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 s...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).展开更多
Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair perip...Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.展开更多
Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughp...Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.展开更多
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t...Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.展开更多
Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different c...Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different classes of cardiomyopathies remain elusive.This paper aims to describe the similarities and differences in molecular features of dilated cardiomyopathy(DCM)and ischemic cardiomyopathy(ICM).We firstly detected the co-expressed modules using the weighted gene co-expression network analysis(WGCNA).Significant modules associated with DCM/ICM were identified by the Pearson correlation coefficient(PCC)between the modules and the phenotype of DCM/ICM.The differentially expressed genes in the modules were selected to perform functional enrichment.The potential transcription factors(TFs)prediction was conducted for transcription regulation of hub genes.Apoptosis and cardiac conduction were perturbed in DCM and ICM,respectively.TFs demonstrated that the biomarkers and the transcription regulations in DCM and ICM were different,which helps make more accurate discrimination between them at molecular levels.In conclusion,comprehensive analyses of the molecular features may advance our understanding of DCM and ICM causes and progression.Thus,this understanding may promote the development of innovative diagnoses and treatments.展开更多
Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in ...Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.展开更多
BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic tre...BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic treatment.Psoriasis is also associated with many diseases,such as cardiometabolic diseases,malignant tumors,infections,and mood disorders.Psoriasis can appear at any age,and lead to a substantial burden for individuals and society.At present,psoriasis is still a treatable,but incurable,disease.Previous studies have found that micro RNAs(mi RNAs)play an important regulatory role in the progression of various diseases.Currently,mi RNAs studies in psoriasis and dermatology are relatively new.Therefore,the identification of key mi RNAs in psoriasis is helpful to elucidate the molecular mechanism of psoriasis.AIM To identify key molecular markers and signaling pathways to provide potential basis for the treatment and management of psoriasis.METHODS The mi RNA and m RNA data were obtained from the Gene Expression Omnibus database.Then,differentially expressed m RNAs(DEm RNAs)and differentially expressed mi RNAs(DEmi RNAs)were screened out by limma R package.Subsequently,DEm RNAs were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomics functional enrichment.The“WGCNA”R package was used to analyze the co-expression network of all mi RNAs.In addition,we constructed mi RNA-m RNA regulatory networks based on identified hub mi RNAs.Finally,in vitro validation was performed.All experimental procedures were approved by the ethics committee of Chinese PLA General Hospital(S2021-012-01).RESULTS A total of 639 DEm RNAs and 84 DEmi RNAs were identified.DEm RNAs screening criteria were adjusted P(adj.P)value<0.01 and|log Fold Change|(|log FC|)>1.DEmi RNAs screening criteria were adj.P value<0.01 and|logFC|>1.5.KEGG functional analysis demonstrated that DEm RNAs were significantly enriched in immune-related biological functions,for example,tolllike receptor signaling pathway,cytokine-cytokine receptor interaction,and chemokine signaling pathway.In weighted gene co-expression network analysis,turquoise module was the hub module.Moreover,10 hub mi RNAs were identified.Among these 10 hub mi RNAs,only 8 hub mi RNAs predicted the corresponding target m RNAs.97 negatively regulated mi RNA-m RNA pairs were involved in the mi RNA-m RNA regulatory network,for example,hsa-mi R-21-5 pclaudin 8(CLDN8),hsa-mi R-30 a-3 p-interleukin-1 B(IL-1 B),and hsa-mi R-181 a-5 p/hsa-mi R-30 c-2-3 p-C-X-C motif chemokine ligand 9(CXCL9).Real-time polymerase chain reaction results showed that IL-1 B and CXCL9 were up-regulated and CLDN8 was down-regulated in psoriasis with statistically significant differences.CONCLUSION The identification of potential key molecular markers and signaling pathways provides potential research directions for further understanding the molecular mechanisms of psoriasis.This may also provide new research ideas for the prevention and treatment of psoriasis in the future.展开更多
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.展开更多
Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four...Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment;module purple positively correlates with tumor location (sclera) and negatively correlates with patient age;展开更多
Artificial gynogenesis is of great research value in fish genetics and breeding technology. However, existing studies did not explain the mechanism of some interesting phenomena. Severe developmental defects in gynoge...Artificial gynogenesis is of great research value in fish genetics and breeding technology. However, existing studies did not explain the mechanism of some interesting phenomena. Severe developmental defects in gynogenetic haploids can lead to death during hatching. After diploidization of chromosomes, gynogenetic diploids may dispense from the remarkable malformation and restore the viability, although the development time is longer and the survival rate is lower compared with normal diploids. The aim of this study was to reveal key mechanism in haploid syndrome of Japanese flounder, a commercially important marine teleost in East Asia. We measured genome-scale gene expression of flounder haploid, gynogenetic diploid and normal diploid embryos using RNA-Seq, constructed a module-centric co-expression network based on weighted correlation network analysis(WGCNA) and analyzed the biological functions of correlated modules. Module gene content analysis revealed that the formation of gynogenetic haploids was closely related to the abnormality of plasma proteins, and the up-regulation of p53 signaling pathway might rescue gynogenetic embryos from haploid syndrome via regulating cell cycle arrest, apoptosis and DNA repair. Moreover, normal diploid has more robust nervous system. This work provides novel insights into molecular mechanisms in haploid syndrome and the rescue process by gynogenetic diploidization.展开更多
