本文選題：口腔鱗狀細(xì)胞癌 + GO分析�。� 參考：《山東大學(xué)》2014年博士論文

【摘要】：口腔鱗狀細(xì)胞癌是口腔頜面部最常見(jiàn)的惡性腫瘤。它具有惡性程度高,淋巴結(jié)易轉(zhuǎn)移,預(yù)后差等特點(diǎn)。從分子水平研究口腔鱗狀細(xì)胞癌的發(fā)生發(fā)展,對(duì)于口腔鱗狀細(xì)胞癌的預(yù)防、控制和治療具有重要意義。 生物信息學(xué)是一門交叉學(xué)科。它整合了信息學(xué)、統(tǒng)計(jì)學(xué)和計(jì)算機(jī)學(xué)等多種技術(shù)分析海量生物數(shù)據(jù)所包含的信息。它先對(duì)生物芯片的海量數(shù)據(jù)進(jìn)行篩選,再采用序列比對(duì)、統(tǒng)計(jì)分析、生物聚類、通路分析、可視化作圖等方式,進(jìn)行數(shù)據(jù)挖掘,從而對(duì)疾病從分子水平進(jìn)行分析,豐富對(duì)疾病進(jìn)展的認(rèn)識(shí)。隨著生物信息學(xué)的發(fā)展,形成了新的生物學(xué)研究模式,即利用現(xiàn)有的數(shù)據(jù)信息,先作理論推測(cè),再行實(shí)驗(yàn)驗(yàn)證。 本研究課題以GEO及TCGA數(shù)據(jù)庫(kù)為研究基礎(chǔ),采用BRB-ArrayTools軟件分別篩選口腔鱗狀細(xì)胞癌中差異表達(dá)的基因、microRNA及l(fā)ncRNA,聯(lián)合生物信息軟件和文獻(xiàn)挖掘等方法對(duì)他們之間相互作用關(guān)系進(jìn)行分析,從而探索與口腔鱗狀細(xì)胞癌相關(guān)的基因、microRNA及l(fā)ncRNA,為更好地理解口腔鱗狀細(xì)胞癌發(fā)生、發(fā)展的分子機(jī)制提供重要的信息,為進(jìn)一步研究口腔鱗狀細(xì)胞癌的發(fā)生、發(fā)展提供新的方向。 第一部分：口腔鱗狀細(xì)胞癌差異表達(dá)基因的生物信息學(xué)分析 研究背景：口腔鱗狀細(xì)胞癌是目前我國(guó)常見(jiàn)的腫瘤之一。我國(guó)口腔鱗狀細(xì)胞癌的發(fā)病率約在3.6/10萬(wàn)-8.0/10萬(wàn)人�，F(xiàn)已證實(shí),口腔鱗狀細(xì)胞癌是復(fù)雜的多基因疾病,環(huán)境因素和遺傳因素共同參與了疾病的發(fā)生和發(fā)展�；蛐酒蚱渚哂懈咄俊⒏咛禺愋�、快速等特點(diǎn),可檢測(cè)基因的豐度和種類,并從整個(gè)基因組層面進(jìn)行相關(guān)分析。 目的：通過(guò)對(duì)多個(gè)口腔鱗狀細(xì)胞癌表達(dá)芯片的生物信息學(xué)分析,篩選與該腫瘤相關(guān)的差異表達(dá)基因,對(duì)差異表達(dá)基因進(jìn)行功能注釋、通路分析及蛋白質(zhì)互作網(wǎng)絡(luò)分析,為探索口腔鱗狀細(xì)胞癌發(fā)生、發(fā)展的分子機(jī)制提供理論基礎(chǔ)。 方法：本課題整理GEO公共數(shù)據(jù)庫(kù)的基因芯片數(shù)據(jù)集,以針對(duì)口腔鱗狀細(xì)胞癌目標(biāo)的Affymetrix芯片表達(dá)譜數(shù)據(jù)作為研究對(duì)象,系統(tǒng)地分析口腔鱗狀細(xì)胞癌的基因表達(dá)譜芯片數(shù)據(jù),進(jìn)行數(shù)據(jù)預(yù)處理后,選擇非配對(duì)t檢驗(yàn)統(tǒng)計(jì)方法篩選差異表達(dá)基因,應(yīng)用DAVID軟件選取GO數(shù)據(jù)庫(kù)進(jìn)行功能注釋、KEGG數(shù)據(jù)庫(kù)進(jìn)行通路分析,導(dǎo)入STRING在線數(shù)據(jù)庫(kù)繪制差異表達(dá)基因編碼蛋白互作網(wǎng)絡(luò)圖,并應(yīng)用Cytoscape軟件計(jì)算網(wǎng)絡(luò)及各節(jié)點(diǎn)的拓?fù)涮匦浴?結(jié)果：(1)本研究在口腔鱗狀細(xì)胞癌中發(fā)現(xiàn)92個(gè)基因表達(dá)異常,其中表達(dá)上調(diào)的61個(gè),表達(dá)下調(diào)的31個(gè)。