Dynamic Change of Serum Proteomics of Occupational MedicamentosalikeDermatitis Induced by Trichloroethylene
Dynamic Change of Serum Proteomics of Occupational MedicamentosalikeDermatitis Induced by Trichloroethylene
复制标题
DOI：
10.4172/2161-0495.1000275
复制
发表时间：
2015-12
期刊：
影响因子：
--
通讯作者：
Liu Wei;W. Hong;Yawen Zhang;X. Ren;Peimao Li;Zhimin Zhang;Hai-yan Huang;Xinfeng Huang;Yanfang Zhang;Jianjun Liu
中科院分区：
文献类型：
--
作者：
Liu Wei;W. Hong;Yawen Zhang;X. Ren;Peimao Li;Zhimin Zhang;Hai-yan Huang;Xinfeng Huang;Yanfang Zhang;Jianjun Liu
目的：近年来，三氯乙烯职业药疹样皮炎（OMLDT）生物标志物的研究得到广泛开展。但血清中蛋白质生物标志物的动态变化却很少有报道。本研究旨在探讨OMLDT不同时期血清蛋白/多肽的动态变化规律，寻找潜在的生物标志物，为监测疾病进展和筛查高危人群提供科学依据。研究设计：我们开发了一种结合基于磁珠的弱阳离子交换色谱（MB-WCX）、基质辅助激光解吸电离飞行时间质谱（MALDITOF- MS）和ClinProTools软件的方法。根据血清多肽指纹图谱（PFS）的变化，建立OMLDT诊断模型，筛选特异性蛋白/多肽生物标志物，进一步研究典型OMLDT患者不同时期的动态变化规律。结果：在OMLDT/Normal模型中得到72个峰，其中52个峰为差示峰。在OMLDT/TCE接触模型中得到69个显著峰，但差示峰只有35个。两种模型的差异峰中有21个特征峰相似，表达量变化一致。在21个特异峰中，4个峰（m/z 410942675065和9287 Da）在4例复发患者的3个周期内变化基本一致，2个峰（4109和9173 Da）在3例稳定患者的3个周期内变化基本一致。有趣的是，两组中均出现m/z 4109 Da，且表达水平随病程增加而增加。因此，它可能是OMLDT的特异性血清标志物。结论：总体而言，结果表明，特定的PFS可以作为一个有用的工具，以反映蛋白质/多肽在OMLDT的不同时期的动态变化。为临床应用提供了新的思路。
Objective: Extensive researches about biomarkers of Occupational medicamentosa-like dermatitis induced by Trichloroethylene (OMLDT) have been carried out in recent years. But dynamic change of protein biomarkers in serum has rarely been reported. The aim of our study was to explore the dynamic changing law of serum proteins/ polypeptides in different periods of OMLDT, identify potential biomarkers and provide the scientific fundamentals for monitoring the progression of the disease and screening high-risk population. Study design: We developed an approach in the combination of magnetic beads based weak cation exchange chromatography (MB-WCX), matrix assisted laser desorption ionization time of flight mass spectrometry (MALDITOF- MS) and ClinProTools software. Based on the alternations in the polypeptides fingerprint of serum (PFS), we built diagnostic models of OMLDT, and screened the special proteins/ polypeptides biomarkers and further studied the dynamic changing law of different periods in typical OMLDT patients. Results: We attained 72 peaks which were statistical content in OMLDT/Normal model, of which 52 peaks were differential peaks. We also obtained 69 significant peaks in OMLDT/TCE Contact model, but the differential peaks were 35. There were 21 specific peaks which were alike among the differential peaks in these two models and the change of their expression level was consistent. Among the 21 specific peaks, we found 4 peaks, which were m/z 410942675065 and 9287Da, changed nearly the same in 3 periods of 4 recurrent patients, and 2 peaks (4109 and 9173 Da) changed consistent in 3 periods of 3 stable patients. Interestingly, m/z 4109 Da appeared in both groups and the expression level was increased with the course of disease. So it may be the special serum biomarker of OMLDT. Conclusion: Overall, the results indicate specific PFS could serve as a useful tool to reflect the dynamic change of proteins/ polypeptides in different periods of OMLDT. And it may provide a new clue for clinical application.