口腔鳞状细胞癌的生物信息学分析

发布时间：2018-05-19 04:46

本文选题：口腔鳞状细胞癌 + GO分析　；参考：《山东大学》2014年博士论文

【摘要】：口腔鳞状细胞癌是口腔颌面部最常见的恶性肿瘤。它具有恶性程度高,淋巴结易转移,预后差等特点。从分子水平研究口腔鳞状细胞癌的发生发展,对于口腔鳞状细胞癌的预防、控制和治疗具有重要意义。生物信息学是一门交叉学科。它整合了信息学、统计学和计算机学等多种技术分析海量生物数据所包含的信息。它先对生物芯片的海量数据进行筛选,再采用序列比对、统计分析、生物聚类、通路分析、可视化作图等方式,进行数据挖掘,从而对疾病从分子水平进行分析,丰富对疾病进展的认识。随着生物信息学的发展,形成了新的生物学研究模式,即利用现有的数据信息,先作理论推测,再行实验验证。本研究课题以GEO及TCGA数据库为研究基础,采用BRB-ArrayTools软件分别筛选口腔鳞状细胞癌中差异表达的基因、microRNA及lncRNA,联合生物信息软件和文献挖掘等方法对他们之间相互作用关系进行分析,从而探索与口腔鳞状细胞癌相关的基因、microRNA及lncRNA,为更好地理解口腔鳞状细胞癌发生、发展的分子机制提供重要的信息,为进一步研究口腔鳞状细胞癌的发生、发展提供新的方向。第一部分：口腔鳞状细胞癌差异表达基因的生物信息学分析研究背景：口腔鳞状细胞癌是目前我国常见的肿瘤之一。我国口腔鳞状细胞癌的发病率约在3.6/10万-8.0/10万人。现已证实,口腔鳞状细胞癌是复杂的多基因疾病,环境因素和遗传因素共同参与了疾病的发生和发展。基因芯片因其具有高通量、高特异性、快速等特点,可检测基因的丰度和种类,并从整个基因组层面进行相关分析。目的：通过对多个口腔鳞状细胞癌表达芯片的生物信息学分析,筛选与该肿瘤相关的差异表达基因,对差异表达基因进行功能注释、通路分析及蛋白质互作网络分析,为探索口腔鳞状细胞癌发生、发展的分子机制提供理论基础。方法：本课题整理GEO公共数据库的基因芯片数据集,以针对口腔鳞状细胞癌目标的Affymetrix芯片表达谱数据作为研究对象,系统地分析口腔鳞状细胞癌的基因表达谱芯片数据,进行数据预处理后,选择非配对t检验统计方法筛选差异表达基因,应用DAVID软件选取GO数据库进行功能注释、KEGG数据库进行通路分析,导入STRING在线数据库绘制差异表达基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。结果：(1)本研究在口腔鳞状细胞癌中发现92个基因表达异常,其中表达上调的61个,表达下调的31个。(2)GO分析发现表达上调的差异表达基因主要集中在对损伤的反应、胶原代谢过程、多细胞生物大分子代谢过程等。其中参与胶原代谢过程有MMP9、MMP1、MMP10、MMP11、MMP3、MMP7等基因。KEGG通路分析发现,表达上调的差异表达基因主要集中在细胞外基质受体相互作用、黏着斑、肿瘤通路、Toller样受体通路等通路。(3)GO分析发现表达下调的差异表达基因主要集中在上皮细胞分化、上皮发育、表皮发育、外胚层发育等过程。KEGG通路分析发现,表达下调的差异表达基因主要集中在通过视黄醇的代谢、细胞色素p450外源性物质代谢、药物代谢等通路。(4)经STRING软件共筛选出35个差异表达基因编码的蛋白产物存在相互作用,构建差异表达基因互作网络图,Cytoscape软件共筛选五个关键基因,分别为MMP-9、MMP-1、 COL1A2、MMP-7、PLAU。结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的92个基因,并对其进行功能注释与通路分析,为该疾病的实验室研究提供了理论基础。(2)成功构建口腔鳞状细胞癌差异表达基因的蛋白质相互作用网络,并筛选出五个关键基因,提示MMPs家族成员可能参与在口腔鳞状细胞癌发展过程,有利于进一步研究差异表达基因的相互作用关系,并为该疾病的诊断和治疗提供了研究方向。第二部分口腔鳞状细胞癌差异表达microRNA的生物信息学分析研究背景：microRNA是内源性非编码小RNA(18-25nt)的总称。microRNA通过转录后抑制基因的表达。它可以通过与靶基因mRNA的3’端非翻译区(3'-untranslationalregion,3'-UTR)结合达到抑制蛋白翻译的作用。目前发现miRNA可调节约60%的基因,且可能与多种不同的靶基因有调控关系。越来越多的研究发现,miRNA在细胞的生长、分化、增殖和调亡等重要过程发挥了重要的作用,并参与了肿瘤的发生发展过程。