基于差异调控分析探究胃癌形成过程中转录因子和microRNA的异常调控机制

发布时间：2018-03-15 18:05

本文选题：胃癌　切入点：复合基因调控网络　出处：《华东理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：胃癌(GastricCancer,GC)是全世界范围内发病率和死亡率最高的癌症类型之一。尽管已经鉴定出很多与胃癌相关的基因(gene)和microRNA(miRNA),但它们在系统层面的作用机理仍然不清楚。为了在系统层面探究胃癌形成过程中的异常调控机制,本课题建立了用来识别癌症相关调控关系的方法,该方法创造性地整合了差异调控、差异表达及调控子(Regulator)对靶基因调控效应三方面的信息,并将该方法用于胃癌组学数据研究胃癌发生发展的机制。本课题基于TCGA胃癌mRNA和miRNA表达数据,首先用差异共表达分析(Differential Coexpression Analysis,DCEA)策略获得一组在正常和癌症状态之间表达水平的相关性发生显著变化的gene和miRNA(gene/miRNA),并用这些gene/miRNA分别构建正常和癌症条件下包含转录因子(Transcriptional Factor,TF)和miRNA的条件特异的复合基因调控网络(combinational Gene Regulatory Network,cGRN),发现条件特异的cGRN能显著富集已知的癌症相关的gene/miRNA;然后建立了度量不同条件下调控关系差异的方法,发现该方法能将癌症相关的gene/miRNA显著地排在前面,并用该方法筛选调控强度发生显著变化的调控关系;随后,通过整合差异调控、差异表达及Regulator对靶基因因的调控效应三方面的信息定义了差异调控关系(Differentially Regulated Link,DRL);最后,通过整合DRL及临床生存时间数据,筛选出三个关键的Regulator,TCF7L1、TCF4和MEIS1。围绕这三个Regulator,及其相关的DRL,结合文献信息,在系统水平上提出了一个胃癌发生的异常调控机制假说。在该项研究中,miRNA微调效应在系统层面被观察到。此外,本课题还将差异调控分析方法应用到中国人胃癌表达谱数据GSE54129中,对癌症和癌旁之间的差异调控基因(Differentially Regulated Genes,DRG)和差异调控关系(DRL)排序。从计算的结果中选取排在最靠前的一个TF CREB1,及两个靶基因TCEAL2和MBNL1,用分子生物学实验重现了预测的这两个调控关系在正常和癌症条件下的差异调控结果。本课题提出的胃癌机制假说能为今后的研究提供指导,构建的差异调控分析策略还可以用于探索其它复杂疾病以及表型变化现象背后的基因表达调控机制。
[Abstract]:Gastric cancer is one of the most common cancer types with the highest morbidity and mortality in the world. Although many genes related to gastric cancer gene genetics and microRNAs miRNAs have been identified, the mechanism of their action at the system level is still unclear. To explore the mechanism of abnormal regulation in the formation of gastric cancer, In this study, a method was developed to identify cancer-related regulatory relationships. This method creatively integrates information on differential regulation, differential expression and regulatory effects of regulators on target genes. The method was used to study the mechanism of gastric carcinogenesis and development in gastric cancer. This study was based on mRNA and miRNA expression data of TCGA gastric cancer. First, differential Coexpression Analysis (DCEA) strategy was used to obtain a group of gene and miRNAgene / miRNAs with significantly different expression levels between normal and cancer states, and these gene/miRNA were used to construct transcription factors under normal and cancer conditions, respectively. The combined Gene Regulatory Network (CGRN) and the conditional specific gene regulatory network of miRNA found that conditional cGRN significantly enriched known cancer-related gene / miRNAs, and then established a method to measure differences in regulatory relationships under different conditions. It was found that this method can significantly rank the cancer related gene/miRNA in the first place, and screen out the regulatory relationships with significant changes in regulatory intensity by using this method, and then, by integrating differential regulation, Differential expression and the regulatory effect of Regulator on target gene cause define differential Regulated link DRL. Finally, by integrating DRL and clinical survival time data, Three key Regulators, TCF7L1, TCF4 and MEIS1, were screened around the three Regulators, and their associated DRLs, combined with literature information, A hypothesis of abnormal regulatory mechanism for gastric carcinogenesis has been proposed at the systemic level. In this study, the effect of miRNA fine-tuning was observed at the systemic level. The method of differential regulation analysis was also applied to Chinese gastric cancer expression profile data GSE54129. The differential Regulated genes (DRGs) and differential regulatory relationships (DRLs) were sequenced between cancer and adjacent cancer. The TF CREB1, two target genes TCEAL2 and MBNL1 were selected from the calculated results, and predicted by molecular biological experiments. The results of these two regulatory relationships are different in normal and cancer conditions. The hypothesis of gastric cancer mechanism proposed in this paper can provide guidance for future research. The strategy can also be used to explore the gene expression regulation mechanism behind other complex diseases and phenotypic changes.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R735.2

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