Hub genes

Hub 基因
  • 文章类型: Journal Article
    喉鳞状细胞癌(LSCC)是头颈部突出的癌症,这极大地影响了患者的生活质量。LSCC的发病机制尚不清楚。目前,LSCC治疗包括化疗,手术和放射治疗;然而,这些方法对复发和持续癌症患者的疗效较差.因此,这项研究确定了伴有LSCC的hub基因,这可能是未来潜在的治疗目标。
    我们从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库中提取了全转录组高通量测序(HTS)LSCC数据,并使用统计软件RStudio计算LSCC和正常样品之间的差异表达基因(DEGs)。通过加权基因共表达网络分析(WGCNA),基因和基因组(KEGG)途径和基因本体论(GO)功能的京都百科全书的富集检查,并检查蛋白质-蛋白质相互作用(PPI)网络,我们获得了网络hub基因,并验证了hub基因的预后价值和蛋白表达水平。
    通过对差异基因表达的分析,从GEO和TCGA数据库获得了2,139和2,774个DEG,分别,通过WGCNA从TCGA-LSCC和GSE127165数据集中筛选了13和15个模块,分别。WGCNA和DEG列表中最显著的正相关和负相关模块重叠,检索到总共36个共表达的重叠基因。通过对GO和KEGG的富集分析,发现基因功能高度集中在细胞连接组装中,基底膜,细胞外基质(ECM)结构成分等。,这些途径主要集中在ECM受体相互作用中,病灶粘连,小细胞肺癌,和弓形虫病.通过对PPI网络分析,10个网络集线器基因(SNAI2,ITGA6,LAMB3,LAMC2,CAV1,COL7A1,GJA1,EHF,OAT,和GPT)获得。最后,这些基因的生存分析和蛋白表达验证证实,低OAT表达和高CAV1表达显著影响LSCC患者的生存预后。
    我们认识到与LSCC几乎相关的hub基因和关键模块,这些基因通过生存分析和人类蛋白质图谱(HPA)数据库进行了验证,这对于揭示LSCC的发病机制和探索新的精确生物学标志物和潜在的治疗靶标非常重要。
    UNASSIGNED: Laryngeal squamous cell carcinoma (LSCC) is the prominent cancer in head and neck, which greatly affects life quality of patients. The pathogenesis of LSCC is not clear. Presently, the LSCC treatments include chemotherapy, surgery and radiotherapy; however, these methods have poor efficacy in patients with recurrent and persistent cancer. Therefore, the study identified the hub genes accompanied with LSCC, which may be a potential therapeutic target in the future.
    UNASSIGNED: We extracted whole transcriptome high-throughput sequencing (HTS) LSCC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and calculate differentially expressed genes (DEGs) between LSCC and normal samples using statistical software RStudio. Through weighted gene co-expression network analysis (WGCNA), enrichment examination of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) functions, and examination of protein-protein interaction (PPI) network, we obtained network hub genes and validated the hub genes prognostic value and expression levels of protein.
    UNASSIGNED: Through analysis of differential gene expression, from the GEO and TCGA databases 2,139 and 2,774 DEGs were obtained, respectively, 13 and 15 modules were screened from TCGA-LSCC and GSE127165 datasets by WGCNA, respectively. The most significant positive and negative correlation modules in the WGCNA and DEG lists were overlapped, and overall 36 co-expressed overlapping genes were retrieved. Through enrichment analysis of GO and KEGG, it was found that the gene functions were highly concentrated in cell junction assembly, basement membrane, extracellular matrix (ECM) structural constituent etc., and the pathways were mainly concentrated in ECM receptor interaction, focal adhesion, small cell lung cancer, and toxoplasmosis. Through analysis of PPI network analysis, 10 network hub genes (SNAI2, ITGA6, LAMB3, LAMC2, CAV1, COL7A1, GJA1, EHF, OAT, and GPT) were obtained. Finally, survival analysis and protein expression validation of these genes confirmed that low OAT expression and high CAV1 expression remarkably influenced the survival of patient\'s prognosis with LSCC.
    UNASSIGNED: We recognized the hub genes and key modules nearly associated to LSCC and these genes were validated by survival analysis and the database of Human Protein Atlas (HPA), which is of high importance for unveiling the pathogenesis of LSCC and probing for new precise biological marker and potential therapeutic targets.