目的：通过整理TCGA数据库的口腔鳞状细胞癌miRNA数据,并进行生物信息学分析,探索口腔鳞状细胞癌差异表达miRNA,进一步研究其靶基因的作用。方法：本研究利用BRB-ArrayTools对来自TCGA数据库的口腔鳞状细胞癌miRNA进行分析,得到差异表达miRNA;通过miRecords预测差异miRNA的靶基因,对差异靶基因进行GO功能注释、KEGG通路分析,应用STRING在线数据库绘制靶基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。结果：(1)采用BRB-ArrayTools分析TCGA数据集中miRNA表达谱的数据,我们发现了53个显著差异的miRNA。(2)针对差异靶基因的GO功能注释发现,差异表达的靶基因参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)KEGG通路分析中,差异表达靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)经STRING软件在线数据库分析共筛选出73个差异表达microRNA的靶基因存在相互作用,构建靶基因编码蛋白互作网络图；Cytoscape软件共筛选出十二个关键靶基因,分别为STAT3, CCND1, PTGS2, IL8, PPARG, ERBB2, MMP2, PLAU, FGF1, CASP3, FASLG和IL10. 结论：(1)成功筛选口腔鳞状细胞癌中差异表达的microRNA。其中,miR-375可能是口腔鳞状细胞癌分子标志物。miR-21、miR-101、let-7c和mir-200c表达异常为研究口腔鳞状细胞癌EMT过程提供了生物信息学证据。(2)差异表达microRNA的靶基因主要参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)差异表达microRNA的靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)成功构建差异表达microRNA对应靶基因的蛋白质相互作用网络图,并筛选出12个关键靶基因。第三部分口腔鳞状细胞癌差异表达长链非编码RNA的生物信息学分析研究背景：长链非编码RNA (long non-coding RNA, lncRNA)因其在生物基因调控方面的潜在巨大作用,在近几年获得广泛关注。研究显示长链非编码RNA和疾病发生及发展进程相关,但是其发挥作用的具体机制尚不十分清楚。目前lncRNA在口腔鳞状细胞癌中作用及机制知之甚少。目的：本研究拟通过生物信息学的方法,分析GEO数据库中的口腔鳞状细胞癌数据,探索口腔鳞状细胞癌中的差异表达lncRNA,为后续研究lncRNA在口腔鳞状细胞癌中的作用机制提供了新的思路。方法：本研究利用BRB-ArrayTools对GEO数据库的口腔鳞状细胞癌数据集进行分析,筛选得到差异lncRNA。结果：本部分研究发现,与正常组织相比,口腔鳞状细胞癌17个lncRNA的表达出现差异。其中表达上调的有4个,表达下调的有13个。H19在口腔鳞状细胞癌中表达显著下调。结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的lncRNA17个,为进一步研究lncRNA在该疾病中的作用提供了方向。(2)LncRNA H19在口腔鳞状细胞癌中表达下调,提示其可能与mir-200家族作用,调控了口腔鳞状细胞癌上皮-间质转变(EMT)的生物学过程。
[Abstract]:Oral squamous cell carcinoma is the most common malignant tumor in the oral and maxillofacial region. It has the characteristics of high malignancy, easy lymph node metastasis and poor prognosis. It is of great significance to study the development of oral squamous cell carcinoma at the molecular level and to prevent, control and treat oral squamous cell carcinoma.
