Marine organisms cannot grow and reproduce without proper metabolic regulation.Within a metabolic network,problems with a given link will affect the normal life activities of the organism.Many metabolic mechanisms ass...Marine organisms cannot grow and reproduce without proper metabolic regulation.Within a metabolic network,problems with a given link will affect the normal life activities of the organism.Many metabolic mechanisms associated with behaviors of Am-phioctopus fangsiao are still unclear.Moreover,as a factor affecting the normal growth of A.fangsiao,egg protection has rarely been considered in previous behavioral studies.In this research,we analyzed the transcriptome profile of gene expression in A.fangsiao egg-unprotected larvae and egg-protected larvae,and identified 818 differentially expressed genes(DEGs).We used GO and KEGG enrichment analyses to search for metabolism-related DEGs.Protein-protein interaction networks were constructed to examine the interactions between metabolism-related genes.Twenty hub genes with multiple protein-protein interaction relationships or that were involved in multiple KEGG signaling pathways were obtained and verified by quantitative RT-PCR.We first studied the effects of egg protection on the metabolism of A.fangsiao larvae by means of protein-protein interaction networks,and the results provide va-luable gene resources for understanding the metabolism of invertebrate larvae.The data serve as a foundation for further research on the egg-protecting behavior of invertebrates.展开更多
Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies....Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.展开更多
Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes...Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.展开更多
Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported t...Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported to play a crucial role in axonal regeneration.Howeve r,the role of the IncRNA-microRNAmessenger RNA(mRNA)-competitive endogenous RNA(ceRNA)network in exosome-mediated axonal regeneration remains unclear.In this study,we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts(FC-EXOs)and Schwann cells(SCEXOs).Diffe rential gene expression analysis,Gene Ontology analysis,Kyoto Encyclopedia of Genes and Genomes analysis,and protein-protein intera ction network analysis were used to explo re the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs.We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs,which suggests that it may promote axonal regeneration.In addition,using the miRWalk and Starbase prediction databases,we constructed a regulatory network of ceRNAs targeting Rps5,including 27 microRNAs and five IncRNAs.The ceRNA regulatory network,which included Ftx and Miat,revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury.Our findings suggest that exosomes derived from fibro blast and Schwann cells could be used to treat injuries of peripheral nervous system.展开更多
BACKGROUND Gastric cancer(GC)is one of the most common cancers and has a poor prognosis.Treatment of GC has remained unchanged over the past few years.AIM To investigate the potential therapeutic targets and related r...BACKGROUND Gastric cancer(GC)is one of the most common cancers and has a poor prognosis.Treatment of GC has remained unchanged over the past few years.AIM To investigate the potential therapeutic targets and related regulatory biomarkers of GC.METHODS We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database.The datasets contained 348 GC tissues and 141 healthy tissues.In total,251 differentially expressed genes(DEGs)were identified,including 187 down-regulated genes and 64 up-regulated genes.The DEGs’enriched functions and pathways include Progesterone-mediated oocyte maturation,cell cycle,and oocyte meiosis,Hepatitis B,and the Hippo signaling pathway.Survival analysis showed that BUB1,MAD2L1,CCNA2,CCNB1,and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway.We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection.RESULTS We focused on three critical genes,which were highly expressed in GC,but negatively related to patient survival.Furthermore,we found that knockdown of Yu K et al.Biochemical analysis in GC WJCC https://www.wjgnet.com 5024 July 26,2023 Volume 11 Issue 21 BIRC5,TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis.In addition,knockdown of BIRC5,TRIP13 or UBE2C increased cellular sensitivity to cisplatin.CONCLUSION Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods.展开更多