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  • 文章类型: Journal Article
    农业土壤中的砷(As)污染对作物生产力和食品安全构成了严重威胁。氧化锌纳米颗粒(ZnONPs)已成为减轻As胁迫对植物不利影响的潜在改良剂。大豆作物大多生长在边缘化的土地上,并且以根中的As积累比其他组织高而闻名。因此,本研究旨在阐明ZnONPs改善大豆砷毒性的潜在机制。我们的结果表明,ZnOB显着改善了暴露于砷的大豆植物的生长性能。这种改善伴随着As积累的减少(55%)和光合效率的增加。ZnOB还调节荷尔蒙平衡,随着生长素(149%)的显著增加,脱落酸(118%),在As(V)胁迫下,赤霉素(160%)和茉莉酸含量(92%)确保ZnONPs可以通过调节激素信号来增强根的生长和发育。然后,我们进行了转录组学分析,以进一步了解NP诱导的As(V)耐受性的分子机制。该分析确定了响应于ZnONPs补充而差异表达的基因,包括那些涉及生长素的人,脱落酸,赤霉素,和茉莉酸生物合成和信号通路。加权基因共表达网络分析确定了37个编码应激反应者的潜在枢纽基因,运输商,和六个模块中的信号传感器潜在地促进了砷从细胞中的流出,降低其毒性。我们的研究为大豆中与类金属耐受性相关的分子机制提供了有价值的见解,并为改善污染土壤中的As耐受性提供了新的途径。
    Arsenic (As) contamination of agricultural soils poses a serious threat to crop productivity and food safety. Zinc oxide nanoparticles (ZnONPs) have emerged as a potential amendment for mitigating the adverse effects of As stress in plants. Soybean crop is mostly grown on marginalized land and is known for high accumulation of As in roots than others tissue. Therefore, this study aimed to elucidate the underlying mechanisms of ZnONPs in ameliorating arsenic toxicity in soybean. Our results demonstrated that ZnOB significantly improved the growth performance of soybean plants exposed to arsenic. This improvement was accompanied by a decrease (55%) in As accumulation and an increase in photosynthetic efficiency. ZnOB also modulated hormonal balance, with a significant increase in auxin (149%), abscisic acid (118%), gibberellin (160%) and jasmonic acid content (92%) under As(V) stress assuring that ZnONPs may enhance root growth and development by regulating hormonal signaling. We then conducted a transcriptomic analysis to understand further the molecular mechanisms underlying the NPs-induced As(V) tolerance. This analysis identified genes differentially expressed in response to ZnONPs supplementation, including those involved in auxin, abscisic acid, gibberellin, and jasmonic acid biosynthesis and signaling pathways. Weighted gene co-expression network analysis identified 37 potential hub genes encoding stress responders, transporters, and signal transducers across six modules potentially facilitated the efflux of arsenic from cells, reducing its toxicity. Our study provides valuable insights into the molecular mechanisms associated with metalloid tolerance in soybean and offers new avenues for improving As tolerance in contaminated soils.
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  • 文章类型: Journal Article
    基孔肯雅病毒(CHIKV)是一种单链RNA病毒,属于α病毒属,负责引起基孔肯雅热,一种虫媒病毒热。尽管进行了广泛的研究,CHIKV在宿主细胞内的致病机制尚不清楚.在这项研究中,使用计算机模拟方法预测CHIKV产生的微小RNA靶向与宿主细胞调控途径相关的宿主特异性基因.使用miRNAFold和VmirRNA结构网络服务器预测CHIKV的推定微RNA,并使用RNAfold进行二级结构预测。然后预测宿主特异性靶基因,和hub基因使用CytoHubba和模块选择通过MCODE鉴定。hub基因的功能注释揭示了它们与各种途径的关联,包括破骨细胞分化,神经活性配体-受体相互作用,mRNA监测。我们使用免费获得的数据集GSE49985来确定宿主特异性靶基因的表达水平,并发现两个基因,F盒和富含亮氨酸的重复蛋白16(FBXL16)和视黄酸受体α(RARA),被下调,虽然有四个基因,具有富含丝氨酸结构域1(RNPS1)的RNA结合蛋白,RNA解旋酶和ATP酶(UPF1),神经肽S受体1(NPSR1),和血管活性肠肽受体1(VIPR1),被上调。这些发现提供了与CHIKV感染相关的新型miRNA和hub基因的见解,并提出了治疗干预的潜在靶标。这些靶标的进一步实验验证可以导致CHIKV介导的疾病的有效治疗的发展。
    Chikungunya virus (CHIKV) is a single-stranded RNA virus belonging to the genus Alphavirus and is responsible for causing Chikungunya fever, a type of arboviral fever. Despite extensive research, the pathogenic mechanism of CHIKV within host cells remains unclear. In this study, an in-silico approach was used to predict that CHIKV produces micro-RNAs that target host-specific genes associated with host cellular regulatory pathways. Putative micro-RNAs of CHIKV were predicted using the miRNAFold and Vmir RNA structure web servers, and secondary structure prediction was performed using RNAfold. Host-specific target genes were then predicted, and hub genes were identified using CytoHubba and module selection through MCODE. Functional annotations of hub genes revealed their association with various pathways, including osteoclast differentiation, neuroactive ligand-receptor interaction, and mRNA