本文選題：EBV　切入點(diǎn)：淋巴細(xì)胞　出處：《南華大學(xué)》2012年碩士論文

【摘要】：目的：檢測分析Scid小鼠體內(nèi)EBV相關(guān)淋巴瘤和正常人淋巴細(xì)胞兩者宿主細(xì)胞的差異表達(dá)基因，篩選EBV誘發(fā)淋巴瘤的候選關(guān)鍵基因，探討EBV相關(guān)淋巴瘤發(fā)生的可能分子機(jī)制。 方法：采集健康獻(xiàn)血員新鮮血液樣本，分離出人淋巴細(xì)胞，分別保存正常淋巴細(xì)胞，復(fù)制Scid小鼠體內(nèi)EBV相關(guān)淋巴瘤模型。采用4×44K的Agilent人類全基因組表達(dá)譜芯片進(jìn)行檢測，分析Scid小鼠體內(nèi)EBV相關(guān)淋巴瘤和正常人淋巴細(xì)胞的差異表達(dá)基因，篩選出fold change≥2的基因?yàn)楸磉_(dá)顯著上調(diào)基因，F(xiàn)old change≤0.5為表達(dá)顯著下調(diào)基因。運(yùn)用GO分類、KEGG代謝通路、Biocarta和Reactom調(diào)控通路及DAVID在線軟件對差異基因進(jìn)行功能聚類及通路分析，并結(jié)合STRING、Cytscape分析差異基因的相互作用，預(yù)測差異基因的生物學(xué)功能。 結(jié)果：1、病理學(xué)診斷Scid小鼠體內(nèi)誘發(fā)腫瘤為彌漫大B細(xì)胞淋巴瘤，且PCR證實(shí)此淋巴瘤為人源性，成功復(fù)制體內(nèi)EBV相關(guān)淋巴瘤實(shí)驗(yàn)?zāi)Ｐ汀?例樣本標(biāo)準(zhǔn)化數(shù)據(jù)均采用LIMMA、BRB-Random Variance Model、SAM軟件篩選差異表達(dá)基因，以PDR0.001共篩選出差異表達(dá)探針3928個(gè)。將未映射到HUGO的Probe剔除，再選取fold-change2倍變化視為表達(dá)差異顯著，共篩選出202個(gè)差異表達(dá)基因，其中上調(diào)基因44個(gè)，下調(diào)基因158個(gè)，系統(tǒng)構(gòu)建了6例同源EBV相關(guān)淋巴瘤（T）和正常淋巴細(xì)胞（N）的差異基因表達(dá)譜。 2．差異表達(dá)基因的生物信息學(xué)分析 Gene Ontology分類的BP分析顯示，共30個(gè)上調(diào)基因參與27個(gè)BP分類，，其中與細(xì)胞周期和有絲分裂相關(guān)的“cell cycle”,“cell cycle phase”,“nucleardivision”,“mitosis”,“M phase of mitotic cell cycle”,“cell cycle process”,“organellefission”,“M phase”和“mitotic cell cycle”等10個(gè)GO BP分類的EASE score最低，均2.6E-09。上調(diào)基因CDC6, KIFC1, OIP5, NCAPG, KIF15, BUB1, CDCA2,AURKA, CEP55, PBK參與多個(gè)與細(xì)胞周期相關(guān)的生物過程。126個(gè)下調(diào)基因參與116個(gè)BP分類，其中“inflammatory response”,“response to wounding”,“immune response”,“defense response”,“taxis”,“chemotaxis”,“regulation ofsecretion”,“behavior”,“anti-apoptosis”和“protein kinase cascade”的EASE Score得分最低，均1.6E-04。下調(diào)基因CSF2, CCL2, CXCL5, CXCL2, TLR2, FCN1,LILRA5, IL1RAP, IL1B, THBS1, CFD, PTX3, FCGR3A, IL1A, IL1RN等主要與細(xì)胞損傷、炎癥反應(yīng)、免疫應(yīng)答等生物學(xué)過程相關(guān)。 25個(gè)上調(diào)基因參與13個(gè)MF分類，其中主要涉及核酸結(jié)合活性，如“ATPbinding”,“adenyl ribonucleotide binding”,“adenyl nucleotide binding”,“purinenucleoside binding”和“nucleoside binding”的EASE Score得分最低，均0.006。參與多個(gè)分子功能的基因有CDC6, KIFC1, KIF15, BUB1, AURKA,PBK,TOP2A, GSG2, RAD51。123個(gè)下調(diào)基因參與12個(gè)MF分類，其中主要涉及分子信號(hào)與細(xì)胞因子受體結(jié)合，如“carbohydrate binding”,“cytokine binding”,“polysaccharide binding”,“protein binding”和“glycosaminoglycan binding”,“cytokine activity”“,interleukin-1receptor binding”的EASE Score的得分最低，均0.001。參與多種分子功能的基因有SELP, TNFAIP6, CCL2, C6ORF25, TLR2,PTX3, THBS1, NLRP3, IL1RN, IL1B, IL1A。 