【作者】 王哲；

【导师】 孟子辉；

【作者基本信息】 吉林大学 ， 临床医学硕士（专业学位）， 2024， 硕士

【摘要】 目的:随着对肿瘤研究的不断深入,肿瘤微环境逐渐受到人们的关注。Toll样受体4(Toll-like receptor 4,TLR4)对细菌、免疫细胞等具有一定的影响,发挥着桥梁作用。然而,TLR4在胰腺癌中的作用机制尚未形成明确共识。在正常组织中,免疫细胞表面的TLR4能够识别脂多糖,进而识别革兰氏阴性杆菌,从而激活免疫反应。相比之下,肿瘤细胞内TLR4的表达量明显升高,这促进了肿瘤细胞的免疫逃逸。本研究通过分析TCGA数据库中与胰腺癌相关的数据集,进一步探究了TLR4对胰腺癌肿瘤微环境中免疫细胞浸润的影响,以及相关基因对预后的影响。这一研究旨在探索肿瘤微生物相关的抗肿瘤治疗潜在靶点。方法:在Sanger Box3.0-生物医学数据分析盒子(http://sangerbox.com/home.html)中以“胰腺癌”为关键词,以转录组测序(RNA-Seq)为测序手段,以人类胰腺组织作为测序样本从TCGA(The I Cancer Genome Atlas Program)数据库中检索相关数据集;依据TLR4的表达量高低将样本分为两组,运用limma快速差异分析工具对数据进行差异分析;而后利用差异基因GO、KEGG、GSEA分析探索TLR4的相关通路及功能;运用RStudio软件将差异基因数据进行CIBERSIRT免疫浸润分析;提取差异基因数据并结合临床信息进行生存分析;运用STRING数据库(https://string-db.org/)将与生存相关的差异基因构建PPI蛋白质相互作用网络,再使用Cytoscape软件内的Cytohubba插件筛选Top 10 Degree蛋白的代表基因,探寻胰腺癌潜在的药物治疗靶点。结果:1.根据检索标准,纳入TCGA数据库内胰腺癌数据集进行后续分析。2.数据集中共得到54467个基因,筛选得到与TLR4相关的333个差异表达基因,其中低表达量基因12个,高表达量基因321个。3.差异共表达基因富集到的GO Terms的关键词为“免疫”、“细胞外液”、“抗原结合”、“信号受体结合”、“蛋白结合”等;KEGG富集分析结果显示,最显著富集的是“噬菌体”、“金黄色葡萄球菌”、“细胞因子-细胞因子受体相互作用”等信号通路;GSEA中差异基因高表达且富集于的通路包括参与调节巨噬细胞功能和抗菌反应、参与调节Fox P3+CD4+调节性T细胞(Treg)的功能、参与调节抗原的呈递、参与调节浆细胞分化和T细胞稳态等。4.免疫浸润分析结果提示TLR4与免疫明显相关,其中M2巨噬细胞浸润程度的增加与自然杀伤性细胞浸润程度的降低尤为明显。5.生存分析结果提示,42个差异基因与生存明显相关,可能影响患者预后。6.属于生存分析有明显差异且PPI网络中排名Top 10 Degree蛋白的基因分别为COL8A1、SULF1、MFAP5、ITGBL1、COL10A1、FBN1、COL6A3、THBS2、COL11A1、INHBA。结论:1、结果显示,TLR4表达升高对调节性T细胞、树突状细胞、巨噬细胞等免疫细胞的相关通路产生了明显影响,这说明胰腺癌肿瘤微环境中的浸润程度与TLR4息息相关。2、我们通过差异基因分析与PPI网络构建,筛选出与TLR4表达呈明显相关的十个基因,其中COL8A1、SULF1、MFAP5、ITGBL1、COL10A1、FBN1、COL6A3、THBS2、COL11A1、INHBA与其呈正相关。并且,SULF1、MFAP5、COL11A1、COL6A3、FBN1等基因的高表达与胰腺癌患者预后不佳有关。这可能是基于肿瘤内微生物抗肿瘤治疗的潜在靶点。更多还原

