Roy Bibhas, Chattopadhyay Gautam, Mishra Debasish, Das Tamal, Chakraborty Suman, Maiti Tapas K
Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, India.
Department of Surgical Gastroenterology, Kolkata Medical College, Kolkata, India.
Biomicrofluidics. 2014 Jun 6;8(3):034107. doi: 10.1063/1.4882778. eCollection 2014 May.
An on-chip lectin microarray based glycomic approach is employed to identify glyco markers for different gastritis and gastric cancer. Changes in protein glycosylation have impact on biological function and carcinogenesis. These altered glycosylation patterns in serum proteins and membrane proteins of tumor cells can be unique markers of cancer progression and hence have been exploited to diagnose various stages of cancer through lectin microarray technology. In the present work, we aimed to study the alteration of glycan structure itself in different stages of gastritis and gastric cancer thoroughly. In order to perform the study from both serum and tissue glycoproteins in an efficient and high-throughput manner, we indigenously developed and employed lectin microarray integrated on a microfluidic lab-on-a-chip platform. We analyzed serum and gastric biopsy samples from 8 normal, 15 chronic Type-B gastritis, 10 chronic Type-C gastritis, and 6 gastric adenocarcinoma patients and found that the glycoprofile obtained from tissue samples was more distinctive than that of the sera samples. We were able to establish signature glycoprofile for the three disease groups, that were absent in healthy normal individuals. In addition, our findings elucidated certain novel signature glycan expression in chronic gastritis and gastric cancer. In silico analysis showed that glycoprofile of chronic gastritis and gastric adenocarcinoma formed close clusters, confirming the previously hypothesized linkage between them. This signature can be explored further as gastric cancer marker to develop novel analytical tools and obtain in-depth understanding of the disease prognosis.
一种基于芯片凝集素微阵列的糖组学方法被用于识别不同胃炎和胃癌的糖标记物。蛋白质糖基化的变化会影响生物学功能和致癌作用。肿瘤细胞血清蛋白和膜蛋白中这些改变的糖基化模式可能是癌症进展的独特标记物,因此已被用于通过凝集素微阵列技术诊断癌症的各个阶段。在本研究中,我们旨在深入研究胃炎和胃癌不同阶段聚糖结构本身的变化。为了以高效且高通量的方式从血清和组织糖蛋白进行研究,我们自主开发并采用了集成在微流控芯片实验室平台上的凝集素微阵列。我们分析了8名正常、15名慢性B型胃炎、10名慢性C型胃炎和6名胃腺癌患者的血清和胃活检样本,发现从组织样本获得的糖谱比血清样本更具特异性。我们能够为三个疾病组建立特征性糖谱,而健康正常个体中不存在这些糖谱。此外,我们的研究结果阐明了慢性胃炎和胃癌中某些新的特征性聚糖表达。计算机分析表明,慢性胃炎和胃腺癌的糖谱形成了紧密的聚类,证实了之前假设的它们之间的联系。这种特征可以作为胃癌标记物进一步探索,以开发新的分析工具并深入了解疾病预后。