利用“KEGG Pathway”,“BioCarta”和“Reactome”進(jìn)行Pathway分析顯示，當(dāng)EASE Score0.05時(shí)，上調(diào)基因中不參與“KEGG-pathway”，2個(gè)基因參與1條“BioCarta-pathway”，5個(gè)基因參與1條“Reactome-pathway”；下調(diào)基因中64個(gè)基因參與7條“KEGG-pathway”，30個(gè)基因參與1條“BioCarta-pathway”，33個(gè)基因參與2條“Reactome-pathway”。 將上調(diào)和下調(diào)差異表達(dá)基因涉及的生物學(xué)功能進(jìn)行“Functional AnnotationClustering”分析，結(jié)果顯示上調(diào)基因涉及的生物學(xué)功能分類聚成15個(gè)集合，其中富集分?jǐn)?shù)最高的功能集合主要涉及細(xì)胞周期和細(xì)胞分裂；下調(diào)基因涉及的生物學(xué)功能分類聚成63個(gè)集合，富集分?jǐn)?shù)最高的功能集合主要涉及細(xì)胞趨向性、細(xì)胞成分及蛋白、多糖結(jié)合活性。 利用STRING、Cytoscape、PATHWAY及GO分類等生物信息學(xué)軟件綜合分析202個(gè)差異表達(dá)基因（上調(diào)44個(gè)，下調(diào)158個(gè)），對此202個(gè)基因進(jìn)行生物學(xué)功能分析及預(yù)測，上調(diào)基因CDC6, KIFC1, OIP5, NCAPG, KIF15, BUB1, CDCA2,AURKA, CEP55, PBK等主要參與細(xì)胞周期、有絲分裂等生物學(xué)過程；上調(diào)基因TNFRSF13B, TNFRSF17, CXCL9，下調(diào)基因CSF2, CCL2, FOS, EGF, IL1A, IL1B,DUSP6等則與腫瘤相關(guān)信號(hào)通路密切相關(guān)，如Inflammation，Angiogenesis，MAPKsignal pathway，Adherens junction，NOD-like receptor signaling pathway等；下調(diào)基因CSF2, CCL2, CXCL5, CXCL2, TLR2, FCN1, LILRA5, IL1RAP, IL1B, THBS1,CFD、PTX3, FCGR3A, IL1A, IL1RN等主要與細(xì)胞損傷、炎癥反應(yīng)、免疫應(yīng)答等生物學(xué)過程相關(guān)，如“response to wounding”,“inflammatory response”,“immuneresponse”。本實(shí)驗(yàn)結(jié)合上述多種生物信息學(xué)分析結(jié)果顯示，15個(gè)差異表達(dá)基因在蛋白網(wǎng)絡(luò)中處于中心位置，包括EGF, IL1B, PBK, CSF2, TLR2, DUSP6, HDC,CD68, TREM1, IL1A, CCL2, SPI1, PLAU, TGFB1和FOS，其中EGF, IL1B, PBK,CSF2, TLR2這5個(gè)基因在度數(shù)和介度中的排名均靠前，我們推測EGF, IL1B, PBK,CSF2和TLR2可能是導(dǎo)致EBV相關(guān)淋巴瘤發(fā)生的關(guān)鍵分子。 3.綜合信號(hào)通路、基因生物學(xué)分類、基因間相互作用分析及已有文獻(xiàn)報(bào)道，提示EBV可能上調(diào)宿主細(xì)胞PBK基因促進(jìn)細(xì)胞增殖，下調(diào)宿主細(xì)胞EGF基因發(fā)揮抗凋亡作用，下調(diào)宿主細(xì)胞IL1β, CSF2, TLR2基因等降低細(xì)胞免疫能力，從而導(dǎo)致EBV相關(guān)淋巴瘤的發(fā)生。 結(jié)論： 1、系統(tǒng)構(gòu)建了體內(nèi)EBV相關(guān)淋巴瘤和正常人淋巴細(xì)胞的差異基因表達(dá)譜，發(fā)現(xiàn)淋巴瘤細(xì)胞和正常淋巴細(xì)胞的基因表達(dá)模式存在明顯差異。 2、生物信息學(xué)分析篩選出202個(gè)差異表達(dá)基因，包括44個(gè)上調(diào)基因和158個(gè)下調(diào)基因，表明EBV相關(guān)淋巴瘤的發(fā)生是一個(gè)多基因參與，多通路涉及、病毒基因與宿主基因相互作用的過程。 3、推測EGF, IL1β, CSF2, PBK和TLR2可能是導(dǎo)致EBV相關(guān)淋巴瘤發(fā)生的關(guān)鍵分子。
[Abstract]:Objective: to detect and analyze the differentially expressed genes of host cells of EBV related lymphoma and normal human lymphocytes in Scid mice, and to screen candidate key genes of EBV induced lymphoma, and to explore the possible molecular mechanism of EBV related lymphoma.