【Abstract】 Purpose:With the deepening of tumor research,the tumor microenvironment has gradually attracted attention,and Toll-like receptor 4(TLR4)plays a bridging role by influencing bacteria,immune cells,etc.However,there is no clear consensus on the mechanism of TLR4 in pancreatic cancer.However,there is no clear consensus on the mechanism of TLR4 in pancreatic cancer.In normal tissues,TLR4 on the surface of immune cells is able to recognize lipopolysaccharides,which in turn recognize Gram-negative bacilli,thus activating the immune response.In contrast,the expression of TLR4 in tumor cells is significantly elevated,which promotes the immune escape of tumor cells.In this study,we further explored the effect of TLR4 on immune cell infiltration in the tumor microenvironment of pancreatic cancer and the prognostic impact of related genes by analyzing the TCGA database dataset related to pancreatic cancer.This study aims to explore potential targets for tumor microbe-related antitumor therapy.Methods:In Sanger Box 3.0-Biomedical Data Analysis Box(http://sangerbox.com/home.html),the keyword "pancreatic cancer" was used,and human pancreatic tissues were used as sequencing samples from the TCGA(The I Cancer Genome Activity Group),and the sequencing samples were sequenced by RNA-Seq.The TCGA(The I Cancer Genome Atlas Program)database was used to retrieve the relevant datasets;the samples were divided into two groups according to the level of TLR4 expression,and the data were analyzed using the limma rapid difference analysis tool;the GO,KEGG,and GSEA differential genes were used to explore the relevant pathways and functions of TLR4;and RStudio software was used to analyze the differential genes and the functions of TLR4.RStudio software was used to analyze the differential gene data for CIBERSIRT immuno-infiltration analysis;the differential gene data were extracted and combined with clinical information for survival analysis;the survival-related differential genes were used to construct a PPI protein interaction network using the STRING database(https://string-db.org/),and then the Cytoscape software was used to analyze the differential gene data using Cytohubba.The Cytohubba plug-in in Cytoscape software was used to screen the representative genes of Top 10 Degree proteins to explore the potential therapeutic targets of pancreatic cancer.Results:1.According to the search criteria,the pancreatic cancer dataset within the TCGA database was included for subsequent analysis.2.A total of 54,467 genes were obtained from the dataset,and 333 differentially expressed genes related to TLR4 were identified,including 12 low-expression genes and 321 high-expression genes.3.The keywords of GO Terms enriched for differentially co-expressed genes are "immunity","extracellular fluid","antigen binding","signal receptor binding","signaling receptor binding","signaling receptor binding","signaling receptor binding","signaling receptor binding","signaling receptor binding","signaling receptor binding" and "signaling receptor binding".Signal receptor binding "," protein binding ",etc.KEGG enrichment analysis showed that the most significantly enriched genes were " phage "," Staphylococcus aureus The KEGG enrichment analysis showed that the most significantly enriched signaling pathways were "phage","Staphylococcus aureus","cytokine-cytokine receptor interaction",etc.The differentially expressed and enriched pathways in GSEA included those involved in the regulation of macrophage function and antimicrobial response,the regulation of the function of Fox P3+ CD4+ regulatory T-cells(Treg),the regulation of antigen presentation,and the regulation of antigen delivery.The pathways that are highly expressed and enriched in these pathways include those involved in the regulation of macrophage function and antimicrobial response,the regulation of Fox P3+ CD4+regulatory T cells(Treg)function,the regulation of antigen presentation,the regulation of plasma cell differentiation,and T cell homeostasis.4.The results of immune infiltration analysis suggested that TLR4 was significantly correlated with immunity,in which the increase in the degree of M2 macrophage infiltration and the decrease in the degree of natural killer cell infiltration were particularly obvious.5.The results of survival analysis suggested that 42 differential genes were significantly correlated with survival,which may affect the prognosis of patients.6.The proteins belonging to the survival analysis that were significantly different and ranked within the Top 10 Degrees in the PPI network were COL8A1,SULF1,MFAP5,ITGBL1,COL10A1,FBN1,COL6A3,THBS2,COL11A1,and INHBA,respectively.Conclusion:1,The results showed that elevated TLR4 expression had a significant impact on the relevant pathways of regulatory T cells,dendritic cells,macrophages and other immune cells,which suggests that the degree of infiltration in the tumor microenvironment of pancreatic cancer is closely related to TLR4.2.Through differential gene analysis and PPI network construction,we screened ten genes that were significantly correlated with TLR4 expression,among which COL8A1,SULF1,MFAP5,ITGBL1,COL10A1,FBN1,COL6A3,THBS2,COL11A1,and INHBA were positively correlated with it.Moreover,high expression of SULF1,MFAP5,COL11A1,COL6A3,and FBN1 was associated with poor prognosis of pancreatic cancer patients.This may be a potential target for anti-tumor therapy based on microbes within the tumor.更多还原