基于大数据分析CAP2基因在肝细胞癌中的表达意义

[目的]研究CAP2基因在肝细胞癌中的表达及临床意义.[方法]对TCGA和Oncomine数据库中CAP2进行检索,并对所获取的数据二次分析.[结果]Oncomine数据库中共收集了33项(高表达14项、低表达19项)CAP2在肿瘤组织与正常对照组织中表达差异具有统计学意义的结果.肝细胞癌中CAP2高表达有5项,低表达...     

基于生物信息学分析SCHIP1在急性髓系白血病中的表达及其临床意义

通过数据挖掘和生物信息学分析手段,探讨施旺膜蛋白相互作用因子1(schwannomin interacting protein 1,SCHIP1)基因在急性髓系白血病患者中的表达情况及其临床意义。首先,对Oncomine数据库中收录的所有急性髓系白血病(acute myloid leukaemia,AML)数据集进行荟萃分析,筛选出目标基因SCHIP1并进一步分析其在AML病人中的表达变化。随后,从GEO数据库中下载含生存信息的AML数据集源文件,分析SCHIP1表达对疾病的预后作用。另外,利用TCGA数据库对SCHIP1的表达情况进行亚组分析及与FLT3基因突变、PML/RARα融合基因和RAS活化等高危因素进行相关性分析。最后,利用GEPIA2工具验证SCHIP1的表达情况、预后意义及与FLT3、PML基因表达的相关性。结果发现Oncomine数据库中收录了44个AML数据集,总计共3534个样本数据。其中5个数据集共1188个样本包含“Cancer vs.Normal”的mRNA表达数据,对其进行荟萃分析显示SCHIP1位于显著高表达分子的第17位。生存分析显示,SCHIP1表达量与AML患者总体生存率呈负相关。亚组分析显示SCHIP1在M0/M1/M2中较M3/M6中表达更高,但与年龄、性别和种族无关。另外,相关性研究分析显示SCHIP1与FLT3基因突变弱相关,但与PML/RARα融合基因和RAS活化等高危因素无显著相关性。这些结果表明SCHIP1在急性髓系白血病中高表达,且其高表达与患者的生存预后呈显著负相关。因此,SCHIP1可作为疾病的预后生物标志物,并有望成为AML的精准治疗靶点。     

幽门螺杆菌感染与胃癌相关基因的筛选及预后分析

目的通过分析幽门螺杆菌感染胃黏膜组织和胃癌细胞系后的差异基因变化,并在癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库和肿瘤基因芯片(Oncomine)数据库进行验证,探究幽门螺杆菌导致胃癌发生、发展的分子机制。方法分析基因表达汇编(Gene Expression Omnibus,GEO)数据库幽门螺杆菌感染相关芯片集GSE5081与GSE70394,绘制维恩图查找幽门螺杆菌感染后共同上调的差异基因。对共同上调的差异基因进行功能富集分析。通过TCGA和Oncomine数据库验证差异基因在胃癌中的表达。利用Kaplan-Meier Plotter数据库和GEPIA数据库分析差异基因表达高低与胃癌患者预后是否存在相关性。结果通过差异基因筛选和维恩分析,两个芯片集共有21个共同上调差异基因。GO分析发现共同上调差异基因主要富集在对细菌来源分子的反应、趋化因子CXCR受体结合、中性粒细胞趋化作用等相关的基因功能上;KEGG通路主要富集在癌症通路、TNF信号通路、趋化因子信号通路等。STRING以及PPI数据库分析发现21个基因中PRDM1、IL10、NRP1、BIRC3、GNG13、CXCL1、CXCL2、CXCL3、CXCL8基因存在有网络关系,属于关键枢纽基因。通过TCGA和Oncomine数据库筛选及验证,发现在胃癌组织中NRP1、CXCL1、CXCL8基因明显上调,结果差异有统计学意义(TCGA数据库中,三者P值均小于0.05,Oncomine数据库中,NRP1:t=4.607,P0.01;CXCL1:t=5.854,P0.01;CXCL8:t=5.316,P0.01)。在Kaplan-Meier Plotter数据库(210615-at芯片:P0.01;210510-s-at芯片:P0.01;212298-at芯片:P0.01)以及GEPIA数据库(P0.01)两个数据库中,NRP1的高表达均与胃癌的预后负相关。结论不同的数据库均显示NRP1、CXCL1、CXCL8三个基因与幽门螺杆菌感染相关,同时在胃癌中高表达,并且NRP1的高表达与胃癌的不良预后相关,这些结果为进一步探究幽门螺杆菌导致胃癌发生、发展的分子机制提供了重要基础。     

