本文選題：肺腺癌 + 基因相互作用��； 參考：《山東大學》2016年博士論文

【摘要】：肺癌已成為發(fā)達及發(fā)展中國家和地區(qū)中癌癥患者死亡的最主要原因,而非小細胞肺癌發(fā)病率占據(jù)肺癌的80%。肺腺癌是一種主要的非小細胞肺癌類型,其發(fā)病于細支氣管或肺泡上皮細胞,血運豐富,具有典型的周邊轉(zhuǎn)移性,其死亡率約占肺癌死亡率的50%。生物信息學是整合了信息學、統(tǒng)計學和計算機學等多種技術(shù)分析海量生物數(shù)據(jù)所包含的信息的一門交叉學科。隨著生物信息學的發(fā)展,形成了新的生物學研究模式,即利用現(xiàn)有的數(shù)據(jù)信息,先作理論推測,再行實驗驗證。從分子水平研究疾病的發(fā)生和發(fā)展,進一步指導疾病的預防、診斷和治療。本課題以ArrayExpress數(shù)據(jù)庫為研究基礎(chǔ),篩選肺腺癌患者與正常對照樣本之間的差異表達基因(DEG),聯(lián)合相互作用基因／蛋白檢索工具(STRING)數(shù)據(jù)庫、差異共表達的基因和邊方法(DCGL)、經(jīng)驗貝葉斯法(EB)以及加權(quán)基因共表達網(wǎng)絡分析法(WGCNA)對差異基因之間相互作用關(guān)系進行研究,從而提出構(gòu)建基因相互作用網(wǎng)絡的新方法�；诒磉_分析系統(tǒng)檢測算法(EASE)測試,對異常表達基因進行京都基因與基因組百科全書(KEGG)通路分析。利用合并的新方法和置換檢驗挖掘肺腺癌不同時期(ⅠA、ⅠB、ⅡA、ⅡB、Ⅲ A、 ⅢB和Ⅳ期)激活的通路,為更好地理解肺腺癌的發(fā)病機制提供潛在分子標志和重要信息,為進一步研究肺腺癌的發(fā)生和發(fā)展、診斷及治療提供新的方向。第一部分構(gòu)建肺腺癌基因相互作用網(wǎng)絡的新方法背景：肺癌死亡率占據(jù)惡性腫瘤死亡率首位,肺腺癌是其主要的病理類型之一,肺腺癌發(fā)病率高,五年生存率低,目前靶向藥物治療越來越多地應用到肺腺癌的治療中。近年應用網(wǎng)絡進行癌癥基因表達研究逐漸成為熱點,但僅在差異表達基因?qū)用娌蛔阋蕴骄考膊〉陌l(fā)病機制�；蜷g相互作用關(guān)系對基因的表達具有很大的影響,全面認識基因間直接和間接的相互作用關(guān)系對全面描述細胞機制和功能具有重要的意義。此外,不同的基因相互作用網(wǎng)絡研究方法會導致基因間相互作用關(guān)系研究結(jié)果的不一致。目的：本研究通過對肺腺癌基因表達譜分析,篩選與該腫瘤相關(guān)的差異表達基因,建立構(gòu)建基因相互作用網(wǎng)絡的新方法,獲取可能與肺腺癌關(guān)系密切的相關(guān)基因和信號通路,為進一步研究肺腺癌的分子機制提供理論基礎(chǔ)。方法：從ArrayExpress數(shù)據(jù)庫中下載與肺腺癌相關(guān)的基因表達譜數(shù)據(jù),使用RankProd包篩選差異表達基因。聯(lián)合STRING數(shù)據(jù)庫、DCGL法、EB法和WGCNA方法構(gòu)建差異基因之間相互作用關(guān)系網(wǎng)絡,將四種網(wǎng)絡基因相互作用表達值合并轉(zhuǎn)換后形成新的基因相互作用表達值,根據(jù)新的表達值構(gòu)建了一個新的基因相互作用網(wǎng)絡,從而創(chuàng)造了一種將現(xiàn)有的方法結(jié)合起來的新的算法,稱之為合并的方法。之后對五種網(wǎng)絡進行了拓撲特性分析；并根據(jù)合并的網(wǎng)絡獲取中心節(jié)點基因。對五種方法篩選的基因?qū)M行通路富集分析。結(jié)果：(1)本研究篩選出941個肺腺癌差異表達基因,其中上調(diào)基因386個,下調(diào)基因555個。(2)根據(jù)已有的四種方法分別構(gòu)建了基因相互作用網(wǎng)絡,并成功建立了構(gòu)建基因相互作用網(wǎng)絡的新方法。(3)對比分析了STRING、DCGL、 EB、WGCNA和合并的方法構(gòu)建的基因相互作用網(wǎng)絡的拓撲學特性,結(jié)果表明,五種網(wǎng)絡的節(jié)點度數(shù)經(jīng)曲線擬合后的擬合系數(shù)分別是0.931、0.938、0.963、0.264和0.977,而平均最短路徑長度分別為5.337、2.715、3.673、1.783和4.195。WGCNA方法創(chuàng)建的網(wǎng)絡擁有最短的平均路徑長度,而合并的網(wǎng)絡具有最高的擬合系數(shù)。(4)根據(jù)合并的網(wǎng)絡,篩選出15個中心節(jié)點基因,其中TOP2A、PAICS、BUB1、 ADAM12、FGB、NONO、UGT8、SRPX2、AOC1、AURKA、NCAPG、RACGAP1屬于上調(diào)基因,IL1RL1、TAC1、DARC屬于下調(diào)基因。(5)對941個差異表達基因進行通路富集分析得到7條顯著富集的通路：細胞外基質(zhì)受體相互作用、細胞粘附分子、p53信號通路、粘著斑、血管平滑肌收縮、細胞周期和補體系統(tǒng),通過合并的方法得到的基因?qū)χ饕患诩毎芷谕泛蚉53通路,而五種方法中得到的共同的基因?qū)Ω患耐肥羌毎芷�。結(jié)論：(1)成功篩選出肺腺癌中941個差異表達基因,并對其進行通路富集分析,為更好地理解肺腺癌的分子機制提供理論依據(jù)。(2)成功建立了構(gòu)建基因相互作用網(wǎng)絡的新方法,網(wǎng)絡拓撲學分析結(jié)果顯示,該方法構(gòu)建的網(wǎng)絡擁有更明顯的無標度網(wǎng)絡特征,具有較高的穩(wěn)健性,它能夠提供一個更可靠并可行的結(jié)果,具有廣闊的應用前景；WGCNA方法創(chuàng)建的網(wǎng)絡更具有小世界網(wǎng)絡性質(zhì),能夠?qū)崿F(xiàn)信息的快速集成。(3)篩選出15個中心節(jié)點基因,他們可能與肺腺癌的發(fā)病關(guān)系密切,為進一步研究肺腺癌的發(fā)病機制及治療提供研究方向。(4)差異基因通路富集分析證明細胞周期通路與肺腺癌發(fā)病機制有密切關(guān)系。第二部分肺腺癌發(fā)展過程中激活通路的研究背景：近年來,肺腺癌的發(fā)生率和死亡率不斷提高,大部分患者的治療和預后依舊非常差。肺癌相關(guān)的基因表達譜研究、信號通路研究和靶向治療受到越來越多的關(guān)注,基于網(wǎng)絡的信號通路篩選和分類方法逐漸成熟,在疾病中,信號通路存在激活與未激活兩種狀態(tài),激活的通路在疾病中更積極地發(fā)揮著作用,未激活的通路只是存在于疾病中,可能與此病的發(fā)病機制沒有直接的關(guān)系。因此研究癌癥中激活的通路對癌癥的治療和預防有重要的意義。目的：利用基因相互作用網(wǎng)絡分析及通路活性分析,挖掘肺腺癌發(fā)展進程中激活的信號通路,為肺腺癌的診斷及治療提供分子標志。方法：從ArrayExpress數(shù)據(jù)庫中下載與肺腺癌不同時期相關(guān)的基因表達譜數(shù)據(jù),使用RankProd包篩選差異表達基因。對差異表達基因進行KEGG通路富集分析。以差異表達基因為基礎(chǔ),利用第一部分中得到的新方法構(gòu)建肺腺癌不同時期(ⅠA, ⅠB, IⅡA,ⅡB,Ⅲ A,ⅢB和Ⅳ期)基因相互作用網(wǎng)絡,結(jié)合置換檢驗方法識別富集的通路在肺腺癌的不同時期是否被激活。結(jié)果：(1)本研究篩選出了211個肺腺癌的差異表達基因。(2)在肺腺癌發(fā)展過程的七個不同時期中,基因之間相互作用關(guān)系的多少沒有明顯的變化規(guī)律。(3) KEGG通路富集分析發(fā)現(xiàn)了肺腺癌不同時期的10條共同富集的信號通路,分別是：細胞周期、黃體酮調(diào)節(jié)的卵母細胞成熟、卵母細胞減數(shù)分裂、細胞外基質(zhì)受體相互作用、血管平滑肌收縮、刺激神經(jīng)組織的配體-受體互作、癌癥通路、p53信號通路、腎素血管緊張素系統(tǒng)和腎細胞癌。(4)通路活性分析結(jié)果顯示,細胞周期、黃體酮調(diào)節(jié)的卵母細胞成熟和卵母細胞減數(shù)分裂在肺腺癌疾病的各個時期都被激活。同時,p53信號通路和癌癥通路在大部分時期都是被激活的,除了ⅢA期；但腎素血管緊張素系統(tǒng)通路在各時期都未被激活。結(jié)論：(1)根據(jù)肺腺癌差異表達基因,我們發(fā)現(xiàn)了10條肺腺癌不同時期共同富集的通路。(2)我們成功挖掘了肺腺癌進程中三條共同激活的通路：細胞周期、黃體酮調(diào)節(jié)的卵母細胞成熟和卵母細胞減數(shù)分裂通路,這些通路或許是肺腺癌診斷和治療的潛在標記。