AIM: To reveal the mechanisms of heat-shock transcription factor 4(HSF4) mutation-induced cataract. METHODS: GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus databas...AIM: To reveal the mechanisms of heat-shock transcription factor 4(HSF4) mutation-induced cataract. METHODS: GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes(DEGs) were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery(DAVID) tool, functional and pathway enrichment analyses were performed for the DEGs. Followed by protein-protein interaction(PPI) network was constructed using STRING database and Cytoscape software. Furthermore, the validated microRNA(miRNA)-DEG pairs were obtained from miRWalk2.0 database, and then miRNA-DEG regulatory network was visualized by Cytoscape software. RESULTS: A total of 176 DEGs were identified in HSF4-null lens compared with wild-type lens. In the PPI network,FBJ osteosarcoma oncogene(FOS), early growth response1(EGR1) and heme oxygenase(decycling) 1(HMOX1) had higher degrees and could interact with each other. Besides,mmu-miR-15 a-5 p and mmu-miR-26 a-5 p were among the top 10 miRNAs in the miRNA-DEG regulatory network.Additionally, mmu-miR-26 a-5 p could target EGR1 in the regulatory network. CONCLUSION: FOS, EGR1, HMOX1, mmu-miR-26 a-5 p and mmu-miR-15 a-5 p might function in the pathogenesis of HSF4 mutation-induced cataract.展开更多
BACKGROUND Heart failure is a health burden responsible for high morbidity and mortality worldwide, and dilated cardiomyopathy(DCM) is one of the most common causes of heart failure. DCM is a disease of the heart musc...BACKGROUND Heart failure is a health burden responsible for high morbidity and mortality worldwide, and dilated cardiomyopathy(DCM) is one of the most common causes of heart failure. DCM is a disease of the heart muscle and is characterized by enlargement and dilation of at least one ventricle alongside impaired contractility with left ventricular ejection fraction < 40%. It is also associated with abnormalities in cytoskeletal proteins, mitochondrial ATP transporter, microvasculature, and fibrosis. However, the pathogenesis and potential biomarkers of DCM remain to be investigated.AIM To investigate the candidate genes and pathways involved in DCM patients.METHODS Two expression datasets(GSE3585 and GSE5406) were downloaded from the Gene Expression Omnibus database. The differentially expressed genes(DEGs) between the DCM patients and healthy individuals were identified using the R package “linear models for microarray data.” The pathways with common DEGs were analyzed via Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes(KEGG), and gene set enrichment analyses. Moreover, a protein-protein interaction network(PPI) was constructed to identify the hub genes and modules. The MicroRNA Database was applied to predict the microRNAs(miRNAs) targeting the hub genes. Additionally, immune cell infiltration in DCM was analyzed using CIBERSORT.RESULTS In total, 97 DEGs(47 upregulated and 50 downregulated) were identified. GO analysis showed that the DEGs were mainly enriched in “response to growth factor,” “extracellular matrix,” and “extracellular matrix structural constituent.” KEGG pathway analysis indicated that the DEGs were mainly enriched in “protein digestion and absorption” and “interleukin 17(IL-17) signaling pathway.” The PPI network suggested that collagen type Ⅲ alpha 1 chain(COL3A1) and COL1A2 contribute to the pathogenesis of DCM. Additionally, visualization of the interactions between miRNAs and the hub genes revealed that hsa-miR-5682 and hsa-miR-4500 interacted with both COL3A1 and COL1A2, and thus these miRNAs might play roles in DCM. Immune cell infiltration analysis revealed that DCM patients had more infiltrated plasma cells and fewer infiltrated B memory cells, T follicular helper cells, and resting dendritic cells.CONCLUSION COL1A2 and COL3A1 and their targeting miRNAs, hsa-miR-5682 and hsa-miR-4500, may play critical roles in the pathogenesis of DCM, which are closely related to the IL-17 signaling pathway and acute inflammatory response. These results may provide useful clues for the diagnosis and treatment of DCM.展开更多
Objective To screen the key genes of chronic pain and provide a reference for the treatment of chronic pain.Methods We performed comprehensive bioinformatics analysis by screening chronic primary pain-related datasets...Objective To screen the key genes of chronic pain and provide a reference for the treatment of chronic pain.Methods We performed comprehensive bioinformatics analysis by screening chronic primary pain-related datasets to obtain differentially expressed genes(DEGs)and then imported DEGs into the DAVID database for Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Gene Set Enrichment Analysis(GESA)analysis was done by GSEA_4.1.0 software.At the same time,we imported the intersecting genes into the STRING database and processed them by Cytoscape_3.8.1 software to obtain the protein-protein interaction(PPI)network and the central gene.Results As a result,a total of 54 DEGs were screened,including 47 up-regulated genes,1 down-regulated gene,and 6 genes that were expressed differently in different datasets.23 GO terms and 8 KEGG pathways were enriched by DAVID.PPI network analysis found that SPI1,STAT3,TNFRSF1B,PTGS2,and CXCL1 genes interacted more strongly with other genes,and were predicted to be key genes in chronic primary pain.Conclusion Our results suggested that 5 DEGs,STAT3,SPI1,TNFRSF1B,PTGS2,and CXCL1,have the potential to be used as prognostic and predictive markers for the clinical management of patients with this disease.展开更多
