肾纤维化关键基因的生信筛选及分析

[目的]利用生物信息学技术筛选与肾纤维化相关基因,并预测与基因相关通路,疾病、细胞类型和有关药物。[方法]在公共基因芯片数据库(GEO)中获取与肾纤维化相关三个基因数据集,利用Venn图鉴定出共表达的差异基因,Metascape工具对差异基因进行功能(GO)和通路富集(KEGG)分析,还利用STRING构建蛋白相互作用网络(PPI)网络以及可视化工具Cytoscape筛选关键基因,最后用及Enrichr和Comparative Toxicogenomics Database(CTD)数据分析有关疾病、细胞类型和药物。[结果]与肾纤维化相关的数据集GSE148420、GSE38117、GSE54441经Venn图共得到83个DEGs。经Cytoscape对STRING工具得到的PPI网络可视化后,筛选出10个与肾纤维化相关的关键基因,分别是F13B、ALDH8A1、A1CF、PAH、KMO、ALDH6A1、SPP2、ACAT1、ABAT、CAT。GO和KEGG富集显示这些基因与氧化还原酶活性,血小板致密颗粒,色氨酸、结氨酸、亮氨酸和异亮氨酸等氨基酸代谢通路有关。利用Enrichr和CTD...     

浆液性卵巢癌铁死亡关键基因的筛选及[]生物信息学分析

利用生物信息学方法筛选浆液性卵巢癌相关铁死亡关键基因,并预测其生物学功能。从GEO数据库中获得有关浆液性卵巢癌的数据集GSE54388和GSE12470,采用R语言中的“Limma”包分析挑选浆液性卵巢癌上皮组织与正常卵巢上皮组织中差异表达基因,绘制火山图、热图。利用Venn软件在线工具绘制GSE54388,GSE12470,FerrDb三个数据集韦恩图。对相关基因进行功能富集分析、蛋白互作分析、生存分析,对关键基因绘制ROC曲线进行诊断分析。采用GEPIA2 数据库对筛选基因进行验证,并进行免疫浸润分析。结果发现:从GSE54388中筛选出2458个差异基因,其中上调1309个,下调1149个。从GSE12470中筛选出3534个差异基因,其中上调1 837个,下调1 697个。与铁死亡基因数据集取交集,共得到16个差异基因,蛋白互作网络筛选出7个基因构建的关键模块,绘制生存曲线发现浆液性卵巢癌患者中5个基因与患者总生存率不良相关,其中NRAS,PSAT1,CDKN2A,GDF15这4个基因高表达,CAV1低表达。ROC曲线显示这5个基因中CAV1,NRAS,PSAT1的AUC诊断曲线面积大于0.95,有较高的诊断价值。GEPIA2 数据库验证发现5个基因的表达情况与预测相符,仅NRAS基因表达在浆液性卵巢癌患者Ⅱ期、Ⅲ期、Ⅳ期有显著差异(P<0.05)。免疫浸润分析发现CDKN2A表达与aDC细胞浸润水平呈正相关(P<0.05,spearman相关系数0.353);CAV1表达与Mast细胞浸润正向关(P<0.05,spearman相关系数0.327);NRAS与T helper细胞浸呈正向关(P<0.05,spearman相关系数0.362)。通过生物信息学方法筛选出与浆液性卵巢癌铁死亡相关的5个基因CAV1,NRAS,PSAT1,CDKN2A,GDF15,可能在浆液性卵巢癌的发生发展中起重要作用,有望成为该病诊断、治疗和预后的潜在分子生物标志物。     

基于生物信息学分析的肝癌核心基因的筛选及验证

本研究基于GEO数据库,选取由慢性乙型肝炎诱导的肝细胞癌芯片数据GSE121248为研究对象,利用GEO2R软件分析数据,筛选出差异表达基因,利用DAVID数据库进行GO分析和KEGG pathway富集分析.利用STRING数据库构建PPI网络,分析筛选核心基因.利用GEPIA对核心基因的表达进行验证,Kaplan ...     

