Cloning and Bioinformatic Analysis of Cinnamoyl-CoA Reductase Gene (CCR) from Pennisetum purpureum

[Objective] The aim was to clone the cDNA and DNA sequences of the CCR （Cinnamoyl-CoA reductase） gene which involves in lignin biosynthesis, from Pennisetum purpureum, and to make comprehensive analysis on these sequences. [Method] CCR sequences were cloned from P. purpureum by using conventional RT-PCR and RACE （Rapid Amplification of cDNA Ends） methods; and the bioinformatic analyses of the CCR were conducted by means of NCBI, ProtParam ProtScale, TMHMM, TargetP, SignalP, Pfam20.0, Prosite, Swiss-Model, ClustalW2, DNAman, DNAstar and MEGA5. [Result] The cloned PpCCR （P. purpureum CCR） cDNA sequence was 1 316 bp, including a 1 110 bp ORF and 206 bp 3’-UTR. The cloned DNA sequence from PpCCR was 6 133 bp in full-length, containing five exons and four introns. Bioinformatic analysis indicated that PpCCR encoded a polypeptide of 369 amino acids, the secondary structure of which was primarily composed of random coil and α-helix, belonging to NAD-dependent epimerase/dehydratase family, and its co-factor binding sites and substrate binding sites were highly conserved. [Conclusion] DNA and cDNA sequences of CCR gene were obtained from P. purpureum, which had the typical characteristics of other homologous genes. The obtained bioinformatic data provided theoretical references for the further analysis of CCR and better application of P. purpureum in the future.

Key factors and potential drug combinations of nonalcoholic steatohepatitis:Bioinformatic analysis and experimental validation-based study

Background:Nonalcoholic fatty liver disease and its advanced stage,nonalcoholic steatohepatitis(NASH),are the major cause of hepatocellular carcinoma(HCC)and other end-stage liver disease.However,the potential mechanism and therapeutic strategies have not been clarified.This study aimed to identify potential roles of mi RNA/m RNA axis in the pathogenesis and drug combinations in the treatment of NASH.Methods:Microarray GSE59045 and GSE48452 were downloaded from the Gene Expression Omnibus and analyzed using R.Then we obtained differentially expressed genes(DE-genes).DAVID database was used for Gene Ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment pathway analysis.Protein-protein interaction(PPI)networks were used for the identification of hub genes.We found upstream regulators of hub genes using mi RTar Base.The expression and correlation of key mi RNA and its targets were detected by q PCR.Drug Pair Seeker was employed to predict drug combinations against NASH.The expression of mi RNA and hub genes in HCC was identified in the Cancer Genome Atlas database and Human Protein Atlas database.Results:Ninety-four DE-genes were accessed.GO and KEGG analysis showed that these predicted genes were linked to lipid metabolism.Eleven genes were identified as hub genes in PPI networks,and they were highly expressed in cells with vigorous lipid metabolism.hsa-mi R-335-5 p was the upstream regulator of 9 genes in the 11 hub genes,and it was identified as a key mi RNA.The hub genes were highly expressed in NASH models,while hsa-mi R-335-5 p was lowly expressed.The correlation of mi RNA-m RNA was established by q PCR.Functional verification indicated that hsa-mi R-335-5 p had inhibitory effect on the development of NASH.Finally,drug combinations were predicted and the expression of mi RNA and hub genes in HCC was identified.Conclusions:In the study,potential mi RNA-m RNA pathways related to NASH were identified.Targeting these pathways may be novel strategies against NASH.