AIM TO detect significant clusters of co-expressed genes associated with tumorigenesis that might help to predict stomach adenocarcinoma （SA） prognosis.METHODS The Cancer Genome Atlas database was used to obtain RNA...AIM TO detect significant clusters of co-expressed genes associated with tumorigenesis that might help to predict stomach adenocarcinoma （SA） prognosis.METHODS The Cancer Genome Atlas database was used to obtain RNA sequences as well as complete clinical data of SA and adjacent normal tissues from patients. Weighted gene co-expression network analysis （WGCNA） was used to investigate the meaningful module along with hub genes. Expression of hub genes was analyzed in 362 paraffin-embedded SA biopsy tissues by immunohistochemical staining. Patients were classified into two groups （according to expression of hub genes）： Weak expression and over-expression groups. Correlation of biomarkers with clinicopathological factors indicated patient survival.RESULTS Whole genome expression level screening identified 6,231 differentially expressed genes. Twenty-four co- expressed gene modules were identified using WGCNA. Pearson＇s correlation analysis showed that the tan module was the most relevant to tumor stage （r = 0.24, P = 7 × 10 -6）. In addition, we detected sorting nexin （SNX）10 as the hub gene of the tan module. SNX10 expression was linked to T category （P = 0.042, x2= 8.708）, N category （P = 0.000, x2= 18.778）, TNM stage （P = 0.001, x2 = 16.744） as well as tumor differentiation （P = 0.000,x2= 251.930）. Patients with high SNX10 expression tended to have longer diseasefree survival （DFS; 44.97 mo vs 33.85 mo, P = 0.000） as well as overall survival （OS; 49.95 vs 40.84 mo, P = 0.000） in univariate analysis. Multivariate analysis showed that dismal prognosis could be precisely predicted clinicopathologically using SNX10 [DFS： P = 0.014, hazard ratio （HR） = 0.698, 95% confidence interval （CI）： 0.524-0.930, OS： P = 0.017, HR = 0.704, 95%CI： 0.528-0.940].CONCLUSION This study provides a new technique for screening prognostic biomarkers of SA. Weak expression of SNX10 is linked to poor prognosis, and is a suitable prognostic biomarker of SA.展开更多
Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomark...Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC.Here,we identified 2397 common difTerentially expressed genes(DEGs)using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas(TCGA).Then,we performed weighted gene co-expression network analysis and protein-protein interaction network analysis,17 candidate hub genes were identified.These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified.All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC.Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome.ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples,and between early stage and advanced stage ccRCC.Moreover,all the hub genes were positively associated with distant metastasis,lymph node infiltration,tumor recurrence and the expression of MKi67,suggesting these genes might promote tumor proliferation,invasion and metastasis.Furthermore,the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function.In summary,our study identified 14 potential biomarkers for predicting tumorigenesis and progression,which might contribute to early diagnosis,prognosis prediction and therapeutic intervention.展开更多
Objective: To identify module genes that are closely related to clinical features of hepatocellular carcinoma (HCC) by weighted gene co‑expression network analysis, and to provide a reference for early clinical diagno...Objective: To identify module genes that are closely related to clinical features of hepatocellular carcinoma (HCC) by weighted gene co‑expression network analysis, and to provide a reference for early clinical diagnosis and treatment. Methods: GSE84598 chip data were downloaded from the GEO database, and module genes closely related to the clinical features of HCC were extracted by comprehensive weighted gene co‑expression network analysis. Hub genes were identified through protein interaction network analysis by the maximum clique centrality (MCC) algorithm;Finally, the expression of hub genes was validated by TCGA database and the Kaplan Meier plotter online database was used to evaluate the prognostic relationship between hub genes and HCC patients. Results: By comparing the gene expression data between HCC tissue samples and normal liver tissue samples, a total of 6 262 differentially expressed genes were obtained, of which 2 207 were upregulated and 4 055 were downregulated. Weighted gene co‑expression network analysis was applied to identify 120 genes of key modules. By intersecting with the differentially expressed genes, 115 candidate hub genes were obtained. The results of enrichment analysis showed that the candidate hub genes were closely related to cell mitosis, p53 signaling pathway and so on. Further application of the MCC algorithm to the protein interaction network of 115 candidate hub genes identified five hub genes, namely NUF2, RRM2, UBE2C, CDC20 and MAD2L1. Validation of hub genes by TCGA database revealed that all five hub genes were significantly upregulated in HCC tissues compared to normal liver tissues;Moreover, survival analysis revealed that high expression of hub genes was closely associated with poor prognosis in HCC patients. Conclusions: This study identifies five hub genes by combining multiple databases, which may provide directions for the clinical diagnosis and treatment of HCC.展开更多
Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the G...Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the Gene Expression Omnibus database.The biological processes and pathways related to MDD were investigated using the GO and KEGG pathway tools.Weighted gene coexpression network analysis was conducted to identify modules related to MDD.The hub genes associated with MDD were obtained via protein-protein interaction analysis.Finally,the expression of hub genes in the hippocampal tissues of depression-like rats was detected by reverse transcription-polymerase chain reaction and Western blotting.Results:A total of 658 differentially expressed genes were identified from the Gene Expression Omnibus datasets;thus,these genes and the GSE98793 dataset were used to conduct weighted gene coexpression network analysis.A total of 244 module-related genes were identified and these genes were highly correlated with MDD.These genes were involved in the Ras signaling pathway,regulation of the actin cytoskeleton,and axon guidance according to the KEGG analysis.Hub genes,including MAPK14,SOCS1,TLR2,PTK2B,and GRB2,were obtained via protein-protein interaction analysis.All these hub genes showed better diagnostic efficiency in the GSE52790,GSE39653,and GSE98793 datasets.In vivo experiments revealed that compared with those in control rats,SOCS1 and MAPK14 expression was significantly decreased;while GRB2,TLR2,and PTK2B expression was increased in the hippocampi of depression-like rats.Conclusions:Our study demonstrates that GRB2,TLR2,SOCS1,PTK2B,and MAPK14 are promising hub genes,and targeting these five genes may be an effective treatment strategy for MDD.展开更多
Objective To evaluate the effects of incretin-based therapies on body weight as the primary outcome,as well as on body mass index(BMI)and waist circumference(WC)as secondary outcomes.Methods Databases including Medlin...Objective To evaluate the effects of incretin-based therapies on body weight as the primary outcome,as well as on body mass index(BMI)and waist circumference(WC)as secondary outcomes.Methods Databases including Medline,Embase,the Cochrane Library,and clinicaltrials.gov(www.clinicaltrials.gov)were searched for randomized controlled trials(RCTs).Standard pairwise meta-analysis and network meta-analysis(NMA)were both carried out.The risk of bias(ROB)tool recommended by the Cochrane handbook was used to assess the quality of studies.Subgroup analysis,sensitivity analysis,meta-regression,and quality evaluation based on the Grading of Recommendations Assessment,Development,and Evaluation(GRADE)were also performed.Results A total of 292 trials were included in this study.Compared with placebo,dipeptidyl-peptidase IV inhibitors(DPP-4 Is)increased weight slightly by 0.31 kg[95%confidence interval(CI):0.05,0.58]and had negligible effects on BMI and WC.Compared with placebo,glucagon-like peptide-1 receptor agonists(GLP-1 RAs)lowered weight,BMI,and WC by-1.34 kg(95%CI:-1.60,-1.09),-1.10 kg/m2(95%CI:-1.42,-0.78),and-1.28 cm(95%CI:-1.69,-0.86),respectively.Conclusion GLP-1 RAs were more effective than DPP-4 Is in lowering the three indicators.Overall,the effects of GLP-1 RAs on weight,BMI,and WC were favorable.展开更多
The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis...The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis was performed on the crested tissues of 6 Chinese crested ducks and the scalp tissues of 6 cherry valley ducks(CVs)from 2 developmental stages.This study identified 261 differentially expressed genes(DEGs),122 upregulated and 139 downregulated,in the E28 stage and 361 DEGs,154 upregulated and 207 downregulated in the D42 stage between CC and CV ducks.The subsequent results of weighted gene co-expression network analysis(WGCNA)revealed that the turquoise and cyan modules were associated with the crest trait in the D42 stage,meanwhile,the green,brown,and pink modules were associated with the crest trait in the E28 stage.Venn analysis of the DEGs and WGCNA showed that 145 and 45 genes are associated between the D42 and E28 stages,respectively.The expression of WNT16,BMP2,SLC35F2,SLC6A15,APOBEC2,ABHD6,TNNC2,MYL1,and TNNI2 were verified by real-time quantitative PCR.This study provides an approach to reveal the molecular mechanisms underlying the crested trait development.展开更多
A better understanding of previous accidents is an effective way to reduce the occurrence of similar accidents in the future. In this paper, a complex network approach is adopted to construct a directed weighted hazar...A better understanding of previous accidents is an effective way to reduce the occurrence of similar accidents in the future. In this paper, a complex network approach is adopted to construct a directed weighted hazard network(DWHN) to analyze topological features and evolution of accidents in the subway construction. The nodes are hazards and accidents, the edges are multiple relationships of these nodes and the weight of edges are occurrence times of repetitive relationships. The results indicate that the DWHN possesses the property of small-world with small average path length and large clustering coefficient, indicating that hazards have better connectivity and will spread widely and quickly in the network. Moreover,the DWHN has the property of scale-free network for the cumulative degree distribution follows a power-law distribution.It makes DWHN more vulnerable to target attacks. Controlling key nodes with higher degree, strength and betweenness centrality will destroy the connectivity of DWHN and mitigate the spreading of accidents in the network. This study is helpful for discovering inner relationships and evolutionary features of hazards and accidents in the subway construction.展开更多
BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic...BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic KRAS mutations,resulting in the continuous activation of epidermal growth factor receptor signaling.AIM To investigate the key pathogenic genes in KRAS mutant colon cancer holds considerable importance.METHODS Weighted gene co-expression network analysis,in combination with additional bioinformatics analysis,were conducted to screen the key factors driving the progression of KRAS mutant colon cancer.Meanwhile,various in vitro experiments were also conducted to explore the biological function of transglutaminase 2(TGM2).RESULTS Integrated analysis demonstrated that TGM2 acted as an independent prognostic factor for progression-free survival.Immunohistochemical analysis on tissue microarrays revealed that TGM2 was associated with an elevated probability of perineural invasion in patients with KRAS mutant colon cancer.Additionally,biological roles of the key gene TGM2 was also assessed,suggesting that the downregulation of TGM2 attenuated the proliferation,invasion,and migration of the KRAS mutant colon cancer cell line.CONCLUSION This study underscores the potential significance of TGM2 in the progression of KRAS mutant colon cancer.This insight not only offers a theoretical foundation for therapeutic approaches but also highlights the need for additional clinical trials and fundamental research to support our preliminary findings.展开更多
Objective:The present study was aimed to identify novel key genes,prognostic biomarkers and molecular pathways implicated in tumorigenesis of colon cancer.Methods:The microarray data GSE41328 containing 10 colon cance...Objective:The present study was aimed to identify novel key genes,prognostic biomarkers and molecular pathways implicated in tumorigenesis of colon cancer.Methods:The microarray data GSE41328 containing 10 colon cancer samples and 10 adjacent normal tissues was analyzed to identify 4763 differentially expressed genes.Meanwhile,another microarray data GSE17536 was performed for weighted gene co-expression network analysis(WGCNA).Results:In present study,12 co-expressed gene modules associated with tumor progression were identified for further studies.The red module showed the highest association with pathological stage by Pearson's correlation analysis.Functional enrichment analysis revealed that genes in red module focused on cell division,cell proliferation,cell cycle and metabolic related pathway.Then,a total of 26 key hub genes were identified,and GEPIA database was subsequently selected for validation.Holliday junction-recognizing protein(HJURP)and cell division cycle 25 homolog C(CDC25C)were identified as effective prognosis biomarkers,which were all detrimental to prognosis.Gene set enrichment analyses(GSEA)found the two hub genes were enriched in“oocyte meiosis”,“oocyte maturation that are progesterone-mediated”,“p53 signaling pathway”,and“cell cycle”.Furthermore,the immunohistochemistry and western blotting showed that HJURP was highly expressed in colon cancer tissue.Conclusion:HJURP was identified as a key gene associated with colon cancer progression and prognosis by WGCNA,which might influence the prognosis by regulating cell cycle pathways.展开更多
Introduction:Osteoarthritis(OA)is still an important health problem,and understanding its pathological mechanisms is essential for its diagnosis and treatment.There is evidence that autophagy may play a role in OA pro...Introduction:Osteoarthritis(OA)is still an important health problem,and understanding its pathological mechanisms is essential for its diagnosis and treatment.There is evidence that autophagy may play a role in OA progression,but the exact mechanism remains unclear.Methods:In this study,we adopted a multi-prong approach to systematically identify the key autophagy-related genes(ARGs)associated with OA.Through weighted gene coexpression network analysis,we initially identified significant gene modules associated with OA.Subsequent differential gene analysis performed on normal and OA specimens.Further analysis later using the MCC algorithm highlighted hub ARGs.These genes were then incorporated into the prediction model of OA.In addition,the expression patterns of these DEGs were verified by in vitro experiments.Results:A total of 104 differentially expressed genes(DEGs)were identified by differential gene analysis,of which 102 were up-regulated and 2 were down-regulated.These differentially expressed genes were closely related to key signaling pathways,such as PI3K-Akt signaling pathway,IL-17 signaling pathway and osteoclast differentiation.Further MCC analysis highlighted 10 hub ARGs,among which ATF3,CYCS,FOXO3,KLF6,NFKBIA and SOCS3 were particularly significant,which were then included in the prediction model of OA,which showed robust prediction ability with an area under the curve of 0.783.In vitro experiments confirmed that the expression pattern of these DEGs was consistent with our prediction.Conclusion:In summary,our comprehensive analysis not only provides new insights into the molecular basis of OA,but also suggests potential biomarkers for its diagnosis.展开更多
基金supported by the Notional Natural Science Foundation of China,No.81960417 (to JX)Guangxi Key Research and Development Program,No.GuiKeA B20159027 (to JX)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,No.2022GXNSFBA035545 (to YG)。
文摘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).
基金supported by the National Major Project of Research and Development of China,No.2017YFA0104701(to BY)the National Natural Science Foundation of China,No.32000725(to QQC)+1 种基金the Natural Science Foundation of Jiangsu Province of China,No.BK20200973(to QQC)the Jiangsu Provincial University Innovation Training Key Project of China,No.202010304021Z(to ML)。
文摘Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.
基金Fund supported by the National Natural Science Foundation of China(81460598 and 81660644)the Natural Science Foundation of Jiangsu Province(BK20170267)Guangxi Special Fund for the First-Class Discipline Construction Project(05019038).
文摘Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.
文摘Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.
