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OBJECTIVE@#To establish an immune gene prognostic model of acute myeloid leukemia (AML) and explore its correlation with immune cells in bone marrow microenvironment.@*METHODS@#Gene expression profile and clinical data of TCGA-AML were downloaded from TCGA database. Immune genes were screened by LASSO analysis to construct prognosis prediction model, and prediction accuracy of the model was quantified by receiver operating characteristic curve and area under the curve. Survival analysis was performed by Log-rank test. Enriched pathways in the different immune risk subtypes were evaluated from train cohort. The relationship between immune prediction model and bone marrow immune microenvironment was verified by flow cytometry in the real world.@*RESULTS@#Patients with low-risk score of immune gene model had better prognosis than those with high-risk score. Multivariate analysis showed that the immune gene risk model was an independent prognostic factor. The risk ratio for AML patients in the training concentration was HR=24.594 (95%CI: 6.180-97.878), and the AUC for 1-year, 3-year, and 5-year overall survival rate was 0.811, 0.815, and 0.837, respectively. In addition, enrichment analysis of differential gene sets indicated activation of immune-related pathways such as cytokines and chemokines as well as autoimmune disease-related pathways. At the same time, real world data showed that patients with high immune risk had lower numbers of CD8+T cells and B lymphocytes compared with low immune risk patients.@*CONCLUSION@#We constructed a stable prognostic model for AML, which can not only predict the prognosis of AML, but also reveal the dysregulation of immune microenvironment.
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Humans , Leukemia, Myeloid, Acute/genetics , Prognosis , ROC Curve , Risk Factors , Transcriptome , Tumor Microenvironment/geneticsABSTRACT
Objective::To explore the mechanism of Xiao Banxiatang in preventing and treating chemotherapy-induced nausea and vomiting by using network pharmacology. Method::The targets of chemotherapy-related nausea and vomiting were collected by therapeutic target database (TTD), Drugbank database and DisGeNET database. The target genes were normalized by Uniprot database. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was selected according to oral bioavailabilityc (OB) ≥ 30%, drug-likeness (DL) ≥ 0.14 and the literature research. The active constituents of pinellia ternata and ginger were collected through the PubChem database, the ALOGPS2.1 database and the Swiss Target Prediction database, and the target of ginger was collected and standardized through the Uniprot database, the molecular inverse docking of the important component 6-gingerol was carried out through the DRAR-CPI database, gene ontology (GO) analysis and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed through DAVID 6.8 database, and relationship diagrams were drawn by Cytoscape 3.2.1 software and network topology parameters were analyzed, GO and KEGG bubble maps were drawn by ImageGP tool. Result::A total of 148 targets for chemotherapeutic nausea and vomiting, and 27 active ingredients of Xiao Banxiatang were collected, including 22 associated with chemotherapeutic nausea and vomiting, 38 control targets, 67 biological processes based on GO analysis, 11 cell components, 18 molecular functions, 21 KEGG pathways, involving cyclic Adenosine monophosphate (cAMP) signaling pathway, calcium signaling pathway, Rap1 signaling pathway. Conclusion::Based on network pharmacology, chemotherapy-related nausea and vomiting and Xiao Banxiatang were analyzed to provide ideas for the prevention and treatment of chemotherapy-induced nausea and vomiting.
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Objective@#To explore susceptibility genes for autism spectrum disorders (ASD).@*Methods@#Whole-exome sequencing was carried out for 60 family trios affected with sporadic ASD. Genetic variants discovered in over 10% of the patients were selected for genotype-phenotype correlation and pathway enrichment analysis using Phenolyzer software and metascape database. Combining gene-phenotypic scores, pathway-related genes associated with neural and neurite triggering were screened for the candidates.@*Results@#A total of 170 common variants were found to be associated with the ASD phenotype. Among these, there was only one high-confidence gene [SHANK2 (0.8146)] and four medium-confidence genes [ERBB2 (0.1322), LAMC3 (0.1117), PPFIA4 (0.1059), DISC1 (0.1002)]. Twenty-pathways and four biological processes were found to be statistically significant by pathway enrichment analysis, which included neuron projection morphogenesis (GO: 0048812), regulation of neuroblast proliferation (GO: 1902692), modulation of excitatory postsynaptic potential (GO: 0098815), and dendrite morphogenesis (GO: 0048813). Twenty-one genes were found to be closely associated with neurological and neurite triggering, among which only SHANK2, ERBB2, and DISC1 had above-medium confidence correlation scores with the ASD phenotypes.@*Conclusion@#Abnormal neuron projection morphogenesis (GO: 0048812) may be closely related to the occurrence of ASD. SHANK2, ERBB2, and DISC1 are susceptibility genes for ASD.