AIM:To identify metastatic genes and mi RNAs and to investigate the metastatic mechanism of uveal melanoma(UVM).METHODS:GSE27831,GSE39717,and GSE73652 gene expression profiles were downloaded from the Gene Expression ...AIM:To identify metastatic genes and mi RNAs and to investigate the metastatic mechanism of uveal melanoma(UVM).METHODS:GSE27831,GSE39717,and GSE73652 gene expression profiles were downloaded from the Gene Expression Omnibus(GEO)database,and the limma R package was used to identify differentially expressed genes(DEGs).Gene Ontology(GO)term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed using the DAVID online tool.A comprehensive list of interacting DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes(STRING)database and Cytoscape software.The Cytoscape MCODE plug-in was used to identify clustered sub-networks and modules of hub genes from the proteinprotein interaction network.GEPIA online software was used for survival analysis of UVM patients(n=80)from the The Cancer Genome Atlas(TCGA)cohort.Oncomi R online software was used to find that the mi RNAs were associated with UVM prognosis from the TCGA cohort.Target Scan Human 7.2 software was then used to identify the mi RNAs targeting the genes.RESULTS:There were 1600 up-regulated genes and 1399 down-regulated genes.The up-regulated genes were mainly involved in protein translation in the cytosol,whereas the down-regulated genes were correlated with extracellular matrix organization and cell adhesion in the extracellular space.Among the 2999 DEGs,five genes,Znf391,Mrps11,Htra3,Sulf2,and Smarcd3 were potential predictors of UVM prognosis.Otherwise,three mi RNAs,hsa-mi R-509-3-5 p,hsa-mi R-513 a-5 p,and hsa-mi R-1269 a were associated with UVM prognosis.CONCLUSION:After analyzing the metastasis-related enriched terms and signaling pathways,the up-regulated DEGs are mainly involved in protein synthesis and cell proliferation by ribosome and mitogen-activated protein kinase(MAPK)pathways.However,the down-regulated DEGs are mainly involved in processes that reduced cell-cell adhesion and promoted cell migration in the extracellular matrix through PI3 K-Akt signaling pathway,focal adhesion,and extracellular matrix-receptor interactions.Bioinformatics and interaction analysis may provide new insights on the events leading up to the development and progression of UVM.展开更多
Huosu Yangwei(HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the...Huosu Yangwei(HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD,AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.展开更多
Identifying essential proteins from protein-protein interaction networks is important for studies onbiological evolution and new drug’s development.Most of the presented criteria for prioritizing essential proteinson...Identifying essential proteins from protein-protein interaction networks is important for studies onbiological evolution and new drug’s development.Most of the presented criteria for prioritizing essential proteinsonly focus on a certain attribute of the proteins in the network,which suffer from information loss.In order toovercome this problem,a relatively comprehensive and effective novel method for essential proteins identificationbased on improved multicriteria decision making(MCDM),called essential proteins identification-technique fororder preference by similarity to ideal solution(EPI-TOPSIS),is proposed.First,considering different attributes ofproteins,we propose three methods from different aspects to evaluate the significance of the proteins:gene-degreecentrality(GDC)for gene expression sequence;subcellular-neighbor-degree centrality(SNDC)and subcellular-indegree centrality(SIDC)for subcellular location information and protein complexes.Then,betweenness centrality(BC)and these three methods are considered together as the multiple criteria of the decision-making model.Analytic hierarchy process is used to evaluate the weights of each criterion,and the essential proteins are prioritizedby an ideal solution of MCDM,i.e.,TOPSIS.Experiments are conducted on YDIP,YMIPS,Krogan and BioGRIDnetworks.The results indicate that EPI-TOPSIS outperforms several state-of-the-art approaches for identifyingthe essential proteins through the performance measures.展开更多
Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,g...Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,gene expression data are prone to significant fluctuations due to noise interference in topological networks.In this work,we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation.We then proposed the Pearson Jaccard coefficient(PJC)that consisted of continuous and discrete similarities in the gene expression data.Using the graph theory as the basis,we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins.This strategy exhibited a high recognition rate and good specificity.We validated the new similarity coefficient PJC on PPI datasets of Krogan,Gavin,and DIP of yeast species and evaluated the results by receiver operating characteristic analysis,jackknife analysis,top analysis,and accuracy analysis.Compared with that of node-based network topology centrality and fusion biological information centrality methods,the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC,IC,Eigenvector centrality,subgraph centrality,betweenness centrality,closeness centrality,NC,PeC,and WDC.We also compared the PJC coefficient with other methods using the NF-PIN algorithm,which predicts proteins by constructing active PPI networks through dynamic gene expression.The experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.展开更多
基金supported by the earmarked fund for the Modern Agro-industry Technology Research System(No.CARS-49)the Natural Science Foundation of Shan-dong Province(No.ZR2019BC052)the National Natural Science Foundation of China(No.42006077).
文摘Marine organisms cannot grow and reproduce without proper metabolic regulation.Within a metabolic network,problems with a given link will affect the normal life activities of the organism.Many metabolic mechanisms associated with behaviors of Am-phioctopus fangsiao are still unclear.Moreover,as a factor affecting the normal growth of A.fangsiao,egg protection has rarely been considered in previous behavioral studies.In this research,we analyzed the transcriptome profile of gene expression in A.fangsiao egg-unprotected larvae and egg-protected larvae,and identified 818 differentially expressed genes(DEGs).We used GO and KEGG enrichment analyses to search for metabolism-related DEGs.Protein-protein interaction networks were constructed to examine the interactions between metabolism-related genes.Twenty hub genes with multiple protein-protein interaction relationships or that were involved in multiple KEGG signaling pathways were obtained and verified by quantitative RT-PCR.We first studied the effects of egg protection on the metabolism of A.fangsiao larvae by means of protein-protein interaction networks,and the results provide va-luable gene resources for understanding the metabolism of invertebrate larvae.The data serve as a foundation for further research on the egg-protecting behavior of invertebrates.
基金support from the Shanghai Science and Technology Development Program (Grant Nos. 03DZ14024 & 07ZR14010)the 863 High Technology Foundation of China (Grant No. 2006AA02A310)+1 种基金US NIH 1R01AI064806-01A2, 5R21DK082706U.S. Department of Energy, the Office of Science (BER) (Grant No. DE-FG02- 07ER64422)
文摘Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.
基金National Natural Science Foundation of China,No.31971180 and No.11474013.
文摘Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.
基金supported by the National Natural Science Foundation of China,No.81870975(to SZ)。
文摘Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported to play a crucial role in axonal regeneration.Howeve r,the role of the IncRNA-microRNAmessenger RNA(mRNA)-competitive endogenous RNA(ceRNA)network in exosome-mediated axonal regeneration remains unclear.In this study,we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts(FC-EXOs)and Schwann cells(SCEXOs).Diffe rential gene expression analysis,Gene Ontology analysis,Kyoto Encyclopedia of Genes and Genomes analysis,and protein-protein intera ction network analysis were used to explo re the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs.We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs,which suggests that it may promote axonal regeneration.In addition,using the miRWalk and Starbase prediction databases,we constructed a regulatory network of ceRNAs targeting Rps5,including 27 microRNAs and five IncRNAs.The ceRNA regulatory network,which included Ftx and Miat,revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury.Our findings suggest that exosomes derived from fibro blast and Schwann cells could be used to treat injuries of peripheral nervous system.
