EB病毒相关伯基特淋巴瘤差异基因表达分析
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摘要
目的从分子层面分析EB病毒(EBV)相关伯基特淋巴瘤(BL)的差异表达基因(DEGs),为其诊疗提供新的思路。方法从美国国立生物技术信息中心(NCBI)获取EBV阳性与阴性BL相关基因芯片数据集GSE100458。通过morpheus筛选出DEGs,分别将上调和下调基因输入Database for Annotation Visualizationand Integrated Discovery(DAVID)数据库,进行GO分析;进一步采用cytoscape筛选出10个TOP基因,实时荧光定量PCR方法验证其在EBV阳性与阴性BL细胞系中表达情况。结果分析EBV阳性和EBV阴性的BL细胞系的前400个DEGs,包括200个上调基因和200个下调基因,上调基因主要集中在生长因子活性通路、肝素结合通路、细胞外间隙通路;下调基因主要集中在伽马微管蛋白结合通路、内质网膜通路、逆行性小囊泡运输通路。对DEGs进行蛋白质相互作用分析后,筛选出核心基因乙酰辅酶A羧化酶β(ACACB)等10个基因。实时荧光定量PCR检测结果显示,在EBV阳性与阴性BL组间,CDH1、PRPF19、UBE2N、F2、H6PD、VEGFA、YARS共7个基因的转录表达差异有统计学意义(t=3.878～32.601,P<0.05),ACACB、CTTN、IGF1共3个基因表达差异无统计学意义(P>0.05)。结论 EBV感染可导致宿主细胞基因表达谱的改变,生物信息学分析法可初步筛选出DEGs和相互作用的蛋白,为进一步深入研究提供有价值的信息和思路。
Objective To analyze the differentially expressed genes(DEGs) in EB virus(EBV)-associated Burkitt lymphoma(BL) at molecular level, and to provide new ideas for its diagnosis and treatment. Methods The EBV-positive and-negative BL-related gene microarray data set GSE100458 was obtained from the National Center for Biotechnology Information(NCBI). DEGs were screened out by Morpheus, and the up-regulated and down-regulated genes were entered into the Database for Annotation Visualization and Integrated Discovery(DAVID) for GO analysis. Ten top genes were identified by cytoscape, and their expression in EBV-positive and EBV-negative BL cell lines was verified by real-time fluorescence quantification PCR. Results The top 400 DEGs of EBV-positive and EBV-negative BL cell lines were analyzed, including 200 up-regulated genes and 200 down-regulated genes. The up-regulated genes were mainly concentrated in the growth factor activity pathway, heparin binding pathway, and extracellular gap pathway. The down-regulated genes were mainly concentrated in the gamma-tubulin binding pathway, endoplasmic reticulum pathway, and retrograde small vesicle transport pathway. After protein interaction analysis of DEGs,10 core genes such as acetyl coenzyme A carboxylase beta(ACACB) were screened out. Quantitative real-time PCR results showed that there were significant differences in transcriptional expression of 7 genes(CDH1, PRPF19, UBE2N, F2, H6PD, VEGFA, and YARS) between EBV-positive and EBV-negative BL groups(t=3.878-32.601,P<0.05), and there were no significant diffe-rences in the expression of ACACB, CTTN, and IGF1(P>0.05). Conclusion EBV infection can lead to changes in the gene expression profiles of host cells. Bioinformatics analysis can preliminarily screen out DEGs and interacting proteins, providing valuable information and ideas for further research.
Objective To analyze the differentially expressed genes(DEGs) in EB virus(EBV)-associated Burkitt lymphoma(BL) at molecular level, and to provide new ideas for its diagnosis and treatment. Methods The EBV-positive and-negative BL-related gene microarray data set GSE100458 was obtained from the National Center for Biotechnology Information(NCBI). DEGs were screened out by Morpheus, and the up-regulated and down-regulated genes were entered into the Database for Annotation Visualization and Integrated Discovery(DAVID) for GO analysis. Ten top genes were identified by cytoscape, and their expression in EBV-positive and EBV-negative BL cell lines was verified by real-time fluorescence quantification PCR. Results The top 400 DEGs of EBV-positive and EBV-negative BL cell lines were analyzed, including 200 up-regulated genes and 200 down-regulated genes. The up-regulated genes were mainly concentrated in the growth factor activity pathway, heparin binding pathway, and extracellular gap pathway. The down-regulated genes were mainly concentrated in the gamma-tubulin binding pathway, endoplasmic reticulum pathway, and retrograde small vesicle transport pathway. After protein interaction analysis of DEGs,10 core genes such as acetyl coenzyme A carboxylase beta(ACACB) were screened out. Quantitative real-time PCR results showed that there were significant differences in transcriptional expression of 7 genes(CDH1, PRPF19, UBE2N, F2, H6PD, VEGFA, and YARS) between EBV-positive and EBV-negative BL groups(t=3.878-32.601,P<0.05), and there were no significant diffe-rences in the expression of ACACB, CTTN, and IGF1(P>0.05). Conclusion EBV infection can lead to changes in the gene expression profiles of host cells. Bioinformatics analysis can preliminarily screen out DEGs and interacting proteins, providing valuable information and ideas for further research.