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OBJECTIVE： To provide reference for interpretation of pathogenesis， early prevention and diagnosis， and selection of therapeutic targets of Alzheimer’s disease （AD）. METHODS： The gene chip dataset GSE28146 was downloaded from the NCBI public data platform GEO， and the AD-related differentially expressed genes （DEGs） were identified by using GEO2R online analysis tool. GO analysis and KEGG enrichment pathway analysis were performed by using DAVID 6.8 bioinformatics resource database. The protein-protein interaction （PPI） network analysis was performed by using STRING database and Cytoscape 3.2.1 software. RESULTS & CONCLUSIONS： A total of 1 478 AD-related DEGs were identified， consisting of 913 up-regulated genes and 565 down-regulated genes. GO function enrichment analysis showed that DEGs mainly distributed in cytoplasm， membrane， extracellular space， and induced AD via biological processes such as positive/negative regulation of transcription， positive regulation of NF-κB activity， regulation of Rho protein signaling transduction， protein phosphorylation； via protein binding， DNA binding， transcription factor activity （sequence specific DNA binding） and other molecular functions. KEGG pathway enrichment analysis showed that DEGs was enriched in cancer pathway， pulmonary tuberculosis， osteoclast differentiation， JAK/STAT signaling pathway， FoxO signaling pathway， EB virus infection and other signaling pathways. There are 1 205 nodes and 3 931 edges in the PPI network of DEGs coding protein. Among them， the key genes are SOCS3， NEDD4 and CBLB， which may be the potential target of AD development.
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Objective: To explore the potential mechanism of Shema Zhichuan liquid in treatment of asthma by network pharmacology. Method: Bioinformatics analysis tool for molecular mechanism of traditional Chinese medicine (TCM), systematic pharmacological database and analysis platform of TCM were employed to find the components in Shema Zhichuan liquid and their targets, and asthma-related genes were obtained from the comparative toxicogenomics database (CTD). The data set of Shema Zhichuan liquid-gene and asthma-gene were imported into the Draw Venn Diagram for intersection analysis. The obtained data set of Shema Zhichuan liquid-asthma-gene was imported into String 11.0 for protein-protein interaction (PPI) analysis, and was visualized by Cytoscape 3.6.1, and further important modules were analyzed with MCODE. DAVID 6.8 was used to analyze pathway enrichment and biological process of Shema Zhichuan liquid-asthma-gene. Result: A total of 399 components and 2 099 potential targets were obtained from Shema Zhichuan liquid, 98 asthma-related targets were retrieved, 45 common genes and 16 hub genes were screened, including transforming growth factor-β1(TGF-β1), heme oxygenase-1 (HMOX1), interleukin-4 (IL-4), etc. Enrichment analysis showed that the common biological processes of Shema Zhichuan liquid and asthma were related to inflammation, contraction and remodeling of airway, cell proliferation and apoptosis, etc. The common biological pathways mainly included tumor necrosis factor (TNF) signaling pathway, receptor with high affinity for immunoglobulin E (Fc epsilon RI) signaling pathway, nuclear transcription factor-kappa B (NF-κB) signaling pathway, nucleotide binding oligomerization domain (NOD)-like receptor signaling pathway and so on. Conclusion: Shema Zhichuan liquid serves as a multi-target, multi-pathway treatment for asthma, which can provide a reference for the further research and clinical application of this preparation.
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Objective Sjgren's Syndrome (SS) is considered to be a common rheumatoid immune disease only second to rheumatoid arthritis in prevalence. This study aimed to screen SS-related genes with gene expression profiling data, explore the pathogenesis of SS and search for the potential drug targets for the treatment of the disease.Methods Using Affymetrix Human Genome U133 Plus 2.0 Array, we obtained the cell expression profiles of human parotid tissue in SS patients from the GEO database, including 24 SS samples and 25 non-SS samples up to the diagnostic criteria. We screened differentially expressed genes with the GEO2R online tools and enriched the functions and pathways of the genes with the DAVID tools. Then we constructed a network of interaction among differentially expressed gene protein products using the STRING database, imported the data into the Cytoscape software, calculated the topological properties, and screened the core genes.Results Totally, 24 up-regulated and 147 down-regulated differentially expressed genes were screened out from the SS samples, involved in cell adhesion molecules, intestinal immune networkIgA secretion, viral myocarditis, rheumatoid arthritis and the leukocyte transendothelial migration pathway, among which PTPRC, CD86, STAT1, FYN and LCP2 were the key genes.Conclusion SS-related biological pathways and key genes can be screened by bioinformatics, which can provide some experimental reference for further revealing the pathogenesis of SS.