文摘BACKGROUND Gastric cancer(GC)is one of the most common cancers and has a poor prognosis.Treatment of GC has remained unchanged over the past few years.AIM To investigate the potential therapeutic targets and related regulatory biomarkers of GC.METHODS We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database.The datasets contained 348 GC tissues and 141 healthy tissues.In total,251 differentially expressed genes(DEGs)were identified,including 187 down-regulated genes and 64 up-regulated genes.The DEGs’enriched functions and pathways include Progesterone-mediated oocyte maturation,cell cycle,and oocyte meiosis,Hepatitis B,and the Hippo signaling pathway.Survival analysis showed that BUB1,MAD2L1,CCNA2,CCNB1,and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway.We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection.RESULTS We focused on three critical genes,which were highly expressed in GC,but negatively related to patient survival.Furthermore,we found that knockdown of Yu K et al.Biochemical analysis in GC WJCC https://www.wjgnet.com 5024 July 26,2023 Volume 11 Issue 21 BIRC5,TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis.In addition,knockdown of BIRC5,TRIP13 or UBE2C increased cellular sensitivity to cisplatin.CONCLUSION Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods.
基金Supported by the Scientific and Technological Developing Scheme of Jilin Province(No.20150414038GH)
文摘AIM: To reveal the mechanisms of heat-shock transcription factor 4(HSF4) mutation-induced cataract. METHODS: GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes(DEGs) were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery(DAVID) tool, functional and pathway enrichment analyses were performed for the DEGs. Followed by protein-protein interaction(PPI) network was constructed using STRING database and Cytoscape software. Furthermore, the validated microRNA(miRNA)-DEG pairs were obtained from miRWalk2.0 database, and then miRNA-DEG regulatory network was visualized by Cytoscape software. RESULTS: A total of 176 DEGs were identified in HSF4-null lens compared with wild-type lens. In the PPI network,FBJ osteosarcoma oncogene(FOS), early growth response1(EGR1) and heme oxygenase(decycling) 1(HMOX1) had higher degrees and could interact with each other. Besides,mmu-miR-15 a-5 p and mmu-miR-26 a-5 p were among the top 10 miRNAs in the miRNA-DEG regulatory network.Additionally, mmu-miR-26 a-5 p could target EGR1 in the regulatory network. CONCLUSION: FOS, EGR1, HMOX1, mmu-miR-26 a-5 p and mmu-miR-15 a-5 p might function in the pathogenesis of HSF4 mutation-induced cataract.
基金Supported by National Nature Science Foundation of China,No.81960051,No.8217021743,and No.82160060Project of High–Level Innovative Talents of Guizhou Province,No.[2016]4034Construction Funding from Characteristic Key Laboratory of Guizhou Province,No.[2021]313.
