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Objective To explore the expression, correlation with clinicopathologic parameters, and clinical significance of MIS18 binding protein 1 (MIS18BP1) in bladder cancer. Methods TCGA and GEO databases were used to analyze the mRNA expression of MIS18BP1 in tumors and controls, and the results were verified via qRT-PCR. UALCAN online database was utilized in the analysis of the expression of MIS18BP1 and its correlation with clinicopathological parameters and the degree of immune cell infiltration. Immunohistochemistry was employed to analyze the expression of MIS18BP1 in bladder cancer and its relationship with clinicopathological features. The ROC curve was applied to evaluate the diagnostic value of MIS18BP1 mRNA in bladder cancer. Results Bioinformatics analysis and qRT-PCR results revealed the increased expression of MIS18BP1 mRNA in bladder cancer compared with that in the control group (P<0.05). Immunohistochemistry unveiled the significantly high positive rate of MIS18BP1 protein in bladder cancer (P<0.05) and its correlation with the clinical stage of tumors, depth of invasion, and lymph node metastasis (P<0.05). The immune infiltration analysis showed the association of MIS18BP1 with immune cell infiltration in bladder cancer. Conclusion The increased expression level of MIS18BP1 gene and protein in bladder cancer may regulate the development of bladder cancer by influencing immune cell infiltration.
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BACKGROUND:In the process of exploring the mechanism of Alzheimer's disease,the important role of bioinformatics for common target screening has been revealed,enabling the use of its screening results as a basis for exploring the therapeutic effects of drugs on the disease. OBJECTIVE:To predict the targets of liraglutide,a glucagon-like peptide-1 receptor agonist,in the treatment of Alzheimer's disease by bioinformatics and molecular biology. METHODS:DisGeNET database and SEA database were used to obtain the common genes of Alzheimer's disease and liraglutide.GO/KEGG enrichment analysis of common targets was conducted using DAVID online database.Protein-protein interaction networks were constructed using STRING database.The optimal dosage of liraglutide was determined using cell counting kit-8 assay.Expression of key proteins was analyzed using immunofluorescence and immunoblotting techniques.The mouse hippocampal neuron HT22 cell line was used for ex vivo experiments,and the cells were randomly divided into three groups:HT22 group,HT22+Aβ group,and HT22+Aβ+Lir group.No special treatment was done in the HT22 group,while Aβ1-42 was used to intervene in the HT22 cell line for 24 hours to construct an Aβ injury cell model in the HT22+Aβ group.In additional to modeling,liraglutide was added to the HT22+Aβ+Lir group for 12 hours. RESULTS AND CONCLUSION:A total of 3 333 genes associated with Alzheimer's disease were screened from DisGeNET database.Then 147 potential targets of liraglutide were obtained from SEA database.Finally,64 common targets of Alzheimer's disease and Liraglutide were determined using R packets.GO/KEGG analysis of common targets using DAVID online database suggested that common targets were mainly enriched in the following biological processes:neuroactive ligand-receptor interaction,renin-angiotensin system,bladder cancer,endopeptidase activity,peptide receptor activity,G protein-coupled peptide receptor activity,and transport vesicles.The obtained 64 common target proteins were imported into SRTING online database for protein-protein interaction network construction,and the top three genes,matrix metalloproteinases 2,9 and interleukin 1β,were obtained.The activity of cultured cells was detected by the cell counting kit-8 kit.Liraglutide at 100 nmol/L was the optimal concentration for antagonizing Aβ1-42.In the western blot and immunofluorescence assays,the expression of matrix metalloproteinases 2,9 and interleukin 1β was significantly increased in the HT22+Aβ group compared with the HT22 group(P＜0.05)but significantly decreased in the HT22+Aβ+Lir group compared with the HT22+Aβ group(P＜0.05).To conclude,the above bioinformatics data and secondary validation of differential genes in the GEO database suggest that both matrix metalloproteinases 2,9 and interleukin 1β could be potential targets of liraglutide in the treatment of Alzheimer's disease.
