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从胃癌分泌组中挖掘:GRN 作为早期胃癌潜在诊断标志物的鉴定。

Mining the gastric cancer secretome: identification of GRN as a potential diagnostic marker for early gastric cancer.

机构信息

Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore , 8 Medical Drive, Singapore 117597.

出版信息

J Proteome Res. 2012 Mar 2;11(3):1759-72. doi: 10.1021/pr201014h. Epub 2012 Feb 2.

DOI:10.1021/pr201014h
PMID:22204653
Abstract

Gastric cancer is the second leading cause of cancer deaths worldwide, and currently, there are no clinically relevant biomarkers for gastric cancer diagnosis or prognosis. In this study, we applied a 2D-LC-MS/MS based approach, in combination with iTRAQ labeling, to study the secretomes of the gastric cancer cell lines AGS and MKN7. By performing a comparative analysis between the conditioned media and the whole cell lysates, our workflow allowed us to differentiate the bona fide secreted proteins from the intracellular contaminants within the conditioned media. Ninety proteins were found to have higher abundance in the conditioned media as compared to the whole cell lysates of AGS and MKN7 cells. Using a signal peptide and nonclassical secretion prediction tool and an online exosome database, we demonstrated that up to 92.2% of these 90 proteins can be exported out of the cells by classical or nonclassical secretory pathways. We then performed quantitative comparisons of the secretomes between AGS and MKN7, identifying 43 differentially expressed secreted proteins. Among them, GRN was found to be frequently expressed in gastric tumor tissues, but not in normal gastric epithelia by immunohistochemistry. Sandwich ELISA assay also showed elevation of serum GRN levels in gastric cancer patients, particularly those with early gastric cancer. Receiver operating characteristic (ROC) curves analysis confirmed that serum GRN can provide diagnostic discriminations for gastric cancer patients.

摘要

胃癌是全球癌症死亡的第二大主要原因,目前尚无用于胃癌诊断或预后的临床相关生物标志物。在本研究中,我们应用了一种基于 2D-LC-MS/MS 的方法,结合 iTRAQ 标记,来研究胃癌细胞系 AGS 和 MKN7 的分泌组。通过对条件培养基和全细胞裂解物进行比较分析,我们的工作流程使我们能够区分条件培养基中真正的分泌蛋白和细胞内污染物。与 AGS 和 MKN7 细胞的全细胞裂解物相比,有 90 种蛋白在条件培养基中的丰度更高。使用信号肽和非经典分泌预测工具以及在线外泌体数据库,我们证明了这些 90 种蛋白中有高达 92.2%可以通过经典或非经典分泌途径从细胞内输出。然后,我们对 AGS 和 MKN7 之间的分泌组进行了定量比较,鉴定出 43 种差异表达的分泌蛋白。其中,GRN 通过免疫组织化学染色在胃癌肿瘤组织中频繁表达,但在正常胃上皮组织中不表达。夹心 ELISA 检测还显示,胃癌患者,尤其是早期胃癌患者的血清 GRN 水平升高。受试者工作特征(ROC)曲线分析证实,血清 GRN 可用于胃癌患者的诊断鉴别。

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