本文選題：食管基底細(xì)胞樣鱗癌 + 生物信息學(xué)��； 參考：《河北醫(yī)科大學(xué)》2017年碩士論文

【摘要】：目的:食管癌是我國(guó)的十大特色腫瘤之一,同時(shí)我省處于食管癌高發(fā)地帶,且多數(shù)患者在就診時(shí)已經(jīng)錯(cuò)過(guò)了最佳的治療階段,雖然在對(duì)食管癌的病理及治療手段研究有大宗的報(bào)道,但對(duì)其中一種較為罕見(jiàn)且惡性度較高的食管癌亞型:食管基底細(xì)胞樣鱗癌(basaloid squamous cell carcinoma of the esophagus,BSCCE)的研究卻受限于其罕見(jiàn)性,而鮮有報(bào)道,目前的研究表明BSCCE的最佳治療手段是手術(shù)治療,然而其遠(yuǎn)期生存率并不理想,為了進(jìn)一步研究BSCCE的病理特征,挖掘可能存在的治療靶點(diǎn),從而提高臨床治療后的遠(yuǎn)期生存率,本研究利用生物信息學(xué)方法和基因芯片手段,對(duì)BSCCE的組織樣本基因水平表達(dá)情況進(jìn)行分析,探討其可能的病理學(xué)過(guò)程和腫瘤免疫逃逸機(jī)制,同時(shí)對(duì)BSCCE獨(dú)特的腫瘤微環(huán)境及其臨床指標(biāo)在對(duì)其遠(yuǎn)期預(yù)后的病理基礎(chǔ)進(jìn)行討論,以期為臨床工作中更好的治療BSCCE提供一定的理論基礎(chǔ)。方法:本實(shí)驗(yàn)利用高通量的生物信息學(xué)手段,將BSCCE組織樣本與正常組織樣本的基因表達(dá)情況進(jìn)行對(duì)比分析,通過(guò)樣本送檢獲得原始的基因芯片數(shù)據(jù),利用R語(yǔ)言軟件(R 3.2.3)完成質(zhì)量控制,數(shù)據(jù)歸一化和降噪處理,自主獲取真實(shí)可靠的BSCCE組織樣本與同體正常組織樣本的基因差異表達(dá)情況(log|FC|≥2,P0.01),利用DAVID在線(xiàn)分析系統(tǒng)對(duì)差異表達(dá)基因進(jìn)行常規(guī)的基因本體論(gene ontology,GO)分析和京都基因與基因組百科全書(shū)(kyoto encyclopedia of genes and genomes,KEGG)信號(hào)通路分析以及差異基因疾病分析(Disease)獲取對(duì)BSCCE組織病理情況相關(guān)的分析結(jié)果,利用STRING-OL工具對(duì)差異表達(dá)基因的可信度(可信度≥0.4)進(jìn)行篩選,在盡力降低假陽(yáng)性可能的情況下獲取差異表達(dá)基因的蛋白質(zhì)相互作用分析(Protein-protein interaction,PPI),并進(jìn)一步利用Cytoscape軟件對(duì)篩選后的PPI結(jié)果制作相應(yīng)的基因相互作用網(wǎng)狀圖,并進(jìn)一步篩選核心表達(dá)的差異基因。利用以上分析進(jìn)一步深入理解BSCCE的病理學(xué)狀態(tài),對(duì)其獨(dú)特的是中性粒細(xì)胞侵入原因及惡性遠(yuǎn)期預(yù)后進(jìn)行了一定分析。結(jié)果:BSCCE組織相對(duì)于正常組織的上調(diào)差異表達(dá)基因共489個(gè),下調(diào)差異表達(dá)基因922個(gè)(log|FC|≥2,P0.01)。1 GO分析:BSCCE組織相對(duì)于正常組織的上調(diào)表達(dá)基因GO分析結(jié)果共238條,選取可信度較高(P0.01,FDR0.01)的19條進(jìn)行分析,為了進(jìn)一步分析BSCCE可能的病理改變或腫瘤微環(huán)境,將GO分析中細(xì)胞外或細(xì)胞基質(zhì)等作為主要的分析對(duì)象,其結(jié)果顯示上下調(diào)表達(dá)的差異基因中與細(xì)胞外或細(xì)胞外基質(zhì)相關(guān)的分析條目的可信度與參與基因數(shù)都遠(yuǎn)遠(yuǎn)超過(guò)其他GO條目(尤其在下調(diào)差異基因部分),其中上調(diào)表達(dá)的差異基因中GO分析結(jié)果為:GO:0030574-collagen catabolic process,16個(gè)參與基因,GO:0030198-extracellular matrix organization 24個(gè)參與基因,GO:0005578-proteinaceous extracellular matrix 25個(gè)參與基因,下調(diào)表達(dá)的差異基因中GO分析結(jié)果為:GO:0070062-extracellular exosome 117個(gè)參與基因,GO:0005615-extracellular space 89個(gè)參與基因,GO:0005576-extracellular region 90個(gè)參與基因,對(duì)上調(diào)的GO分析條目中所包含的差異基因進(jìn)行進(jìn)一步分析,發(fā)現(xiàn)了幾個(gè)在BSCCE腫瘤組織中擁有腫瘤標(biāo)志物潛力或?qū)h(yuǎn)期臨床預(yù)后會(huì)有較大幫助的基因,其中包括:ITGB4、COL5A1、LAMB3等13個(gè)基因。2 KEGG分析:在這一分析中提取了幾個(gè)可能與腫瘤病理及免疫微環(huán)境有重要關(guān)聯(lián)的信號(hào)通路,其中上調(diào)表達(dá)的差異基因分析結(jié)果為:p53signaling pathway,Toll-like receptor signaling pathway等。下調(diào)表達(dá)的差異基因分析結(jié)果包括:Drug metabolism-cytochrome P450 pathway,MAPK signaling pathway,Calcium signaling pathway,Cytokine-cytokine receptor interaction pathway。結(jié)果篩選出LAMB3、LAMC2、MFAP2等11個(gè)基因。3疾病相關(guān)分析:進(jìn)一步對(duì)可能與腫瘤病理相關(guān)的605027-Lymphoma,non-Hodgkin,somatic分析結(jié)果及其參與基因RAD54B,RAD54L進(jìn)行了重點(diǎn)分析。4核心差異基因篩選及分析:在利用STRING-OL工具完成高可信度PPI分析后,篩選其中相互作用數(shù)目≥20的差異表達(dá)基因作為核心差異基因共30個(gè),其中上調(diào)的24個(gè),下調(diào)的6個(gè),并對(duì)其進(jìn)行了逐個(gè)的分析,篩選獲得TOP2A、CDC20、CDC6等15個(gè)基因。結(jié)論:我們的分析結(jié)果共篩選腫瘤相關(guān)基因25個(gè),其中GO分析獲得ITGB4、LAMB3、ITGA6、TGFBI、LAMC2、MFAP2,膠原蛋白家族COL5A1、COL7A1、COL1A1、COL1A2、膠原蛋白酶家族(MMP1、3、9)共13個(gè)基因;KEGG分析獲得LAMB3、LAMC2、MFAP2、膠原蛋白酶家族(MMP1、3、9)、TOP2A、CDC20、CDC6、CDC25A、CYP1B1共11個(gè)基因;PPI分析的結(jié)果提示我們TOP2A、CDC20、CDC6、CDC25A、CYP1B1、COL1A1、COL1A2、MMP9、AURKA、CCNA2、BUB1、CDCA5、CCNE1、MCM2、NEK2共15個(gè)基因,這些基因在BSCCE的腫瘤病理指標(biāo),遠(yuǎn)期生存率預(yù)測(cè)診斷以及腫瘤基因標(biāo)靶治療等研究中值得進(jìn)一步深入研究。
