血清小分子代谢产物与大肠癌淋巴结转移状态相关性的初步研究

发布时间：2018-04-21 15:19

本文选题：大肠癌 + 代谢组学　；参考：《吉林大学》2017年硕士论文

【摘要】：目的:寻找有无淋巴结转移的大肠癌患者血清中差异性小分子代谢产物,探索代谢产物对不同淋巴结转移状态大肠癌的区分能力;初步探索小分子代谢产物对大肠癌淋巴结转移状态预测的生物学机制,为代谢产物对大肠癌淋巴结转移状态的预测提供理论依据;基于代谢产物和临床病理资料用逻辑回归建立大肠癌淋巴结转移预测模型。方法:1、运用色谱质谱仪器(LC-MS)对上清液进行检测,得到不同淋巴结分期患者代谢产物的表达丰度值,寻找具有差异性的代谢产物。2、根据筛选出的差异性代谢产物对单独样本进行分组,应用免疫组化染色(Immunohistochemistry,IHC)技术检测各组癌组织中VEGF-C、VEGF-D表达,癌旁组织淋巴管密度(LVD),应用酶联免疫吸附法(ELISA)测定各组样本血清中VEGF-C、VEGF-D含量。3、用多因素逻辑回归筛统计方法筛选出大肠癌淋巴结转移的独立危险因素,并建立大肠癌淋巴结转移逻辑回归模型。4、代谢组学数据运用主成分分析、t检验、判别分析、聚类分析等方法对数据进行统计分析,免疫组化数据应用统计软件SPSS17.0对数据进行统计分析。结果:1、通过应用高效液相色谱-质谱技术分别对50例T3N0M0和T3N1-3M0期大肠癌患者血清中代谢产物进行测定,经统计学分析,找到6种差异性代谢产物,这6种差异性代谢产物能很好判别大肠癌淋巴结转移状态。2、基于6种差异性代谢产物对56例单独T3N0-3M0期大肠癌患者血清样本进行分组,可大致将样本分为A、B两组,B组中淋巴结转移阳性样本显著多于A组(P=0.000),B组样本癌组织中的VEGF-C(P=0.007)、D(P=0.014)水平和癌旁组织淋巴管密度(P=0.001)均显著高于A组,A、B两组样本血清中VEGF-C(P=0.339)和VEGF-D(P=0.451)浓度差异无统计学意义,A组患者总的生存率显著高于B组(P=0.04)。3、将6种差异性代谢产物和临床病理资料通过多因素逻辑回归筛选出大肠癌淋巴结转移的6种独立危险因素,并根据独立危险因素建立风险评分模型,该模型对大肠癌淋巴结转移具有良好预测能力。结论:1.不同淋巴结转移状态大肠癌患者血清中存在差异性代谢产物;2.代谢产物可以对大肠癌患者不同淋巴结转移状态进行较好区分;3.对大肠癌淋巴结转移状态有区分能力的代谢产物与癌组织中VEGF-C、D的表达和癌旁组织新生淋巴管具有相关性;4.根据临床病理资料和代谢产物用逻辑回归选出Tyramine、Docosahexaenoic acid、Calcitroic acid、Glucosylsphingosine、Lyso PE(24:1(15Z)/0:0)、Ki-67六个独立危险因素;5.根据六种独立危险因素所建立的Logistic回归模型对大肠癌淋巴结转移状态具有良好预测能力。
[Abstract]:Objective: to explore the differential small molecule metabolites in the serum of colorectal cancer patients with or without lymph node metastasis, and to explore the ability of the metabolites to differentiate colorectal cancer with different lymph node metastases. To explore the biological mechanism of small molecular metabolites in predicting lymph node metastasis status of colorectal cancer, and to provide theoretical basis for predicting lymph node metastasis status of colorectal cancer by metabolites. Based on metabolites and clinicopathological data, a predictive model for lymph node metastasis of colorectal cancer was established by logical regression. Methods: 1. The supernatant was detected by the chromatographic mass spectrometer (LC-MS), and the expression abundance of metabolites in patients with different lymph node stages was obtained. To find the different metabolite. 2. To group the individual samples according to the different metabolites, and to detect the VEGF-D expression in the tissues of each group by immunohistochemical staining. Lymphatic vessel density (LVD) in adjacent tissues was determined by Elisa. Serum VEGF-CnVEGF-D was determined by Elisa. The independent risk factors for lymph node metastasis of colorectal carcinoma were screened by multivariate logistic regression screening. The logistic regression model of lymph node metastasis of colorectal cancer was established. The main component analysis (PCA), discriminant analysis and cluster analysis were used to analyze the data of metabonomics. Immunohistochemical data were analyzed by statistical software SPSS17.0. Results by using high performance liquid chromatography-mass spectrometry (HPLC / MS), the metabolites in serum of 50 patients with colorectal cancer in T3N0M0 and T3N1-3M0 stage were determined, and six different metabolites were found by statistical analysis. These six different metabolites can distinguish the lymph node metastasis status of colorectal cancer. Based on the six different metabolites, 56 serum samples of patients with T3N0-3M0 stage colorectal cancer were divided into two groups. It can be roughly divided into two groups: the positive samples of lymph node metastasis in group B are significantly higher than those in group A (P = 0.000) and the levels of VEGF-CnP 0.007 (P _ (0.014)) and the density of lymphatic vessels in adjacent tissues (P _ (0.001)) are significantly higher than those in group A (group A) and group A (AB) (0.339) and VEGF-DU (0.451)). The overall survival rate of patients in group A was significantly higher than that in group B (P 0.04). Six independent risk factors for lymph node metastasis of colorectal cancer were screened by multivariate logistic regression based on 6 different metabolites and clinicopathological data. Risk scoring model was established according to independent risk factors. The model has good predictive ability for lymph node metastasis of colorectal cancer. Conclusion 1. There are different metabolites in the serum of colorectal cancer patients with different lymph node metastases. Metabolites can distinguish different lymph node metastasis status of colorectal cancer patients. The metabolites which have the ability to distinguish the metastatic status of colorectal cancer are related to the expression of VEGF-CfD and the new lymphatic vessels in the adjacent tissues of colorectal carcinoma. Based on the clinicopathological data and metabolites, six independent risk factors of Tyramineus Docosahexaenoic acido Calcitroic acido Glucosylsphingosine Lyso 24: 1 / 0: 0% Ki-67 were selected. The Logistic regression model based on six independent risk factors can predict lymph node metastasis of colorectal cancer.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R735.34

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