surveillance. We used the freely available dataset GSE49985 to determine the level of expression of host-specific target genes and found that two genes, F-box and leucine-rich repeat protein 16 (FBXL16) and retinoic acid receptor alpha (RARA), were down-regulated, while four genes, RNA binding protein with serine-rich domain 1 (RNPS1), RNA helicase and ATPase (UPF1), neuropeptide S receptor 1 (NPSR1), and vasoactive intestinal peptide receptor 1 (VIPR1), were up-regulated. These findings provide insight into novel miRNAs and hub genes associated with CHIKV infection and suggest potential targets for therapeutic intervention. Further experimental validation of these targets could lead to the development of effective treatments for CHIKV-mediated diseases.
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  • 文章类型: Journal Article
    青光眼是导致永久性失明的主要原因,影响全球8000万人。最近的研究强调了神经炎症在青光眼早期阶段的重要性,涉及免疫和神经胶质细胞。为了进一步调查,我们使用来自GEO(基因表达Omnibus)数据库的GSE27276数据集和来自GeneCards数据库的神经炎症基因来鉴定与原发性开角型青光眼(POAG)相关的差异表达的神经炎症相关基因.随后,这些基因被提交给基因本体论和京都百科全书的基因和基因组的途径富集分析。通过蛋白质-蛋白质相互作用网络挑选出Hub基因,并使用外部数据集(GSE13534和GSE9944)和实时PCR分析进一步验证。基因-miRNA调控网络,接收机工作特性(ROC)曲线,全基因组关联研究(GWAS),并进行区域表达分析以进一步验证hub基因在青光眼中的参与。共鉴定出179个差异表达基因,包括60个上调和119个下调的基因。其中,发现18个差异表达的神经炎症相关基因与神经炎症相关基因重叠,具有六个基因(SERPINA3,LCN2,MMP3,S100A9,IL1RN,和HP)被确定为潜在的集线器基因。这些基因与IL-17信号通路和酪氨酸代谢有关。基因-miRNA调控网络显示,这些hub基因受到118个miRNAs的调控。值得注意的是,GWAS数据分析成功地鉴定了对应于这六个hub基因的显著单核苷酸多态性(SNP)。ROC曲线分析表明,我们的基因在POAG中显示出显著的准确性。这些基因在小胶质细胞中的表达被进一步证实,穆勒细胞,星形胶质细胞,和眼镜数据库中的视网膜神经节细胞。此外,三个枢纽基因,SERPINA3,IL1R1和LCN2被验证为高危青光眼患者的潜在诊断生物标志物。在OGD/R诱导的青光眼模型中显示表达增加。这项研究表明,确定的hub基因可能通过调节神经炎症影响POAG的发育,它可能为POAG的管理提供新的见解。
    Glaucoma is a leading cause of permanent blindness, affecting 80 million people worldwide. Recent studies have emphasized the importance of neuroinflammation in the early stages of glaucoma, involving immune and glial cells. To investigate this further, we used the GSE27276 dataset from the GEO (Gene Expression Omnibus) database and neuroinflammation genes from the GeneCards database to identify differentially expressed neuroinflammation-related genes associated with primary open-angle glaucoma (POAG). Subsequently, these genes were submitted to Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes for pathway enrichment analyses. Hub genes were picked out through protein-protein interaction networks and further validated using the external datasets (GSE13534 and GSE9944) and real-time PCR analysis. The gene-miRNA regulatory network, receiver operating characteristic (ROC) curve, genome-wide association study (GWAS), and regional expression analysis were performed to further validate the involvement of hub genes in glaucoma. A total of 179 differentially expressed genes were identified, comprising 60 upregulated and 119 downregulated genes. Among them, 18 differentially expressed neuroinflammation-related genes were found to overlap between the differentially expressed genes and neuroinflammation-related genes, with six genes (SERPINA3, LCN2, MMP3, S100A9, IL1RN, and HP) identified as potential hub genes. These genes were related to the IL-17 signaling pathway and tyrosine metabolism. The gene-miRNA regulatory network showed that these hub genes were regulated by 118 miRNAs. Notably, GWAS data analysis successfully identified significant single nucleotide polymorphisms (SNPs) corresponding to these six hub genes. ROC curve analysis indicated that our genes showed significant accuracy in POAG. The expression of these genes was further confirmed in microglia, Müller cells, astrocytes, and retinal ganglion cells in the Spectacle database. Moreover, three hub genes, SERPINA3, IL1R1, and LCN2, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the OGD/R-induced glaucoma model. This study suggests that the identified hub genes may influence the development of POAG by regulation of neuroinflammation, and it may offer novel insights into the management of POAG.
