reduce the level of glutathione, improve the quality of reactive oxygen species and reduce mitochondrial membrane potential, indicating that it could cause hepatotoxicity by destroying cell membrane structure, inhibiting antioxidant enzyme activity, activating oxidative stress and inducing apoptosis. These results proved the reliability of results of network pharmacology. This study preliminarily clarified the material base and the mechanism of potential hepatotoxicity of Epimedii Folium, which provided important information for further research and safe application.


Subject(s)
Drugs, Chinese Herbal/toxicity , Plant Leaves , Protein Interaction Maps , Reproducibility of Results
15.
Braz. j. med. biol. res ; 54(11): e11363, 2021. graf
Article in English | LILACS | ID: biblio-1339445

ABSTRACT

Cervical cancer (CC) is the most common malignant tumor in females. Although persistent high-risk human papillomavirus (HPV) infection is a leading factor that causes CC, few women with HPV infection develop CC. Therefore, many mechanisms remain to be explored, such as aberrant expression of oncogenes and tumor suppressor genes. To identify promising prognostic factors and interpret the relevant mechanisms of CC, the RNA sequencing profile of CC was downloaded from the Cancer Genome Atlas and the Gene Expression Omnibus databases. The GSE63514 dataset was analyzed, and differentially expressed genes (DEGs) were obtained by weighted coexpression network analysis and the edgeR package in R. Fifty-three shared genes were mainly enriched in nuclear chromosome segregation and DNA replication signaling pathways. Through a protein-protein interaction network and prognosis analysis, the kinesin family member 14 (KIF14) hub gene was extracted from the set of 53 shared genes, which was overexpressed and associated with poor overall survival (OS) and disease-free survival (DFS) of CC patients. Mechanistically, gene set enrichment analysis showed that KIF14 was mainly enriched in the glycolysis/gluconeogenesis signaling pathway and DNA replication signaling pathway, especially in the cell cycle signaling pathway. RT-PCR and the Human Protein Atlas database confirmed that these genes were significantly increased in CC samples. Therefore, our findings indicated the biological function of KIF14 in cervical cancer and provided new ideas for CC diagnosis and therapies.


Subject(s)
Humans , Female , Uterine Cervical Neoplasms/genetics , Papillomavirus Infections , Gene Expression Regulation, Neoplastic , Cell Cycle/genetics , Kinesins/genetics , Oncogene Proteins , Disease-Free Survival , Computational Biology , Protein Interaction Maps
16.
Braz. arch. biol. technol ; 64: e21200118, 2021. tab, graf
Article in English | LILACS | ID: biblio-1339316

ABSTRACT

Abstract This paper focuses on developing a reduced distance matrix to improve the computational performance during the protein interactions clustering. This proposed matrix considers as centroids two alpha carbon atoms from a protein structure and stores the distances between these centroids and the other atoms from this same structure. Each row in this matrix represents a database record and each column is a distance value. Through this build matrix, clusters were performed using K-Means Clustering. The precision and performance of this presented technique were compared with aCSM, RID and another distance matrix methodology that considers the distances between all atoms from each protein structure. The results were satisfactory. The reduced distance matrix obtained a high precision and the best computational performance.


Subject(s)
Protein Interaction Maps , Carbon , Cluster Analysis , Computing Methodologies
17.
Journal of Zhejiang University. Science. B ; (12): 246-255, 2020.
Article in English | WPRIM | ID: wpr-1010531

ABSTRACT

To identify novel genes in castration-resistant prostate cancer (CRPC), we downloaded three microarray datasets containing CRPC and primary prostate cancer in Gene Expression Omnibus (GEO). R packages affy and limma were performed to identify differentially expressed genes (DEGs) between primary prostate cancer and CRPC. After that, we performed functional enrichment analysis including gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway. In addition, protein-protein interaction (PPI) analysis was used to search for hub genes. Finally, to validate the significance of these genes, we performed survival analysis. As a result, we identified 53 upregulated genes and 58 downregulated genes that changed in at least two datasets. Functional enrichment analysis showed significant changes in the positive regulation of osteoblast differentiation pathway and aldosterone-regulated sodium reabsorption pathway. PPI network identified hub genes like cortactin-binding protein 2 (CTTNBP2), Rho family guanosine triphosphatase (GTPase) 3 (RND3), protein tyrosine phosphatase receptor-type R (PTPRR), Jagged1 (JAG1), and lumican (LUM). Based on PPI network analysis and functional enrichment analysis, we identified two genes (PTPRR and JAG1) as key genes. Further survival analysis indicated a relationship between high expression of the two genes and poor prognosis of prostate cancer. In conclusion, PTPRR and JAG1 are key genes in the CRPC, which may serve as promising biomarkers of diagnosis and prognosis of CRPC.