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BACKGROUND:At present,the biological functions and molecular changes of bone marrow mesenchymal stem cells in the tumor microenvironment of acute myeloid leukemia are still unclear. OBJECTIVE:To explore the changes in the biological function of bone marrow mesenchymal stem cells in acute myeloid leukemia and the role of acute myeloid leukemia conditioned medium by bioinformatics and experiment. METHODS:Differential genes were screened from GEO data sets,and enrichment analysis was performed.The protein-protein interaction network was constructed and the Hub gene was obtained.Bone marrow mesenchymal stem cells from patients with acute myeloid leukemia and healthy donors were cultured.Bone marrow mesenchymal stem cells from healthy donors were treated with acute myeloid leukemia conditioned culture solution.Each group was subjected to the adipogenic differentiation,osteogenic differentiation,staining of β-galactosidase,detection of the cell cycle,and validation of Hub genes. RESULTS AND CONCLUSION:(1)Gene expression data of bone marrow mesenchymal stem cells from acute myeloid leukemia patients and healthy donors were obtained from GSE84881,and 184 up-regulated genes and 140 down-regulated genes were screened.(2)The biological functions of enrichment mainly include cell cycle,adipocyte differentiation,cell metabolism,and MYC pathway.According to the Degree algorithm,10 up-regulated Hub genes and 10 down-regulated Hub genes were selected.(3)The cell in vitro experiment found that:compared with the control group,the surface antigen of acute myeloid leukemia mesenchymal stem cells did not change,but it showed enhanced lipid differentiation ability,weakened osteogenic differentiation ability,increased β-galactosidase positive cell number,altered cell morphology,arrested cell cycle,increased LGALS3 expression,and decreased MYC expression.Mesenchymal stem cells from healthy donors showed similar changes after being cultured in acute myeloid leukemia conditioned medium.(4)The results show that biological function of mesenchymal stem cells is altered in the acute myeloid leukemia microenvironment,which provides new insights into the interaction between mesenchymal stem cells and tumor cells.
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BACKGROUND:Autophagy and ferroptosis play important roles in the development of chronic kidney disease,but the molecular mechanisms and gene targets related to autophagy and ferroptosis in renal tissue of chronic kidney disease are still unclear. OBJECTIVE:To screen differentially expressed genes in chronic kidney disease-related datasets based on bioinformatics,and to explore potential key biomarkers suitable for screening renal function progression in patients with chronic kidney disease. METHODS:(1)The GSE137570 dataset was obtained from GEO database to screen the differentially expressed genes by Networkanalyst database analysis.Ferroptosis and autophagy related targets were obtained by OMIM,GENECARD,FerrDb and HAMdb databases.The respective data were intersected to obtain autophagy-ferroptosis related differentially expressed genes in chronic kidney disease for parallel enrichment analysis.The STRING website was used to construct the protein-protein interaction network of differentially expressed genes,which was imported into Cytoscape software and analyzed by MCODE and Cytohubba plug-in to screen potential core targets.Enrichment analysis was performed to obtain the functions of these potential core targets.(2)In the in vitro experiment,mouse renal tubular epithelial cells were divided into two groups:the control group received no intervention,while the model group was stimulated with 5 ng/mL transforming growth factor β1 for 24 hours to induce mesenchymal transformation of renal tubular epithelial cells.Flow cytometry was used to measure the levels of reactive oxygen species and changes in mitochondrial membrane potential in the cells.RT-PCR was employed to assess ferroptosis,autophagy-related markers,and the mRNA expression of potential core targets in the cells. RESULTS AND CONCLUSION:After screening the GSE137570 dataset,a total of 480 differentially expressed genes were obtained,including 104 upregulated genes and 376 downregulated genes(log2|(FC)|>1,P<0.05).There were 562 ferroptosis-related targets and 1 266 autophagy-related targets obtained from the OMIM,GENECARD,FerrDb,and HAMdb databases.Intersection of differentially expressed genes with ferroptosis-and autophagy-related targets yielded 15 ferroptosis-related targets and 18 autophagy-related targets,respectively.The enrichment analysis results indicate that ferroptosis-related differentially expressed genes are primarily involved in biological processes such as sulfur amino acid metabolism,neutrophil degranulation,and ferroptosis signaling pathways.Autophagy-related differentially expressed genes are mainly enriched in biological processes such as platelet degranulation,extracellular matrix degradation,and receptor tyrosine kinase signaling.After screened by MCODE and CytoHubba,key genes were identified in the protein-protein interaction network,including CD44,ALB,TIMP1,PLG,CCL2,and DPP4.Immune infiltration analysis results indicate that immune cells such as B cells,CD4+ T cells,NK cells,and monocytes show significant differential expression in renal tissue after chronic kidney disease,and the core targets are also significantly correlated with these immune cells(P<0.05).The results of receiver operator characteristic curve analysis further demonstrate that the pathological progression of chronic kidney disease can be effectively diagnosed by CD44,ALB,TIMP1,PLG,CCL2,and DPP4.Single-cell sequencing results show that,except for PLG,the expression of target genes in the renal tissue of mice in each model group is generally consistent with the results of this experiment.RT-PCR results demonstrate that,for the validation of autophagy and ferroptosis phenotypes,compared with the control group,the model group shows a significant decrease in mRNA expression of LC3B,Nrf2,and SLC7A11(P<0.05),and a significant increase in P62 mRNA expression(P<0.05).Regarding the validation of potential core targets,compared with the control group,the model group exhibits a significant decrease in mRNA expression of ALB and PLG(P<0.05),and a significant increase in TIMP1 and CCL2 mRNA expression(P<0.05).Overall,these findings indicate that,through bioinformatics analysis and experimental validation,CD44,ALB,TIMP1,PLG,and CCL2 are abnormally expressed in the renal tissue of patients with chronic kidney disease,closely correlated with estimated glomerular filtration rate and tubulointerstitial fibrosis,and maybe play a predictive role in the progression of chronic kidney disease.