MAML2基因表达及临床参数与低级别胶质瘤(LGG)患者的诊断及预后价值

脑胶质瘤(Glioma)是最常见的中枢系统恶性肿瘤,MAML2是NOTCH信号通路的共激活因子,通过癌基因组数据库(TCGA)分析验证MAML2基因表达及相关临床参数与低级别胶质瘤(LGG)的诊断及预后价值。从癌基因数据库LGG数据库中下载患者基因表达量数据及患者临床数据,采用统计学方法验证MAML2基因表达差异及临床参数与胶质瘤的诊断与预后关系。在TCGA LGG队列中,发现LGG组织中的MAML2基因较正常组织明显上调(P<0.001),其差异表达可作为低级别胶质瘤的潜在诊断标志物。同时,MAML2低表达组的LGG患者总体生存率低于高表达组(P=0.005 2)。此外,单因素多因素分析提示肿瘤分级,初治后肿瘤再发事件及MAML2低表达是低级别胶质瘤患者的独立危险因素。研究结果表明MAML2基因有可能成为诊断及预测低级别胶质瘤的一个潜在分子标记物。     

基于数据挖掘分析ONECUT2基因在胃癌的表达及与幽门螺杆菌感染的相关性

目的分析ONECUT2基因在胃癌中的表达及其与幽门螺杆菌(Helicobacter pylori,H.pylori)感染的相关性。方法 (1)利用Oncomine数据库、TCGA数据库分析ONECUT2基因在胃癌中的表达,R软件包进行基因的共聚类微阵列数据分析。(2)利用Kaplan-Meier Plotter数据库和GEPIA数据库分析ONECUT2差异表达与胃癌患者预后的关系。(3)利用生物信息学功能注释数据平台DAVID对胃癌中与ONECUT2基因表达正相关的前200个基因进行功能富集分析。(4)利用GEO数据库中的数据分析H.pylori感染与ONECUT2表达的相关性。结果 (1)Oncomine数据库中的数据在胃癌、膀胱癌等8种肿瘤中共有14项研究显示ONECUT2基因在肿瘤组织中的高表达;其中胃癌相关的有两项(t=6.064,P0.000 1;t=4.335,P0.000 1);TCGA数据库的数据也证实胃癌中ONECUT2高表达(t=6.680,P0.001)。(2)胃癌中ONECUT2与EHF、FUT6、TNFRSF11A、RSAEF、EPCAM等20个基因有较高的共表达。(3)GO分析发现胃癌中ONECUT2富集在分子结构活性等相关的基因功能上;而KEGG富集分析发现ONECUT2富集于紧密连接功能等6个通路。(4)Kaplan-Meier Plotter数据库中207676-at芯片结果显示ONECUT2高表达组患者远期生存率下降(P0.001);GEPIA数据库中的分析结果同样显示ONECUT2高表达组患者其总体生存率(P0.05)和无病生存率(P0.01)下降。GEO数据库中GSE74577(P=0.005)、GSE70394(P=0.034)和GSE25146(P=0.036)三个数据集均显示H.pylori感染AGS和GES-1细胞系后ONECUT2表达上调。结论 ONECUT2在胃癌中高表达,且与胃癌一类致癌原H.pylori感染相关。ONECUT2高表达组患者远期生存率下降,表明其与胃癌发生发展密切相关,可能成为胃癌治疗的新靶点。     