HBV感染者肝细胞样本的关键基因和信号通路的生物信息学挖掘

为探究乙型肝炎病毒(Hepatitis B virus,HBV)感染后肝细胞基因表达和信号通路的改变情况,从Gene Expression Omnibus(GEO)数据库中下载了HBV感染者肝细胞样本制作的基因表达谱数据集GSE83148,进行质量检测、数据标准化后筛选出差异表达基因,进一步做GO和KEGG富集分析以及基因网络相互作用分析,筛选关键基因和信号通路。从HBV感染样本中筛选出fold change≥2,p-value0. 05的上调差异表达基因44个,GO分析获得关键基因BAK1和TP63,差异表达基因网络互作获得5个位于枢纽位置的基因:NDUFS1、NDUFS2、COX7B、ATP5B、OPA1。KEGG分析获得关键信号通路有:乙型肝炎信号通路、病毒癌变信号通路、Fox O信号通路、PI3K-Akt信号通路。本研究筛选出的多数基因与线粒体和氧化呼吸链有关,造成这一现象的具体机制还需进一步探究。     

家族性双侧大结节性肾上腺增生症生物标志物的生信分析

为寻找与家族性双侧大结节性肾上腺皮质增生症发展有关的潜在治疗靶点和生物标志物。从GEO数据库中下载GSE171558数据集,筛选受家族影响的肾上腺结节与正常的肾上腺组织之间的差异表达基因(Differentially expressed genes, DEGs),并进行基因功能富集分析和蛋白质-蛋白质相互作用网络分析。通过Cytoscape v3.9.1软件中的插件cytoHubba筛选出关键基因,进一步经NetworkAnalyst分析TF-miRNA共调控网络和蛋白质-化合物相互作用。共鉴定出336个DEGs,这些基因主要富集在细胞粘附过程、细胞增殖的正调节过程和RNA加工过程等生物过程,并涉及钙信号通路、PI3K-Akt信号通路和cAMP信号通路等。通过cytoHubba插件获得5个hub基因,经验证分析,多功能蛋白聚糖(Versican,VCAN)、双糖链蛋白聚糖(Biglycan,BGN)被认为是家族性双侧大结节性肾上腺皮质增生症的潜在生物标志物。进一步的GSEA分析结果显示,VCAN主要与丁酸代谢、ECM-受体相互作用和类固醇生物合成等有关。BGN主要涉及剪接体、皮质醇的合...     

肿瘤相关候选基因在舌鳞癌中的筛选

目的：寻找舌癌特异性相关基因,阐明舌癌发病的分子机制,为舌癌的诊断、治疗和预后提供分子靶标。方法：采用半定量RT-PCR方法检测了所选9个肿瘤相关基因DLC1、ANXA1、BCAT1、KRAS2、KCNJ8、LDHB、DNM1L、ETNK1、PTX1在舌鳞癌中的表达情况。结果：DLC1、ANXA1、LDHB、DNM1L、ETNK1、PTX16个基因在舌鳞癌组织与配对正常组织中无明显表达差异;而BCAT1、KRAS2、KCNJ8在舌鳞癌组织中表达上调,上调频率分别为45%（9/20）、50%（10/20）和33.3%（4/12）。结论：BCAT1、KRAS2和KCNJ8参与了舌鳞癌的发生发展,也为进一步在舌鳞癌中分析3个基因的功能提供实验依据。     