(2)GO分析發(fā)現(xiàn)表達(dá)上調(diào)的差異表達(dá)基因主要集中在對(duì)損傷的反應(yīng)、膠原代謝過(guò)程、多細(xì)胞生物大分子代謝過(guò)程等。其中參與膠原代謝過(guò)程有MMP9、MMP1、MMP10、MMP11、MMP3、MMP7等基因。KEGG通路分析發(fā)現(xiàn),表達(dá)上調(diào)的差異表達(dá)基因主要集中在細(xì)胞外基質(zhì)受體相互作用、黏著斑、腫瘤通路、Toller樣受體通路等通路。(3)GO分析發(fā)現(xiàn)表達(dá)下調(diào)的差異表達(dá)基因主要集中在上皮細(xì)胞分化、上皮發(fā)育、表皮發(fā)育、外胚層發(fā)育等過(guò)程。KEGG通路分析發(fā)現(xiàn),表達(dá)下調(diào)的差異表達(dá)基因主要集中在通過(guò)視黃醇的代謝、細(xì)胞色素p450外源性物質(zhì)代謝、藥物代謝等通路。(4)經(jīng)STRING軟件共篩選出35個(gè)差異表達(dá)基因編碼的蛋白產(chǎn)物存在相互作用,構(gòu)建差異表達(dá)基因互作網(wǎng)絡(luò)圖,Cytoscape軟件共篩選五個(gè)關(guān)鍵基因,分別為MMP-9、MMP-1、 COL1A2、MMP-7、PLAU。 結(jié)論：(1)成功篩選出口腔鱗狀細(xì)胞癌中差異表達(dá)的92個(gè)基因,并對(duì)其進(jìn)行功能注釋與通路分析,為該疾病的實(shí)驗(yàn)室研究提供了理論基礎(chǔ)。(2)成功構(gòu)建口腔鱗狀細(xì)胞癌差異表達(dá)基因的蛋白質(zhì)相互作用網(wǎng)絡(luò),并篩選出五個(gè)關(guān)鍵基因,提示MMPs家族成員可能參與在口腔鱗狀細(xì)胞癌發(fā)展過(guò)程,有利于進(jìn)一步研究差異表達(dá)基因的相互作用關(guān)系,并為該疾病的診斷和治療提供了研究方向。 第二部分口腔鱗狀細(xì)胞癌差異表達(dá)microRNA的生物信息學(xué)分析 研究背景：microRNA是內(nèi)源性非編碼小RNA(18-25nt)的總稱。microRNA通過(guò)轉(zhuǎn)錄后抑制基因的表達(dá)。它可以通過(guò)與靶基因mRNA的3’端非翻譯區(qū)(3'-untranslationalregion,3'-UTR)結(jié)合達(dá)到抑制蛋白翻譯的作用。目前發(fā)現(xiàn)miRNA可調(diào)節(jié)約60%的基因,且可能與多種不同的靶基因有調(diào)控關(guān)系。越來(lái)越多的研究發(fā)現(xiàn),miRNA在細(xì)胞的生長(zhǎng)、分化、增殖和調(diào)亡等重要過(guò)程發(fā)揮了重要的作用,并參與了腫瘤的發(fā)生發(fā)展過(guò)程。 目的：通過(guò)整理TCGA數(shù)據(jù)庫(kù)的口腔鱗狀細(xì)胞癌miRNA數(shù)據(jù),并進(jìn)行生物信息學(xué)分析,探索口腔鱗狀細(xì)胞癌差異表達(dá)miRNA,進(jìn)一步研究其靶基因的作用。 方法：本研究利用BRB-ArrayTools對(duì)來(lái)自TCGA數(shù)據(jù)庫(kù)的口腔鱗狀細(xì)胞癌miRNA進(jìn)行分析,得到差異表達(dá)miRNA;通過(guò)miRecords預(yù)測(cè)差異miRNA的靶基因,對(duì)差異靶基因進(jìn)行GO功能注釋、KEGG通路分析,應(yīng)用STRING在線數(shù)據(jù)庫(kù)繪制靶基因編碼蛋白互作網(wǎng)絡(luò)圖,并應(yīng)用Cytoscape軟件計(jì)算網(wǎng)絡(luò)及各節(jié)點(diǎn)的拓?fù)涮匦浴?結(jié)果：(1)采用BRB-ArrayTools分析TCGA數(shù)據(jù)集中miRNA表達(dá)譜的數(shù)據(jù),我們發(fā)現(xiàn)了53個(gè)顯著差異的miRNA。