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  • 文章类型: Journal Article
    背景:肝细胞癌(HCC)代表原发性肝肿瘤,其特征是预后暗淡和死亡率升高,然而,其精确的分子机制尚未完全阐明。这项研究使用先进的生物信息学技术来辨别与HCC发病机理有关的差异表达基因(DEGs)。主要目标是发现新的生物标志物和潜在的治疗靶标,可以促进HCC研究的发展。
    方法:本研究中的生物信息学分析主要利用基因表达综合(GEO)数据库作为数据源。最初,转录组分析控制台(TAC)筛选DEG。随后,我们利用STRING数据库构建了与已鉴定的DEG相关的蛋白质-蛋白质相互作用(PPI)网络.我们使用Cytoscape获得了hub基因,并通过GEPIA数据库确认了结果。此外,我们使用GEPIA数据库评估了已鉴定的hub基因的预后意义.为了探索调控相互作用,还构建了一个miRNA-基因相互作用网络,合并来自miRDB数据库的信息。为了预测基因过表达对药物作用的影响,我们使用了癌症DP。
    结果:对HCC基因表达谱的综合分析显示,总共有4716个DEGs,与健康对照组相比,HCC样品中的2430个上调基因和2313个下调基因。这些DEGs在PI3K-Akt信号通路等关键通路中表现出显著的富集,核受体meta通路,和各种代谢相关的途径。对PPI网络的进一步探索揭示了P53信号通路和嘧啶代谢是最突出的通路。我们确定了10个hub基因(ASPM,RRM2,CCNB1,KIF14,MKI67,SHCBP1,CENPF,ANLN,HMMR,和EZH2),与健康对照组相比,HCC样本中显示出显着的上调。生存分析表明,这些基因的表达水平升高与HCC患者的总体生存率变化密切相关。最后,我们确定了特定的miRNA,这些miRNA被发现影响这些基因的表达,为HCC进展的潜在调节机制提供有价值的见解。
    结论:这项研究的发现已经成功地确定了与HCC发病机制有关的关键基因和途径。这些新发现有可能在分子水平上显著增强我们对HCC的理解。为开发靶向治疗和改善预后评估开辟了新的途径。
    BACKGROUND: Hepatocellular carcinoma (HCC) represents a primary liver tumor characterized by a bleak prognosis and elevated mortality rates, yet its precise molecular mechanisms have not been fully elucidated. This study uses advanced bioinformatics techniques to discern differentially expressed genes (DEGs) implicated in the pathogenesis of HCC. The primary objective is to discover novel biomarkers and potential therapeutic targets that can contribute to the advancement of HCC research.
    METHODS: The bioinformatics analysis in this study primarily utilized the Gene Expression Omnibus (GEO) database as data source. Initially, the Transcriptome analysis console (TAC) screened for DEGs. Subsequently, we constructed a protein-protein interaction (PPI) network of the proteins associated to the identified DEGs with the STRING database. We obtained our hub genes using Cytoscape and confirmed the results through the GEPIA database. Furthermore, we assessed the prognostic significance of the identified hub genes using the GEPIA database. To explore the regulatory interactions, a miRNA-gene interaction network was also constructed, incorporating information from the miRDB database. For predicting the impact of gene overexpression on drug effects, we utilized CANCER DP.