抗口蹄疫病毒相关基因的筛选及分析

口蹄疫是一种烈性传染病,其广泛流行给社会造成了巨大经济损失。为了研究口蹄疫灭活疫苗免疫的分子机制,同时也为抗口蹄疫病毒药物的研制奠定基础,本研究应用mRNA差异显示技术,以PK-15细胞为材料,系统比较了口蹄疫疫苗刺激组（A组）和正常的PK-15细胞（B组）的基因表达情况,回收差异片段,经二次扩增并纯化后,得到30条ESTs。将30条ESTs采用以地高辛标记的反向Northern点杂交鉴定,将阳性条带克隆测序,筛选出8条ESTs,编号E1~E8,应用BLASTn工具将8条ESTs对核酸数据库nr和dbEST中所有序列进行了同源性分析,其中E1,E2分别与猪的热休克蛋白基因、猪的MHCⅠ类基因同源,序列相似性都达到100%。E3,E4,E5,E7分别与已有核酸数据库中的基因克隆或EST具有较高同源性,为已知的EST,但功能未知;E6,E8在数据库中没有发现与其相似性较高的序列,为新的EST。应用数据库资源将E5、E7进行电子延伸后,将延伸序列进行开放阅读框分析,又经TBLASTx分析发现E7蛋白质序列与猪的精氨酸酶Ⅰ类蛋白序列有很高同源性。将E1、E2、E4、E5序列进行了基因表达谱分析,对E6、E8用BLASTx工具对非冗余蛋白质数据库nr进行了相似性搜索,在其他物种中找到了相似的基因序列。本研究筛选出的热休克蛋白基因、MHCⅠ类基因、精氨酸酶Ⅰ类基因和其他未知功能基因可以作为抗口蹄疫病毒研究中的侯选基因,其具体的功能有待今后进一步研究。     

基于生物信息学分析的宫颈鳞状细胞癌预后相关基因的筛选

为了分析宫颈鳞状细胞癌(cervical squamous cell carcinoma, CESC)与正常组织中的差异表达基因(differentially expressed genes, DEGs),鉴定与CESC预后相关的关键基因,从GEO和TCGA数据库下载CESC的基因表达谱数据,利用R软件筛选CESC组织与正常组织中的DEGs,并对这些DEGs开展功能和通路富集分析;然后构建蛋白质-蛋白质相互作用(protein-protein interaction, PPI)网络,筛选出关键(hub)基因;最后对hub基因进行LASSO COX回归及总体生存率(overall survival, OS)分析。研究共筛选出167个DEGs,这些基因主要涉及染色体分离、DNA复制等生物过程,介导染色质结合、G蛋白偶联受体结合等分子功能,富集于染色体区域、纺锤体和MCM复合体。GSEA分析结果显示,富集的通路主要涉及DNA复制和细胞周期信号通路。此外,从PPI网络中筛选出20个hub基因, LASSO COX回归结果显示MAD2L1、ZWINT、RRM2、TTK、CDC6、PBK、TOP2A、KIF11、KIF20A、NCAPG、NUSAP1、CCNB1及CDK1与CESC患者的预后相关; Kaplan-Meier曲线显示, ZWINT、DTL、CCNB1、CDC6、TOP2A、CDK1、PBK、RFC4及NUSAP1的m RNA表达水平与CESC患者生存预后相关。本研究结果表明, ZWINT、CDC6、PBK、TOP2A、NUSAP1、CCNB1和CDK1为CESC的预后关键基因,为阐明CESC的分子机制提供了理论依据。     

生物信息学分析筛选结直肠癌靶基因及评估预后价值

为寻找与结直肠癌发展和预后相关的潜在关键基因及信号通路.从美国国立信息中心NCBI的GEO数据库获得结直肠癌基因表达数据集GSE106582,通过PCA对样本进行分组,利用GEO2R进行综合分析,筛选结直肠癌与癌旁对照组的差异表达基因;通过DAVID在线工具对差异表达基因进行GO本体分析和KEGG通路富集分析,初步分析...     