胶质母细胞瘤预后相关基因的数据挖掘分析

胶质母细胞瘤（glioblastoma, GBM）是恶性程度最高的颅内恶性肿瘤，目前临床上缺乏有效治疗药物，复发率高且预后差，开发新的抗GBM药物是目前临床上亟待解决的问题。为了筛选与GBM预后密切相关的基因，为寻找新的药物靶点提供线索，采用GEO2R工具从GEO数据库中的269个肿瘤组织和61个正常组织中初步筛选出差异表达基因，然后利用Cluster Profiler数据库进行基因功能富集分析，STRING及Cytoscape进一步筛选出37个差异表达基因，采用GEPIA交互分析对这37个基因在GBM肿瘤组织中的表达进行验证。为了进一步探索这些差异表达基因与患者预后的关系，研究中利用GEPIA工具对TCGA数据库中与患者预后相关的数据进行深入挖掘，最终发现PTTG1、RRM2、E2F7与患者中位生存期呈显著性负相关。研究筛选出的与患者预后密切相关的基因不仅可以为评估患者预后提供参考，同时也为开发新的抗GBM药物提供了潜在的靶点。     

基于Oncomine数据库分析COL5A2基因在胰腺癌中的表达及其临床意义

目的:探讨COL5A2基因在胰腺癌中的表达及临床意义。方法:收集Oncomine和NCBI/GEO Profiles数据库中关于COL5A2的信息,对目前数据库中的资料进行二次分析,并对其在胰腺癌组织和正常胰腺组织中的表达进行荟萃分析,利用Kaplan-Meier Plotter数据库分析COL5A2与胰腺癌患者预后的关系。结果:Oncomine数据库中共收集了417项不同类型的研究,其中COL5A2高表达有75项研究,低表达有3项研究。共有7项研究涉及COL5A2在胰腺癌组织与正常组织中的表达,包括178例样本,与正常组织相比,COL5A2在胰腺癌组织中高表达(P0.05)。NCBI/GEO Profiles数据库分析同样发现COL5A2在胰腺癌组织中高表达(P0.05),与达沙替尼(dasatinib)敏感细胞株相比,达沙替尼耐药细胞株中COL5A2表达升高,进一步分析发现TGF-β处理48 h后COL5A2表达升高。Kaplan-Meier Plotter数据库分析表明COL5A2高、低表达组胰腺癌患者的总体生存率(OS)无统计学差异(HR=1.45,95%CI:0.96～2.18,P=0.077),但高表达组胰腺癌患者的无复发生存率(RFS)明显差于低表达组(HR=4.13,95%CI:1.46～11.72,P=0.0045)。结论:基于Oncomine和NCBI/GEO Profiles数据库分析发现COL5A2在胰腺癌组织高表达,且与胰腺癌患者的无复发生存及达沙替尼耐药性密切相关,有望成为胰腺癌诊断和治疗的重要靶标。     

用于基因数据挖掘的基因表达数据库GEO

使用高通量方法学来检测基因表达情况在最近几年已非常普遍。微集芯片技术可同时定量成千上万的基因转录本。基因表达综合数据库（Gene Expression Omnibus 简称GEO）是目前最大的而且完全公开的高通量分子丰度数据库,主要储存基因表达数据。该数据库以一个灵活开放的设计理念,允许用户或科研人员来递呈,保存和检索多种不同类型的数据。本文综合描述一下近年来该数据库在基因表达数据挖掘中的应用,同时介绍一些通过使用用户友好网络界面能有效探索、查询和再现数百个实验和数百万个基因表达谱的工具,以方便数据进行挖掘和可视化。登录GEO公用数据库的网址为：http://www.ncbi.nlm.nih.gov/geo.     