    RESULTS: A comprehensive analysis of HCC gene expression profiles revealed a total of 4716 DEGs, consisting of 2430 upregulated genes and 2313 downregulated genes in HCC sample compared to healthy control group. These DEGs exhibited significant enrichment in key pathways such as the PI3K-Akt signaling pathway, nuclear receptors meta-pathway, and various metabolism-related pathways. Further exploration of the PPI network unveiled the P53 signaling pathway and pyrimidine metabolism as the most prominent pathways. We identified 10 hub genes (ASPM, RRM2, CCNB1, KIF14, MKI67, SHCBP1, CENPF, ANLN, HMMR, and EZH2) that exhibited significant upregulation in HCC samples compared to healthy control group. Survival analysis indicated that elevated expression levels of these genes were strongly associated with changes in overall survival in HCC patients. Lastly, we identified specific miRNAs that were found to influence the expression of these genes, providing valuable insights into potential regulatory mechanisms underlying HCC progression.
    CONCLUSIONS: The findings of this study have successfully identified pivotal genes and pathways implicated in the pathogenesis of HCC. These novel discoveries have the potential to significantly enhance our understanding of HCC at the molecular level, opening new ways for the development of targeted therapies and improved prognosis evaluation.
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  • 文章类型: Journal Article
    子宫内膜异位症是一种慢性妇科疾病,其特征是子宫内膜组织在子宫外异位生长,导致受影响的女性衰弱的疼痛和不孕。尽管其患病率和临床意义,子宫内膜异位症进展的分子机制仍知之甚少.这项研究采用生物信息学工具和分子对接模拟来解开与子宫内膜异位症进展相关的复杂遗传和分子网络。
    这项研究的主要目的是鉴定与子宫内膜异位症相关的差异表达基因(DEGs)。使用注释数据库阐明相关的生物学途径,可视化,和集成发现(DAVID),构建蛋白质-蛋白质相互作用(PPI)网络来识别集线器基因,并进行分子对接模拟以探索与子宫内膜异位症相关的潜在配体-蛋白质相互作用。
    来自智人的微阵列数据,具体加入:GDS3092系列=GSE5108(平台:GPL2895),从NCBI基因表达综合(GEO)中检索。使用NCBIGEO2对数据进行了严格的预处理和DEG分析。注释数据库,可视化,集成发现分析用于功能注释,使用STITCH数据库和Cytoscape3.8.2构建PPI网络。使用MVD7.0对与子宫内膜异位症相关的靶蛋白进行分子对接模拟。
    从微阵列数据中总共鉴定出1911个与子宫内膜异位症相关的独特元素。注释数据库,可视化,和整合发现分析显示,途径和生物学特征与子宫内膜异位症呈正相关和负相关。Hub基因,包括BCL2,CCNA2,CDK7,EGF,通过PPI网络分析鉴定GAS6、MAP3K7和TAB2。分子对接模拟突出了潜在的配体,例如槲皮素-3-o-吡喃半乳糖苷和苦参醇E,与子宫内膜异位症相关的靶蛋白表现出良好的相互作用。
    这项研究提供了对分子特征的见解,通路,和与子宫内膜异位症相关的hub基因。在这项研究中利用DAVID阐明了与子宫内膜异位症相关的生物学途径,揭示对复杂遗传网络的见解。分子对接模拟确定了配体,用于进一步探索治疗干预措施。这些配体在不同靶标中的一致功效表明广谱有效性,鼓励进一步探索潜在的治疗干预措施。该研究有助于更深入地了解子宫内膜异位症的发病机制,为改善患者预后的靶向治疗和精准医学方法铺平道路。这些发现促进了我们对子宫内膜异位症(EMS)分子机制的理解,为解决这一复杂疾病的未来研究和治疗发展提供了有希望的途径。
    UNASSIGNED: Endometriosis is a chronic gynecological disorder characterized by the ectopic growth of endometrial tissue outside the uterus, leading to debilitating pain and infertility in affected women. Despite its prevalence and clinical significance, the molecular mechanisms underlying the progression of endometriosis remain poorly understood. This study employs bioinformatics tools and molecular docking simulations to unravel the intricate genetic and molecular networks associated with endometriosis progression.