Proteomic signatures of infiltrative gastric cancer by proteomic and bioinformatic analysis

BACKGROUND Proteomic signatures of Ming's infiltrative gastric cancer(IGC)remain unknown.AIM To elucidate the molecular characteristics of IGC at the proteomics level.METHODS Twelve pairs of IGC and adjacent normal tissues were collected and their proteomes were analyzed by high performance liquid chromatography tandem mass spectrometry.The identified peptides were sequenced de novo and matched against the SwissProt database using Maxquant software.The differentially expressed proteins(DEPs)were screened using|log2(Fold change)|>1 and P-adj<0.01 as the thresholds.The expression levels of selected proteins were verified by Western blotting.The interaction network of the DEPs was constructed with the STRING database and visualized using Cytoscape with cytoHubba software.The DEPs were functionally annotated using clusterProfiler,STRING and DAVID for Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways.P<0.05 was considered statistically significant.RESULTS A total of 7361 DEPs were identified,of which 94 were significantly up-regulated and 223 were significantly down-regulated in IGC relative to normal gastric tissues.The top 10 up-regulated proteins were MRTO4,BOP1,PES1,WDR12,BRIX1,NOP2,POLR1C,NOC2L,MYBBP1A and TSR1,and the top 10 down-regulated proteins were NDUFS8,NDUFS6,NDUFA8,NDUFA5,NDUFC2,NDUFB8,NDUFB5,NDUFB9,UQCRC2 and UQCRC1.The up-regulated proteins were enriched for 9 biological processes including DNA replication,ribosome biogenesis and initiation of DNA replication,and the cellular component MCM complex.Among the down-regulated proteins,17 biological processes were enriched,including glucose metabolism,pyruvic acid metabolism and fatty acidβ-oxidation.In addition,the mitochondrial inner membrane,mitochondrial matrix and mitochondrial proton transport ATP synthase complex were among the 6 enriched cellular components,and 11 molecular functions including reduced nicotinamide adenine dinucleotide dehydrogenase activity,acyl-CoA dehydrogenase activity and nicotinamide adenine dinucleotide binding were also enriched.The significant KEGG pathways for the up-regulated proteins were DNA replication,cell cycle and mismatch repair,whereas 18 pathways including oxidative phosphorylation,fatty acid degradation and phenylalanine metabolism were significantly enriched among the down-regulated proteins.CONCLUSION The proteins involved in cell cycle regulation,DNA replication and mismatch repair,and metabolism were significantly altered in IGC,and the proteomic profile may enable the discovery of novel biomarkers.

Prokaryotic Expression of Rice Ospgip1 Gene and Bioinformatic Analysis of Encoded Product

Using the reference sequences of pgip genes in GenBank,a fragment of 930 bp covering the open reading frame(ORF) of rice Ospgip1(Oryza sativa polygalacturonase-inhibiting protein 1) was amplified.The prokaryotic expression product of the gene inhibited the growth of Rhizoctonia solani,the causal agent of rice sheath blight,and reduced its polygalacturonase activity.Bioinformatic analysis showed that OsPGIP1 is a hydrophobic protein with a molecular weight of 32.8 kDa and an isoelectric point(pI) of 7.26.The protein is mainly located in the cell wall of rice,and its signal peptide cleavage site is located between the 17th and 18th amino acids.There are four cysteines in both the N-and C-termini of the deduced protein,which can form three disulfide bonds(between the 56th and 63rd,the 278th and 298th,and the 300th and 308th amino acids).The protein has a typical leucine-rich repeat(LRR) domain,and its secondary structure comprises α-helices,β-sheets and irregular coils.Compared with polygalacturonase-inhibiting proteins(PGIPs) from other plants,the 7th LRR is absent in OsPGIP1.The nine LRRs could form a cleft that might associate with proteins from pathogenic fungi,such as polygalacturonase.

Bioinformatic Analysis of Structural Proteins of Paramyxovirus Tianjin Strain

The amino acid sequences of the NP, P, M, F, HN and L proteins of the paramyxovirus Tianjin strain were analyzed by using the bioinformatics methods. Phylogenetic analysis based on 6 structural proteins among the Tianjin strain and 25 paramyxoviruses showed that the Tianjin strain belonged to the genus Respirovirus, in the subfamily Paramyxovirinae, and was most closely related to Sendai virus (SeV). Phylogenetic analysis with 14 known SeVs showed that Tianjin strain represented a new evolutionary lineage. Similarities comparisons indicated that Tianjin strain P protein was poorly conserved, sharing only 78.7% - 91.9% amino acid identity with the known SeVs, while the L protein was the most conserved, having 96.0% - 98.0% amino acid identity with the known SeVs. Alignments of amino acid sequences of 6 structural proteins clearly showed that Tianjin strain possessed many unique amino acid substitutions in their protein sequences, 15 in NP, 29 in P, 6 in M, 13 in F, 18 in HN, and 29 in L. These results revealed that Tianjin strain was most likely a new genotype of SeV. The presence of unique amino acid substitutions suggests that Tianjin strain maybe has a significant difference in biological, pathological, immunological, or epidemiological characteristics from the known SeVs.

