Analysis of differentially expressed genes related to cerebral ischaemia in young rats based on the Gene Expression Omnibus database

BACKGROUND The incidence rate of cerebral infarction in young people is increasing day by day,the age of onset tends to be younger,and its internal pathogenesis and mechanism are very complicated,which leads to greater difficulties in treatment.Therefore,it is essential to analyze the key pathway that affects the onset of cerebral infarction in young people from the perspective of genetics.AIM To compare the differentially expressed genes in the brain tissue of young and aged rats with middle cerebral artery occlusion and to analyse their effect on the key signalling pathway involved in the development of cerebral ischaemia in young rats.METHODS The Gene Expression Omnibus 2R online analysis tool was used to analyse the differentially expressed genes in the GSE166162 dataset regarding the development of cerebral ischaemia in young and aged groups of rats.DAVID 6.8 software was further used to filter the differentially expressed genes.These genes were subjected to Gene Ontology(GO)function analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to determine the key gene pathway that affects the occurrence of cerebral ischaemia in young rats.RESULTS Thirty-five differentially expressed genes(such as Igf2,Col1a2,and Sfrp1)were obtained;73 GO enrichment analysis pathways are mainly involved in biological processes such as drug response,amino acid stimulation response,blood vessel development,various signalling pathways,and enzyme regulation.They are involved in molecular functions such as drug binding,protein binding,dopamine binding,metal ion binding,and dopamine neurotransmitter receptor activity.KEGG pathway enrichment analysis showed a significantly enriched pathway:The cyclic adenosine monophosphate(c-AMP)signalling pathway.CONCLUSION The c-AMP signalling pathway might be the key pathway in the intervention of cerebral infarction in young people.

Analysis of differentially expressed genes in Verruca vulgaris vs.adjacent normal skin by RNA-sequencing

Introduction:Verruca vulgaris is one of the most common low-risk HPV infections and is characterized by excessive proliferation of keratinocytes.Currently,very little genetic information is available regarding verruca vulgaris in the Chinese population.This study aimed to obtain comprehensive transcript information of verruca vulgaris by RNA sequencing.Methods:High-throughput sequencing was performed on three fresh verruca vulgaris samples and adjacent normal skin on the Illumina sequencing platform.The transcriptomes were analyzed using bioinformatics and the differentially expressed genes(DEGs)were verified by immunohistochemistry.Verruca vulgaris exhibited a unique molecular signature.Results:In total,1,643 DEGs were identified in verruca vulgaris compared to normal skin.The functions of the DEGs were studies by Gene Ontology(GO)enrichment,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis,DEGs Reactome analysis,disease annotation function,and STRING protein-protein interaction(PPI)network analysis.The results revealed 595 GO terms associated with the cell cycle,signal transduction,immune system,signaling molecules,and interaction.The Reactome analysis revealed enrichment in reversible hydration of carbon dioxide and BMP signaling,while the disease annotation function revealed that the enriched DEGs are involved in keratosis disorders.The STRING PPI network showed that the edges with the highest density mainly included the 2′-5′oligoadenylate synthase(OAS)family-related proteins.Furthermore,the M-code analysis found ISG15,IRF7,and OASL were scored as significant modules and their high expression compared to the control was verified by immunohistochemistry.Conclusion:These findings contribute to the genetic information of verruca vulgaris in the Chinese population,revealing that interferon-stimulated genes may play essential roles in verruca vulgaris.

Analysis of Growth Characteristics and Differentially Expressed Homologous Genes in Rhodobacter sphaeroides under Normal and Simulated Microgravity Conditions