Methods: donors fresh blood samples isolated from human peripheral blood lymphocytes, preservation of normal lymphocytes respectively, EBV replication in Scid mice lymphoma model. Using 4 * 44K Agilent genome expression microarray detection, difference analysis of EBV in Scid mice lymphoma and normal human lymphocyte gene expression, screened fold change more than 2 genes were upregulated the expression of Fold gene, change gene expression was significantly reduced to less than 0.5. The use of GO classification, KEGG pathway, Reactom pathway and Biocarta and DAVID online software on different gene function analysis and pathway, and the combination of STRING, Cytscape gene interaction analysis, prediction of biological function difference genes.
Results: 1, the pathological diagnosis of Scid mice induced by tumor for diffuse large B cell lymphoma, PCR lymphoma and confirmed that this is the source of EBV in the experimental model of.6 related lymphoma samples standard data successfully copied by LIMMA, BRB-Random Variance Model, SAM software for screening differentially expressed genes were screened out by PDR0.001. 3928. The expression of the probe is not mapped to HUGO Probe removed, then select fold-change2 times change as expression differences were screened 202 differentially expressed genes, including 44 up-regulated genes and 158 down regulated genes, constructs 6 cases of homologous EBV related lymphoma (T) and normal lymphocytes (N) expression the spectrum of genes.
Bioinformatics analysis of 2. differentially expressed genes
Gene Ontology classification BP analysis showed that a total of 30 up-regulated genes in 27 BP classification, including cell cycle and mitosis related to the "cell cycle", "cell cycle phase", "nucleardivision", "mitosis", "M phase of mitotic cell cycle", "cell cycle," process "organellefission", "M phase" and "mitotic cell cycle" 10 GO BP classification EASE score minimum, 2.6E-09. KIFC1, OIP5 up-regulated genes CDC6, NCAPG, KIF15, BUB1, CDCA2, AURKA, CEP55, PBK participated in a number of cell cycle associated with the biological process of.126 downregulated genes involved in 116 a BP classification, including "inflammatory response", "response to wounding", "immune response", "defense response", "taxis", "chemotaxis", "regulation ofsecretion", "behavior", "anti-apoptosis" and "protein ki The lowest score of EASE Score was nase cascade ", all 1.6E-04. down regulated genes CSF2, CCL2, CXCL5, CXCL2, TLR2, FCN1, TLR2,", ",", ",", ",", ",", ",", "," and "were mainly related to biological processes such as cell injury, inflammatory reaction, immune response and so on.
