本文選題：胃癌　切入點：復合基因調控網絡　出處：《華東理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：胃癌(GastricCancer,GC)是全世界范圍內發(fā)病率和死亡率最高的癌癥類型之一。盡管已經鑒定出很多與胃癌相關的基因(gene)和microRNA(miRNA),但它們在系統(tǒng)層面的作用機理仍然不清楚。為了在系統(tǒng)層面探究胃癌形成過程中的異常調控機制,本課題建立了用來識別癌癥相關調控關系的方法,該方法創(chuàng)造性地整合了差異調控、差異表達及調控子(Regulator)對靶基因調控效應三方面的信息,并將該方法用于胃癌組學數據研究胃癌發(fā)生發(fā)展的機制。本課題基于TCGA胃癌mRNA和miRNA表達數據,首先用差異共表達分析(Differential Coexpression Analysis,DCEA)策略獲得一組在正常和癌癥狀態(tài)之間表達水平的相關性發(fā)生顯著變化的gene和miRNA(gene/miRNA),并用這些gene/miRNA分別構建正常和癌癥條件下包含轉錄因子(Transcriptional Factor,TF)和miRNA的條件特異的復合基因調控網絡(combinational Gene Regulatory Network,cGRN),發(fā)現條件特異的cGRN能顯著富集已知的癌癥相關的gene/miRNA;然后建立了度量不同條件下調控關系差異的方法,發(fā)現該方法能將癌癥相關的gene/miRNA顯著地排在前面,并用該方法篩選調控強度發(fā)生顯著變化的調控關系;隨后,通過整合差異調控、差異表達及Regulator對靶基因因的調控效應三方面的信息定義了差異調控關系(Differentially Regulated Link,DRL);最后,通過整合DRL及臨床生存時間數據,篩選出三個關鍵的Regulator,TCF7L1、TCF4和MEIS1。圍繞這三個Regulator,及其相關的DRL,結合文獻信息,在系統(tǒng)水平上提出了一個胃癌發(fā)生的異常調控機制假說。在該項研究中,miRNA微調效應在系統(tǒng)層面被觀察到。此外,本課題還將差異調控分析方法應用到中國人胃癌表達譜數據GSE54129中,對癌癥和癌旁之間的差異調控基因(Differentially Regulated Genes,DRG)和差異調控關系(DRL)排序。從計算的結果中選取排在最靠前的一個TF CREB1,及兩個靶基因TCEAL2和MBNL1,用分子生物學實驗重現了預測的這兩個調控關系在正常和癌癥條件下的差異調控結果。本課題提出的胃癌機制假說能為今后的研究提供指導,構建的差異調控分析策略還可以用于探索其它復雜疾病以及表型變化現象背后的基因表達調控機制。
[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.
【學位授予單位】：華東理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R735.2

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