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Objective By screening key genes and related pathways for hepatic fibrosis treatment through bioinformatics analysis,the differentially expressed genes of hepatic fibrosis patients were mined to predict potential therapeutic targets for liver fibrosis.Methods Gene expression profiles GSE197112 were obtained from GEO database.Differentially expressed genes were screened by Limma.DAVID online database was used to conduct GO enrichment analysis and KEGG signaling pathway enrichment analysis of differentially expressed genes.The protein-protein interaction(PPI)network diagram of differentially expressed genes were obtained from STRING database and visualize by Cytoscape software.At the same time,the plug-in CytoHubba in Cytoscape software was used to screen the target genes of hepatic fibrosis.Results A total of 399 differentially expressed genes were screened(P<0.01,∣log2FC∣>1.5),including 300 down-regulated genes and 99 up-regulated genes.These genes were mainly involved in GO biological processes such as mitosis checkpoint,DNA replication,chromosome segregation,cell division,apoptosis,adaptive immune response and so on,and mainly regulated the intestinal immune network for IgA production,progesterone-mediated oocyte maturation,human T-cell leukemia virus 1 infection,cell cycle,antigen processing and presentation,p53 signaling pathway,cancer transcription disorder,cell adhesion molecules and so on.Five target genes were screened by Cytoscape software:TTK,KIF2C,ASPM,DLGAP5,PBK.Conclusion In this study,399 differentially expressed genes and 5 target genes in hepatic fibrosis were screened by bioinformatics methods,which play key roles in the biological processes related to hepatic fibrosis,and provide a new direction for the pharmacological treatment of liver fibrosis.
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Objective:To construct the regulatory network of competitive endogenous RNA(ceRNA)and explore the mo-lecular mechanism of ischemic stroke(IS)by using bioinformatic analysis to screen the differentially-expressed genes. Method:The expression profiles of miRNA,mRNA and lncRNA in IS were downloaded from the NCBI GEO database.Differentially-expressed miRNAs,lncRNAs,and mRNAs were identified by the limma package in R software.The prediction of the relationship of lncRNA-miRNA and miRNA-mRNA were performed by starBase,miRDB and miRwalk databases.The results of prediction and differential analysis were taken to inter-sect and screened out differentially-expressed target mRNA(DETmRNAs),Kyoto Encyclopedia of Genes and Genomes(KEGG)and gene ontology(GO)enrichment analysis was performed by using the DAVID database.The protein-protein interaction(PPI)network was constructed by using the STRING database and the core tar-get genes in the network were identified by Cytoscape software. Result:A total of 20 differentially-expressed miRNAs,1512 lncRNAs,and 278 mRNAs were identified,and a ceRNA network was successfully constructed with the interactions of 5 lncRNAs-6 miRNAs-102 mRNAs in IS.The 285 DETmRNAs functions are mostly involved in the biological process such as chromatin organization,negative regulation of phosphoprotein phosphatase activity,or cell cycle.KEGG mainly enriched the signaling pathway including leukocyte trans-endothelial migration and platelet activation.The top 10 core genes were CREB1,MAPK1,GSK3B,SP1,PIK3R1,NR3C1,NCOR1,NFATC1,SETD2,and NSD1. Conclusion:The construction of the ceRNA network can help to further understand the molecular mechanism of IS and screen potential biomarkers,providing clues to further define rehabilitation targets and develop reha-bilitation strategies.
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Objective @#To screen the core genes of diabetic kidney disease ( DKD) based on bioinformatics , ex- plore the therapeutic targets of DKD , and discuss its possible regulatory mechanism .@*Methods @#The expression da- ta matrix of glomerular transcriptome in patients with DKD in GEO database (GSE30528 , GSE47183) was extrac- ted , and the differentially expressed genes ( DEGs) were screened by bioinformatics methods to identify the core differential genes , and then gene expression and enrichment analysis (GSEA) were conducted to predict effective targets . @*Results @#By screening and identifying the mRNA expression matrix of DKD , five core genes were screened out. Among them , C1orf21 and NPHS1 were significantly down regulated , and CD48 , COL1A2 , and TGFBI were up regulated . NPHS1 and CD48 were significantly related to immune differences , intercellular communication , and cell surface interaction . Through receiver operating characteristic curve ( ROC) analysis and GSEA analysis and drug target prediction , it might be of great significance for the treatment of DKD .@*Conclusion @#The core genes screened in this study have significant correlation with DKD , which may be used as effective markers for the treat- ment of diabetes . And then , this study provides a theoretical basis for the treatment and identification of DKD .