[Abstract]:Lung cancer has become the most important cause of cancer deaths in developed and developing countries and regions. 80%. lung adenocarcinoma, which is not the incidence of small cell lung cancer, is a major non small cell lung cancer, which occurs in bronchioles or alveolar epithelial cells, rich in blood, and with typical peripheral metastases, with a mortality rate of about 50%. bioinformatics of lung cancer mortality is an interdisciplinary subject that integrates Informatics, statistics and computer science to analyze the information contained in mass biological data. With the development of bioinformatics, a new model of biological research has been formed, that is, using the existing data information, first to make theoretical speculation, and then to test it by experiment. Study the occurrence and development of disease from the molecular level and further guide the prevention, diagnosis and treatment of the disease. This subject uses the ArrayExpress database as the basis to screen the differential expression genes (DEG) between the lung adenocarcinoma patients and the normal control samples, and the joint interaction gene / protein retrieval tool (STRING) database. Gene and edge method (DCGL), empirical Bayesian method (EB) and weighted gene co expression network analysis (WGCNA) are used to study the interaction relationship between different genes, and a new method for constructing the gene interaction network is proposed. Based on the expression analysis system detection algorithm (EASE) test, the abnormally expressed genes are in Kyoto gene and base. In order to further study the pathogenesis and development of lung adenocarcinoma and to further study the pathogenesis and development of lung adenocarcinoma, the new method and replacement test of the combined KEGG pathway are used to excavate the pathways activated in the different periods of lung adenocarcinoma (I A, I B, II A, II B, III A, III B and IV). The first part constructs a new method background for the construction of lung adenocarcinoma gene interaction network: lung cancer mortality takes the first place in the mortality of malignant tumors, lung adenocarcinoma is one of the main pathological types, the incidence of lung adenocarcinoma is high, and the five year survival rate is low. At present, targeted drug therapy is more and more applied to the treatment of lung adenocarcinoma. In recent years, the research of gene expression of cancer has become a hot spot in the application of network, but only at the level of differentially expressed genes is not sufficient to explore the pathogenesis of the disease. The INTERGENE interaction has a great influence on the expression of genes. The comprehensive understanding of the direct and indirect interactions between genes is a comprehensive description of the mechanism and function of the cells. It is of great significance. In addition, different methods of gene interaction network can lead to inconsistencies in the results of INTERGENE interaction. Objective: This study screened the differentially