Objective:In the realm of Class I pathogens,Burkholderia pseudomallei(BP)stands out for its propensity to induce severe pathogenicity.Investigating the intricate interactions between BP and host cells is imperative fo...Objective:In the realm of Class I pathogens,Burkholderia pseudomallei(BP)stands out for its propensity to induce severe pathogenicity.Investigating the intricate interactions between BP and host cells is imperative for comprehending the dynamics of BP infection and discerning biomarkers indicative of the host cell response process.Methods:mRNA extraction from BP-infected mouse macrophages constituted the initial step of our study.Employing gene expression arrays,the extracted RNA underwent conversion into digital signals.The percentile shift method facilitated data processing,with the identification of genes manifesting significant differences accomplished through the application of the t-test.Subsequently,a comprehensive analysis involving Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway was conducted on the differentially expressed genes(DEGs).Leveraging the ESTIMATE algorithm,gene signatures were utilized to compute risk scores for gene expression data.Support vector machine analysis and gene enrichment scores were instrumental in establishing correlations between biomarkers and macrophages,followed by an evaluation of the predictive power of the identified biomarkers.Results:The functional and pathway associations of the DEGs predominantly centered around G protein-coupled receptors.A noteworthy positive correlation emerged between the blue module,consisting of 416 genes,and the StromaScore.FZD4,identified through support vector machine analysis among intersecting genes,indicated a robust interaction with macrophages,suggesting its potential as a robust biomarker.FZD4 exhibited commendable predictive efficacy,with BP infection inducing its expression in both macrophages and mouse lung tissue.Western blotting in macrophages confirmed a significant upregulation of FZD4 expression from 0.5 to 24 h post-infection.In mouse lung tissue,FZD4 manifested higher expression in the cytoplasm of pulmonary epithelial cells in BP-infected lungs than in the control group.Conclusion:Thesefindings underscore the upregulation of FZD4 expression by BP in both macrophages and lung tissue,pointing to its prospective role as a biomarker in the pathogenesis of BP infection.展开更多
TIME,Immunity,Prognosis,BioinformaticsThis study used transcriptome and epigenetic data to predict the prognosis of immune-related genes(IRGs)Apelin(APLN)in patients with hepatocellular carcinoma(HCC).The TCGA databas...TIME,Immunity,Prognosis,BioinformaticsThis study used transcriptome and epigenetic data to predict the prognosis of immune-related genes(IRGs)Apelin(APLN)in patients with hepatocellular carcinoma(HCC).The TCGA database has gene expression and clinical data for HCC.And DNA methylation 450 k data for HCC was download from the University of California Santa Cruz(UCSC)Xena browser.Performing clinical and prognostic analysis of APLN expression,results show that APLN is highly expressed in tumor samples.And it has an increasing trend with the development of clinical stage and T stage.To explore the prognostic role of APLN,the Immune-related DNA methylation(DNAm)sites associated with APLN analyzed by bioinformatics.Univariate COX screened the methylation sites that are related to both APLN and survival.The risk score related to methylation site signature was determined according to their least absolute shrinkage and selection operator(LASSO)coefficients.Then the patients were divided into high-risk groups and low-risk groups.Significant differences in overall survival(OS)were found in the training cohort.Nomogram shows that APLN or methylation signature can effectively predict the prognosis of HCC patients.In summary,APLN may be a diagnostic and prognostic marker for HCC.展开更多
基金The study was supported by Yuying Program Incubation Project of General Hospital of Center Theater(ZZYFH202104)Wuhan Young and Middle-Aged Medical Backbone Talent Project 2020(2020-55)Logistics Research Program Project 2019(CLB19J029).
文摘Objective:In the realm of Class I pathogens,Burkholderia pseudomallei(BP)stands out for its propensity to induce severe pathogenicity.Investigating the intricate interactions between BP and host cells is imperative for comprehending the dynamics of BP infection and discerning biomarkers indicative of the host cell response process.Methods:mRNA extraction from BP-infected mouse macrophages constituted the initial step of our study.Employing gene expression arrays,the extracted RNA underwent conversion into digital signals.The percentile shift method facilitated data processing,with the identification of genes manifesting significant differences accomplished through the application of the t-test.Subsequently,a comprehensive analysis involving Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway was conducted on the differentially expressed genes(DEGs).Leveraging the ESTIMATE algorithm,gene signatures were utilized to compute risk scores for gene expression data.Support vector machine analysis and gene enrichment scores were instrumental in establishing correlations between biomarkers and macrophages,followed by an evaluation of the predictive power of the identified biomarkers.Results:The functional and pathway associations of the DEGs predominantly centered around G protein-coupled receptors.A noteworthy positive correlation emerged between the blue module,consisting of 416 genes,and the StromaScore.FZD4,identified through support vector machine analysis among intersecting genes,indicated a robust interaction with macrophages,suggesting its potential as a robust biomarker.FZD4 exhibited commendable predictive efficacy,with BP infection inducing its expression in both macrophages and mouse lung tissue.Western blotting in macrophages confirmed a significant upregulation of FZD4 expression from 0.5 to 24 h post-infection.In mouse lung tissue,FZD4 manifested higher expression in the cytoplasm of pulmonary epithelial cells in BP-infected lungs than in the control group.Conclusion:Thesefindings underscore the upregulation of FZD4 expression by BP in both macrophages and lung tissue,pointing to its prospective role as a biomarker in the pathogenesis of BP infection.
基金This work was supported by the Fund of Biosecurity Specialized Project of PLA(No.19SWAQ18).
文摘TIME,Immunity,Prognosis,BioinformaticsThis study used transcriptome and epigenetic data to predict the prognosis of immune-related genes(IRGs)Apelin(APLN)in patients with hepatocellular carcinoma(HCC).The TCGA database has gene expression and clinical data for HCC.And DNA methylation 450 k data for HCC was download from the University of California Santa Cruz(UCSC)Xena browser.Performing clinical and prognostic analysis of APLN expression,results show that APLN is highly expressed in tumor samples.And it has an increasing trend with the development of clinical stage and T stage.To explore the prognostic role of APLN,the Immune-related DNA methylation(DNAm)sites associated with APLN analyzed by bioinformatics.Univariate COX screened the methylation sites that are related to both APLN and survival.The risk score related to methylation site signature was determined according to their least absolute shrinkage and selection operator(LASSO)coefficients.Then the patients were divided into high-risk groups and low-risk groups.Significant differences in overall survival(OS)were found in the training cohort.Nomogram shows that APLN or methylation signature can effectively predict the prognosis of HCC patients.In summary,APLN may be a diagnostic and prognostic marker for HCC.