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Objective·To establish a prognostic model for the overall survival(OS)of hepatocellular carcinoma(HCC)based on mitochondrial genes and clinical information.Methods·The gene expression and the clinical data of 369 HCC patients and 50 controls with normal liver were downloaded from The Cancer Genome Atlas(TCGA)database.The nuclear-encoded mitochondrial genes(NEMGs)were obtained from the MitoCarta3.0 database.The"DESeq2"R package and univariate Cox analysis were used to select NEMGs[ubiquinol cytochrome C reductase hinge protein(UQCRH),ATP citrate lyase(ACLY),phosphoenolpyruvate carboxykinase 2(PCK2),Bcl-2 homologous antagonist/killer1(BAK1),Bcl-2-associated X protein(BAX)and Bcl-2/adenovirus E1B interacting protein 3-like(BNIP3L)]in HCC that were associated with OS of HCC and participated in dysregulation of oxidative phosphorylation,tricarboxylic acid cycle and cell apoptosis.Multivariate Cox analysis was applied to select independent risk factors for OS of HCC.A comprehensive prognostic model and a prognostic nomogram with 6-NEMG risk characteristics and TNM staging were established.By using the median of prognostic scores as a cut-off,HCC patients were classified into low-risk and high-risk group.Kaplan-Meier survival curve analysis was conducted and log-rank test was performed to evaluate the survival rates between the low-risk and high-risk group.The area under the curve(AUC)values of receiver operating characteristic(ROC)curve were calculated via using the"timeROC"package.The prognostic model for HCC was validated by using the GEO HCC cohort(GSE14520)for 1,3 and 5 years.Finally,the relative expression level of 6-NEMG was validated in 34 clinical samples of HCC from Xinhua Hospital,Shanghai Jiao Tong University School of Medicine by using real-time quantitative polymerase chain reaction(qPCR)method.Results·Compared to 6-NEMG risk signature only(AUCs for 1,3 and 5 years were 0.77,0.66 and 0.65,respectively)or TNM stage only(AUCs for 1,3 and 5 years were 0.66,0.67 and 0.63,respectively),ROC curve analysis showed that this integrated prognostic model displayed better predictive performance for 1-year(AUC,0.78),3-year(AUC,0.73)and 5-year(AUC,0.69)OS of HCC.The Kaplan-Meier survival curve analysis showed that the OS of HCC patients in the high-risk group was significantly worse than that in the low-risk group(P=0.001).In addition,predictive performance of the prognostic model(AUC for 1,3 and 5 years is 0.67,0.66 and 0.74,respectively)and prognostic differences between the high-risk and low-risk group(P=0.001)were further validated in GEO(GSE14520)external cohort,and these results were consistent with the TCGA data.In addition to BNIP3L,dysregulation of five other NEMGs in the clinical HCC cohort was validated.The correlation analysis in GSE14520 and HCC clinical cohort showed a positive correlation between prognosis score and the size and number of tumors.Conclusion·A new prognostic model that combines 6-NEMG risk characteristics with TNM staging for predicting OS in HCC patients was constructed and validated.This model may help improve the prognosis prediction of HCC patients.
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【Objective】 To investigate the expression of optineurin (OPTN) in multiple myeloma (MM) and explore the mechanism and clinical value of OPTN gene in the occurrence and development of MM. 【Methods】 In this study, three gene expression omnibus (GEO) data sets were used to analyze the expression level of OPTN in MM. Clinical bone marrow samples of MM patients were collected. qRT-PCR was used to further verify the expression of OPTN in MM patients. The Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to analyze the value of OPTN in the prognosis and diagnosis of MM. At the same time, MM transcriptome data were downloaded from the Cancer Genome Atlas (TCGA) database. According to the median boundary of OPTN mRNA expression level, the MM patients were divided into OPTN high- and low-expression groups. In order to investigate the possible molecular mechanisms of OPTN in MM, gene set enrichment analysis (GSEA) was made after the differentially expressed genes were filtered using the limma package of the R language. 【Results】 The expression level of OPTN was significantly lower in MM tissues than in normal tissues (P<0.05). OPTN expression level was significantly correlated with International Staging System (ISS) in MM patients (P<0.05). ROC results showed that the expression level of OPTN could distinguish between normal and MM patients. Survival analysis showed that the overall survival (OS) of patients with low OPTN expression was significantly lower than that of patients with high OPTN expression (P<0.05). GO, KEGG and GSEA enrichment analyses indicated that OPTN might affect apoptosis and autophagy, and regulate cellular immune response by regulating Nod-like receptors, NF-κB, TNF and RAS/MAPK pathways. 【Conclusion】 Low expression of OPTN in MM is associated with poor prognosis of patients, and thus may be an important potential biomarker for the diagnosis and treatment of MM.