Screening and identification of hub genes in pancreatic cancer by integrated bioinformatics analysis

Pancreatic cancer (Pa) is a malignant tumor of the digestive tract with high degree of malignancy, this study aimed to obtain the hub genes in the tumorigenesis of Pa. Microarray datasets GSE15471, GSE16515, and GSE62452 were downloaded from Gene Expression Omnibus (GEO) database, GEO2R was conducted to screen the differentially expressed genes (DEGs), and functional enrichment analyses were carried out by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) network was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING), and the hub genes were identified by Cytoscape. Totally 205 DEGs were identified, consisting of 51 downregulated genes and 154 upregulated genes enriched in Gene Ontology terms including extracellular matrix (ECM) organization, collagen binding, cell adhesion, and pathways associated with ECM-receptor interaction, focal adhesion, and protein digestion. Two modules in the PPI were chosen and biological process analyses showed that the module genes were mainly enriched in ECM and cell adhesion. Twenty-four hub genes were confirmed, the survival analyses from the cBioPortal online platform revealed that topoisomerase (DNA) II α (TOP2A), periostin (POSTN), plasminogen activator, urokinase (PLAU), and versican (VCAN) may be involved in the carcinogenesis and progression of Pa, and the receiver-operating characteristic curves indicated their diagnostic value for Pa. Among them, TOP2A, POSTN, and PLAU have been previously reported as biomarkers for Pa, and far too little attention has been paid to VCAN. Analysis from R2 online platform showed that Pa patients with high VCAN expression were more sensitive to gemcitabine than those with low level, suggesting that VCAN may be an indicator to guide the use of the chemotherapeutic drug. In vitro experiments also showed that the sensitivity of the VCAN siRNA group to gemcitabine was lower than that of the control group. In conclusion, this study discerned hub genes and pathways related to the development of Pa, and VCAN was identified as a novel biomarker for the diagnose and therapy of Pa.     

Identification of key microRNAs and hub genes in non-small-cell lung cancer using integrative bioinformatics and functional analyses

Non-small-cell lung cancer (NSCLC) is an extremely debilitating respiratory malignancy. However, the pathogenesis of NSCLC has not been fully clarified. The main objective of our study was to identify potential microRNAs (miRNAs) and their regulatory mechanism in NSCLC. Using a systematic review, two NSCLC-associated miRNA data sets (GSE102286 and GSE56036) were obtained from Gene Expression Omnibus, and the differentially expressed miRNAs (DE-miRNAs) were accessed by GEO2R. Survival analysis of candidate DE-miRNAs was conducted using the Kaplan-Meier plotter database. To further illustrate the roles of DE-miRNAs in NSCLC, their potential target genes were predicted by miRNet and were annotated by the Database for Annotation, Visualization and Integrated Discovery (DAVID) program. Moreover, the protein-protein interaction (PPI) and miRNA-hub gene regulatory network were established using the STRING database and Cytoscape software. The function of DE-miRNAs in NSCLC cells was evaluated by transwell assay. Compared with normal tissues, a total of eight DE-miRNAs was commonly changed in two data sets. The survival analysis showed that six miRNAs (miR-21-5p, miR-31-5p, miR-708-5p, miR-30a-5p, miR-451a, and miR-126-3p) were significantly correlated with overall survival. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that target genes of upregulated miRNAs were enriched in pathways in cancer, microRNAs in cancer and proteoglycans in cancer, while the target genes of downregulated miRNAs were mainly associated with pathways in cancer, the PI3K-Akt signaling pathway and HTLV-I infection. Based on the miRNA-hub gene network and expression analysis, PTEN, EGFR, STAT3, RHOA, VEGFA, TP53, CTNNB1, and KRAS were identified as potential target genes. Furthermore, all six miRNAs exhibited significant effects on NSCLC cell invasion. These findings indicate that six DE-miRNAs and their target genes may play important roles in the pathogenesis of NSCLC, which will provide novel information for NSCLC treatments.     

Screening of hub genes and prediction of putative drugs in arsenic-related bladder carcinoma: An in silico study