    UNASSIGNED: The primary objectives of this research are to identify differentially expressed genes (DEGs) linked to endometriosis, elucidate associated biological pathways using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), construct a Protein-Protein Interaction (PPI) network to identify hub genes, and perform molecular docking simulations to explore potential ligand-protein interactions associated with endometriosis.
    UNASSIGNED: Microarray data from Homo sapiens, specifically Accession: GDS3092 Series = GSE5108 (Platform: GPL2895), were retrieved from the NCBI Gene Expression Omnibus (GEO). The data underwent rigorous preprocessing and DEG analysis using NCBI GEO2. Database for Annotation, Visualization, and Integrated Discovery analysis was employed for functional annotation, and a PPI network was constructed using the STITCH database and Cytoscape 3.8.2. Molecular docking simulations against target proteins associated with endometriosis were conducted using MVD 7.0.
    UNASSIGNED: A total of 1 911 unique elements were identified as DEGs associated with endometriosis from the microarray data. Database for Annotation, Visualization, and Integrated Discovery analysis revealed pathways and biological characteristics positively and negatively correlated with endometriosis. Hub genes, including BCL2, CCNA2, CDK7, EGF, GAS6, MAP3K7, and TAB2, were identified through PPI network analysis. Molecular docking simulations highlighted potential ligands, such as Quercetin-3-o-galactopyranoside and Kushenol E, exhibiting favorable interactions with target proteins associated with endometriosis.
    UNASSIGNED: This study provides insights into the molecular signatures, pathways, and hub genes associated with endometriosis. Utilizing DAVID in this study clarifies biological pathways associated with endometriosis, revealing insights into intricate genetic networks. Molecular docking simulations identified ligands for further exploration in therapeutic interventions. The consistent efficacy of these ligands across diverse targets suggests broad-spectrum effectiveness, encouraging further exploration for potential therapeutic interventions. The study contributes to a deeper understanding of endometriosis pathogenesis, paving the way for targeted therapies and precision medicine approaches to improve patient outcomes. These findings advance our understanding of the molecular mechanisms in endometriosis (EMS), offering promising avenues for future research and therapeutic development in addressing this complex condition.
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  • 文章类型: Journal Article
    前列腺癌(PCa)骨转移的病因尚不清楚。本研究旨在鉴定参与这一过程的hub基因。我们利用机器学习,GO,KEGG,GSEA,单细胞分析,使用TCGA和GEO数据库鉴定PCa骨转移的hub基因的ROC方法。鉴定了靶向这些基因的潜在药物。我们使用来自PCa患者的16个样本验证了这些结果,并分析了hub基因与临床特征之间的关系。通过体外实验评估APOC1对PCa的影响。鉴定了7个AUC值为0.727-0.926的hub基因。APOC1,CFH,NUSAP1和LGALS1在骨转移组织中高表达,而NR4A2、ADRB2和ZNF331表现出相反的趋势。免疫组织化学进一步证实了这些结果。所鉴定的基因显著富集了氧化磷酸化途径。黄曲霉毒素B1,苯并(a)芘,环孢素被确定为潜在药物。APOC1的表达与PCa转移的临床特征相关。沉默APOC1显著抑制PCa细胞增殖,克隆,和体外迁移。这项研究确定了7个hub基因,它们可能通过线粒体代谢重编程促进PCa的骨转移。APOC1成为PCa骨转移的有希望的治疗靶点和预后标志物。
    The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.
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  • 文章类型: Journal Article
    目的:miR-497/195位于17p13.1,是一个高度保守的miRNA簇,其异常表达是癌变的关键调节因子。我们使用公开可用的数据集对miR-497/195簇进行了全面分析,以确定其在宫颈癌(CC)中的预后效用和作用。
    结果:计算机模拟分析和验证表明,该集群在CC中下调。miR-497/195簇的总共60个靶基因被鉴定为在正常和CC样品之间差异表达。ShinyGO,STRING,CytoHubba,定时器2.0,HPA,和HCMBD用于功能富集,PPIN网络建设,枢纽基因鉴定,免疫浸润相关性,组织病理学表达,并测定miR-497/195簇及其靶基因的转移潜能。PPIN分析确定CCNE1、CCNE2、ANLN、RACGAP1,KIF23,CHEK1,CDC25A,E2F7、CDK1和CEP55是前10个hub基因(HG)。此外,RECK的上调,ATD5和BCL2、OSBPL3、RCAN3和HIST1H3H的下调影响CC患者的总生存期。我们确定了6个目标(TFAP2A,CLSPN,RASEF,HIST1H3H,AKT3,和ITPR1)对miR-497/195簇转移的影响。此外,还鉴定了8个可药用基因和38种潜在药物。我们的研究确定了miR-497/195簇靶基因和途径,可用于CC的预后和治疗应用。
    OBJECTIVE: miR-497/195, located at 17p13.1, is a highly conserved miRNA cluster whose abnormal expression is a key regulator of carcinogenesis. We performed a comprehensive analysis of the miR-497/195 cluster to determine its prognostic utility and role in cervical cancer (CC) using publicly available datasets.