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Resumen Introducción : El objetivo de este estudio fue exami nar cómo la variabilidad geográfica y los determinantes sociales de la salud influyen en la tasa de letalidad por COVID-19 en Bariloche. Métodos : Se utilizó una base de datos del Sistema Nacional de Vigilancia Epidemiológica para analizar los casos positivos de COVID-19 desde enero de 2020 hasta diciembre de 2021. Los datos se geo-codificaron y se incorporaron en un sistema de información geográfica (SIG). Se aplicó un marco de análisis en tres pasos para medir la inequidad en salud, utilizando indicadores socioeconómicos y de acceso a servicios. Se realizó un análisis multivariado para predecir la letalidad. Resultados : Se diagnosticaron un total de 25 020 casos de COVID-19 en Bariloche durante el período de estudio. La letalidad fue del 2.1%. Se observó una variabilidad significativa en indicadores socioeconó micos entre las diferentes delegaciones territoriales de la ciudad. Discusión : Los resultados mostraron inequida des en salud y una asociación entre determinantes sociales y letalidad por COVID-19 en Bariloche. Las personas que vivían en áreas con mayor vulnerabili dad socioeconómica presentaron un mayor riesgo de mortalidad. Estos hallazgos resaltan la importancia de abordar las inequidades en salud en la respuesta a una pandemia.
Abstract Introduction : The objective of this study was to ana lyze the geographic variability and the relationship between social determinants of health and COVID-19 lethality in Bariloche. Methods : A database from the National Epidemiologi cal Surveillance System was used to analyze COVID-19 positive cases from January 2020 to December 2021. The data were geocoded and incorporated into a geo graphic information system (GIS). A three-step analytical framework was applied to measure health inequity, us ing socioeconomic indicators and access to services. A multivariate analysis was conducted to predict fatality. Results : A total of 25 020 COVID-19 cases were diag nosed in Bariloche during the study period. The fatality rate was 2.1%. Significant variability in socioeconomic indicators was observed among different territorial delegations of the city. Discussion : The results showed health inequities and an association between social determinants and COVID-19 lethality in Bariloche. Individuals living in areas with higher socioeconomic vulnerability had a higher risk of mortality. These findings highlight the importance of addressing health inequities in a pan demic response.
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At the Chennai Coast in Tamil Nadu, India, research is done. Finding out whether Marina Beach and Elliott's Beach are suitable for ecotourism is the study's main goal. For the research using the ecotourism suitability index methodology, land use, land cover, erosion, accretion, beach type, beach width, proximity to bus stop, proximity to train station, and suspended sediment load have all been taken into account. The suitability index of eco tourism is assigned into 4 (four) classes, which are: Class S1 (Highly suitable), Class S2 (Quite Suitable), Class S3 (Suitable with condition) and Class N (Not Suitable). Result of analysis indicates that coast area of Marina Beach and Elliots beach area comes in the class of Highly suitable (S1) by score total of 129 or 95.5 % and 116 or 85.9 % respectively. According to the research, Marina Beach has a sand feature as a land use land cover, 213 metres of beach width, good clarity (500 mg/L), is located 361 metres from a bus stop and 681 metres from a train station, has moderate erosion, and has not experienced any accretion. The beach type is white sand. Likewise, Elliots Beach has a sand feature as a land use land cover, with 222 metres of beach width, good clarity (600 mg/L), 642 metres from the bus stop, and 2351 metres from the railway station, which is high. There is moderate erosion and no accretion, and the sand is of the beach type, which is white. Marina beach has high tourism suitability index as compared to Elliot's beach. By considering marina beach, all the eight parameters are considered to be ne whereas Elliot's beach has far away accessibility this is the main reason for lowering the tourism suitability.