The term “microgravity” is used to describe the “weightlessness” or “zero-g” circumstances that can only be found in space beyond earth’s atmosphere. Rhodobacter sphaeroides is a gram-negative purple phototroph, used as a model organism for this study due to its genomic complexity and metabolic versatility. Its genome has been completely sequenced, and profiles of the differential gene expression under aerobic, semi-aerobic, and photosynthetic conditions were examined. In this study, we hypothesized that R. sphaeroides will show altered growth characteristics, morphological properties, and gene expression patterns when grown under simulated microgravity. To test that, we measured the optical density and colony-forming units of cell cultures grown under both microgravity and normal gravity conditions. Differences in the cell morphology were observed using scanning electron microscopy (SEM) images by measuring the length and the surface area of the cells under both conditions. Furthermore, we also identified homologous genes of R. spheroides using the differential gene expression study of Acidovorax under microgravity in our laboratory. Growth kinetics results showed that R. sphaeroides cells grown under microgravity experience a shorter log phase and early stationary phase compared to the cells growing under normal gravity conditions. The length and surface area of the cells under microgravity were significantly higher confirming that bacterial cells experience altered morphological features when grown under microgravity conditions. Differentially expressed homologous gene analysis indicated that genes coding for several COG and GO functions, such as metabolism, signal-transduction, transcription, translation, chemotaxis, and cell motility are differentially expressed to adapt and survive microgravity.

Effects of pyraclostrobin on growth,oxidative stress,and gene expression in relation to stress and ATP-binding cassette transporters in Tetrahymena thermophila

Pyraclostrobin(PYR),a widely used fungicide,has negative effects on fish and algae,but its toxicity in protozoa remains unclear.In this study,the effects of PYR on the growth,oxidative stress,and gene expression related to stress and ATP-binding cassette(ABC)transporters in Tetrahymena thermophila were investigated.The result showed that the 96-h IC_(50)of PYR against T.thermophila was 17.2 mg/L.Moreover,PYR inhibited the growth of T.thermophila in concentration-or time-dependent manner.A morphological study revealed that the shape and size of T.thermophila changed,and damage of cell membrane surface was observed by scanning electron microscopy after 96 h of PYR exposure.The activities of superoxide dismutase(SOD)and catalase(CAT)increased throughout the experiment.In contrast,the glutathione(GSH)content was increased at 24 h and 48 h of exposure and decreased at 96 h.Moreover,a significant increase in malondialdehyde(MDA)level was observed in T.thermophila after96 h of exposure.Furthermore,PYR upregulated the HSP703,HSP705,GPx2,and ABAC15 gene expression in the 0.1–5-mg/L groups and downregulated the HSP704,HSP90,TGR,and ABCC52 mRNA levels at 96 h of exposure.These results suggest that PYR may exert adverse effects on T.thermophila by inducing oxidative stress and changing the gene expression related to ABC transporters and stress,which may enrich the understanding of the toxicity mechanism of PYR in aquatic organisms and provide reference data for aquatic ecological risk assessments.

Identifying genetic susceptibility to Aspergillus fumigatus infection using collaborative cross mice and RNA-Seq approach

Background:Aspergillus fumigatus(Af)is one of the most ubiquitous fungi and its infection potency is suggested to be strongly controlled by the host genetic back-ground.The aim of this study was to search for candidate genes associated with host susceptibility to Aspergillus fumigatus(Af)using an RNAseq approach in CC lines and hepatic gene expression.Methods:We studied 31 male mice from 25 CC lines at 8 weeks old;the mice were infected with Af.Liver tissues were extracted from these mice 5 days post-infection,and next-generation RNA-sequencing(RNAseq)was performed.The GENE-E analysis platform was used to generate a clustered heat map matrix.Results:Significant variation in body weight changes between CC lines was ob-served.Hepatic gene expression revealed 12 top prioritized candidate genes differ-entially expressed in resistant versus susceptible mice based on body weight changes.Interestingly,three candidate genes are located within genomic intervals of the previ-ously mapped quantitative trait loci(QTL),including Gm16270 and Stox1 on chromo-some 10 and Gm11033 on chromosome 8.Conclusions:Our findings emphasize the CC mouse model's power in fine mapping the genetic components underlying susceptibility towards Af.As a next step,eQTL analysis will be performed for our RNA-Seq data.Suggested candidate genes from our study will be further assessed with a human cohort with aspergillosis.

Genome-wide identification and expression profiling of photosystem II(PsbX)gene family in upland cotton(Gossypium hirsutum L.)