    RESULTS: In silico analysis and validation revealed that this cluster is downregulated in CC. A total of 60 target genes of miR-497/195 cluster were identified as differentially expressed between normal and CC samples. ShinyGO, STRING, CytoHubba, Timer 2.0, HPA, and HCMBD were used for functional enrichment, PPIN network construction, hub gene identification, immune infiltration correlation, histopathological expression, and determination of the metastatic potential of miR-497/195 cluster and their target genes. PPIN analysis identified CCNE1, CCNE2, ANLN, RACGAP1, KIF23, CHEK1, CDC25A, E2F7, CDK1, and CEP55 as the top 10 hub genes (HGs). Furthermore, the upregulation of RECK, ATD5, and BCL2, downregulation of OSBPL3, RCAN3, and HIST1H3H effected overall survival of CC patients. We identified 6 targets (TFAP2A, CLSPN, RASEF, HIST1H3H, AKT3, and ITPR1) of miR-497/195 cluster to influence metastasis. In addition, 8 druggable genes and 38 potential drugs were also identified. Our study identified miR-497/195 cluster target genes and pathways that could be used for prognostic and therapeutic applications in CC.
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  • 文章类型: Journal Article
    目的:年龄相关性黄斑变性(AMD)是一种慢性进行性黄斑变性疾病,最终导致中心视力逐渐恶化。尽管流行,AMD的关键生物标志物尚未完全阐明.在这项研究中,我们旨在有效鉴定对诊断AMD至关重要的生物标志物.方法:从GEO数据库中选择与AMD相关的视网膜色素上皮(RPE)/脉络膜组织相关的三个数据集。利用GSE50195数据集进行加权基因共表达网络分析(WGCNA)以鉴定与AMD相关的模块基因。随后对这些模块基因进行KEGG和GO富集分析。对GSE29801和GSE135092数据集进行差异表达分析,以查明与模块基因相交的DEG。随后,开发了湿性AMD(WAMD)和干性AMD(DAMD)小鼠模型,从其中收获RPE/脉络膜组织以通过RT-qPCR和Western印迹验证hub基因。结果:使用WGCNA,我们选择了“antiquetwhite4”模块(r=0.91,p=7e-07),总共包含325个基因。通过模块基因与DEG的交叉,确定了9个hub基因。涉及补体和凝血级联的通路,ECM-受体相互作用,不饱和脂肪酸生物合成,脂肪酸伸长在AMD中起重要作用。值得注意的是,CDH18在所有三个数据集上表现出显著的差异。使用RT-qPCR实验的后验证揭示了在dAMD和wAMD两者中CDH18的显著下调。EGLN3在wAMD中低水平表达。在dAMD中,EYA2、LTB、和PODXL显著下调,而APOC1明显上调。Westernblot证实CDH18在dAMD和wAMD小鼠模型中低表达。结论:CDH18是参与AMD发病的关键基因。补体和凝血级联的失衡是AMD的潜在机制。本研究为今后AMD的诊断和治疗提供了新的思路。
    Purpose: Age-related macular degeneration (AMD) is a chronic and progressive macular degenerative disease that culminates in a gradual deterioration of central vision. Despite its prevalence, the key biomarkers for AMD have not yet been fully elucidated. In this study, we aimed to efficiently identify biomarkers crucial for diagnosing AMD. Methods: Three datasets pertaining to retinal pigment epithelium (RPE)/choroid tissues associated with AMD were selected from the GEO database. The GSE50195 dataset was utilized to conduct weighted gene co-expression network analysis (WGCNA) for identifying module genes linked to AMD. KEGG and GO enrichment analyses were subsequently conducted on these module genes. GSE29801 and GSE135092 datasets were subjected to differential expression analysis to pinpoint the DEGs intersecting with the module genes. Subsequently, wet AMD (wAMD) and dry AMD (dAMD) mouse models were developed, from which RPE/choroid tissues were harvested to validate the hub genes via RT-qPCR and Western blot. Results: Using the WGCNA, we selected the \"antiquewhite4\" module (r = 0.91 and p = 7e-07), which contains a total of 325 genes. Through the intersection of module genes with