胰腺星状细胞差异表达基因的筛

发布时间：2018-04-16 21:14

  本文选题：胰腺星状细胞 + 胰腺癌　； 参考：《吉林大学》2017年硕士论文

【摘要】：第一部分静止几活化胰腺星状细胞差异表达基因的筛选及生物信息学分析目的:胰腺癌具有发现晚、进展快、可手术比例小、高耐药率以及高病死率的特点,被称为“癌症之王”,而其显著病理特点为:以PSC为中心,ECM主导的胰腺癌组织纤维结缔组织生成。随着基因技术、信息技术的飞速发展,大数据时代的到来,生物信息学这一门跨学科手段成为人们从宏观角度解读疾病的又一利器。因此我们采用这一手段,筛选静止及活化状态下PSC的差异表达基因并对其进行生物信息学分析。方法:选取北京协和医院8例经病理确诊为胰腺导管腺癌患者的癌组织原代培养PSC。连续5天每天加入ATRA避光培养获得静止状态PSC,分别提取静止及活化状态下PSC基因组进行测序分析,从中筛选出DEG,利用包括GO分析和KEGG生物学通路富集分析在内的生物信息学方法,进一步探索DEG间的生物关联及作用。结果:从33289条基因中筛选出192个DEG,其中上调表达基因109个,下调表达基因83个,其中排在前三位的下调基因是:HR、RP11-624L4.1和FGF9。GO富集分析生物过程BP部分排在前2位的是:细胞外结构组织和细胞外基质组织;CC部分排在前3位的是:细胞外基质、蛋白质细胞外基质和间质基质;MF部分排在前3位的是硫化物结合、肝素结合和生长因子。KEGG通路分析占首位的是TGF-β通路。将BP、CC、MF三个部分,按P值进行从小到大排序可发现细胞外基质和生长因子在PSC活化过程中最为关键。统计各类别中所包含基因,按照基因出现频率进行排序,出现频率≥4的共有18个基因,结合DEG筛选结果,前三位DEG中,仅FGF9在GO富集分析结果中同样较高频率出现。结论:PSC静止及活化状态间的转化由多种基因调控,当PSC转为静止状态后,以细胞外基质、间质、生长因子等相关成分基因下调为主,提示基质在PSC活化中可能发挥了重要作用。选定FGF9作为拟验证的候选基因。第二部分FGF9及其相关受体表达的RT-q PCR验证目的:测序结果客观且庞大,如果不做进一步的分析验证则反而会使大量的数据成为“数据垃圾”,因此完成生物信息学分析后,我们根据第一部分实验的结果,结合文献和既往研究进行分析,从中筛选出在众多DEG中占相对主导地位的基因进行验证分析。而从上一部分我们已经得到FGF9是PSC活化的关键基因,因此对FGF9及其相关受体基因进行验证。方法:培养PSC,用ATRA进行去活化,分别提取活化PSC和去活化PSC中的RNA,进行反转录获得c DNA,用q PCR进行候选基因验证,候选基因选择:FGF9及其密切相关的受体FGFR2c、FGFR3b和FGFR3c,确定第一部分筛选结果,进而为进一步探究DEG功能和机制奠定基础。结果:FGF9、FGFR3b和FGFR3c的表达在ATRA去活化组较活化组显著下调,FGFR2c表达在ATRA去活化组较活化组显著上调。结论:FGF9能够促进PSC活化,FGFR3b和FGFR3c可能存在协同作用,FGFR2c在PSC活化中的作用仍不明确。
[Abstract]:Part I screening of differentially expressed genes in stationary activated pancreatic stellate cells and bioinformatics analysis objective: pancreatic cancer is characterized by late discovery, rapid progression, low operative rate, high drug resistance and high mortality.It is called the "king of cancer", and its prominent pathological characteristics are: connective tissue formation of pancreatic cancer tissue dominated by PSC.With the rapid development of gene technology and information technology and the arrival of big data's era, bioinformatics, as an interdisciplinary means, has become another powerful tool for people to interpret diseases from a macro perspective.So we used this method to screen the differentially expressed genes of PSC in stationary and activated state and to analyze them by bioinformatics.Methods: primary culture of PSCs was performed in 8 patients with pancreatic ductal adenocarcinoma diagnosed pathologically in Peking Union Hospital.For 5 consecutive days, the stationary PSC was obtained by adding ATRA in the dark culture every day, and the PSC genome was sequenced and analyzed in the inactive and activated state, respectively.The bioinformatics methods including go analysis and KEGG biological pathway enrichment analysis were used to further explore the biological association and function between DEG.Results: 192 DEG genes were screened from 33289 genes, of which 109 were up-regulated and 83 were down-regulated.Among them, the down-regulated genes in the first three places were: 1 / HRN RP11-624L4.1 and FGF9.GO enrichment analysis. The BP part of the biological process ranked first 2: extracellular structure tissue and extracellular matrix tissue (CC) were in the top three positions: extracellular matrix.The protein extracellular matrix (ECM) and interstitial matrix (MF) in the top 3 were sulfide-binding, while heparin binding and growth factor.KEGG pathway were the most important in TGF- 尾 pathway.It was found that extracellular matrix (ECM) and growth factor (GF) were the most critical in the activation of PSC by ranking the three parts of BPCCMF from small to large according to P value.According to the frequency of gene occurrences, there were 18 genes with frequency 鈮，

本文编号：1760596