Bioinformatic analysis reveals novel biomarkers and candidate drug compositions in prostate cancer

As prostate cancer(PC)patients do more and more genome sequencing,we can predict prognosis through individual oncogenic mutations.Although great success have been made to clarify the incidence of PC,the mechanisms was not completely understood.Recurrence and metastasis of PC remains to be resolved,and novel therapeutic targets need to be found urgently.Microarray datasets GSE6919,GSE55945 and GSE46602 about the PC tissues vs.normal organizations,were obtained from Gene Expression Omnibus.In this study,86 differentially expressed genes were determined having more important clinical significance in the process of PC.29 hub genes significantly enriched in biological processes were analyzed using Cytoscape.The function of these hub genes included the effect of cellular process,skeletal system development,cholesterol transport,regulation of protein oligomerization and cellular component biogenesis,enzyme inhibitor activity and so on.The three of these hub genes were picked out because of their relationships,which can be used as a potential target for the diagnosis and the direction of therapy.And drug predictions were designed for these candidate target molecules,providing direction for future treatment of PC.

Prognostic value of potential biomarkers in prostate cancer via bioinformatic analysis

Background:The Genotype-Tissue Expression was used to expanded normal tissue of the Cancer Genome Atlas database.This study aimed to investigate genes associated with the pathogenesis and prognosis of prostate cancer.Methods:We conducted prognostic related genes for prostate cancer by using transcriptome data from the Genotype-Tissue Expression Project and the Cancer Genome Atlas data sources,which were analyzed using an integrated bioinformatics strategy.Clinically significant modules were distinguished,and GO and KEGG analysis were used to Database for Annotation,Visualization and Integrated Discovery.Further annotation was performed through Gene set enrichment analysis.Logistic regression was carried out to analyze the associations between clinicopathologic characteristics and the hub genes.Logistic regression model and survival analysis were performed.Results:By using data available from the Cancer Genome Atlas and the Genotype-Tissue Expression databases,we here show that 53 differential expression genes were identified.Through GO and KEGG analysis a prognostic related gene signature consisted of GOLM1,EIF4A1,ABCC4,RPL7P16,NPIPB12 and PCA3 was constructed with a good performance in predicting overall survivals.The majority of the six hub genes were associated with clinical characteristics of prostate cancer.Conclusion:These genes might be considered as new targets for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy since they showed differently expressed in prostate cancer and correlate with overall survival prognosis.

Identification and Validation of SLC9A2 as A Potential Tumor Suppressor in Colorectal Cancer:Integrating Bioinformatics Analysis with Experimental Confirmation

