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使用凝集素/糖抗体阵列法检测胰腺癌血清

Pancreatic cancer serum detection using a lectin/glyco-antibody array method.

作者信息

Li Chen, Simeone Diane M, Brenner Dean E, Anderson Michelle A, Shedden Kerby A, Ruffin Mack T, Lubman David M

机构信息

Department of Chemistry, The University of Michigan, Ann Arbor, Michigan 48109, USA.

出版信息

J Proteome Res. 2009 Feb;8(2):483-92. doi: 10.1021/pr8007013.

Abstract

Pancreatic cancer is a formidable disease and early detection biomarkers are needed to make inroads into improving the outcomes in these patients. In this work, lectin antibody microarrays were utilized to detect unique glycosylation patterns of proteins from serum. Antibodies to four potential glycoprotein markers that were found in previous studies were printed on nitrocellulose coated glass slides and these microarrays were hybridized against patient serum to extract the target glycoproteins. Lectins were then used to detect different glycan structural units on the captured glycoproteins in a sandwich assay format. The biotinylated lectins used to assess differential glycosylation patterns were Aleuria aurentia lectin (AAL), Sambucus nigra bark lectin (SNA), Maackia amurensis lectin II (MAL), Lens culinaris agglutinin (LCA), and Concanavalin A (ConA). Captured glycoproteins were evaluated on the microarray in situ by on-plate digestion and direct analysis using MALDI QIT-TOF mass spectroscopy. Analysis was performed using serum from 89 normal controls, 35 chronic pancreatitis samples, 37 diabetic samples and 22 pancreatic cancer samples. We found that this method had excellent reproducibility as measured by the signal deviation of control blocks as on-slide standard and 41 pairs of pure technical replicates. It was possible to discriminate cancer from the other disease groups and normal samples with high sensitivity and specificity where the response of Alpha-1-beta glycoprotein to lectin SNA increased by 69% in the cancer sample compared to the other noncancer groups (95% confidence interval 53-86%). These data suggest that differential glycosylation patterns detected on high-throughput lectin glyco-antibody microarrays are a promising biomarker approach for the early detection of pancreatic cancer.

摘要

胰腺癌是一种可怕的疾病,需要早期检测生物标志物来改善这些患者的治疗结果。在这项研究中,凝集素抗体微阵列被用于检测血清中蛋白质独特的糖基化模式。将先前研究中发现的四种潜在糖蛋白标志物的抗体印在硝酸纤维素包被的载玻片上,这些微阵列与患者血清杂交以提取目标糖蛋白。然后使用凝集素以夹心测定形式检测捕获的糖蛋白上不同的聚糖结构单元。用于评估差异糖基化模式的生物素化凝集素是橙黄网柄菌凝集素(AAL)、黑接骨木树皮凝集素(SNA)、山嵛菜凝集素II(MAL)、菜豆凝集素(LCA)和伴刀豆球蛋白A(ConA)。通过板上消化和使用基质辅助激光解吸电离四级杆飞行时间质谱(MALDI QIT-TOF MS)直接分析,对微阵列上捕获的糖蛋白进行原位评估。使用来自89名正常对照、35份慢性胰腺炎样本、37份糖尿病样本和22份胰腺癌样本的血清进行分析。我们发现,以对照块的信号偏差作为载玻片上的标准以及41对纯技术重复样本进行测量时,该方法具有出色的重现性。能够以高灵敏度和特异性将癌症与其他疾病组和正常样本区分开来,其中癌症样本中α-1-β糖蛋白对凝集素SNA的反应比其他非癌症组增加了69%(95%置信区间53-86%)。这些数据表明,在高通量凝集素糖抗体微阵列上检测到的差异糖基化模式是一种有前景的胰腺癌早期检测生物标志物方法。

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