Bioinformatics is a cross discipline. It integrates information science, statistics and computer science to analyze the information contained in mass biological data. It first filters the mass data of biochip, and then uses sequence alignment, statistical analysis, biological clustering, path analysis, visualization as map and so on. With the development of the bioinformatics, a new model of biological research has been formed with the development of bioinformatics, that is to use the existing data information to make theoretical speculation first, and then test it by experiment.
Based on the GEO and TCGA database, this research uses BRB-ArrayTools software to select the differentially expressed genes in oral squamous cell carcinoma, microRNA and lncRNA, combined with biological information software and literature mining to analyze the interaction relationship between them, so as to explore the base of oral squamous cell carcinoma. MicroRNA and lncRNA provide important information for a better understanding of the molecular mechanisms of the development of oral squamous cell carcinoma, and provide a new direction for further research on the development of oral squamous cell carcinoma.
Part one: bioinformatics analysis of differentially expressed genes in oral squamous cell carcinoma
Background: oral squamous cell carcinoma is one of the common tumors in China. The incidence of oral squamous cell carcinoma in China is about 3.6/10 10000 -8.0/10 million people. It has been proved that oral squamous cell carcinoma is a complex polygenic disease. Environmental and genetic factors are involved in the occurrence and development of the disease. The characteristics of flux, high specificity and rapidness can be used to detect the abundance and species of genes and analyze them from the whole genome level.
Objective: through the bioinformatics analysis of multiple oral squamous cell carcinoma expression chips, the differential expression genes related to the tumor were screened, the functional annotation of differentially expressed genes, pathway analysis and protein interaction network analysis were used to provide a theoretical basis for the exploration of the molecular mechanism of the development of oral squamous cell carcinoma.
Methods: this topic collate the gene chip data set of the GEO public database, take the Affymetrix chip expression data of the oral squamous cell carcinoma target as the research object, systematically analyze the gene expression chip data of the oral squamous cell carcinoma, and select the non paired t test statistics to select the difference table after the data preprocessing. DAVID software is used to select GO database for functional annotation, KEGG database is used for path analysis, and STRING online database is introduced to draw the network diagram of differentially expressed gene encoding protein, and the topology characteristics of network and each node are calculated by using Cytoscape software.
Results: (1) in this study, 92 genes were found in oral squamous cell carcinoma, including 61 up-regulated and 31 down-regulation. (2) GO analysis found that the differentially expressed genes were mainly concentrated in the response to injury, collagen metabolism, and the metabolic process of multicellular macromolecules. MMP9, MMP1, MMP10, MMP11, MMP3, MMP7 and other gene.KEGG pathway analysis showed that the up-regulated differentially expressed genes were mainly concentrated in the extracellular matrix receptor interaction, plaque, tumor pathway, Toller like receptor pathway. (3) GO analysis found that the differentially expressed genes were mainly concentrated in epithelial cell differentiation and epithelial development. The.KEGG pathway analysis of epidermal development and ectoderm development found that the differentially expressed genes expressed mainly concentrated in the metabolism of retinol, the metabolism of cytochrome P450 exogenous substances, and the pathway of drug metabolism. (4) a total of 35 differentially expressed protein products were screened by STRING software to interact with each other, and the construction was poor. The Cytoscape software interactively screened five key genes, namely MMP-9, MMP-1, COL1A2, MMP-7, PLAU..
Conclusions: (1) the 92 genes differentially expressed in oral squamous cell carcinoma were successfully screened, and the functional annotation and pathway analysis were used to provide a theoretical basis for the laboratory study of the disease. (2) a protein phase interaction network of differentially expressed genes in oral squamous cell carcinoma was successfully constructed and five key genes were screened for MMPs. Family members may be involved in the development of oral squamous cell carcinoma, which is beneficial to further study the interaction of differentially expressed genes and provide a research direction for the diagnosis and treatment of the disease.
Second part bioinformatics analysis of differential expression of microRNA in oral squamous cell carcinoma
Background: microRNA is the expression of the endogenous non coding small RNA (18-25nt) general name.MicroRNA through the posttranscriptional suppressor gene. It can inhibit protein translation by binding to the target gene mRNA's 3 'terminal non translation region (3'-untranslationalregion, 3'-UTR). It is found that miRNA can regulate about 60% of the gene and may be more likely to be associated with more than the target gene mRNA. More and more studies have shown that miRNA plays an important role in cell growth, differentiation, proliferation and apoptosis, and has been involved in the process of tumor development.