Background Photosystem II(PSII)constitutes an intricate assembly of protein pigments,featuring extrinsic and intrinsic polypeptides within the photosynthetic membrane.The low-molecular-weight transmembrane protein PsbX has been identified in PSII,which is associated with the oxygen-evolving complex.The expression of PsbX gene protein is regulated by light.PsbX’s central role involves the regulation of PSII,facilitating the binding of quinone molecules to the Qb(PsbA)site,and it additionally plays a crucial role in optimizing the efficiency of photosynthesis.Despite these insights,a comprehensive understanding of the PsbX gene’s functions has remained elusive.Results In this study,we identified ten PsbX genes in Gossypium hirsutum L.The phylogenetic analysis results showed that 40 genes from nine species were classified into one clade.The resulting sequence logos exhibited substantial conservation across the N and C terminals at multiple sites among all Gossypium species.Furthermore,the ortholo-gous/paralogous,Ka/Ks ratio revealed that cotton PsbX genes subjected to positive as well as purifying selection pressure might lead to limited divergence,which resulted in the whole genome and segmental duplication.The expression patterns of GhPsbX genes exhibited variations across specific tissues,as indicated by the analysis.Moreover,the expression of GhPsbX genes could potentially be regulated in response to salt,intense light,and drought stresses.Therefore,GhPsbX genes may play a significant role in the modulation of photosynthesis under adverse abiotic conditions.Conclusion We examined the structure and function of PsbX gene family very first by using comparative genom-ics and systems biology approaches in cotton.It seems that PsbX gene family plays a vital role during the growth and development of cotton under stress conditions.Collectively,the results of this study provide basic information to unveil the molecular and physiological function of PsbX genes of cotton plants.

Identification and validation of a new prognostic signature based on cancer-associated fibroblast-driven genes in breast cancer

BACKGROUND Breast cancer(BC),a leading malignant disease,affects women all over the world.Cancer associated fibroblasts(CAFs)stimulate epithelial-mesenchymal transition,and induce chemoresistance and immunosuppression.AIM To establish a CAFs-associated prognostic signature to improve BC patient out-come estimation.METHODS We retrieved the transcript profile and clinical data of 1072 BC samples from The Cancer Genome Atlas(TCGA)databases,and 3661 BC samples from the The Gene Expression Omnibus.CAFs and immune cell infiltrations were quantified using CIBERSORT algorithm.CAF-associated gene identification was done by weighted gene co-expression network analysis.A CAF risk signature was established via univariate,least absolute shrinkage and selection operator regression,and mul-tivariate Cox regression analyses.The receiver operating characteristic(ROC)and Kaplan-Meier curves were employed to evaluate the predictability of the model.Subsequently,a nomogram was developed with the risk score and patient clinical signature.Using Spearman's correlations analysis,the relationship between CAF risk score and gene set enrichment scores were examined.Patient samples were collected to validate gene expression by quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS Employing an 8-gene(IL18,MYD88,GLIPR1,TNN,BHLHE41,DNAJB5,FKBP14,and XG)signature,we attemp-ted to estimate BC patient prognosis.Based on our analysis,high-risk patients exhibited worse outcomes than low-risk patients.Multivariate analysis revealed the risk score as an independent indicator of BC patient prognosis.ROC analysis exhibited satisfactory nomogram predictability.The area under the curve showed 0.805 at 3 years,and 0.801 at 5 years in the TCGA cohort.We also demonstrated that a reduced CAF risk score was strongly associated with enhanced chemotherapeutic outcomes.CAF risk score was significantly correlated with most hallmark gene sets.Finally,the prognostic signature were further validated by qRT-PCR.CONCLUSION We introduced a newly-discovered CAFs-associated gene signature,which can be employed to estimate BC patient outcomes conveniently and accurately.