BackgroundEvidence showed that inorganic arsenic (iAs) can trigger malignant transformation in cells with complex mechanisms. Thus, we aimed to investigate the possible molecules, pathways and therapeutic drugs for iAs-induced bladder cancer (BC) by using bioinformatics approaches.MethodsMicroarray-based data were analyzed to screen the differentially expressed genes (DEGs) between iAs-related BC cells and controls. Then, the roles of DEGs were annotated and the hub genes were screened out by protein-protein interaction network. The key genes were further selected from the hub genes through an assessment of the prognostic values. Afterward, potential drugs were predicted by using CMAP analysis.ResultsAnalysis of a dataset (GSE90023) generated 21 upregulated and 47 downregulated DEGs, which were enriched in various signaling pathways. Among the DEGs, four hub genes including WNT7B, SFRP1, DNAJB2, and ATF3, were identified as the key genes because they might predict poor prognosis in BC patients. Lastly, Cantharidin was predicted to be a potential drug reversing iAs-induced malignant transformation in urinary epithelium cells.ConclusionThe present study found several hub genes involved in iAs-induced malignant transformation in urinary epithelium cells, and predicted several small agents for iAs toxicity prevention or therapy.     

Identification of core genes and outcomes in hepatocellular carcinoma by bioinformatics analysis

Hepatocellular carcinoma (HCC) is the most common malignant liver disease in the world. However, the mechanistic relationships among various genes and signaling pathways are still largely unclear. In this study, we aimed to elucidate potential core candidate genes and pathways in HCC. The expression profiles GSE14520, GSE25097, GSE29721, and GSE62232, which cover 606 tumor and 550 nontumour samples, were downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, HCC RNA-seq datasets were also downloaded from the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were filtered using R software, and we performed gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the online databases DAVID 6.8 and KOBAS 3.0. Furthermore, the protein-protein interaction (PPI) network complex of these DEGs was constructed by Cytoscape software, the molecular complex detection (MCODE) plug-in and the online database STRING. First, a total of 173 DEGs (41 upregulated and 132 downregulated) were identified that were aberrantly expressed in both the GEO and TCGA datasets. Second, GO analysis revealed that most of the DEGs were significantly enriched in extracellular exosomes, cytosol, extracellular region, and extracellular space. Signaling pathway analysis indicated that the DEGs had common pathways in metabolism-related pathways, cell cycle, and biological oxidations. Third, 146 nodes were identified from the DEG PPI network complex, and two important modules with a high degree were detected using the MCODE plug-in. In addition, 10 core genes were identified, TOP2A, NDC80, FOXM1, HMMR, KNTC1, PTTG1, FEN1, RFC4, SMC4, and PRC1. Finally, Kaplan-Meier analysis of overall survival and correlation analysis were applied to these genes. The abovementioned findings indicate that the identified core genes and pathways in this bioinformatics analysis could significantly enrich our understanding of the development and recurrence of HCC; furthermore, these candidate genes and pathways could be therapeutic targets for HCC treatment.     

低温胁迫下烤烟幼苗叶片光合作用和抗氧化能力基因差异表达谱

对低温(5—7℃)胁迫下烤烟"K326"幼苗叶片光合指标、膜氧化水平及其抗氧化指标进行测定,并利用数字化基因表达谱技术进行基因差异表达分析。低温胁迫后烤烟幼苗叶绿素含量、光合能力显著下降,脯氨酸含量、丙二醛含量上升,超氧化物歧化酶活性、过氧化氢酶活性、抗坏血酸含量和谷胱甘肽含量均显著上升。低温胁迫后有2357个基因发生了显著差异表达,其中1673个基因表达上调、684个基因表达下调,其分子功能、细胞位置和主要代谢过程均涉及光系统、膜氧化系统和抗氧化系统。对涉及到的代谢过程进行分析,结果表明:光合天线蛋白调控基因表达量均显著下降、光合作用的主要调控基因表达量多数表现为显著下调、而与氧化能力相关的谷胱甘肽代谢差异表达基因大多数显著上调。基因差异表达谱分析结果和低温胁迫后叶片光合能力、抗氧化能力生理生态指标测定结果基本一致,为进一步研究低温胁迫对作物的生态影响和研究基因克隆与功能提供基础。     

Investigation of hub genes and immune status in heart transplant rejection using endomyocardial biopsies