引文
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[21] ZOU Xiang,QU Zhongyuan,FANG Yi,et al.Endoplasmic reticulum stress mediates sulforaphane-induced apoptosis of HepG2 human hepatocellular carcinoma cells[J].Molecular Medicine Reports,2017,15(1):331-338.
[22] JANG H H.Regulation of protein degradation by proteasomes in cancer[J].J Cancer Prev,2018,23(4):153-161.
[23] COTTAM N P,UNGAR D.Retrograde vesicle transport in the Golgi[J].Protoplasma,2012,249(4):943-955.
[24] 周学付,陈国星,彭晓飞.粤北地区遗传性弥漫型胃癌与CDH1种系突变关系初探[J].消化肿瘤杂志(电子版),2018,10(2):101-104.
[25] ZHANG Yuzhe,LI Yu′e,LIANG Xiao,et al.Crystal structure of the WD40 domain of human PRPF19[J].Biochemical and Biophysical Research Communications,2017,493(3):1250-1253.
[26] DIKSHIT A,ZHANG J Y.UBE2N plays a pivotal role in maintaining melanoma malignancy[J].Oncotarget,2018,9(100):37347-37348.
[27] GIROLAMI A,COSI E,FERRARI S,et al.Prothrombin:another clotting factor after FV that is involved both in blee-ding and thrombosis[J].Clinical and Applied Thrombosis-Hemostasis,2018,24(6):845-849.
[28] SADJJADI S M,EBRAHIMIPOUR M,SADJJADI F S.Comparison between Echinococcus granulosus sensu stricto (G1) and E.canadensis (G6) mitochondrial genes (cox1 and nad1) and their related protein models using experimental and bioinformatics analysis[J].Computational Biology and Chemistry,2019,79(79):103-109.
[2] KAYMAZ Y,ODUOR C I,YU H B,et al.Comprehensive transcriptome and mutational profiling of endemic burkitt lymphoma reveals EBV type-specific differences[J].Molecular Cancer Research,2017,15(5):563-576.
[3] UCCINI S,AL-JADIRY M F,CIPPITELLI C A,et al.Burkitt lymphoma in Iraqi children:a distinctive form of sporadic disease with high incidence of EBV+ cases and more frequent expression of MUM1/IRF4 protein in cases with head and neck presentation[J].Pediatric Blood & Cancer,2018,65(12):e27399.
[4] WANG Anping,ZHANG Guibin.Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database[J].Oncology Letters,2017,14(5):6040-6044.
[5] 董政权,魏垒.骨关节炎基因差异谱的生物信息学分析[J].中国组织工程研究,2019,23(3):335-340.
[6] CHAI Yi,TAN Feng,YE Sumin,et al.Identification of core genes and prediction of miRNAs associated with osteoporosis using a bioinformatics approach[J].Oncology Letters,2019,17(1):468-481.
[7] GAUDET P,DESSIMOZ C.Gene ontology:pitfalls,biases,and remedies[J].Methods Mol Biol,2016,1446:189-205.
[8] VESZTROCY A W,DESSIMOZ C.A gene ontology tutorial in python[J].Methods Mol Biol,2017,1446:221-229.
[9] 赵丹蕊.EB病毒相关胃癌中RASSF1A基因甲基化状态和表达的研究[D].青岛:青岛大学,2017.
[10] LEE H Y,LI C C,HUANG C N,et al.INHBA overexpression indicates poor prognosis in urothelial carcinoma of urinary bladder and upper tract[J].Journal of Surgical Oncology,2015,111(4):414-422.