[Abstract]:Objective: esophageal cancer is one of the ten most distinctive tumors in China. At the same time, our province is in the high incidence area of esophageal cancer, and most patients have missed the best treatment stage. Although there are a large number of reports on the pathology and treatment of esophageal cancer, one of the more rare and high malignant subtypes of esophageal cancer: food. The study of basaloid squamous cell carcinoma of the esophagus, BSCCE is limited by its rare nature, but rarely reported. The present study shows that the best treatment for BSCCE is surgical treatment. However, the long-term survival rate is not ideal. In order to study the pathological features of BSCCE, the possible treatment can be found. To improve the long-term survival rate of the clinical treatment, this study uses bioinformatics and gene chip methods to analyze the expression of gene level in the tissue samples of BSCCE, to explore the possible pathological process and the mechanism of tumor immune escape. At the same time, the unique tumor microenvironment and its clinical indicators of BSCCE are also discussed. The pathological basis of the long-term prognosis is discussed in order to provide a theoretical basis for the better treatment of BSCCE in clinical work. Methods: this experiment uses high throughput bioinformatics to analyze the gene expression of BSCCE tissue samples and normal tissue samples, and obtain the original gene chip by sample inspection. Data, using the R language software (R 3.2.3) to complete the quality control, data normalization and noise reduction processing, independently obtain the true and reliable BSCCE tissue samples and the gene differential expression of the normal tissue samples (log|FC| > 2, P0.01), and use the DAVID online analysis system to carry out the conventional gene Ontology (gene ontology, G) for the differentially expressed genes. O) analysis and the analysis of Kyoto Encyclopedia of genes and genomes, KEGG) signal pathway analysis and differential gene disease analysis (Disease) to obtain the analysis of the pathology of BSCCE tissue, using STRING-OL tool to screen the reliability of differentially expressed genes (reliability > 0.4), and try to do the best. The protein interaction analysis of differentially expressed genes (Protein-protein interaction, PPI) was obtained when the false positive was reduced, and the Cytoscape software was used to make the corresponding gene interaction network map of the selected PPI results, and further screening the differentially expressed genes in the core. In understanding the pathological state of BSCCE, a specific analysis of the causes of neutrophils invasion and malignant long-term prognosis was made. Results: there were 489 differentially expressed genes up regulation of BSCCE tissues relative to normal tissues, and 922 down regulated differentially expressed genes (log|FC| > 2, P0.01).1 GO analysis: up regulation of BSCCE tissues relative to normal tissues In order to further analyze the possible pathological changes of BSCCE or the microenvironment of the tumor, the