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中文摘要
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胰腺癌给社会带来了巨大的负担,目前尚无有效的早期检测方法。一个 Glyco-微阵列方法将用于寻找胰腺癌的早期检测生物标志物 人体血浆。我们将使用多维液相分离完整的N-连接血浆糖蛋白 先前通过凝集素亲和层析柱分离。多维分馏将涉及无孔分馏 层析法分离糖蛋白和毛细管等电聚焦等电聚焦分离 蛋白质异构体,从而提供了一种手段,收集分离的糖形态在液体中进行进一步分析。 紫外线吸收检测将允许描绘癌症和对照之间的变化。感兴趣蛋白质 将通过质谱学进行鉴定。这些组分将在涂有硝基纤维素的显微镜上被发现。 载玻片产生天然糖蛋白微阵列,并将被各种荧光标记的询问 用凝集素探测每个微阵列斑点是否存在不同的糖链。胰腺癌患者 腺癌、胰腺粘液性囊性肿瘤和导管内乳头状黏液性肿瘤 (IPMNS),慢性胰腺炎。II型糖尿病10年或以上,正常患者将服务 作为感兴趣的疾病类别。每个类别30名参与者的血浆将被分析以进行搜索 寻找可以将MCNs/IPMN患者与其他疾病类别区分开来的模式。糖蛋白 这些变化将由QIT-TOF(MALDI-MSN)质谱学分析来检查 可作为生物标志物的糖链结构的详细变化。一旦潜在的生物标记物 将使用高通量抗体阵列来建立规划 验证性研究。这将包括初步分析验证,以确定个体内部和个体之间的关系 每个疾病目录使用30名参与者的可变性。接下来,我们将进行初步的决策分析 在每个疾病类别的50名参与者的开放标签测试集上。最后,一套盲目的化验 将对每个疾病类别的95名参与者进行治疗。这是一种系统的方法来检查分析 化验的特性将提供计划对这些早期检测进行验证所需的信息 胰腺癌的生物标志物。可以预见,这些生物标志物可以用于早期检测 在高危人群中,如吸烟者、长期患有II型糖尿病或慢性胰腺炎的患者。
英文摘要
Pancreatic cancer places a significant burden on society and has no effective early detection method. A glyco-microarray approach will be used to search for early detection biomarkers of pancreatic cancers in human plasma. We will use multi-dimensional liquid phase fractionation of intact N-linked plasma glycoproteins previously isolated by lectin affinity columns. The multi-dimensional fractionation will involve nonporous chromatography to separate the glycoproteins and liquid capillary isoelectric focusing to separate protein isoforms, thus providing a means to collect isolated glycoforms in liquid phase for further analysis. UV absorption detection will allow profiling of changes between cancer versus control. Proteins of interest will be identified by mass spectrometry. These fractions will be spotted on nitrocellulose-coated microscope slides to produce a natural glycoprotein microarray, and will be interrogated by various fluorescently-labeled lectins to probe each microarray spot for the presence of different glycan moieties. Patients with pancreatic adenocarcinoma, pancreatic mucinous cystic neoplasms (MCNs) and intraductal papillary mucinous neoplasms (IPMNs), chronic pancreatitis. Type II diabetes for 10 or more year, and normals patients will serve as the disease categories of interest. Plasma from 30 participants per category will be analyzed to search for patterns that can discriminate patients with MCNs/IPMNS from the other disease categories. Glycoproteins that reveal such changes will be analyzed by QIT-TOF (MALDI-MSn) mass spectrometry to examine the detailed changes in glycan structure that may serve as biomarkers. Once the potential bio-markers are identified, high throughput antibody arrays will be used to establish information necessary to plan a validation study. This will include initial analytical validation to define the within and between indi-vidual varaibility using 30 participants per disease cateogry. Next, preliminary decision analysis will be per-fonned on an open label set of assays from 50 participants per disease category. Finally, a blinded set of assays will be done on 95 particiants per disease category. This systematic approach to examing the analytic characteristics of the assay will provide information requhed to plan a valdiation of these early detection biomarkers for pancreatic cancer. It is envisioned that these biomarkers could be used for early detection among high risk groups such a smoker, patients with long term Type II diabetes or chronic pancreatitis.
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