基于Oncomine和TCGA数据挖掘分析MTERF2在胰腺癌中的表达及临床意义

目的:探究人线粒体转录终止因子2(MTERF2)在胰腺癌中的表达及临床意义。方法:检索Oncomine数据库中的MTERF2信息,对其在胰腺癌组织和正常胰腺组织中的表达进行荟萃分析;从美国癌症基因组图谱(TCGA)中下载胰腺癌数据集MTERF2 RNA Seq V2数据及临床病理资料;利用R 2.15.3软件分析MTERF2表达量与临床病理参数的相关性及预后;利用Kaplan-Meier生存函数分析MTERF2表达量和胰腺癌患者预后的关联。结果:Oncomine数据库中共收集了586个不同类型的研究结果,其中关于MTERF2表达有统计学差异的研究有58个,MTERF2表达增高的研究有26个,表达减低的研究有32个。共有9项研究涉及MTERF2在胰腺癌组织和正常组织中的表达,包括226例临床样本,与对照组相比,MTERF2在胰腺癌中低表达(P=7.34×10-6)。TCGA胰腺癌数据集中共收集179例具有临床病理参数的病例及其对应的MTERF2 mRNA表达量。剔除病理参数不详或不完整的病例,利用R 2.15.3软件分析发现,MTERF2 mRNA表达量与胰腺癌患者T分期、M分期、癌症类型及原发部位存在显著相关(均P<0.05),而与患者的年龄、性别、N分期、AJCC病理分期、等级、组织学类型及饮酒史无显著相关(均P>0.05)。Kaplan-Meier生存分析发现,胰腺癌患者MTERF2的表达水平与总生存率(OS)无显著相关性(P>0.05),而与无病生存率(DFS)显著相关(P<0.001)。结论:Oncomine和TCGA数据挖掘显示,人MTERF2在胰腺癌组织中低表达,且MTERF2表达量与胰腺癌患者总生存率无显著相关性,与无病生存率有显著相关性。     

免疫相关基因FGF13、GZMB、FLT3、CRLF3可能与急性髓系白血病患者预后密切相关

为了构建急性髓系白血病（AML）患者的预后风险模型,本研究通过IMMPORT数据库提取免疫基因,通过基因表达综合（GEO）数据库和AML相关转录组RNA测序数据集筛选差异表达的免疫基因,基于癌症基因组图谱（TCGA）数据库下载AML相关的表达谱数据集（TCGA-LAML）及临床数据,对差异表达的免疫基因进一步进行单因素COX回归分析和多因素COX回归分析,最终确定了关键免疫基因,随后根据免疫基因进行单基因预后分析以及免疫浸润分析。结果显示：与正常对照组相比,在AML患者的骨髓样本中,有55个免疫基因显著上调或下调,其中由4个免疫基因（FGF13、GZMB、FLT3、CRLF3）构建的风险模型能预测AML患者的预后[曲线下面积（AUC）=0.741];高风险组和低风险组之间免疫细胞的含量存在显著差异,其中FGF13、CRLF3为低风险基因,GZMB、FLT3为高风险基因。这为4个免疫基因FGF13、GZMB、FLT3、CRLF3及其构建的风险模型用于监测AML患者的预后和免疫浸润情况提供了理论基础。     

Construction of a mitochondrial-associated protein DRP1 and a lung cancer-associated protein Erbb4 combined regulatory network

ObjectiveThis research was to establish a mitochondrial-related Drp1 gene and a lung cancer-related Erbb4 gene to participate in the regulatory network of lung cancer cell apoptosis, and to provide theoretical support for mitochondria to participate in tumor regulation.MethodThe GO and KEGG methods were used to construct the regulatory networks of lung cancer related Drp1 and Erbb4 proteins that involved in the apoptosis of tumor cells, and to combine with the Bayesian network theory to screen out the largest possible action path acting on this network; The information about Drp1 in Oncomine database was collected, and the data in current database were analyzed twice. The role of Drp1 in lung cancer was meta-analyzed.ResultA regulatory network of Drp1 and Erbb4 involved in the apoptosis of tumor cells was successfully constructed; the optimal pathway was optimized using Bayesian theory; a total of 446 different types of research results were collected in the Oncomine database, of which there were 18 studies with statistical differences in Drp1 expression, 13 studies with increased Drp1’s expression, and 5 studies with decreased expression. Compared with the control group, Drp1 was expressed in lung cancer tissues highly (P < 0.05).ConclusionEstablishment and optimization of mitochondrial-related Drp1 and tumor-related Erbb4 genes involved in the regulation of apoptosis of cancer cells. It was proposed that Drp1 was expressed in lung cancer tissues highly through in-depth excavation of tumor-associated gene information in the Oncomine gene chip database.     