基金supported by the National Natural Science Foundation of China under Grants No.61720106004 and No.61872405the Key R&D Project of Sichuan Province,China under Grants No.20ZDYF2772 and No.2020YFS0243.
文摘Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different classes of cardiomyopathies remain elusive.This paper aims to describe the similarities and differences in molecular features of dilated cardiomyopathy(DCM)and ischemic cardiomyopathy(ICM).We firstly detected the co-expressed modules using the weighted gene co-expression network analysis(WGCNA).Significant modules associated with DCM/ICM were identified by the Pearson correlation coefficient(PCC)between the modules and the phenotype of DCM/ICM.The differentially expressed genes in the modules were selected to perform functional enrichment.The potential transcription factors(TFs)prediction was conducted for transcription regulation of hub genes.Apoptosis and cardiac conduction were perturbed in DCM and ICM,respectively.TFs demonstrated that the biomarkers and the transcription regulations in DCM and ICM were different,which helps make more accurate discrimination between them at molecular levels.In conclusion,comprehensive analyses of the molecular features may advance our understanding of DCM and ICM causes and progression.Thus,this understanding may promote the development of innovative diagnoses and treatments.
基金financially supported by the Chinese Academy of Agricultural Sciences-Agricultural Science and Technology Innovation Programthe Shenzhen Science and Technology Program (Grant No. JCYJ20200109150650397)
文摘Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.
文摘BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic treatment.Psoriasis is also associated with many diseases,such as cardiometabolic diseases,malignant tumors,infections,and mood disorders.Psoriasis can appear at any age,and lead to a substantial burden for individuals and society.At present,psoriasis is still a treatable,but incurable,disease.Previous studies have found that micro RNAs(mi RNAs)play an important regulatory role in the progression of various diseases.Currently,mi RNAs studies in psoriasis and dermatology are relatively new.Therefore,the identification of key mi RNAs in psoriasis is helpful to elucidate the molecular mechanism of psoriasis.AIM To identify key molecular markers and signaling pathways to provide potential basis for the treatment and management of psoriasis.METHODS The mi RNA and m RNA data were obtained from the Gene Expression Omnibus database.Then,differentially expressed m RNAs(DEm RNAs)and differentially expressed mi RNAs(DEmi RNAs)were screened out by limma R package.Subsequently,DEm RNAs were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomics functional enrichment.The“WGCNA”R package was used to analyze the co-expression network of all mi RNAs.In addition,we constructed mi RNA-m RNA regulatory networks based on identified hub mi RNAs.Finally,in vitro validation was performed.All experimental procedures were approved by the ethics committee of Chinese PLA General Hospital(S2021-012-01).RESULTS A total of 639 DEm RNAs and 84 DEmi RNAs were identified.DEm RNAs screening criteria were adjusted P(adj.P)value<0.01 and|log Fold Change|(|log FC|)>1.DEmi RNAs screening criteria were adj.P value<0.01 and|logFC|>1.5.KEGG functional analysis demonstrated that DEm RNAs were significantly enriched in immune-related biological functions,for example,tolllike receptor signaling pathway,cytokine-cytokine receptor interaction,and chemokine signaling pathway.In weighted gene co-expression network analysis,turquoise module was the hub module.Moreover,10 hub mi RNAs were identified.Among these 10 hub mi RNAs,only 8 hub mi RNAs predicted the corresponding target m RNAs.97 negatively regulated mi RNA-m RNA pairs were involved in the mi RNA-m RNA regulatory network,for example,hsa-mi R-21-5 pclaudin 8(CLDN8),hsa-mi R-30 a-3 p-interleukin-1 B(IL-1 B),and hsa-mi R-181 a-5 p/hsa-mi R-30 c-2-3 p-C-X-C motif chemokine ligand 9(CXCL9).Real-time polymerase chain reaction results showed that IL-1 B and CXCL9 were up-regulated and CLDN8 was down-regulated in psoriasis with statistically significant differences.CONCLUSION The identification of potential key molecular markers and signaling pathways provides potential research directions for further understanding the molecular mechanisms of psoriasis.This may also provide new research ideas for the prevention and treatment of psoriasis in the future.
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
文摘Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment;module purple positively correlates with tumor location (sclera) and negatively correlates with patient age;
基金supported by the Scientific and Technological Innovation Project of Qingdao National Laboratory for Marine Science and Technology (No. 2015A SKJ02)the National Natural Science Foundation of China (No. 31540063)
文摘Artificial gynogenesis is of great research value in fish genetics and breeding technology. However, existing studies did not explain the mechanism of some interesting phenomena. Severe developmental defects in gynogenetic haploids can lead to death during hatching. After diploidization of chromosomes, gynogenetic diploids may dispense from the remarkable malformation and restore the viability, although the development time is longer and the survival rate is lower compared with normal diploids. The aim of this study was to reveal key mechanism in haploid syndrome of Japanese flounder, a commercially important marine teleost in East Asia. We measured genome-scale gene expression of flounder haploid, gynogenetic diploid and normal diploid embryos using RNA-Seq, constructed a module-centric co-expression network based on weighted correlation network analysis(WGCNA) and analyzed the biological functions of correlated modules. Module gene content analysis revealed that the formation of gynogenetic haploids was closely related to the abnormality of plasma proteins, and the up-regulation of p53 signaling pathway might rescue gynogenetic embryos from haploid syndrome via regulating cell cycle arrest, apoptosis and DNA repair. Moreover, normal diploid has more robust nervous system. This work provides novel insights into molecular mechanisms in haploid syndrome and the rescue process by gynogenetic diploidization.