Objective: To explore the differential expression of miRNA for oral squamous cell carcinoma (OSCC) and to further study the role of the target gene by sorting out the miRNA data of the oral squamous cell carcinoma of the TCGA database and analyzing the bioinformatics.
Methods: using BRB-ArrayTools to analyze the miRNA of oral squamous cell carcinoma from TCGA database, the differential expression of miRNA was obtained. The target genes of differential miRNA were predicted by miRecords, GO function annotated on the differential target genes, KEGG pathway analysis, and the interaction network diagram of target gene encoding protein was plotted by STRING Online database. Cytoscape software is used to calculate the topological characteristics of the network and nodes.
Results: (1) using BRB-ArrayTools analysis of the data of miRNA expression profiles in TCGA data concentration, we found that 53 significant differences were found in miRNA. (2) for the GO function annotation of differential target genes. The differentially expressed target genes were involved in the regulation of cell proliferation, endogenous stimulus response, organic matter response, hormone stimulation response and so on. (3) KEGG pass. In road analysis, the differentially expressed target genes were mainly involved in the interaction of cytokines and their receptors, MAPK signaling pathway, Wnt signaling pathway, and Jak-STAT signaling pathway. (4) the interaction of 73 differentially expressed microRNA target genes was screened by the STRING software online database analysis, and the interaction network diagram of the target gene encoding protein was constructed; Cyto Scape software screened twelve key target genes, namely STAT3, CCND1, PTGS2, IL8, PPARG, ERBB2, MMP2, PLAU, FGF1, CASP3, CASP3 and PLAU.
Conclusions: (1) the differential expression of microRNA. in oral squamous cell carcinoma is successfully screened, and miR-375 may be the molecular marker of oral squamous cell carcinoma.MiR-21, miR-101, Let-7c and mir-200c expression to provide bioinformatics evidence for the study of EMT process in oral squamous cell carcinoma. (2) the target genes for differentially expressed microRNA are mainly involved in the cells. Regulation of proliferation, endogenous stimulus response, organic matter response, hormone stimulation response and other functions. (3) the target genes of differential expression of microRNA are mainly involved in the interaction of cytokines and their receptors, MAPK signaling pathway, Wnt signaling pathway, Jak-STAT signaling pathway. (4) the protein interaction of differentially expressed microRNA corresponding target genes is constructed. The network map was used and 12 key target genes were screened.
The third part is bioinformatics analysis of differential expression of long chain non coding RNA in oral squamous cell carcinoma.
Background: long chain non coding RNA (long non-coding RNA, lncRNA) has gained wide attention in recent years because of its potential role in biological gene regulation. The study shows that long chain non coding RNA is related to the development and development of disease, but the mechanism of its role is not very clear. At present, lncRNA is in the oral squamous cell. There is little knowledge about the role and mechanism of cell carcinoma.
Objective: To explore the differential expression of lncRNA in oral squamous cell carcinoma (OSCC) by analyzing the data of oral squamous cell carcinoma in GEO database by bioinformatics, and to provide a new idea for the follow-up study of the mechanism of lncRNA in oral squamous cell carcinoma.
Methods: the data of oral squamous cell carcinoma (OSCC) in GEO database were analyzed by BRB-ArrayTools and screened for differential lncRNA..
Results: this part of the study found that the expression of 17 lncRNA in oral squamous cell carcinoma was different from that of normal tissues, of which 4 were up regulated, and 13.H19 down regulated significantly in oral squamous cell carcinoma.
Conclusions: (1) the differential expression of lncRNA17 in oral squamous cell carcinoma is successfully screened, which provides a direction for further study of the role of lncRNA in the disease. (2) LncRNA H19 is down regulated in oral squamous cell carcinoma, suggesting that it may be associated with the role of miR-200 family and regulates the biology of epithelial mesenchymal transition (EMT) of oral squamous cell carcinoma (EMT). Process.
【学位授予单位】：山东大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：R739.8

【共引文献】