文摘BACKGROUND Heart failure is a health burden responsible for high morbidity and mortality worldwide, and dilated cardiomyopathy(DCM) is one of the most common causes of heart failure. DCM is a disease of the heart muscle and is characterized by enlargement and dilation of at least one ventricle alongside impaired contractility with left ventricular ejection fraction < 40%. It is also associated with abnormalities in cytoskeletal proteins, mitochondrial ATP transporter, microvasculature, and fibrosis. However, the pathogenesis and potential biomarkers of DCM remain to be investigated.AIM To investigate the candidate genes and pathways involved in DCM patients.METHODS Two expression datasets(GSE3585 and GSE5406) were downloaded from the Gene Expression Omnibus database. The differentially expressed genes(DEGs) between the DCM patients and healthy individuals were identified using the R package “linear models for microarray data.” The pathways with common DEGs were analyzed via Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes(KEGG), and gene set enrichment analyses. Moreover, a protein-protein interaction network(PPI) was constructed to identify the hub genes and modules. The MicroRNA Database was applied to predict the microRNAs(miRNAs) targeting the hub genes. Additionally, immune cell infiltration in DCM was analyzed using CIBERSORT.RESULTS In total, 97 DEGs(47 upregulated and 50 downregulated) were identified. GO analysis showed that the DEGs were mainly enriched in “response to growth factor,” “extracellular matrix,” and “extracellular matrix structural constituent.” KEGG pathway analysis indicated that the DEGs were mainly enriched in “protein digestion and absorption” and “interleukin 17(IL-17) signaling pathway.” The PPI network suggested that collagen type Ⅲ alpha 1 chain(COL3A1) and COL1A2 contribute to the pathogenesis of DCM. Additionally, visualization of the interactions between miRNAs and the hub genes revealed that hsa-miR-5682 and hsa-miR-4500 interacted with both COL3A1 and COL1A2, and thus these miRNAs might play roles in DCM. Immune cell infiltration analysis revealed that DCM patients had more infiltrated plasma cells and fewer infiltrated B memory cells, T follicular helper cells, and resting dendritic cells.CONCLUSION COL1A2 and COL3A1 and their targeting miRNAs, hsa-miR-5682 and hsa-miR-4500, may play critical roles in the pathogenesis of DCM, which are closely related to the IL-17 signaling pathway and acute inflammatory response. These results may provide useful clues for the diagnosis and treatment of DCM.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFE0197900).
文摘Objective To screen the key genes of chronic pain and provide a reference for the treatment of chronic pain.Methods We performed comprehensive bioinformatics analysis by screening chronic primary pain-related datasets to obtain differentially expressed genes(DEGs)and then imported DEGs into the DAVID database for Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Gene Set Enrichment Analysis(GESA)analysis was done by GSEA_4.1.0 software.At the same time,we imported the intersecting genes into the STRING database and processed them by Cytoscape_3.8.1 software to obtain the protein-protein interaction(PPI)network and the central gene.Results As a result,a total of 54 DEGs were screened,including 47 up-regulated genes,1 down-regulated gene,and 6 genes that were expressed differently in different datasets.23 GO terms and 8 KEGG pathways were enriched by DAVID.PPI network analysis found that SPI1,STAT3,TNFRSF1B,PTGS2,and CXCL1 genes interacted more strongly with other genes,and were predicted to be key genes in chronic primary pain.Conclusion Our results suggested that 5 DEGs,STAT3,SPI1,TNFRSF1B,PTGS2,and CXCL1,have the potential to be used as prognostic and predictive markers for the clinical management of patients with this disease.
基金Supported by the Natural Science Foundation for Young Scholars of Shanxi(No.201801D221256)the Science Foundation for Young Scholars of Shanxi Eye Hospital(No.Q201803)。
文摘AIM:To identify metastatic genes and mi RNAs and to investigate the metastatic mechanism of uveal melanoma(UVM).METHODS:GSE27831,GSE39717,and GSE73652 gene expression profiles were downloaded from the Gene Expression Omnibus(GEO)database,and the limma R package was used to identify differentially expressed genes(DEGs).Gene Ontology(GO)term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed using the DAVID online tool.A comprehensive list of interacting DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes(STRING)database and Cytoscape software.The Cytoscape MCODE plug-in was used to identify clustered sub-networks and modules of hub genes from the proteinprotein interaction network.GEPIA online software was used for survival analysis of UVM patients(n=80)from the The Cancer Genome Atlas(TCGA)cohort.Oncomi R online software was used to find that the mi RNAs were associated with UVM prognosis from the TCGA cohort.Target Scan Human 7.2 software was then used to identify the mi RNAs targeting the genes.RESULTS:There were 1600 up-regulated genes and 1399 down-regulated genes.The up-regulated genes were mainly involved in protein translation in the cytosol,whereas the down-regulated genes were correlated with extracellular matrix organization and cell adhesion in the extracellular space.Among the 2999 DEGs,five genes,Znf391,Mrps11,Htra3,Sulf2,and Smarcd3 were potential predictors of UVM prognosis.Otherwise,three mi RNAs,hsa-mi R-509-3-5 p,hsa-mi R-513 a-5 p,and hsa-mi R-1269 a were associated with UVM prognosis.CONCLUSION:After analyzing the metastasis-related enriched terms and signaling pathways,the up-regulated DEGs are mainly involved in protein synthesis and cell proliferation by ribosome and mitogen-activated protein kinase(MAPK)pathways.However,the down-regulated DEGs are mainly involved in processes that reduced cell-cell adhesion and promoted cell migration in the extracellular matrix through PI3 K-Akt signaling pathway,focal adhesion,and extracellular matrix-receptor interactions.Bioinformatics and interaction analysis may provide new insights on the events leading up to the development and progression of UVM.