文摘AIM TO detect significant clusters of co-expressed genes associated with tumorigenesis that might help to predict stomach adenocarcinoma （SA） prognosis.METHODS The Cancer Genome Atlas database was used to obtain RNA sequences as well as complete clinical data of SA and adjacent normal tissues from patients. Weighted gene co-expression network analysis （WGCNA） was used to investigate the meaningful module along with hub genes. Expression of hub genes was analyzed in 362 paraffin-embedded SA biopsy tissues by immunohistochemical staining. Patients were classified into two groups （according to expression of hub genes）： Weak expression and over-expression groups. Correlation of biomarkers with clinicopathological factors indicated patient survival.RESULTS Whole genome expression level screening identified 6,231 differentially expressed genes. Twenty-four co- expressed gene modules were identified using WGCNA. Pearson＇s correlation analysis showed that the tan module was the most relevant to tumor stage （r = 0.24, P = 7 × 10 -6）. In addition, we detected sorting nexin （SNX）10 as the hub gene of the tan module. SNX10 expression was linked to T category （P = 0.042, x2= 8.708）, N category （P = 0.000, x2= 18.778）, TNM stage （P = 0.001, x2 = 16.744） as well as tumor differentiation （P = 0.000,x2= 251.930）. Patients with high SNX10 expression tended to have longer diseasefree survival （DFS; 44.97 mo vs 33.85 mo, P = 0.000） as well as overall survival （OS; 49.95 vs 40.84 mo, P = 0.000） in univariate analysis. Multivariate analysis showed that dismal prognosis could be precisely predicted clinicopathologically using SNX10 [DFS： P = 0.014, hazard ratio （HR） = 0.698, 95% confidence interval （CI）： 0.524-0.930, OS： P = 0.017, HR = 0.704, 95%CI： 0.528-0.940].CONCLUSION This study provides a new technique for screening prognostic biomarkers of SA. Weak expression of SNX10 is linked to poor prognosis, and is a suitable prognostic biomarker of SA.
基金This work was supported by grants from the National Natural Science Foundation of China(No.81270354)Natural Science for Youth Foundation(No.81300213).
文摘Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC.Here,we identified 2397 common difTerentially expressed genes(DEGs)using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas(TCGA).Then,we performed weighted gene co-expression network analysis and protein-protein interaction network analysis,17 candidate hub genes were identified.These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified.All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC.Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome.ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples,and between early stage and advanced stage ccRCC.Moreover,all the hub genes were positively associated with distant metastasis,lymph node infiltration,tumor recurrence and the expression of MKi67,suggesting these genes might promote tumor proliferation,invasion and metastasis.Furthermore,the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function.In summary,our study identified 14 potential biomarkers for predicting tumorigenesis and progression,which might contribute to early diagnosis,prognosis prediction and therapeutic intervention.
基金National Natural Science Foundation of China (No.81760851)Guangxi University Youth Promotion Program (No.2019KY0348)。
文摘Objective: To identify module genes that are closely related to clinical features of hepatocellular carcinoma (HCC) by weighted gene co‑expression network analysis, and to provide a reference for early clinical diagnosis and treatment. Methods: GSE84598 chip data were downloaded from the GEO database, and module genes closely related to the clinical features of HCC were extracted by comprehensive weighted gene co‑expression network analysis. Hub genes were identified through protein interaction network analysis by the maximum clique centrality (MCC) algorithm;Finally, the expression of hub genes was validated by TCGA database and the Kaplan Meier plotter online database was used to evaluate the prognostic relationship between hub genes and HCC patients. Results: By comparing the gene expression data between HCC tissue samples and normal liver tissue samples, a total of 6 262 differentially expressed genes were obtained, of which 2 207 were upregulated and 4 055 were downregulated. Weighted gene co‑expression network analysis was applied to identify 120 genes of key modules. By intersecting with the differentially expressed genes, 115 candidate hub genes were obtained. The results of enrichment analysis showed that the candidate hub genes were closely related to cell mitosis, p53 signaling pathway and so on. Further application of the MCC algorithm to the protein interaction network of 115 candidate hub genes identified five hub genes, namely NUF2, RRM2, UBE2C, CDC20 and MAD2L1. Validation of hub genes by TCGA database revealed that all five hub genes were significantly upregulated in HCC tissues compared to normal liver tissues;Moreover, survival analysis revealed that high expression of hub genes was closely associated with poor prognosis in HCC patients. Conclusions: This study identifies five hub genes by combining multiple databases, which may provide directions for the clinical diagnosis and treatment of HCC.
基金supported by the National Natural Science Foundation of China(No.81774281 and No.82474303)the Natural Science Foundation of Hunan Province(2023JJ30888)the leading national joint discipline of Chinese and Western medicines to the Chinese Medicine Department,Xiangya Hospital,CSU.