Transcriptome analysis reveals immune-related genes in tissues of Vibrio anguillarum-infected turbot Scophthalmus maximus

Turbot Scophthalmus maximus is an important mariculture fish species with high economic value.However,the bacterial diseases caused by Vibrio anguillarum infection bring huge economic losses to the turbot aquaculture industry.To understand the immune response of the turbot against V.anguillarum infection and to explore novel immune-related genes,the transcriptome analysis of turbot spleen and gills were conducted after V.anguillarum infection.Differentially expressed genes(DEGs)were identified in spleen and gill of the turbot amounted to 17261 and 16436,respectively.A large number of immunerelated DEGs were enriched in cytokine-cytokine receptor interaction signaling pathway,and the others by the kyoto encyclopedia of genes and genomes(KEGG)enrichment.The gene ontology(GO)classification analysis revealed that V.anguillarum infection had the greatest effect on biological processes and cellular components.Twelve immune-related DEGs were identified in the spleen(cstl.1,egfl6,lamb21,v2rx4,calcr,and gpr78a)and gills(ghra,sh3gl2a,cst12,inhbaa,cxcl8,and il-1b)by heat map.The proteinprotein interaction(PPI)networks were constructed to analyze the immune mechanism.The results demonstrate that the maturation and antigen processing of major histocompatibility complex(MHC)class II molecule,and calcitonin-or adrenomedullin-regulated physiological activity were important events in the immunity of turbot against V.anguillarum infection.In the gills,the protein interactions in TGF-βsignaling pathway,production of inflammatory factors,and endocytosis regulation were most significant.Our research laid a foundation for discovering novel immune-related genes and enriching the knowledge of immune mechanisms of turbot against V.anguillarum infection.

A Novel Deep Learning-Based Model for Classification of Wheat Gene Expression

Deep learning(DL)plays a critical role in processing and converting data into knowledge and decisions.DL technologies have been applied in a variety of applications,including image,video,and genome sequence analysis.In deep learning the most widely utilized architecture is Convolutional Neural Networks(CNN)are taught discriminatory traits in a supervised environment.In comparison to other classic neural networks,CNN makes use of a limited number of artificial neurons,therefore it is ideal for the recognition and processing of wheat gene sequences.Wheat is an essential crop of cereals for people around the world.Wheat Genotypes identification has an impact on the possible development of many countries in the agricultural sector.In quantitative genetics prediction of genetic values is a central issue.Wheat is an allohexaploid(AABBDD)with three distinct genomes.The sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat,Therefore,genome sequence approaches based on techniques of Artificial Intelligence(AI)are necessary.This paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources and managing genetic variation in their breeding program,as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current constraints.In this paper,the hyperparameters of the network are optimized in the CNN to decrease the requirement for manual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks(CNN).

Effect of Chuanzhifang component (ZGC) on macrophage inflammatory injury based on whole gene expression profile

Objective: The effect of Chuanzhi Fang (ZGC) on the whole genome expression profile of RAW264.7 cells activated by lipopolysaccharide (LPS) was analyzed, and to explore the possible mechanism of action and core target of this formula on macrophage inflammatory injury at the overall level. Methods: A model of LPS-induced inflammation in RAW264.7 cells was constructed, and the effect of ZGC intervention on the genome-wide expression of inflammatory macrophages 3was examined by gene microarray technology, GO/KEGG enrichment analysis was performed for significantly differentially expressed genes among each group. Results: The results of genome-wide expression profiling microarray analysis showed that the ZGC intervention group upregulated the expression of 5 genes including C4bp and inhibited the expression of 22 genes including Mgat3, Psma6, and Siglecg relative to the LPS model group. KEGG signaling pathway analysis results showed that ZGC mainly acted through cytokine receptor interaction and the C-type lectin receptor signaling pathway. Conclusion: ZGC can interfere with the abnormal expression of 27 genes in inflammatory macrophages, and the related genes may exert corresponding anti-inflammatory effects by affecting cytokine receptor interactions, C-type lectin receptor signaling pathway, and TLR4/ NF-κB signaling pathway.

Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND Gastric cancer(GC)has a high mortality rate worldwide.Despite significant progress in GC diagnosis and treatment,the prognosis for affected patients still remains unfavorable.AIM To identify important candidate genes related to the development of GC and iden-tify potential pathogenic mechanisms through comprehensive bioinformatics analysis.METHODS The Gene Expression Omnibus database was used to obtain the GSE183136 dataset,which includes a total of 135 GC samples.The limma package in R software was employed to identify differentially expressed genes(DEGs).Thereafter,enrichment analyses of Gene Ontology(GO)terms and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways were performed for the gene modules using the clusterProfile package in R software.The protein-protein interaction(PPI)networks of target genes were constructed using STRING and visualized by Cytoscape software.The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram.The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves.Moreover,real-time quantitative polymerase chain reaction(RT-qPCR)and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase(GPT)in GC and normal immortalized cell lines.In addition,cell viability,cell cycle distribution,migration and invasion were evaluated by cell counting kit-8,flow cytometry and transwell assays.Furthermore,we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital,Dingli Clinical College of Wenzhou Medical University,The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020.The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients.RESULTS We selected 19214 genes from the GSE183136 dataset,among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value<0.05.In addition,GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction,whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion,vascular smooth muscle contraction and biosynthesis of the different cofactors.Furthermore,PPI networks were constructed based on the various upregulated and downregulated genes,and there were a total 15 upregulated and 10 downregulated hub genes.After a comprehensive analysis,several hub genes,including runt-related transcription factor 2(RUNX2),salmonella pathogenicity island 1(SPI1),lysyl oxidase(LOX),fibrillin 1(FBN1)and GPT,displayed prognostic values.Interestingly,it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells.Furthermore,the expression level of GPT was found to be associated with age,lymph node metastasis,pathological staging and distant metastasis(P<0.05).CONCLUSION RUNX2,SPI1,LOX,FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis.GPT was significantly associated with the prognosis of GC,and its upregulation can effectively inhibit the proliferative,migrative and invasive capabilities of GC cells.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer

BACKGROUND A growing number of clinical examples suggest that coronavirus disease 2019(COVID-19)appears to have an impact on the treatment of patients with liver cancer compared to the normal population,and the prevalence of COVID-19 is significantly higher in patients with liver cancer.However,this mechanism of action has not been clarified.Gene sets for COVID-19(GSE180226)and liver cancer(GSE87630)were obtained from the Gene Expression Omnibus database.After identifying the common differentially expressed genes(DEGs)of COVID-19 and liver cancer,functional enrichment analysis,protein-protein interaction network construction and scree-ning and analysis of hub genes were performed.Subsequently,the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed.RESULTS Of 518 common DEGs were obtained by screening for functional analysis.Fifteen hub genes including aurora kinase B,cyclin B2,cell division cycle 20,cell division cycle associated 8,nucleolar and spindle associated protein 1,etc.,were further identified from DEGs using the“cytoHubba”plugin.Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation,cell cycle and other functions,and they may serve as potential molecular markers for COVID-19 and liver cancer.Finally,we selected 10 of the hub genes for in vitro expression validation in liver cancer cells.CONCLUSION Our study reveals a common pathogenesis of liver cancer and COVID-19.These common pathways and key genes may provide new ideas for further mechanistic studies.

Decoding Retinoblastoma: Differential Gene Expression

Background: Retinoblastoma, the most common intraocular pediatric cancer, presents complexities in its genetic landscape that necessitate a deeper understanding for improved therapeutic interventions. This study leverages computational tools to dissect the differential gene expression profiles in retinoblastoma. Methods: Employing an in silico approach, we analyzed gene expression data from public repositories by applying rigorous statistical models, including limma and de seq 2, for identifying differentially expressed genes DEGs. Our findings were validated through cross-referencing with independent datasets and existing literature. We further employed functional annotation and pathway analysis to elucidate the biological significance of these DEGs. Results: Our computational analysis confirmed the dysregulation of key retinoblastoma-associated genes. In comparison to normal retinal tissue, RB1 exhibited a 2.5-fold increase in expression (adjusted p Conclusions: Our analysis reinforces the critical genetic alterations known in retinoblastoma and unveils new avenues for research into the disease’s molecular basis. The discovery of chemoresistance markers and immune-related genes opens potential pathways for personalized treatment strategies. The study’s outcomes emphasize the power of in silico analyses in unraveling complex cancer genomics.