基金supported by the Cultivation Project of Clinical Research of Shanghai Shenkang Hospital Development Center (No.SHDC12018X30)the Natural Science Foundation of Shanghai Science and Technology Commission (No.19ZR1452100 and 20ZR 1459300)the Key Program of Yueyang Hospital of Shanghai University of Traditional Chinese Medicine (No.2019YYZ01)。
文摘Huosu Yangwei(HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD,AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.
基金the National Natural Science Foundation of China(Nos.62162040 and 11861045)。
文摘Identifying essential proteins from protein-protein interaction networks is important for studies onbiological evolution and new drug’s development.Most of the presented criteria for prioritizing essential proteinsonly focus on a certain attribute of the proteins in the network,which suffer from information loss.In order toovercome this problem,a relatively comprehensive and effective novel method for essential proteins identificationbased on improved multicriteria decision making(MCDM),called essential proteins identification-technique fororder preference by similarity to ideal solution(EPI-TOPSIS),is proposed.First,considering different attributes ofproteins,we propose three methods from different aspects to evaluate the significance of the proteins:gene-degreecentrality(GDC)for gene expression sequence;subcellular-neighbor-degree centrality(SNDC)and subcellular-indegree centrality(SIDC)for subcellular location information and protein complexes.Then,betweenness centrality(BC)and these three methods are considered together as the multiple criteria of the decision-making model.Analytic hierarchy process is used to evaluate the weights of each criterion,and the essential proteins are prioritizedby an ideal solution of MCDM,i.e.,TOPSIS.Experiments are conducted on YDIP,YMIPS,Krogan and BioGRIDnetworks.The results indicate that EPI-TOPSIS outperforms several state-of-the-art approaches for identifyingthe essential proteins through the performance measures.
基金supported by the Shenzhen KQTD Project(No.KQTD20200820113106007)China Scholarship Council(No.201906725017)+2 种基金the Collaborative Education Project of Industry-University cooperation of the Chinese Ministry of Education(No.201902098015)the Teaching Reform Project of Hunan Normal University(No.82)the National Undergraduate Training Program for Innovation(No.202110542004).
文摘Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,gene expression data are prone to significant fluctuations due to noise interference in topological networks.In this work,we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation.We then proposed the Pearson Jaccard coefficient(PJC)that consisted of continuous and discrete similarities in the gene expression data.Using the graph theory as the basis,we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins.This strategy exhibited a high recognition rate and good specificity.We validated the new similarity coefficient PJC on PPI datasets of Krogan,Gavin,and DIP of yeast species and evaluated the results by receiver operating characteristic analysis,jackknife analysis,top analysis,and accuracy analysis.Compared with that of node-based network topology centrality and fusion biological information centrality methods,the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC,IC,Eigenvector centrality,subgraph centrality,betweenness centrality,closeness centrality,NC,PeC,and WDC.We also compared the PJC coefficient with other methods using the NF-PIN algorithm,which predicts proteins by constructing active PPI networks through dynamic gene expression.The experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.