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Objective:To detect the expression of N6-methyladenosine (m 6A) regulators in colorectal tumor samples and its clinical significance. Methods:From September to December 2021, the data regarding the expression of m 6A regulators in colorectal tumor samples were collected using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and the expression of m 6A regulators was compared between different clinical pathological characteristics and between different molecular subtypes. Survival analysis was conducted in patients with colorectal cancer with different m 6A expression levels. Results:In TCGA, insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1), insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3), and YTH N6-methyladenosine RNA binding protein 1 (YTHDF1) were higher in colorectal tumor samples than normal tissue samples (TCGA-COAD: IGF2BP3: 12.80 vs. 204.46, logFC = 4.00, P = 0.003; YTHDF1: 2 347.56 vs. 3712.77, logFC = 0.66, P < 0.001; TCGA-READ: IGF2BP1: 6.20 vs. 359.32, logFC = 5.82, P = 0.007; YTHDF1: 2 470.10 vs. 4 369.09, logFC = 0.82, P = 0.020). The intersection of TCGA and GEO databases showed that methyltransferase like 14 (METTL14), YTH domain m 6A RNA binding protein 3 (YTHDF3), and α-ketoglutarate dependent dioxygenase AlkB homolog 5 (ALKBH5) were downregulated in colorectal tumor samples compared with normal tissue samples (TCGA-COAD: METTL14: 1 051.56 vs. 711.40, logFC = -0.56, P < 0.001; YTHDF3:4 613.85 vs. 3 155.05, logFC = -0.55, P < 0.001, ALKBH5: 4 250.10 vs. 2 555.55, logFC = -0.73, P < 0.001; TCGA-READ vs. METTL14: 1 113.3 vs. 674.36, logFC = -0.72, P < 0.001; YTHDF3: 5 034.30 vs. 3 331.95, logFC = -0.60, P = 0.004; ALKBH5: 4 902.20 vs. 2 529.71, logFC = -0.95, P < 0.001; GEO-CRC vs. METTL14: 6.58 vs. 6.33, logFC = -0.06, P < 0.001; YTHDF3: 6.28 vs. 6.20, logFC = -0.02, P = 0.002; ALKBH5: 5.07 vs. 4.98, logFC = -0.02, P < 0.001). In colorectal tumor samples of different molecular subtypes, IGF2BP2, HNRNPC, TP53 and YTHDF2 expression was low in KRAS (IGF2BP2: 48.53 vs. 44.04, t = 2.64, P = 0.008; HNRNPC: 121.30 vs. 112.60, t = 2.32, P = 0.020; TP53: 65.30 vs. 60.26, t = 2.11, P = 0.034; YTHDF2: 54.07 vs. 51.19; t = 1.97, P = 0.048). Different clinical pathological characteristics showed that IGF2BP1 was higher in colorectal cancer with positive lymph nodes (8.97 vs. 6.11, W = 20 008, P = 0.002), distant metastasis (8.94 vs. 6.41, W = 19 104, P = 0.009), or stage Ⅲ-Ⅳ (7.46 vs. 7.13, W = 8 779, P = 0.025) than normal tissue. ALKBH5 overexpression, advanced age, presence of vascular invasion, and late pathological staging were significantly related to a short survival period (high ALKBH5 expression vs. low ALKBH5 expression: 5.85 years vs. not available, HR: 1.63, 95% CI: 1.071-2.491, P = 0.021; > 68 years vs. < 68 years: 6.78 years vs. not available, HR: 1.59, 95% CI: 1.049-2.422, P = 0.047; stage Ⅲ-Ⅳ vs. stage Ⅰ-Ⅱ: 4.55 years vs. 8.33 years, HR: 2.89, 95% CI: 1.895-4.425, P < 0.001; presence of vein invasion vs. absence of vein invasion: 5.48 years vs. not available, HR: 2.82, 95% CI: 1.672-4.783, P < 0.001). Conclusion:Some of the m 6A regulators are associated with the biological characteristics and prognosis of colorectal cancer.
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Objective Using bioinformatics methods to study the immune infiltration mechanism of Primary Sj?gren's syndrome(pSS)and to explore potential target Chinese medicines,which can provide new directions for the clinical treatment of pSS.Methods Gene expression profile microarray dataset of pSS was downloaded from the GEO database,differential genes were screened using R software,and gene ontology(GO)and gene pathway enrichment(KEGG)enrichment analysis was performed on these differential genes.Protein interaction network analysis of differential genes was performed by applying the STRING database,key genes were screened by using Cytoscape,and ELISA for the verification of key genes expression.Immune infiltration and correlation of immune cells in pSS were calculated by CIBERSORT inverse convolution method in 22.Finally,the herbal prediction of key target genes was performed by using the Coremine Medical database.Results A total of 232 differential genes were obtained,of which 207 were up-regulated and 25 were down-regulated.GO was mainly enriched in:leukocyte mediated immunity,lymphocyte mediated immunity,leukocyte cell-cell adhesion,etc;KEGG was mainly enriched in Hematopoietic cell lineage,Primary immunodeficiency,Intestinal immune network for IgA production,Phagosome,Leishmaniasis.Ten key genes were screened:PTPRC,CD19,LCP2,CCR5 and CD69 etc.The hub genes expression in the pSS is the same as that of GSE40611.Immune infiltration showed that memory B cells,T cells CD4 memory activated,and T cells CD4 na?ve were highly expressed in the pSS.Immune cell correlation analysis showed a positive correlation between initial Monocytes and T cells regulatory(Tregs),a positive correlation between Macrophages M1 and B cell na?ve,and a negative correlation between Plasma cells and T cells CD4 memory activated.COREMINE Medical predicted that Ginseng,Panax notoginseng,Tripterygium wilfordii,Burnet,Magnolia,and Strychni may treat pSS.Conclusion The development and progression of pSS are the results of the combined involvement of multiple genes and pathways.Memory B cells,T cells CD4 memory activated,and T cells CD4 na?ve may promote the development of pSS.The predicted Ginseng,Panax notoginseng,Tripterygium wilfordii,Burnet,Magnolia,Strychni may be used as target herbs for the potential treatment of pSS.