Objective To uncover the mechanisms underlying the development of colorectal cancer(CRC),we applied bioinformatic analyses to identify key genes and experimentally validated their possible roles in CRC onset and progression.Methods We performed Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis on differentially expressed genes(DEGs),constructed a protein-protein interaction(PPI)network to find the top 10 hub genes,and analyzed their expression in colon adenocarcinoma(COAD)and rectum adenocarcinoma(READ).We also studied the correlation between these genes and immune cell infiltration and prognosis and validated the expression of SLC9A2 in CRC tissues and cell lines using qRT-PCR and Western blotting.Functional experiments were conducted in vitro to investigate the effects of SLC9A2 on tumor growth and metastasis.Results We found 130 DEGs,with 45 up-regulated and 85 down-regulated in CRC.GO analysis indicated that these DEGs were primarily enriched in functions related to the regulation of cellular pH,zymogen granules,and transmembrane transporter activity.KEGG pathway analysis revealed that the DEGs played pivotal roles in pancreatic secretion,rheumatoid arthritis,and the IL-17 signaling pathway.We identified 10 hub genes:CXCL1,SLC26A3,CXCL2,MMP7,MMP1,SLC9A2,SLC4A4,CLCA1,CLCA4,and ZG16.GO enrichment analysis showed that these hub genes were predominantly involved in the positive regulation of transcription.Gene expression analysis revealed that CXCL1,CXCL2,MMP1,and MMP7 were highly expressed in CRC,whereas CLCA1,CLCA4,SLC4A4,SLC9A2,SLC26A3,and ZG16 were expressed at lower levels.Survival analysis revealed that 5 key genes were significantly associated with the prognosis of CRC.Both mRNA and protein expression levels of SLC9A2 were markedly reduced in CRC tissues and cell lines.Importantly,SLC9A2 overexpression in SW480 cells led to a notable inhibition of cell proliferation,migration,and invasion.Western blotting analysis revealed that the expression levels of phosphorylated ERK(p-ERK)and phosphorylated JNK(p-JNK)proteins were significantly increased,whereas there were no significant changes in the expression levels of ERK and JNK following SLC9A2 overexpression.Correlation analysis indicated a potential link between SLC9A2 expression and the MAPK signaling pathway.Conclusion Our study suggests that SLC9A2 acts as a tumor suppressor through the MAPK pathway and could be a potential target for CRC diagnosis and therapy.

Transcriptomic and bioinformatics analysis of the mechanism by which erythropoietin promotes recovery from traumatic brain injury in mice

Recent studies have found that erythropoietin promotes the recovery of neurological function after traumatic brain injury.However,the precise mechanism of action remains unclea r.In this study,we induced moderate traumatic brain injury in mice by intrape ritoneal injection of erythro poietin for 3 consecutive days.RNA sequencing detected a total of 4065 differentially expressed RNAs,including 1059 mRNAs,92 microRNAs,799 long non-coding RNAs,and 2115circular RNAs.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses revealed that the coding and non-coding RNAs that were differentially expressed after traumatic brain injury and treatment with erythropoietin play roles in the axon guidance pathway,Wnt pathway,and MAPK pathway.Constructing competing endogenous RNA networks showed that regulatory relationship between the differentially expressed non-coding RNAs and mRNAs.Because the axon guidance pathway was repeatedly enriched,the expression of Wnt5a and Ephb6,key factors in the axonal guidance pathway,was assessed.Ephb6 expression decreased and Wnt5a expression increased after traumatic brain injury,and these effects were reversed by treatment with erythro poietin.These findings suggest that erythro poietin can promote recove ry of nerve function after traumatic brain injury through the axon guidance pathway.

Molecular Cloning and Bioinformatics Analysis of msrA Gene from Vibrio alginolyticus Strain HY9901

[Objectives]This study was conducted to understand the structure and function of MsrA protein.[Methods]With Vibrio alginolyticus HY9901 as the object of study,primers were designed to amplify the full-length gene of msrA,and its bioinformatics analysis was carried out.[Results]The full length of msrA gene was 639 bp,encoding 212 amino acids,and its theoretical molecular weight was about 23729.60 Da.The protein had a stable structure,and it was hydrophobic overall.The structure of signal peptides at the N terminal of the amino acid sequence was predicted,and it was found that there was no signal peptide cleavage site and no transmembrane region.The amino acid sequence of MsrA contained multiple signal binding sites.Protein subcellular localization showed that MsrA protein was most likely located in the cytoplasm.Homology analysis showed that MsrA of V.alginolyticus had high homology with other Vibrio species,and the highest homology with V.alginolyticus.In the prediction of functional domains,MsrA had the function of methionine sulfoxide reduction.In secondary structure prediction,MsrA contained random coils at a proportion of 46.70%,which was the highest.The similarity between the tertiary structure model of MsrA and template Q87SW6.1.A was 89.15%.PTM analysis showed that MsrA protein had many PTM modification sites such as phosphorylation and glycosylation sites.[Conclusions]This study provides some reference value for further study on the role of MsrA in bacterial antioxidant stress.

