BACKGROUND Identification and treatment in the early stage can significantly improve the prognosis of gastric cancer (GC). However, to date, there is still no ideal biomarker that can be used for the screening of early stage GC (EGC). The proteomics supported by mass spectrometry offers more possibilities for discovering tumor biomarkers. The aim of this study was to explore candidate protein biomarkers for EGC screening with mass spectrometry and bioinformatics technology. METHODS Plasma samples were collected from 15 EGC patients and 15 healthy controls. After a selective immune-depletion to remove high abundance proteins, plasma samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with the tandem mass tags (TMT) labeling. RESULTS A total of 2040 proteins were identified, and 11 proteins were found to be differentially expressed. The results of the logistic regression model and orthogonal signal correction-partial least squares discriminant analysis (OPLS-DA) model showed that the changed proteins identified by plasma proteomics could help distinguish EGC patients from healthy controls. CONCLUSION The proteins identified by plasma proteomics using LC-MS/MS combined with TMT labeling could help distinguish EGC from healthy controls.

中文翻译：

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基于血浆蛋白质组学的早期胃癌新生物标志物的鉴定。

背景技术早期的鉴定和治疗可以显着改善胃癌（GC）的预后。然而，迄今为止，仍然没有理想的生物标志物可用于筛选早期GC（EGC）。质谱支持的蛋白质组学为发现肿瘤生物标志物提供了更多可能性。这项研究的目的是探索质谱和生物信息学技术用于EGC筛选的候选蛋白质生物标记。方法收集15例EGC患者和15例健康对照者的血浆样本。在选择性免疫去除以去除高丰度蛋白质后，通过液相色谱-串联质谱（LC-MS / MS）结合串联质量标签（TMT）标记来分析血浆样品。结果共鉴定出2040种蛋白质，发现11种蛋白质差异表达。Logistic回归模型和正交信号校正-偏最小二乘判别分析（OPLS-DA）模型的结果表明，血浆蛋白质组学鉴定的蛋白质变化有助于将EGC患者与健康对照区分开。结论血浆蛋白质组学使用LC-MS / MS结合TMT标记鉴定出的蛋白质可帮助将EGC与健康对照区分开。