The 25 up-regulated genes in 13 MF classification, which mainly relates to nucleic acid binding activity, such as "ATPbinding", "adenyl ribonucleotide binding", "adenyl nucleotide binding", "purinenucleoside binding" and "nucleoside binding" EASE Score 0.006. the lowest score, were involved in a number of molecular function genes CDC6, KIFC1, KIF15 BUB1, AURKA, PBK, TOP2A, GSG2, RAD51.123, downregulated genes involved in 12 MF classification, which mainly involves a combination of molecular signaling and cytokine receptors, such as "carbohydrate binding", "cytokine binding", "polysaccharide binding", "protein binding" and "glycosaminoglycan binding", "cytokine activity". Interleukin-1receptor binding "EASE Score 0.001. the lowest score, were involved in a variety of molecular function genes SELP, TNFAIP6, CCL2, C6ORF25, TLR2, PT X3, THBS1, NLRP3, IL1RN, IL1B, IL1A.
The use of "KEGG Pathway", "BioCarta" and "Reactome" by Pathway analysis showed that when EASE Score0.05, up-regulated genes do not participate in the "KEGG-pathway", 2 genes involved in the 1 "BioCarta-pathway", 5 genes involved in the 1 "Reactome-pathway"; down regulated genes in 64 genes involved in 7 "KEGG-pathway" 30, 1 "BioCarta-pathway" genes, 33 genes involved in the 2 "Reactome-pathway".
The up and down expression of genes involved in the biological function of "Functional AnnotationClustering" analysis, results showed that the biological function of classification of up-regulated genes involving poly 15 sets, of which the highest score of the set of functional enrichment mainly involved in cell cycle and cell division; down regulated genes involved in biological function classification of poly 63 sets, functional enrichment the highest score of the collection mainly involves cell tropism, cell composition and protein, polysaccharide binding activity.
The use of STRING, Cytoscape, PATHWAY and GO classification and bioinformatics analysis software 202 genes (44 up-regulated and 158 down regulated), this 202 gene analysis and prediction of biological function, increase KIFC1, OIP5, gene CDC6, NCAPG, KIF15, BUB1, CDCA2, AURKA, CEP55, PBK etc. mainly involved in cell cycle, mitosis and other biological processes; up-regulated genes TNFRSF13B, TNFRSF17, CXCL9, CCL2, down-regulation of CSF2, FOS, EGF, IL1A, IL1B, DUSP6 and tumor related signaling pathways are closely related, such as Inflammation, Angiogenesis, MAPKsignal pathway, Adherens junction, NOD-like receptor signaling pathway down regulated genes; CSF2, CCL2, CXCL5, CXCL2, TLR2, FCN1, LILRA5, IL1RAP, IL1B, THBS1, CFD, PTX3, FCGR3A, IL1A, IL1RN and cell injury, inflammatory response, immune response and other related biological processes, such as "R Esponse to wounding "," inflammatory response "," immuneresponse ". The combination of these kinds of bioinformatics analysis showed that the gene in the center, in the 15 differentially expressed protein networks including EGF, IL1B, PBK, CSF2, TLR2, DUSP6, HDC, CD68, TREM1, IL1A, CCL2, SPI1. PLAU, TGFB1 and FOS, EGF, IL1B, PBK, CSF2, TLR2 were on the 5 genes in the degree and betweenness in the top, we speculate that EGF, IL1B, PBK, CSF2 and TLR2 might be the key molecular EBV related lymphoma.
3. integrated signal pathway, gene classification, gene interaction analysis and has been reported, suggesting that EBV may increase the host cell PBK gene can promote cell proliferation and downregulation of EGF gene in the host cell apoptosis, down-regulation of host cell IL1 beta, CSF2, TLR2 gene to reduce cellular immunity, resulting in EBV related lymphoma happen.
Conclusion:
1, we constructed differential gene expression profiles of EBV related lymphoma and normal human lymphocytes in vivo, and found that there were significant differences in gene expression patterns between lymphoma cells and normal lymphocytes.
2, bioinformatics analysis screened 202 differentially expressed genes, including 44 up-regulated genes and 158 down regulated genes, indicating that the occurrence of EBV related lymphoma is a multi gene involvement, and multipath involves the interaction between viral genes and host genes.
3, it is presumed that EGF, IL1 beta, CSF2, PBK and TLR2 may be the key molecules that lead to the occurrence of EBV related lymphoma.

【學(xué)位授予單位】：南華大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：R733.1;R-332

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相關(guān)期刊論文 前1條

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