expressed genes related to the tumor by analyzing the gene expression profiles of lung adenocarcinoma, and established a new method for constructing the construction gene interaction network. The related genes and signaling pathways that are closely related to lung adenocarcinoma provide a theoretical basis for further study of the molecular mechanisms of lung adenocarcinoma. Methods: downloading gene expression profiles associated with lung adenocarcinoma from the ArrayExpress database and using RankProd packets to screen differentially expressed genes. Combined with STRING database, DCGL, EB and WGCNA methods. Build a new gene interaction network based on the new expression values, and create a new algorithm to combine the existing methods, which is called the combination of the existing methods. After the analysis of the topology characteristics of the five kinds of networks, the central node gene was obtained by the combined network. The gene pairs screened by the five methods were enriched and analyzed. Results: (1) 941 differentially expressed genes of lung adenocarcinoma were screened in this study, including 386 up-regulated and 555 down-regulated genes. (2) according to the existing four formulas. The gene interaction network was constructed respectively, and a new method for constructing the gene interaction network was successfully established. (3) the topological properties of the gene interaction network constructed by STRING, DCGL, EB, WGCNA and the combined method were compared and analyzed. The results showed that the fitting coefficients of the node degrees of the five networks were 0.93 after the curve fitting. 1,0.938,0.963,0.264 and 0.977, and the average shortest path length of the 5.337,2.715,3.673,1.783 and 4.195.WGCNA methods has the shortest average path length, and the merged network has the highest fitting coefficient. (4) according to the merged network, 15 middle heart node genes are screened, including TOP2A, PAICS, BUB1, ADAM12, FGB, NONO. UGT8, SRPX2, AOC1, AURKA, NCAPG, RACGAP1 belong to up-regulated genes, IL1RL1, TAC1, and DARC belong to the down regulated genes. (5) the pathway enrichment analysis of 941 differentially expressed genes obtained 7 significant pathways: extracellular matrix receptor interaction, cell adhesion molecules, p53 signaling pathways, adhesion spots, vascular smooth muscle contraction, cell cycle and supplement. The gene pairs obtained by the combined method are mainly enriched in the cell cycle pathway and the P53 pathway, and the common gene pairs in the five methods are cell cycles. Conclusion: (1) the 941 differentially expressed genes in the lung adenocarcinoma were successfully screened and the pathway was enriched and analyzed to better understand the lung adenocarcinoma. The molecular mechanism provides a theoretical basis. (2) a new method for constructing the gene interaction network has been successfully established. The network topology analysis results show that the network constructed by this method has more obvious characteristics of the scale-free network, and has high robustness. It can provide a more reliable and feasible result, and has a broad application prospect; WGCNA The network created by the method has the nature of small world network and can realize the rapid integration of information. (3) screening out 15 central node genes, they may be closely related to the pathogenesis of lung adenocarcinoma, and