GO analysis results of the expression gene GO were analyzed. In order to further analyze the possible pathological changes of BSCCE or the microenvironment of the tumor, the extracellular or cellular matrix in the GO analysis was used as the main analysis object. The results showed that the differentially expressed genes were obviously down to the cells or cells. The reliability and number of involved genes involved in the matrix related analysis were far more than the other GO entries (especially in the down-regulation of differential genes), in which the GO analysis results of the differentially expressed genes were GO:0030574-collagen catabolic process, 16 participating genes, GO: 0030198-extracellular matrix organization 24 participating genes, G, G. O:0005578-proteinaceous extracellular matrix 25 participates in genes, and the GO analysis results of down regulated differentially expressed genes are: GO:0070062-extracellular exosome 117 participating genes, GO:0005615-extracellular space 89 participating genes, GO:0005576-extracellular region 90 participating genes, and package of GO analysis items up to up Further analysis of the differentially expressed genes found several genes that have the potential for tumor markers in BSCCE tumor tissues or are of great help to the long-term clinical prognosis, including 13 genes, such as ITGB4, COL5A1, LAMB3, and.2 KEGG analysis. In this analysis, several factors may be important for tumor pathology and immune microenvironment. P53signaling pathway, Toll-like receptor signaling pathway and so on. The results of differential gene analysis of down regulated expression include: Drug metabolism-cytochrome P450 pathway, MAPK signaling. Action pathway. results screened 11 genes related to.3 disease related to LAMB3, LAMC2, MFAP2 and other genes: 605027-Lymphoma, non-Hodgkin, somatic analysis and RAD54B, which may be associated with tumor pathology, and RAD54L on the screening and analysis of.4 core differential genes. After PPI analysis, a total of 30 differentially expressed genes with the number of more than 20 of the interaction were selected as the core differentially expressed genes, including 24 up and 6 down regulated genes, and 15 genes were screened for TOP2A, CDC20, and CDC6. Conclusion: our analysis results were screened for a total of 25 tumor related genes, of which GO analysis obtained I TGB4, LAMB3, ITGA6, TGFBI, LAMC2, MFAP2, collagen family COL5A1, COL7A1, COL1A1, COL1A2, collagenase family (MMP1,3,9) a total of 13 genes. COL1A1, COL1A2, MMP9, AURKA, CCNA2, BUB1, CDCA5, CCNE1, MCM2, NEK2 are 15 genes. These genes are worthy of further study in BSCCE tumor pathological indicators, forward survival predictive diagnosis and tumor gene target therapy.

【學(xué)位授予單位】：河北醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R735.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 ;Expression of Vascular Endothelial Growth Factor C and Its Clinical Significance in Human Esophageal Squamous Cell Carcinoma[J];Chinese Journal of Clinical Oncology;2007年02期

2 鄒小農(nóng);;食管癌流行病學(xué)[J];中華腫瘤防治雜志;2006年18期

3 徐衛(wèi)國(guó),楊國(guó)利,ボ立新,謝玉泉,張力建;PROGNOSTIC VALUE OF VEGF EXPRESSION IN PRIMARY ESOPHAGEAL SQUAMOUS CELL CARCINOMA[J];Chinese Journal of Cancer Research;2004年02期

，

本文編號(hào)：1845725