反义核酸在肿瘤研究中的应用

反义核酸研究已活跃于肿瘤研究及基因治疗领域,反义核酸通过碱基配对待异性地抑制基因表达,因此为研究肿瘤中癌基因和生长因子的功能及癌基因突变检测提供了更为有效的手段,并为肿瘤的基因治疗提供了可能途径.文章综述了反义核酸在基因治疗中所面临的问题及部分解决办法.     

Mixture models for assessing differential expression in complex tissues using microarray data

MOTIVATION: The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous. RESULTS: In this paper, we outline a general framework for determining differential expression in the presence of mixed cell populations. We consider study designs in which paired tissues and unpaired tissues are available. A hierarchical mixture model is used for modeling the data; a combination of methods of moments procedures and the expectation-maximization algorithm are used to estimate the model parameters. The finite-sample properties of the methods are assessed in simulation studies; they are applied to two microarray datasets from cancer studies. Commands in the R language can be downloaded from the URL http://www.sph.umich.edu/~ghoshd/COMPBIO/COMPMIX/.     

Crystallization of human c-H-ras oncogene products

There is compelling evidence that cancer develops as a consequence of genetic changes (probably multiple) in some members of a selected set of cellular genes. DNA isolated from a variety of tumors, but not normal tissues, possesses the ability to malignantly transform non-tumorigenic cells. Many oncogenes responsible for such transformation have been isolated from transformed cell lines and animal and human tumors induced spontaneously, by virus, by chemical, or by radiation. The most commonly found transforming genes isolated from human tumor cells by DNA transfection assay are the ras gene family (c-H-ras, c-K-ras and N-ras). We report crystallization of several human c-H-ras oncogene proteins.     

The HL-60 transforming sequence: a ras oncogene coexisting with altered myc genes in hematopoietic tumors

The oncogene of the HL-60 human promyelocytic leukemia cell line has been passed serially through NIH/3T3 mouse fibroblasts. Oncogene-specific probes prepared from the resulting tertiary transfectants by molecular cloning have been used to show that loss of the transfected oncogene from NIH/3T3 cells correlates with reversion to nontransformed morphology. Analysis of cells transfected by the oncogenes of other tumors and tumor cell lines indicates that the transforming gene of the HL-60 leukemia cell line is closely related to oncogenes of a Burkitt's lymphoma, an acute myelogenous leukemia, an adenocarcinoma of the colon, a neuroblastoma, and two sarcomas. This oncogene is distantly related to the viral oncogenes of Kirsten and Harvey sarcoma viruses. It has been termed N-ras. The active N-ras oncogene coexists with altered versions of the myc oncogene in the HL-60 and AW Ramos human tumors. This suggests a multistep mechanism involving both ras and myc genes in the creation of these tumors.     

Signal transduction events in mammalian cells in response to ionizing radiation

Ionizing radiations elicit a variety of biological effects in mammalian cells. In recent years altered signal transduction has been recognized as a key cellular response to ionizing radiation. Several oncogenes, the products of which are components of signal transduction pathways and which are over-expressed in many tumors, are specifically induced in cells exposed to radiation. It has also become evident that the oncogene ras and the serine/threonine protein kinase oncogenes raf and PKC confer radio-resistance to tumor cells. Modulation of these genes or their activity by natural compounds may offer a strategy to treat cancer by enhancing radiation-induced apoptosis of tumor cells.