(2)針對(duì)差異靶基因的GO功能注釋發(fā)現(xiàn),差異表達(dá)的靶基因參與細(xì)胞增殖的調(diào)節(jié)、內(nèi)源性刺激應(yīng)答、有機(jī)物質(zhì)應(yīng)答、激素刺激應(yīng)答等功能。(3)KEGG通路分析中,差異表達(dá)靶基因主要參與了細(xì)胞因子及其受體的相互作用、MAPK信號(hào)通路、Wnt信號(hào)通路、Jak-STAT信號(hào)通路。(4)經(jīng)STRING軟件在線數(shù)據(jù)庫(kù)分析共篩選出73個(gè)差異表達(dá)microRNA的靶基因存在相互作用,構(gòu)建靶基因編碼蛋白互作網(wǎng)絡(luò)圖；Cytoscape軟件共篩選出十二個(gè)關(guān)鍵靶基因,分別為STAT3, CCND1, PTGS2, IL8, PPARG, ERBB2, MMP2, PLAU, FGF1, CASP3, FASLG和IL10. 結(jié)論：(1)成功篩選口腔鱗狀細(xì)胞癌中差異表達(dá)的microRNA。其中,miR-375可能是口腔鱗狀細(xì)胞癌分子標(biāo)志物。miR-21、miR-101、let-7c和mir-200c表達(dá)異常為研究口腔鱗狀細(xì)胞癌EMT過(guò)程提供了生物信息學(xué)證據(jù)。(2)差異表達(dá)microRNA的靶基因主要參與細(xì)胞增殖的調(diào)節(jié)、內(nèi)源性刺激應(yīng)答、有機(jī)物質(zhì)應(yīng)答、激素刺激應(yīng)答等功能。(3)差異表達(dá)microRNA的靶基因主要參與了細(xì)胞因子及其受體的相互作用、MAPK信號(hào)通路、Wnt信號(hào)通路、Jak-STAT信號(hào)通路。(4)成功構(gòu)建差異表達(dá)microRNA對(duì)應(yīng)靶基因的蛋白質(zhì)相互作用網(wǎng)絡(luò)圖,并篩選出12個(gè)關(guān)鍵靶基因。 第三部分口腔鱗狀細(xì)胞癌差異表達(dá)長(zhǎng)鏈非編碼RNA的生物信息學(xué)分析 研究背景：長(zhǎng)鏈非編碼RNA (long non-coding RNA, lncRNA)因其在生物基因調(diào)控方面的潛在巨大作用,在近幾年獲得廣泛關(guān)注。研究顯示長(zhǎng)鏈非編碼RNA和疾病發(fā)生及發(fā)展進(jìn)程相關(guān),但是其發(fā)揮作用的具體機(jī)制尚不十分清楚。目前l(fā)ncRNA在口腔鱗狀細(xì)胞癌中作用及機(jī)制知之甚少。 目的：本研究擬通過(guò)生物信息學(xué)的方法,分析GEO數(shù)據(jù)庫(kù)中的口腔鱗狀細(xì)胞癌數(shù)據(jù),探索口腔鱗狀細(xì)胞癌中的差異表達(dá)lncRNA,為后續(xù)研究lncRNA在口腔鱗狀細(xì)胞癌中的作用機(jī)制提供了新的思路。 方法：本研究利用BRB-ArrayTools對(duì)GEO數(shù)據(jù)庫(kù)的口腔鱗狀細(xì)胞癌數(shù)據(jù)集進(jìn)行分析,篩選得到差異lncRNA。 結(jié)果：本部分研究發(fā)現(xiàn),與正常組織相比,口腔鱗狀細(xì)胞癌17個(gè)lncRNA的表達(dá)出現(xiàn)差異。其中表達(dá)上調(diào)的有4個(gè),表達(dá)下調(diào)的有13個(gè)。H19在口腔鱗狀細(xì)胞癌中表達(dá)顯著下調(diào)。 結(jié)論：(1)成功篩選出口腔鱗狀細(xì)胞癌中差異表達(dá)的lncRNA17個(gè),為進(jìn)一步研究lncRNA在該疾病中的作用提供了方向。(2)LncRNA H19在口腔鱗狀細(xì)胞癌中表達(dá)下調(diào),提示其可能與mir-200家族作用,調(diào)控了口腔鱗狀細(xì)胞癌上皮-間質(zhì)轉(zhuǎn)變(EMT)的生物學(xué)過(guò)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.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：R739.8