Subject(s)
Humans , Male , Computational Biology/methods , Gene Ontology , Jagged-1 Protein/genetics , Prognosis , Prostatic Neoplasms, Castration-Resistant/mortality , Protein Interaction Maps , Receptor-Like Protein Tyrosine Phosphatases, Class 7/genetics
18.
Chinese Medical Sciences Journal ; (4): 54-64, 2020.
Article in English | WPRIM | ID: wpr-1008965

ABSTRACT

Objective Many physiological and pathological conditions, including cyanotic congenital heart diseases (CCHD), are accompanied by chronic hypoxia, which might interfere with the transcription process. However, the transcriptome profile in peripheral blood under hypoxia is still unidentified. The present work aimed to explore the transcriptional profile alteration of peripheral blood in chronic hypoxia. Methods The present study used a chronic hypoxia rat model to simulate the hypoxic state of CCHD patients. Two groups of Sprague-Dawley rats (n=6 per group) were either exposed to hypoxia (10% O2) or normoxia (21% O2) for 3 weeks. Body weight was measured weekly. Peripheral blood was collected and total RNA was extracted for RNA-Seq at the end of the hypoxia treatment. After quality assessment, the library was sequenced by the Illumina Hiseq platform. The differentially expressed genes were screened (false discovery rate<0.05 and fold change>2). The functional annotation analysis and cluster analysis of differentially expressed genes were performed based on the adjusted P-value (padj<0.05). Results Compared with the control group, the body weight of the rats in the hypoxia group was significantly lowered (P<0.01). RNA-Seq results showed that the transcriptome patterns of the two groups had significant differences. In total, 872 genes were identified as differentially expressed. Among all, 803 genes were down-regulated, while only 69 genes were up-regulated in the hypoxia group. The functional enrichment analysis of the 872 genes showed that multiple biological processes involved, such as porphyrin-containing compound metabolic process, hemoglobin complex and oxygen transporter activity. Conclusions Our study demonstrated the transcriptional profile alteration in peripheral blood of chronic hypoxia rat model. This study provided basic data and directions to further understand the physiological and pathological changes in patients with CCHD.


Subject(s)
Animals , Humans , Chronic Disease , Cluster Analysis , Disease Models, Animal , Gene Expression Profiling/methods , Gene Ontology , Gene Regulatory Networks , Heart Defects, Congenital/genetics , Hypoxia/genetics , Protein Interaction Maps/genetics , Rats, Sprague-Dawley
19.
China Journal of Chinese Materia Medica ; (24): 2611-2618, 2020.
Article in Chinese | WPRIM | ID: wpr-828038

ABSTRACT

To explore the main target and signal pathway of Simiao Yongan Decoction in the treatment of psoriatic arthritis(PsA) by network pharmacology, so as to reveal the intervention mechanism of Simiao Yongan Decoction in the treatment of psoriatic arthritis. The platform of pharmacology technology of traditional Chinese medicine system(TCMSP) was used to predict and screen the active ingredients of Simiao Yongan Decoction, and GeneCards database was searched to obtain the disease target related to the psoriatic arthritis. Protein interaction network model was constructed with STRING platform; drug-component-target-disease network map was constructed with Cytoscape Software; Wayne Diagram of common target of Simiao Yongan Decoction and psoriasis arthritis was drawn with the help of ClusterProfiler R Software. At the same time, the genetic ontology(GO) enrichment analysis and the Kyoto encyclopedia of genes and genomes(KEGG) pathway analysis were conducted. Through database analysis, 1 128 targets related to 70 main active components of Simiao Yongan Decoction and psoriatic arthritis were selected. On this basis, the interaction network between Simiao Yongan Decoction and psoriatic arthritis was constructed, and 38 common targets were screened out. By GO and KEGG enrichment analysis, 135 signal pathways related to the main components of Simiao Yongan Decoction were selected. It was found that Simiao Yong-an Decoction may play a role in the treatment of psoriatic arthritis through antiviral effect, anti-inflammatory repair, protection of vascular endothelial cells, regulation of immunity and other multiple targets. The mechanism of Simiao Yongan Decoction in the treatment of psoriatic arthritis from multi-component, multi-target and multi-pathway was revealed, which provided a research direction for screening its subsequent clinical effect evaluation indexes.


Subject(s)
Humans , Arthritis, Psoriatic , Drugs, Chinese Herbal , Endothelial Cells , Medicine, Chinese Traditional , Protein Interaction Maps
20.
Braz. j. med. biol. res ; 53(9): 0-0, 2020. tab, graf
Article in English | LILACS, ColecionaSUS | ID: biblio-1132553

ABSTRACT

Myocardial ischemia/reperfusion (MI/R) injury is a complex phenomenon that causes severe damage to the myocardium. However, the potential molecular mechanisms of MI/R injury have not been fully clarified. We identified potential molecular mechanisms and therapeutic targets in MI/R injury through analysis of Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were found between MI/R injury and normal samples, and overlapping DEGs were found between GSE61592 and GSE67308. Gene Ontology (GO) and pathway analysis were performed for overlapping DEGs by Database for Annotation, Visualization and Integration Discovery (DAVID). Then, a network of protein-protein interaction (PPI) was constructed through the Search Tool for the Retrieval of Interacting Genes (STRING) database. Potential microRNAs (miRNAs) and therapeutic small molecules were screened out using microRNA.org database and the Comparative Toxicogenomics database (CTD), respectively. Finally, we identified 21 overlapping DEGs related to MI/R injury. These DEGs were significantly enriched in IL-17 signaling pathway, cytosolic DNA-sensing pathway, chemokine signaling, and cytokine-cytokine receptor interaction pathway. According to the degree in the PPI network, CCL2, LCN2, HP, CCL7, HMOX1, CCL4, and S100A8 were found to be hub genes. Furthermore, we identified potential miRNAs (miR-24-3p, miR-26b-5p, miR-2861, miR-217, miR-4251, and miR-124-3p) and therapeutic small molecules like ozone, troglitazone, rosiglitazone, and n-3 polyunsaturated fatty acids for MI/R injury. These results identified hub genes and potential small molecule drugs, which could contribute to the understanding of molecular mechanisms and treatment for MI/R injury.


Subject(s)
Myocardial Reperfusion Injury , MicroRNAs , Computational Biology , Gene Expression Profiling , Gene Regulatory Networks , Protein Interaction Maps , Gene Ontology
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