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Objective:To observe the changes of gene expression in peripheral blood mononuclear cells( PBMCs) of benign and malignant breast tumor based on gene expression profiling. Methods: Datasets of gene expression profiling were downloaded from the GEO database,including PBMCs profilings of benign breast tumor,breast cancer and healthy controls. GEO2R tool was used to analyze the data to identify the differentially expressed genes (DEGs). Function of DEGs were annotated by DAVID. Protein interaction analysis and hub gene select were then performed using STRING database. Results:563 and 237 DEGs respectively were identified. DEGs in breast cancer involved in biological process of leukocyte activation,angiogenesis and leukocyte transendothelial migration. The hub genes are IL8,RHOB,ITGB1. Conclusion:The data suggests that gene expression patterns of these two profilings are different at a certain degree. PBMCs maybe a better noninvasive material for biomarker detection of benign and malignant breast tumor.
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Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.
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Humans , Cardiomyopathy, Dilated/genetics , Computational Biology/methods , Gene Expression Profiling/methods , Transcriptome , Reference Values , Transcription Factors/genetics , Signal Transduction/genetics , Receptors, Androgen/genetics , Down-Regulation , Up-Regulation , MicroRNAsABSTRACT
OBJECTIVE: Major depressive disorder (MDD) is a common mood disorder associated with several psychophysiological changes like disturbances of sleep, appetite, or sexual desire, and it affects the patients' life seriously. We aimed to explore a genetic method to investigate the mechanism of MDD. METHODS: The mRNA expression profile (GSE53987) of MDD was downloaded from Gene Expression Omnibus database, including 105 samples of three brain regions in post-mortem tissue suffered from MDD and unaffected controls. Differentially expressed genes (DEGs) in MDD were identified using the Limma package in R. Gene Ontology functions and Kyoto Enrichment of Genes and Genomes pathways of the selected DEGs were enriched using Database for Annotation, Visualization and Integrated Discovery. Protein-protein interactive network of DEGs was constructed using the Cytoscape software. RESULTS: Totally, 241 DEGs in MDD-hip group, 218 DEGs in MDD-pfc group, and 327 DEGs in MDD-str group were identified. Also, different kinds of biological processes of DEGs in each group were enriched. Besides, glycan biosynthesis of DEGs in MDD-str group, RIG-I-like receptor signaling and pyrimidine metabolism of DEGs in the MDD-hip group were enriched, respectively. Moreover, several DEGs like PTK2, TDG and CETN2 in MDD-str group, DCT, AR and GNRHR in MDD-pfc group, and AKT1 and IRAK1 in MDD-hip group were selected from PPI network. CONCLUSION: Our data suggests that the brain striatum tissue may be greatly affected by MDD, and DEGs like PTK2, GALNT2 and GALNT2 in striatum, AR in prefrontal cortex and IRAK1 and IL12A in hippocampus may provide novel therapeutic basis for MDD treatment.
Subject(s)
Appetite , Biological Phenomena , Brain , Depressive Disorder, Major , Gene Expression , Gene Ontology , Genome , Hippocampus , Metabolism , Microarray Analysis , Mood Disorders , Prefrontal Cortex , RNA, MessengerABSTRACT
Objective Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening condition characterized by excessive inflammation, with a high incidence in children and a death rate of 40%.This study was to analyze the gene expression profile in child-hood HLH and explore the important pathways of childhood HLH using bioinformatic methods . Methods The childhood HLH gene ex-pression profile data GSE26050 were obtained from the Gene Expression Omnibus (GEO) database of the National Center for Biotechnolo-gy Information.Differentially expressed genes were identified with the GEO 2R online analysis tools released recently .The key pathways of the differentially expressed genes were investigated using the Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway enrichment a-nalysis. Results A total of 184 differentially expressed genes were identified , 126 upregulated and the other 58 downregulated .They were enriched in 3 pathways, including cytokine-cytokine receptor interaction , hematopoietic cell lineage and NOD-like receptor signaling pathways. Conclusion Bioinformatic tools allow the identification of the key genes and pathways associated with the development and progression of childhood HLH and point out the potential directions for researches on the mechanisms of childhood HLH .