provide research direction for further research on pathogenesis and treatment of lung adenocarcinoma. (4) differential gene pathway enrichment analysis proves cell cycle pathway and The pathogenesis of lung adenocarcinoma is closely related. Second the research background of the activation pathway in the development of lung adenocarcinoma: the incidence and mortality of lung adenocarcinoma have been improved in recent years, and the treatment and prognosis of most patients are still very poor. The study of gene expression profiles related to lung cancer, the research of signal pathway and target therapy are more and more. It is concerned that the network based signaling pathway screening and classification methods are gradually mature. In the disease, there are two states of activation and inactivation in the signal pathway. The activated pathway plays a more active role in the disease. The inactivated pathway is only in the disease, and it may not be directly related to the pathogenesis of this disease. The activated pathway is of great significance for the treatment and prevention of cancer. Objective: to use gene interaction network analysis and pathway activity analysis to excavate activated signal pathways in the development of lung adenocarcinoma, and to provide molecular markers for the diagnosis and treatment of lung adenocarcinoma. Method: downloading different periods from ArrayExpress database with lung adenocarcinoma. Related gene expression profiles, using RankProd packets to screen differentially expressed genes. KEGG pathway enrichment and analysis of differentially expressed genes. Based on differentially expressed genes, the gene interaction network of lung adenocarcinoma (I A, I B, I II A, I II A, II B, III A, III B and IV phase) was constructed on the basis of differentially expressed genes. The results were as follows: (1) 211 differentially expressed genes of lung adenocarcinoma were screened in this study. (2) there was no obvious change in the relationship between genes in seven different stages of the development of lung adenocarcinoma. (3) enrichment and analysis of KEGG pathway. 10 common signaling pathways in different stages of lung adenocarcinoma are presented: cell cycle, maturation of oocytes regulated by progesterone, meiosis of oocyte, interaction of extracellular matrix receptor, contraction of vascular smooth muscle, ligand receptor interaction of nerve tissue, cancer pathway, p53 signaling pathway, renin angiotensin System and renal cell carcinoma (4) pathway activity analysis showed that cell cycle, progesterone regulated oocyte maturation and oocyte meiosis were activated at all stages of lung adenocarcinoma, while p53 signaling pathways and cancer pathways were stimulated in most stages, except for stage III A; but renin angiotensin system The pathway was not activated at all times. Conclusion: (1) according to the differentially expressed genes of lung adenocarcinoma, we found 10 common enrichment pathways in different stages of lung adenocarcinoma. (2) we successfully excavated three common pathways in the process of lung adenocarcinoma: cell cycle, progesterone regulated oocyte maturation and oocyte meiosis pathway, These pathways may be potential markers for diagnosis and treatment of lung adenocarcinoma.

【學位授予單位】：山東大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：R734.2

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