文摘Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the Gene Expression Omnibus database.The biological processes and pathways related to MDD were investigated using the GO and KEGG pathway tools.Weighted gene coexpression network analysis was conducted to identify modules related to MDD.The hub genes associated with MDD were obtained via protein-protein interaction analysis.Finally,the expression of hub genes in the hippocampal tissues of depression-like rats was detected by reverse transcription-polymerase chain reaction and Western blotting.Results:A total of 658 differentially expressed genes were identified from the Gene Expression Omnibus datasets;thus,these genes and the GSE98793 dataset were used to conduct weighted gene coexpression network analysis.A total of 244 module-related genes were identified and these genes were highly correlated with MDD.These genes were involved in the Ras signaling pathway,regulation of the actin cytoskeleton,and axon guidance according to the KEGG analysis.Hub genes,including MAPK14,SOCS1,TLR2,PTK2B,and GRB2,were obtained via protein-protein interaction analysis.All these hub genes showed better diagnostic efficiency in the GSE52790,GSE39653,and GSE98793 datasets.In vivo experiments revealed that compared with those in control rats,SOCS1 and MAPK14 expression was significantly decreased;while GRB2,TLR2,and PTK2B expression was increased in the hippocampi of depression-like rats.Conclusions:Our study demonstrates that GRB2,TLR2,SOCS1,PTK2B,and MAPK14 are promising hub genes,and targeting these five genes may be an effective treatment strategy for MDD.
基金supported by the National Natural Science Foundation of China[No.81302508,71673003,81473067,and 91646107].
文摘Objective To evaluate the effects of incretin-based therapies on body weight as the primary outcome,as well as on body mass index(BMI)and waist circumference(WC)as secondary outcomes.Methods Databases including Medline,Embase,the Cochrane Library,and clinicaltrials.gov(www.clinicaltrials.gov)were searched for randomized controlled trials(RCTs).Standard pairwise meta-analysis and network meta-analysis(NMA)were both carried out.The risk of bias(ROB)tool recommended by the Cochrane handbook was used to assess the quality of studies.Subgroup analysis,sensitivity analysis,meta-regression,and quality evaluation based on the Grading of Recommendations Assessment,Development,and Evaluation(GRADE)were also performed.Results A total of 292 trials were included in this study.Compared with placebo,dipeptidyl-peptidase IV inhibitors(DPP-4 Is)increased weight slightly by 0.31 kg[95%confidence interval(CI):0.05,0.58]and had negligible effects on BMI and WC.Compared with placebo,glucagon-like peptide-1 receptor agonists(GLP-1 RAs)lowered weight,BMI,and WC by-1.34 kg(95%CI:-1.60,-1.09),-1.10 kg/m2(95%CI:-1.42,-0.78),and-1.28 cm(95%CI:-1.69,-0.86),respectively.Conclusion GLP-1 RAs were more effective than DPP-4 Is in lowering the three indicators.Overall,the effects of GLP-1 RAs on weight,BMI,and WC were favorable.
基金supported by the earmarked fund for CARS,China(CARS-42)the earmarked fund for Jiangsu Agricultural Industry Technology System,China(JATS(2022)331)the Jiangsu Key Research and Development Program,China(BE2021332)。
文摘The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis was performed on the crested tissues of 6 Chinese crested ducks and the scalp tissues of 6 cherry valley ducks(CVs)from 2 developmental stages.This study identified 261 differentially expressed genes(DEGs),122 upregulated and 139 downregulated,in the E28 stage and 361 DEGs,154 upregulated and 207 downregulated in the D42 stage between CC and CV ducks.The subsequent results of weighted gene co-expression network analysis(WGCNA)revealed that the turquoise and cyan modules were associated with the crest trait in the D42 stage,meanwhile,the green,brown,and pink modules were associated with the crest trait in the E28 stage.Venn analysis of the DEGs and WGCNA showed that 145 and 45 genes are associated between the D42 and E28 stages,respectively.The expression of WNT16,BMP2,SLC35F2,SLC6A15,APOBEC2,ABHD6,TNNC2,MYL1,and TNNI2 were verified by real-time quantitative PCR.This study provides an approach to reveal the molecular mechanisms underlying the crested trait development.
基金supported by the Co-Funding of National Natural Science Foundation of China and Shenhua Group Corporation Ltd(Grant No.U1261212)the Program of Major Achievements Transformation and Industrialization of Beijing Education Commission,China(Grant No.ZDZH20141141301)
文摘A better understanding of previous accidents is an effective way to reduce the occurrence of similar accidents in the future. In this paper, a complex network approach is adopted to construct a directed weighted hazard network(DWHN) to analyze topological features and evolution of accidents in the subway construction. The nodes are hazards and accidents, the edges are multiple relationships of these nodes and the weight of edges are occurrence times of repetitive relationships. The results indicate that the DWHN possesses the property of small-world with small average path length and large clustering coefficient, indicating that hazards have better connectivity and will spread widely and quickly in the network. Moreover,the DWHN has the property of scale-free network for the cumulative degree distribution follows a power-law distribution.It makes DWHN more vulnerable to target attacks. Controlling key nodes with higher degree, strength and betweenness centrality will destroy the connectivity of DWHN and mitigate the spreading of accidents in the network. This study is helpful for discovering inner relationships and evolutionary features of hazards and accidents in the subway construction.
