本文關(guān)鍵詞： 肺腺癌 差異表達(dá)分析 WGCNA 富集分析 RNA-seq　出處：《內(nèi)蒙古大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：肺癌是目前全世界最常見(jiàn)的惡性腫瘤之一,是一種復(fù)雜的分子網(wǎng)絡(luò)疾病。目前有效的治療方法是全肺切除加輔助性化療,因此對(duì)于肺癌的治療最重要的是尋找有效的早期診斷和指導(dǎo)預(yù)后的標(biāo)志物。本文分別使用差異表達(dá)分析法(differential expression analysis,DEA)和加權(quán)基因共表達(dá)網(wǎng)絡(luò)分析(weighted gene co-expression network analysis,WGCNA)方法對(duì) coding gene 和 lncRNA 進(jìn)行分析。我們使用WGCNA法構(gòu)建基因表達(dá)譜矩陣并進(jìn)行聚類分析,共獲得47個(gè)模塊,其中八個(gè)是肺腺癌風(fēng)險(xiǎn)模塊,這八個(gè)模塊所包含的全部基因中共有27%是差異表達(dá)基因。然后,我們分別對(duì)這八個(gè)模塊和通過(guò)DEA法找到的差異表達(dá)基因(differentially expressed gene,DEG)進(jìn)行 GO(gene ontology)和 KEGG 功能富集分析。我們發(fā)現(xiàn)通過(guò)WGCNA法可以找到差異表達(dá)分析法沒(méi)有富集到的生物過(guò)程。例如,與膠原生物大分子代謝相關(guān)的生物學(xué)過(guò)程,WGCNA法精確給出了膠原分子調(diào)控的方向。在八個(gè)肺腺癌風(fēng)險(xiǎn)模塊中,green模塊中的DEG和lncRNA分別占整個(gè)模塊所有基因的68.9%和15.4%,是這八個(gè)模塊中DEG比例最高的模塊。Blue模塊中DEG和lncRNA分別占整個(gè)模塊的8%和33.3%,是這八個(gè)模塊中l(wèi)ncRNA含量最高的模塊。Blue模塊前50個(gè)高連接度基因中有16個(gè)lncRNA,greenyellow、green、darkred模塊前50個(gè)高連接度基因中分別含有3個(gè)lncRNA,purple模塊前50個(gè)高連接度基因中有2個(gè)lncRNA,yellow模塊前50個(gè)高連接度基因中有1個(gè)lncRNA。連接度越高的基因越具有顯著的生物學(xué)功能,因此lncRNA可能在肺腺癌的發(fā)生過(guò)程中起了重要的作用。Green 模塊樞紐基因中 SPTBN1、SFTPC、FHL1 和 RP5-826L7.1 都參與了肺腺癌的發(fā)生過(guò)程。其中SFTPC是基因顯著性(GS)值最高的基因,FHL1是模塊身份(MM)值最大的基因。Greenyellow模塊樞紐基因中SAMHD1通過(guò)免疫應(yīng)答過(guò)程在肺腺癌中發(fā)揮作用,而樞紐基因FCER1G和NLRC4也是通過(guò)參與免疫應(yīng)答過(guò)程在其它疾病中發(fā)揮功能,其中FCER1G和NLRC4分別是樞紐基因中MM值最大和GS值最大的基因,雖然還沒(méi)有文獻(xiàn)報(bào)道這兩個(gè)基因參與肺腺癌的發(fā)生,但是我們有理由相信這兩個(gè)基因以及每個(gè)模塊中的樞紐基因可能在肺腺癌的發(fā)生過(guò)程起作用。因此,樞紐基因可能作為肺腺癌有效的早期診斷分子和指導(dǎo)預(yù)后的標(biāo)志物。
[Abstract]:Lung cancer is one of the most common malignant tumors in the world and is a complex molecular network disease. Therefore, the most important thing in the treatment of lung cancer is to find effective markers for early diagnosis and prognosis. Differential expression analysis. Gene co-expression network analysis. Coding gene and lncRNA were analyzed by WGCNA method. We used WGCNA method to construct gene expression matrix and cluster analysis. A total of 47 modules were obtained, eight of which were lung adenocarcinoma risk modules, and 27% of the genes contained in the eight modules were differentially expressed genes. We analyzed the eight modules and the differentially expressed expressed gene by DEA method. For GO(gene ontology). And KEGG functional enrichment analysis. We found that the differential expression analysis method can be used to find the biological processes that are not enriched by differential expression analysis. For example. The biological processes associated with collagen biomolecules metabolism are precisely defined by WGCNA in eight lung adenocarcinoma risk modules. The DEG and lncRNA in the green module accounted for 68.9% and 15.4% of all genes in the whole module, respectively. DEG and lncRNA account for 8% and 33.3% of the entire module, respectively, among the eight modules with the highest proportion of DEG. Blue module has the highest lncRNA content among the eight modules. Blue module has 16 LNC RNA-greenyellow green genes out of the first 50 high connectivity genes. In the first 50 high connectivity genes of darkred module, there were 2 lncRNA in the first 50 high connectivity genes. One of the first 50 high connectivity genes of yellow module had significant biological function with the higher degree of connectivity. Therefore, lncRNA may play an important role in the pathogenesis of lung adenocarcinoma. Both FHL1 and RP5-826L7.1 are involved in the pathogenesis of lung adenocarcinoma, in which SFTPC is the most significant gene. FHL1 is the most important gene. Green yellow module hinge gene SAMHD1 plays a role in lung adenocarcinoma through the immune response process. The pivotal genes FCER1G and NLRC4 also function in other diseases by participating in the immune response process. Among them, FCER1G and NLRC4 are the genes with the largest MM value and the largest GS value in the hinge genes, although there is no literature report that these two genes are involved in the pathogenesis of lung adenocarcinoma. But we have reason to believe that these two genes, as well as the hinge genes in each module, may play a role in the development of lung adenocarcinoma. The hinge gene may be an effective early diagnosis molecule and a prognostic marker for lung adenocarcinoma.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R734.2

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本文編號(hào)：1463832