【共引文獻(xiàn)】

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1 ;Studies on the Expression of MMP-9 and Significance of a Macrophage Assay in Oral Squamous Cell Carcinoma[J];Chinese Journal of Clinical Oncology;2007年05期

2 凌軍軍;周燕;常傲霜;趙厚育;卓賢露;;鋅指轉(zhuǎn)錄因子Snail在頭頸鱗狀細(xì)胞癌組織中的表達(dá)及與血管生成的關(guān)系[J];中國(guó)耳鼻咽喉頭頸外科;2012年05期

3 趙榮志;吳志浩;周清華;;上皮細(xì)胞間質(zhì)化與腫瘤的轉(zhuǎn)移[J];中國(guó)肺癌雜志;2011年07期

4 郭融;汪希鵬;;上皮間充質(zhì)轉(zhuǎn)化在上皮性卵巢腫瘤侵襲和轉(zhuǎn)移中的作用[J];國(guó)際婦產(chǎn)科學(xué)雜志;2012年01期

5 周紅;許文;陳小娥;;瘢痕疙瘩同位素治療方法的臨床研究[J];東南國(guó)防醫(yī)藥;2013年04期

6 蔡建英;楊效東;周明川;;上調(diào)miR-21表達(dá)水平對(duì)胃癌Kato Ⅲ細(xì)胞中CD44 mRNA及蛋白表達(dá)的影響[J];吉林大學(xué)學(xué)報(bào)(醫(yī)學(xué)版);2013年04期

7 蔣國(guó)燕;李瑾;施露;曹進(jìn);張獻(xiàn)全;;RNAi沉默MACC1基因表達(dá)抑制乳腺癌MCF-7細(xì)胞增殖和遷移[J];第三軍醫(yī)大學(xué)學(xué)報(bào);2013年18期

8 崔永奇;耿沁;顧愛(ài)琴;朱淼鑫;孔韓衛(wèi);孫磊;劉蕾;閆明霞;姚明;;肺腺癌骨轉(zhuǎn)移裸小鼠模型的建立及MicroCT觀察[J];中國(guó)肺癌雜志;2013年09期

9 李海明;;動(dòng)態(tài)增強(qiáng)MRI在卵巢腫瘤中的研究進(jìn)展[J];放射學(xué)實(shí)踐;2013年09期

10 李艷華;魏素菊;;凝血功能與非小細(xì)胞肺癌相關(guān)機(jī)制研究進(jìn)展[J];中國(guó)肺癌雜志;2013年12期

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1 李瀚e，

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