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Objective To screen key genes and pathways of acute on-chronic liver failure(ACLF)by multiple bioinformatics,and to provide theoretical basis for molecular biology studies and biomarker screening of ACLF.Methods ACLF transcriptome mRNA mi-croarray data set was downloaded from Gene Expression Omnibus(GEO),and limma package in R software was used to analyze the difference expression genes.The gene ontology(GO)function enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)anal-ysis were analyzed differential genes through David database.Protein-protein interaction(PPI)network was analyzed using STRING da-tabase,the key differential genes were screened by Cytoscape software.Results A total of 329differentially expressed genes were screened,including 185 up-regulated genes and 144 down-regulated genes.GO functional enrichment analysis obtained 385 items,in-cluding immune receptor activity,cytokine receptor activity,T cell receptor binding and other biological functions(P＜0.05).KEGG pathway enrichment analysis screened 36signaling pathways,among which the immune and inflammatory pathways including Th1 and Th2 cell differentiation,Th17 cell differentiation pathway,T cell receptor signaling pathway,primary immune deficiency,NF-κB signaling pathway and TNF signaling pathway.Among these key genes,CD3G,CD3D,IL7R,LCK,IL1R2,IL18R1,IL1R1 and MAPK14 related to ACLF were further obtained,which may become potential biomarkers and therapeutic targets of ACLF.Conclusion This study demon-strates that CD3G,CD3D,IL7R,LCK,IL1R2,IL18R1,IL1R1 and MAPK14may become the core genes related to the occurrence and development of ACLF and new therapeutic targets in the future.
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Objective:The aim of this study was to determine the development and validation of a prognostic prediction model based on genes associated with N7 methylguanosine(m7G)RNA methylation modifications in breast cancer(BC)patients.Methods:We explored the expression patterns of 31 key m7G RNA methylation-related regulators in breast cancer tissues and their prognostic significance.First,we downloaded and analyzed the mRNA gene expression and clinical prognostic data from The Cancer Genome Atlas(TCGA)and Gene Expression Gene Expression(GEO)databases.The prognostic value of each m7G-related gene for survival was assessed by us-ing univariate Cox regression analysis.A prognostic risk model based on m7G methylation-regulat-ed genes was then constructed by applying the least absolute shrinkage and selection operator(LASSO)regression method.Patients were divided into high-risk and low-risk groups according to median risk scores,and the differences in overall survival(OS)between high-and low-risk groups were compared.Then,gene set enrichment analysis(GSEA)analysis was performed to elaborate the main mechanisms of action in the BC high-risk group.Finally,a prognostic nomogram based on m7G was constructed and validated in TCGA and GEO cohorts respectively.Results:A prognostic risk model based on seven m7G methylation-regulated genes was constructed.The overall survival(OS)was significantly lower in the high-risk group than in the low-risk group(P＜0.001).GSEA anal-ysis showed that the"cell cycle"was the most important pathways in the high-risk group.Using risk scores and clinical characteristics of the training set TCGA cohort,prognostic nomogram was constructed,and calibration curves and decision curve analysis(DCA)showed good concordance and predictive efficacy and were validated in the GEO cohort.Conclusion:The prognostic model based on m7G-related genes plays an important prognostic predictive role in breast cancer and can be used to guide the individualized treatment of breast cancer patients.
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Objective @# To the effects and potential mechanisms of ST3GAL5 on biological behaviors of Bladder Urothelial Carcinoma(BLCA) . @*Methods @# Differentially expressed genes related to bladder cancer were identified using microarray analysis . Suitable bladder cancer cell lines were then screened . In vitro experimental measurements , including CCK8 , EdU , colony formation assays , transwell migration , flow cytometry apoptosis experiments , scratch assay , were used to evaluate the effects of ST3GAL5 on biological behaviors of BLCA . ST3GAL5 gene Kyoto Encyclopedia of Genes and Genomes ( KEGG) , gene set enrichment analysis ( GSEA) were analyzed using The Cancer Genome Atlas (TCGA) database . Finally , Western blot technology was used to verify the classical proliferation and metastasis related pathway factors . @*Results @# The combination of bioinformatics analyses and experimental measurements demonstrate that ST3GAL5 expression is aberrantly down⁃regulated in human cell lines of BLCA . Through Cancer Cell Line Encyclopedia (CCLE) database , HT⁃1376 cell lines were successfully screened for vitro test . Upregulation of ST3GAL5 was found to suppress the malignant biological behaviour of bladder cancer. GSEA enrichment analyses exhibited that ST3GAL5 and its co⁃expressed genes inhibited cell proliferation , invasion and metastasis of bladder urothelial carcinoma by activation of the PPAR pathway and inhibition of the PI3K/AKT pathway . The results of Western blot experiments verified that the key proteins of the PPAR signaling pathway showed a significant increase and the key proteins of the PI3K/AKT signaling pathway showed a significant decrease ( P <0. 05) after ST3GAL5 overexpression in bladder cancer. @*Conclusion @#ST3GAL5 gene might act as an oncogenic suppressor gene in bladder cancer , possibly inhibit the proliferation , invasion and metastasis of bladder cancer cells by activating the PPAR signaling pathway and inhibiting related molecules in the PI3K/AKT signaling pathway .