基金Supported by National Nature Science Foundation of China,No.82100195China Postdoctoral Science Foundation,No.2021M700777Medical Research Project of Foshan Municipal Health Bureau,No.20230349.
文摘BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic KRAS mutations,resulting in the continuous activation of epidermal growth factor receptor signaling.AIM To investigate the key pathogenic genes in KRAS mutant colon cancer holds considerable importance.METHODS Weighted gene co-expression network analysis,in combination with additional bioinformatics analysis,were conducted to screen the key factors driving the progression of KRAS mutant colon cancer.Meanwhile,various in vitro experiments were also conducted to explore the biological function of transglutaminase 2(TGM2).RESULTS Integrated analysis demonstrated that TGM2 acted as an independent prognostic factor for progression-free survival.Immunohistochemical analysis on tissue microarrays revealed that TGM2 was associated with an elevated probability of perineural invasion in patients with KRAS mutant colon cancer.Additionally,biological roles of the key gene TGM2 was also assessed,suggesting that the downregulation of TGM2 attenuated the proliferation,invasion,and migration of the KRAS mutant colon cancer cell line.CONCLUSION This study underscores the potential significance of TGM2 in the progression of KRAS mutant colon cancer.This insight not only offers a theoretical foundation for therapeutic approaches but also highlights the need for additional clinical trials and fundamental research to support our preliminary findings.
基金supported in part by grants from the National Natural Science Foundation of China(No.81072152 and No.81770283)Natural Science Foundation of Hubei Province(No.2015CFA027)+3 种基金Research Foundation of Health and Family Planning Commission of Hubei Province(No.WJ2015MAO10 and No.WJ2017M249)Clinical Medical Research Center of Peritoneal Cancer of Wuhan(No.2015060911020462)Subsidy Project of No.1 Hospital of Lanzhou University(No.Idyyyn2018-13)Innovation fund of universities in Gansu Province(No.2020B-009).
文摘Objective:The present study was aimed to identify novel key genes,prognostic biomarkers and molecular pathways implicated in tumorigenesis of colon cancer.Methods:The microarray data GSE41328 containing 10 colon cancer samples and 10 adjacent normal tissues was analyzed to identify 4763 differentially expressed genes.Meanwhile,another microarray data GSE17536 was performed for weighted gene co-expression network analysis(WGCNA).Results:In present study,12 co-expressed gene modules associated with tumor progression were identified for further studies.The red module showed the highest association with pathological stage by Pearson's correlation analysis.Functional enrichment analysis revealed that genes in red module focused on cell division,cell proliferation,cell cycle and metabolic related pathway.Then,a total of 26 key hub genes were identified,and GEPIA database was subsequently selected for validation.Holliday junction-recognizing protein(HJURP)and cell division cycle 25 homolog C(CDC25C)were identified as effective prognosis biomarkers,which were all detrimental to prognosis.Gene set enrichment analyses(GSEA)found the two hub genes were enriched in“oocyte meiosis”,“oocyte maturation that are progesterone-mediated”,“p53 signaling pathway”,and“cell cycle”.Furthermore,the immunohistochemistry and western blotting showed that HJURP was highly expressed in colon cancer tissue.Conclusion:HJURP was identified as a key gene associated with colon cancer progression and prognosis by WGCNA,which might influence the prognosis by regulating cell cycle pathways.
文摘Introduction:Osteoarthritis(OA)is still an important health problem,and understanding its pathological mechanisms is essential for its diagnosis and treatment.There is evidence that autophagy may play a role in OA progression,but the exact mechanism remains unclear.Methods:In this study,we adopted a multi-prong approach to systematically identify the key autophagy-related genes(ARGs)associated with OA.Through weighted gene coexpression network analysis,we initially identified significant gene modules associated with OA.Subsequent differential gene analysis performed on normal and OA specimens.Further analysis later using the MCC algorithm highlighted hub ARGs.These genes were then incorporated into the prediction model of OA.In addition,the expression patterns of these DEGs were verified by in vitro experiments.Results:A total of 104 differentially expressed genes(DEGs)were identified by differential gene analysis,of which 102 were up-regulated and 2 were down-regulated.These differentially expressed genes were closely related to key signaling pathways,such as PI3K-Akt signaling pathway,IL-17 signaling pathway and osteoclast differentiation.Further MCC analysis highlighted 10 hub ARGs,among which ATF3,CYCS,FOXO3,KLF6,NFKBIA and SOCS3 were particularly significant,which were then included in the prediction model of OA,which showed robust prediction ability with an area under the curve of 0.783.In vitro experiments confirmed that the expression pattern of these DEGs was consistent with our prediction.Conclusion:In summary,our comprehensive analysis not only provides new insights into the molecular basis of OA,but also suggests potential biomarkers for its diagnosis.