[11] GROMIHA M M,YUGANDHAR K,JEMIMAH S.Protein-protein interactions:scoring schemes and binding affinity[J].Current Opinion in Structural Biology,2017,44:31-38.
[12] CUI X J,ZHANG P,DENG W L,et al.Insulin-like growth factor-Ⅰ inhibits progesterone receptor expression in breast cancer cells via the phosphatidylinositol 3-kinase/akt/mammalian target of rapamycin pathway:progesterone receptor as a potential indicator of growth factor activity in breast[J].Molecular Endocrinology,2003,17(4):575-588.
[13] GAVIGLIO A L,KNELSON E H,BLOBE G C.Heparin-binding epidermal growth factor-like growth factor promotes neuroblastoma differentiation[J].FASEB Journal,2017,31(5):1903-1915.
[14] SEVERS N J.Pathophysiology of gap-junctions in heart-disease[J].Journal of Cardiovascular Electrophysiology,1994,5(5):462-475.
[15] XIONG Niya,LI Shun,TANG Kai,et al.Involvement of caveolin-1 in low shear stress-induced breast Cancer cell motility and adhesion:roles of FAK/Src and ROCK/p-MLC pathways[J].Biochimica et Biophysica Acta-Molecular Cell Research,2017,1864(1):12-22.
[16] HUANG Qichao,CAO Haiyan,ZHAN Lei,et al.Mitochondrial fission forms a positive feedback loop with cytosolic Calcium signaling pathway to promote autophagy in hepatocellular carcinoma cells[J].Cancer Letters,2017,403:108-118.
[17] SI Wen,LI Zhanting,HOU Junli.Voltage-driven reversible insertion into and leaving from a lipid bilayer:tuning transmembrane transport of artificial channels[J].Angewandte Chemie-International Edition,2014,53(18):4578-4581.
[18] HUGHES S E,BEELER J S,SEAT A,et al.Gamma-Tubulin is required for bipolar spindle assembly and for proper kinetochore microtubule attachments during prometaphase Ⅰ in drosophila oocytes[J].PLoS Genetics,2011,7(8):e1002209.
[19] MOUTINHO-PEREIRA S,DEBEC A,MAIATO H.Microtubule cytoskeleton remodeling by acentriolar microtubule-organizing centers at the entry and exit from mitosis in Drosophila somatic cells[J].Mol Biol Cell,2009,20(11):2796-2808.
[20] WIGINGTON P,WILLIAMS C.Poly(a)RNA-binding proteins and polyadenosine RNA:new members and novel functions[J].Wiley Interdisciplinary Reviews RNA,2014,5(5):601-622.
[21] ZOU Xiang,QU Zhongyuan,FANG Yi,et al.Endoplasmic reticulum stress mediates sulforaphane-induced apoptosis of HepG2 human hepatocellular carcinoma cells[J].Molecular Medicine Reports,2017,15(1):331-338.
[22] JANG H H.Regulation of protein degradation by proteasomes in cancer[J].J Cancer Prev,2018,23(4):153-161.
[23] COTTAM N P,UNGAR D.Retrograde vesicle transport in the Golgi[J].Protoplasma,2012,249(4):943-955.
[24] 周学付,陈国星,彭晓飞.粤北地区遗传性弥漫型胃癌与CDH1种系突变关系初探[J].消化肿瘤杂志(电子版),2018,10(2):101-104.
[25] ZHANG Yuzhe,LI Yu′e,LIANG Xiao,et al.Crystal structure of the WD40 domain of human PRPF19[J].Biochemical and Biophysical Research Communications,2017,493(3):1250-1253.
[26] DIKSHIT A,ZHANG J Y.UBE2N plays a pivotal role in maintaining melanoma malignancy[J].Oncotarget,2018,9(100):37347-37348.
[27] GIROLAMI A,COSI E,FERRARI S,et al.Prothrombin:another clotting factor after FV that is involved both in blee-ding and thrombosis[J].Clinical and Applied Thrombosis-Hemostasis,2018,24(6):845-849.
[28] SADJJADI S M,EBRAHIMIPOUR M,SADJJADI F S.Comparison between Echinococcus granulosus sensu stricto (G1) and E.canadensis (G6) mitochondrial genes (cox1 and nad1) and their related protein models using experimental and bioinformatics analysis[J].Computational Biology and Chemistry,2019,79(79):103-109.