Molecular Cloning of sodB Gene from Vibrio alginolyticus HY9901 and Its Bioinformatics Analysis

Vibrio alginolyticus is a zoonotic bacterium.A pair of specific primers was designed using the sodB gene sequence of Vibrio alginolyticus HY9901 in order to amplify the full length of the gene by PCR.The results indicated that the total length of the sodB gene was 585 bp and that it could encode 194 amino acids.The predicted amino acid sequence derivation indicated that the molecular weight of the protein was approximately 21.56 kDa,with an isoelectric point of 4.95.Upon prediction of the N-terminal signal peptide structure of the protein,no significant signal peptide cleavage site was observed,indicating that the protein lacked both a signal peptide and a transmembrane region.The amino acid sequence contained an N-glycosylation site,a casein kinase II phosphorylation site,a microsomal C-terminal target signal site,and a manganese and iron superoxide dismutase signal site.The probability of intracytoplasmic localization of the SodB protein was 56.5%,which was analyzed according to the subcellular localization of the protein.The amino acid sequence of the sodB gene of V.alginolyticus exhibited 98%-100%homology to other Vibrio species,clustering into the same subfamily with V.parahaem,indicating a relatively close relationship between them.In the prediction of protein structure,the proportions ofα-helix,random coil,β-sheet,and extended strand were 48.45%,30.41%,5.67%,and 15.46%,respectively.The similarity to template 1dt0.1.A reached 71.58%.A PTM site analysis revealed the presence of phosphorylation,glycosylation,ubiquitination,sumoylation,acetylation,and methylation modification sites,as well as the absence of lactylation modification sites.

Molecular Cloning and Bioinformatics Analysis of cyaA Gene of Vibrio alginolyticus Strain HY9901

[Objectives]This study was conducted to explore the biological functions of cyaA gene of Vibrio alginolyticus.[Methods]With DNA of V.alginolyticus HY 9901 as a template,primers were designed according to the sequence of cyaA gene,and the cyaA gene was amplified by PCR.Bioinformatics analysis was performed.[Results]The cyaA gene of V.alginolyticus HY9901 was 2529 bp in size,and encoded 842 amino acids.The molecular structure of CyaA protein was C_(4358)H_(6745)N_(1171)O_(1286)S_(35).Its theoretical molecular weight was 97.24167 kDa and the theoretical pI value was 5.56.It had no signal peptide and transmembrane domain.CyaA protein had three N-terminal glycosylation sites,one cAMP and cGMP-dependent protein kinase phosphorylation site,nine protein kinase C phosphorylation sites,nine casein kinase II phosphorylation sites,one tyrosine kinase phosphorylation site,seven N-terminal myristoylation sites,one pentenyl binding site and ten microbody C-terminal localization signal sites.Subcellular localization prediction showed that CyaA protein was mainly located in the nucleus and cytoplasm.Through multi-sequence alignment and phylogenetic tree construction,it was concluded that V.alginolyticus had high CyaA homology with other Vibrio species.cyaA of V.alginolyticus was clustered with Vibrio fluminensis and Vibrio marinisedimini,and they were closely related.The secondary structure of CyaA protein consisted ofα-helixes(43.11%),random coils(38.00%)and extended strands(14.49%).In protein network interaction,it was found that the proteins adjacent to CyaA protein were Crp-2,CpdA,Crr,PtsG-2,ANP67209.1,Crp-1,PykF,Pyk,RelA and Ndk.[Conclusions]This study provides a new idea for formulating strategies for the prevention and control of vibriosis.