DEGs, nine hub genes were identified. Pathways involved in complement and coagulation cascades, ECM-receptor interactions, unsaturated fatty acid biosynthesis, and fatty acid elongation play important roles in AMD. Notably, CDH18 demonstrated notable variance across all three datasets. Post validation using RT-qPCR experiments revealed a significant downregulation of CDH18 in both dAMD and wAMD. EGLN3 was expressed at low levels in wAMD. In dAMD, EYA2, LTB, and PODXL were significantly downregulated, whereas APOC1 was notably upregulated. Western blot confirmed that CDH18 was lowly expressed in dAMD and wAMD mouse models. Conclusion: CDH18 was identified as the key gene involved in the pathogenesis of AMD. An imbalance of the complement and coagulation cascades is a potential mechanism of AMD. This study provides a novel idea for diagnosing and treating AMD in the future.
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  • 文章类型: Journal Article
    背景:宫颈癌具有极高的发病率和死亡率,其发病机制尚处于探索阶段。本研究旨在通过生物信息学分析筛选和鉴定与宫颈癌相关的差异表达基因(DEGs)。
    方法:从GEO数据库中选择GSE63514和GSE67522筛选DEG。然后对DEGs进行GO和KEGG分析。通过STRING网站构建DEG的PPI网络,通过Cytoscape软件的12种算法发现了hub基因。同时,从GEO数据库中选择GSE30656筛选DEM,通过TagetScan筛选DEM的靶基因,miRTarBase和miRDB。接下来,从DEG筛选的hub基因与从DEM筛选的目标基因合并。最后,进行ROC曲线和列线图分析以评估hub基因的预测能力。通过TCGA验证了这些hub基因的表达,GEPIA,qRT-PCR,和免疫组织化学。
    结果:六个中心基因,TOP2A,Aurka,CCNA2,IVL,KRT1和IGFBP5是通过蛋白质-蛋白质相互作用网络开采的。通过TCGA验证了这些hub基因的表达,GEPIA,qRT-PCR,和免疫组织化学,结果发现TOP2A,AURKA和CCNA2在宫颈癌中过表达,IGFBP5低表达。
    结论:这项研究表明,TOP2A,Aurka,通过生物信息学分析筛选出的CCNA2和IGFBP5在宫颈癌样本中的表达与正常样本相比有显著差异。这可能是宫颈癌的生物标志物。
    BACKGROUND: Cervical cancer has extremely high morbidity and mortality, and its pathogenesis is still in the exploratory stage. This study aimed to screen and identify differentially expressed genes (DEGs) related to cervical cancer through bioinformatics analysis.
    METHODS: GSE63514 and GSE67522 were selected from the GEO database to screen DEGs. Then GO and KEGG analysis were performed on DEGs. PPI network of DEGs was constructed through STRING website, and the hub genes were found through 12 algorithms of Cytoscape software. Meanwhile, GSE30656 was selected from the GEO database to screen DEMs. Target genes of DEMs were screened through TagetScan, miRTarBase and miRDB. Next, the hub genes screened from DEGs were merged with the target genes screened from DEMs. Finally, ROC curve and nomogram analysis were performed to assess the predictive capabilities of the hub genes. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry.
    RESULTS: Six hub genes, TOP2A, AURKA, CCNA2, IVL, KRT1, and IGFBP5, were mined through the protein-protein interaction network. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry, and it was found that TOP2A, AURKA as well as CCNA2 were overexpressed and IGFBP5 was low expression in cervical cancer.
    CONCLUSIONS: This study showed that TOP2A, AURKA, CCNA2 and IGFBP5 screened through bioinformatics analysis were significantly differentially expressed in cervical cancer samples compared with normal samples, which might be biomarkers of cervical cancer.
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