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OBJECTIVE To utilize RNA sequencing(RNA-seq)data from the GEO database to identify genes with potential diagnostic value for eosinophilic chronic rhinosinusitis with nasal polyps(ECRSwNP).METHODS Three datasets were obtained,and samples were divided into ECRSwNP and nonECRSwNP groups based on the expression levels of CST1 and CLC.A diagnostic model for ECRSwNP was established using R software and algorithms,and its accuracy was assessed.RESULTS The samples were grouped as follows:GSE136825(ECRSwNP 7,nonECRSwNP 19),GSE72713(ECRSwNP 3,nonECRSwNP 3),and GSE179265(ECRSwNP 11,nonECRSwNP 2).The diagnostic performance of the upregulated gene model(ADH1C,CCL26,HRH1,NOS2)and the downregulated gene model(LCN2,MUC5B,PLAT,TMEM45A,XDH)constructed based on the support vector machine(SVM)algorithm for ECRSwNP was excellent.CONCLUSION The diagnostic genes identified by the SVM model may serve as biological markers for the non-invasive diagnosis of ECRSwNP and potentially play a crucial role in the pathogenesis of ECRSwNP.
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Traditional Chinese medicine(TCM)regulatory science,as an emerging interdisciplinary science,evaluates the safety,effectiveness,quality,and risk-benefit profile of regulated Chinese medicinal products,including Chinese medicinal materials,Chinese medicinal slices,and Chinese patent medicines.It highlights the development of new tools,standards,and methods that align with the unique characteristics of TCM.TCM regulatory science plays a crucial role in establishing a TCM scientific regulatory system that suits the features of TCM,accelerating the transformation of emerging TCM technologies and facilitating innovation in the inheritance and development of TCM.Sichuan,known as the"hometown of TCM therapies and the treasure trove of TCM",has built the first national modernized TCM technology industrial base and one of the first national comprehensive TCM reform demonstration zones.It plays a demonstrative and leading role in the high-quality development of the TCM industry in China.Based on the latest progress in new tools,standards,and methods of TCM regulatory science,this article overviewed its significant role and prospects in enhancing the efficiency of TCM regulation,accelerating the transformation and application of new TCM technologies and products,and promoting the high-quality development of the TCM industry in Sichuan.It is of great significance for ensuring and improving the regulatory capabilities of TCM and driving the healthy development of the TCM industry.
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Abstract Background Osteoarthritis (OA) is one of the most frequent chronic diseases with high morbidity worldwide, marked by degradation of the cartilage and bone, joint instability, stiffness, joint space stenosis and subchondral sclerosis. Due to the elusive mechanism of osteoarthritis (OA), we aimed to identify potential markers for OA and explore the molecular mechanisms underlying OA. Methods Expression profiles data of OA were collected from the Gene Expression Omnibus database to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) in OA. Functional annotation and protein-protein interaction (PPI) networks were performed. Then, nearby DEmRNAs of DElncRNAs was obtained. Moreover, GO and KEGG pathway enrichment analysis of nearby DEmRNAs of DElncRNAs was performed. Finally, expression validation of selected mRNAs and lncRNAs was performed by quantitative reverse transcriptase-polymerase chain reaction. Results In total, 2080 DEmRNAs and 664 DElncRNAs were determined in OA. PI3K-Akt signaling pathway, Endocytosis and Rap1 signaling pathway were significantly enriched KEGG pathways in OA. YWHAB, HSPA8, NEDD4L and SH3KBP1 were four hub proteins in PPI network. The AC093484.4/TRPV2 interact pair may be involved in the occurrence and development of OA. Conclusion Our study identified several DEmRNAs and DElncRNAs associated with OA. The molecular characters could provide more information for further study on OA.
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Objective To screen antigen targets for immunotherapy by analyzing over-expressed genes, and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis, protein-protein interaction (PPI) network, and survival analysis based on the Gene Expression Omnibus (GEO) database.Methods By screening with highly expressed genes, we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis, PPI network, and survival analysis. Several software and platforms including Prism 8, R language, Cytoscape, DAVID, STRING, and GEPIA platform were used in the search and/or figure creation.Results Genes MUC13 and EPCAM were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including ALDH3A1, C2, SLC6A1,and ZBTB7C were screened with significant P value of survival curve.Conclusions Genes MUC13 and EPCAM may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes ALDH3A1, C2, SLC6A1,and ZBTB7C may play important roles in the development of esophageal cancer.