Bioinformatics Analysis of the Relationship between Dilated Cardiomyopathy and Chronic Heart Failure

Objective: To screen and analyze the differentially expressed genes between dilated cardiomyopathy (DCM) and chronic heart failure (CHF) based on bioinformatics methods. Methods: The Gene Expression Omnibus (GEO) database was used for data retrieval, and the chip data GSE3585 was downloaded, which was the original data of DCM and normal control group. At the same time, the chip data GSE76701 was downloaded, which was the original data of CHF and control group. Differentially expressed mRNAs (DEmRNAs) were screened by R language limma package, the data were standardized, and the common differentially expressed genes were screened. GO function and KEGG pathway enrichment analysis were performed on the common differentially expressed genes. String11.0 online tool was used for data analysis to obtain differentially expressed genes, and the results were imported into Cytoscape 3.9.1 software. The results were imported into Cytoscape 3.9.1 software, and the common expression gene module was obtained by MOCDE algorithm. Nine Hub genes were obtained by 10 algorithms such as MCC. Results: A total of 248 differentially expressed genes were screened. GO analysis showed that differentially expressed genes were mainly concentrated in 9 different physiological and pathological processes. KEGG analysis showed that the main signaling pathways involved in differentially expressed genes were 2, and 9 key differentially expressed genes were predicted: NPPB, NPPA, MYH6, FRZB, ASPN, SFRP4, RPS4Y1, DDX3Y. Conclusion: This study preliminarily explored the molecular mechanism of DCM and CHF, and obtained the common differentially expressed genes of the two diseases. Further experimental studies are needed to verify the correlation between gene expression and clinicopathological features. Provide new ideas for clinical drug treatment research.

Bioinformatics Analysis of the Association between Ewing’s Sarcoma and Tuberculosis Comorbidity

Objective To screen and analyze the differentially expressed genes of Ewing’s sarcoma (ES) and Tuberculosis (TB) by bioinformatics. Methods GEO gene chip public database in NCBI was used for data retrieval, and chip data GSE17674 and GSE57736 were selected as analysis objects. The R language limma toolkit was used to screen DEmRNAs, and the data were standardized, and the common differentially expressed genes were screened by Venn diagram. The GO function and KEGG pathway enrichment of common differentially expressed genes were analyzed by using the R cluster Profiler package. String database was selected for PPI analysis, and the results were imported into Cytoscape software to obtain PPI interaction map, core module and Hub gene. Import Hub gene into BioGPS database. Results: A total of 3 Hub genes were screened, namely CD3D, LCK, KLRB1;The genes were imported into BioGPS database to obtain the specific genes. Conclusion The selected differential genes and related signaling pathways are helpful to understand the molecular mechanism of ES and TB, and can provide the basis for early diagnosis of ES complicated with TB. It also provides new ideas for clinical treatment and diagnosis.

Bioinformatics Analysis of the Biological Properties of Ewing Sarcoma

Purpose: Bioinformatics-based approach to screen and analyze differentially expressed genes associated with the biological characteristics of Ewing sarcoma. Means: The GSE17674 dataset was selected for analysis, obtained by data retrieval based on the GEO public database. The R language limma toolkit was used to screen DEmRNAs. After the data were normalized, the Metascape online analysis software and the R language clusterProfiler package were used to analyze the GO function and KEGG pathway enrichment of DEmRNAs lines, respectively. The string database was selected for PPI analysis, and the results were imported into Cytoscape software to derive the core modules and predicted core genes. The genes selected above were analyzed for tissue localization specificity. Results: Through the analysis of GSE17674, differentially expressed genes were screened out, and GO and KEGG analyses were performed on the differentially expressed genes. The GO functional enrichment analysis was mainly enriched in the process of muscle system, muscle contraction, myocyte development, contractile fibers, myogenic fibers, myofibers, myofibrillar segments, actin binding, structural composition of muscle, and actin filament binding. KEGG pathway analysis showed that the core pathways associated with the development of ES were the core genes for myocardial contraction, congestive cardiomyopathy, and hypertrophic cardiomyopathy. Five Hub genes were obtained based on Cytoscape prediction. Tissue localization specificity analysis of Hub genes was performed, and a total of 2 Hub genes with tissue specificity were screened;MYH6 was specifically expressed in cardiac cells and MYL1 was specifically expressed in skeletal muscle cells. Conclusions: The differential genes screened will help to understand the molecular mechanisms underlying the highly invasive and metastasis-prone biological characteristics of ES, as well as provide new ideas for clinical drug-targeted treatment of ES.