Gene signatures to therapeutics:Assessing the potential of ivermectin against t(4;14)multiple myeloma

BACKGROUND Multiple myeloma(MM)is a terminal differentiated B-cell tumor disease characterized by clonal proliferation of malignant plasma cells and excessive levels of monoclonal immunoglobulins in the bone marrow.The translocation,(t)(4;14),results in high-risk MM with limited treatment alternatives.Thus,there is an urgent need for identification and validation of potential treatments for this MM subtype.Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets.AIM To elucidate the molecular basis and search for potential effective drugs of t(4;14)MM subtype by employing a comprehensive approach.METHODS The transcriptional signature of t(4;14)MM was sourced from the Gene Expression Omnibus.Two datasets,GSE16558 and GSE116294,which included 17 and 15 t(4;14)MM bone marrow samples,and five and four normal bone marrow samples,respectively.After the differentially expressed genes were identified,the Cytohubba tool was used to screen for hub genes.Then,the hub genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis.Using the STRING database and Cytoscape,protein–protein interaction networks and core targets were identified.Potential small-molecule drugs were identified and validated using the Connectivity Map database and molecular docking analysis,respectively.RESULTS In this study,a total of 258 differentially expressed genes with enriched functions in cancer pathways,namely cytokine receptor interactions,nuclear factor(NF)-κB signaling pathway,lipid metabolism,atherosclerosis,and Hippo signaling pathway,were identified.Ten hub genes(cd45,vcam1,ccl3,cd56,app,cd48,btk,ccr2,cybb,and cxcl12)were identified.Nine drugs,including ivermectin,deforolimus,and isoliquiritigenin,were predicted by the Connectivity Map database to have potential therapeutic effects on t(4;14)MM.In molecular docking,ivermectin showed strong binding affinity to all 10 identified targets,especially cd45 and cybb.Ivermectin inhibited t(4;14)MM cell growth via the NF-κB pathway and induced MM cell apoptosis in vitro.Furthermore,ivermectin increased reactive oxygen species accumulation and altered the mitochondrial membrane potential in t(4;14)MM cells.CONCLUSION Collectively,the findings offer valuable molecular insights for biomarker validation and potential drug development in t(4;14)MM diagnosis and treatment,with ivermectin emerging as a potential therapeutic alternative.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway

BACKGROUND The ubiquitin-proteasome pathway(UPP)has been proven to play important roles in cancer.AIM To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes.METHODS In this study,UPP-related E1,E2,E3,deubiquitylating enzyme,and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG)database,aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based RESULTS Five genes(including autophagy related 10,proteasome 20S subunit alpha 8,proteasome 20S subunit beta 2,ubiquitin specific peptidase 17 like family member 2,and ubiquitin specific peptidase 8)were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer.Among training,validation,and Gene Expression Omnibus sets,the overall survival differed significantly between the high-risk and low-risk groups.The expression of the five genes was significantly associated with immunocyte infiltration,tumor stage,and postoperative recurrence.A total of 111 differentially expressed genes(DEGs)were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways.Cell division cycle 20,Kelch repeat and BTB domain containing 11,and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival.CONCLUSION We have constructed a prognosis predictive model in patients with liver cancer,which contains five genes that associate with immunocyte infiltration,tumor stage,and postoperative recurrence.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer

BACKGROUND Treatment options for patients with gastric cancer(GC)continue to improve,but the overall prognosis is poor.The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present,and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups.AIM To determined the effects of differentially expressed immune-related genes(DEIRGs)on the development,prognosis,tumor microenvironment(TME),and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations.METHODS Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas(TCGA),and immune-related genes(IRGs)were searched from ImmPort.DEIRGs were extracted from the intersection of the differentially-expressed genes(DEGs)and IRGs lists.The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes(KEGGs)and Gene Ontology(GO)databases.To identify genes associated with prognosis,a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression.The tumor risk score was divided into high-and lowrisk groups.The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model.The infiltration of immune cells was obtained using‘CIBERSORT,’and the infiltration of immune subgroups in high-and low-risk groups was analyzed.The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed.RESULTS We collected 412 GC and 36 adjacent tissue samples,and identified 3627 DEGs and 1311 IRGs.A total of 482 DEIRGs were obtained.GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes,receptor ligand activity,and signaling receptor activators.KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors,neuroactive ligand receptor interactions,and viral protein interactions.We ultimately obtained an immune-related signature based on 10 genes,including 9 risk genes(LCN1,LEAP2,TMSB15A mRNA,DEFB126,PI15,IGHD3-16,IGLV3-22,CGB5,and GLP2R)and 1 protective gene(LGR6).Kaplan-Meier survival analysis,receiver operating characteristic curve analysis,and risk curves confirmed that the risk model had good predictive ability.Multivariate COX analysis showed that age,stage,and risk score were independent prognostic factors for patients with GC.Meanwhile,patients in the low-risk group had higher tumor mutation burden and immunophenotype,which can be used to predict the immune checkpoint inhibitor response.Both cytotoxic T lymphocyte antigen4+and programmed death 1+patients with lower risk scores were more sensitive to immunotherapy.CONCLUSION In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME.By providing risk factor analysis and prognostic information,our risk model can provide new directions for immunotherapy in GC patients.

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.

The Influence of Aerial Exposure on Sea Anemones Aulactinia veratra Mucin Genes Expression Using the RNA Sequencing

Mucin genes are the main component of mucus. The sea anemone species, Aulactinia veratra (Phylum Cnidaria) contains different types of mucin genes. In the intertidal zone, A. veratra is found to be exposed to air during the low tide and produces large quantities of mucus as an external covering. The relation between low tide and mucus secretion is still unclear, and what is the role of mucin during arial exposure is not yet investigated. This study hypothesised that the mucin genes in A. veratra would have significantly high expression in response to aerial exposure. Therefore, the aim of current study was to examine and analyses the response of A. veratra mucins in response to an experiment involving three hours of aerial exposure. To achieve this, aim the RNA-sequencing and bioinformatics analyses were used to examine the expression profile of A. veratra mucin genes in response to aerial exposure. The generated results have shown that, Mucin4-like and mucin5B-like were up-regulated in response to the three hours of aerial exposure in A. veratra. This finding shows a significant role of mucin5B-like and mucin4-like genes in response to air stress at low tide. The data generated from this study could be used in conjunction with future mucin gene studies of sea anemones and other cnidarians to compare A. veratra mucin gene expression results across time, and to extend our understanding of mucin stress response in this phylum.

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Background: Hypertension, also known as increased blood pressure, is a phenomenon in which blood flows in blood vessels and causes persistently higher-than-normal pressure on the vessel wall. The identification of novel prognostic and pathogenesis biomarkers plays a key role in the management of hypertension. Methods: The GSE7483 and GSE75815 datasets from the gene expression omnibus (GEO) database were used to identify the genes associated with hypertension that were differentially expressed genes (DEGs). The functional role of the DEGs was elucidated by gene body (GO) enrichment analysis. In addition, we performed an immune infiltration assay and GSEA on the DEGs of hypertensive patients and verified the expression of novel DEGs in the blood of hypertensive patients by RT-qPCR. Results: A total of 267 DEGs were identified from the GEO database. GO analysis revealed that these genes were associated mainly with biological processes such as fibroblast proliferation, cell structural organization, extracellular matrix organization, vasculature development regulation, and angiogenesis. We identified five possible biomarkers, Ecm1, Sparc, Sphk1, Thbsl, and Mecp2, which correlate with vascular development and angiogenesis characteristic of hypertension by bioinformatics, and explored the clinical expression levels of these genes by RT-qPCR, and found that Sparc, Sphk1, and Thbs1 showed significant up-regulation, in agreement with the results of the bioinformatics analysis. Conclusion: Our study suggested that Sparc, Sphk1 and Thbs1 may be potential novel biomarkers for the diagnosis, treatment and prognosis of hypertension and that they are involved in the regulation of vascular development and angiogenesis in hypertension.

Rapid Prototype Development Approach for Genetic Programming

Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.