T cell‒mediated rejection (TCMR) and antibody-mediated rejection (ABMR) are severe post-transplantation complications for heart transplantation (HTx), whose molecular and immunological pathogenesis remains unclear. In the present study, the mRNA microarray data set GSE124897 containing 645 stable, 52 TCMR and 144 ABMR endomyocardial biopsies was obtained to screen for differentially expressed genes (DEGs) between rejected and stable HTx samples and to investigate immune cell infiltration. Functional enrichment analyses indicated roles of the DEGs primarily in immune-related mechanisms. Protein-protein interaction networks were then constructed, and ICAM1, CD44, HLA-A and HLA-B were identified as hub genes using the maximal clique centrality method. Immune cell infiltration analysis revealed differences in adaptive and innate immune cell populations between TCMR, ABMR and stable HTx samples. Additionally, hub gene expression levels significantly correlated with the degree and composition of immune cell infiltration in HTx rejection samples. Furthermore, drug-gene interactions were constructed, and 12 FDA-approved drugs were predicted to target hub genes. Finally, an external GSE2596 data set was used to validate the expression of the hub genes, and ROC curves indicated all four hub genes had promising diagnostic value for HTx rejection. This study provides a comprehensive perspective of molecular and immunological regulatory mechanisms underlying HTx rejection.     

Identification of potentially critical genes in the development of heart failure after ST-segment elevation myocardial infarction (STEMI)

Heart failure (HF) remains a common complication after acute ST-segment elevation myocardial infarction (STEMI). Here, we aim to identify critical genes related to the developed HF in patients with STEMI using bioinformatics analysis. The microarray data of GSE59867, including peripheral blood samples from nine patients with post-infarct HF and eight patients without post-infarct HF, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non-HF groups were screened by LIMMA package. Functional enrichment analyses of DEGs were conducted, followed by construction of a protein-protein interaction (PPI) network. The dynamic messenger RNA (mRNA) level of the hub genes during the follow-up was analyzed to further elucidate their role in HF development. A total of 58 upregulated and 75 downregulated DEGs were screen out. They were mainly enriched in biological processes about inflammatory response, extracellular matrix organization, response to cAMP, immune response, and positive regulation of cytosolic calcium ion concentration. Pathway analysis revealed that the DEGs were also involved in hematopoietic cell lineage, pathways in cancer, and extracellular matrix-receptor interaction. In the PPI network consisting of 58 nodes and 72 interactions, CXCL8 (degree = 15), THBS1 (degree = 8), FOS (degree = 7), and ITGA2B (degree = 6) were identified as the hub genes. In the comparison of patients with and without post-infarct HF, the mRNA level of these hub genes were all higher within 30 days but reached similar at 6 months after STEMI. In conclusion, CXCL8, THBS1, FOS, and ITGA2B may play important roles in the development of HF after acute STEMI.     

Oxidative stress and ischemia-modified albumin in chronic ischemic heart failure

Abstract

Objectives

Knowledge about the role of oxidative stress in human diseases, including cardiovascular system disorders, emphasizes the need for reliable markers of oxidative stress. Here, we evaluated the levels of the novel marker ischemia-modified albumin (IMA), albumin-adjusted IMA (adj-IMA), and the IMA/serum albumin ratio (IMAR) in patients with chronic ischemic heart failure (CIHF).

Methods

A total of 55 patients with CIHF and 40 age- and sex-matched healthy individuals were included in the study. Serum levels of IMA, total antioxidant status, and total oxidant status were analyzed, and the adj-IMA level, IMAR, and oxidative stress index were calculated.

Results

Serum IMA, IMAR, total oxidant status levels, and oxidative stress index were significantly higher in patients with CIHF than in the controls (all P < 0.0001), whereas albumin and total antioxidant status levels were significantly lower in the CIHF patients (P < 0.0001 and P = 0.0004, respectively). However, there was no significant difference in serum adj-IMA levels between the groups (P = 0.8).

Discussion

We observed impaired oxidant/antioxidant status in favor of oxidative stress in CIHF patients. Oxidative stress may be a key factor in the development of hypoalbuminemia in CIHF. Further studies are needed to establish the relationships among IMA, albumin, and redox balance in CIHF.