A Bioinformatics Analysis of FAM3A to Identify its Potential Role as a Biomarker in Liver Hepatocellular Cancer

Liver hepatocellular cancer(LIHC)is positioned as the third cancer with the highest mortalities worldwide,and high mortalities are associated with late diagnosis and recurrence.This study advances bioinformatics analysis of FAM3A expression in LIHC to evaluate its potential as a prognostic,diagnostic and therapeutic biomarker.Bioinformatics tools such as UALCAN,GEPIA2,KM plotter,TIMER2 and cBioPortal are employed to conduct analysis.Initially,the expression analysis revealed up-regulation of FAM3A in LIHC based on various variables.Further,the study observed that FAM3A methylation regulates expression as variation in methylation level of FAM3A was assessed in LIHC.Moreover,this over-expression of FAM3A results in poor overall survival(OS)in LIHC patients.All of these proposed that FAM3A has a role in the progression and development of LIHC.While examined association of FAM3A expression and infiltration level of CD8+T cells in LIHC patients using TIMER2 revealed that FAM3A has a positive correlation with purity in LIHC that highlights the molecular landscape.Analysis of genetic alteration revealed minute role of FAM3A in LIHC still provides valuable insight.Overall,our findings reveal that FAM3A has potential as diagnostic,therapeutic and prognostic biomarkers in LIHC.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

Identification of hub genes associated with Helicobacter pylori infection and type 2 diabetes mellitus:A pilot bioinformatics study

BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.

Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis

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.

Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer

BACKGROUND Gastric cancer(GC)is one of the most common malignant tumors with poor prognosis in terms of advanced stage.However,the survival-associated biomarkers for GC remains unclear.AIM To investigate the potential biomarkers of the prognosis of patients with GC,so as to provide new methods and strategies for the treatment of GC.METHODS RNA sequencing data from The Cancer Genome Atlas(TCGA)database of STAD tumors,and microarray data from Gene Expression Omnibus(GEO)database(GSE19826,GSE79973 and GSE29998)were obtained.The differentially expressed genes(DEGs)between GC patients and health people were picked out using R software(x644.1.3).The intersections were underwent between the above obtained co-expression of differential genes(co-DEGs)and the DEGs of GC from Gene Expression Profiling Interactive Analysis database,and Gene Ontology(GO)analysis,Kyoto Encyclopedia of Gene and Genome(KEGG)pathway analysis,Gene Set Enrichment Analysis(GSEA),Protein-protein Interaction(PPI)analysis and Kaplan-Meier Plotter survival analysis were performed on these DEGs.Using Immunohistochemistry(IHC)database of Human Protein Atlas(HPA),we verified the candidate Hub genes.RESULTS With DEGs analysis,there were 334 co-DEGs,including 133 up-regulated genes and 201 down-regulated genes.GO enrichment analysis showed that the co-DEGs were involved in biological process,cell composition and molecular function pathways.KEGG enrichment analysis suggested the co-DEGs pathways were mainly enriched in ECM-receptor interaction,protein digestion and absorption pathways,etc.GSEA pathway analysis showed that co-DEGs mainly concentrated in cell cycle progression,mitotic cell cycle and cell cycle pathways,etc.PPI analysis showed 84 nodes and 654 edges for the co-DEGs.The survival analysis illustrated 11 Hub genes with notable significance for prognosis of patients were screened.Furtherly,using IHC database of HPA,we confirmed the above candidate Hub genes,and 10 Hub genes that associated with prognosis of GC were identified,namely BGN,CEP55,COL1A2,COL4A1,FZD2,MAOA,PDGFRB,SPARC,TIMP1 and VCAN.CONCLUSION The 10 Hub genes may be the potential biomarkers for predicting the prognosis of GC,which can provide new strategies and methods for the diagnosis and treatment of GC.