iTRAQ联用串联质谱鉴定食管鳞状细胞癌差异表达蛋白质及蛋白质相互作用网络

基于质谱的蛋白质组学结果不仅具有重复性差和覆盖率低等缺陷，并且针对数十至百个差异表达蛋白质分子的分析非常具有挑战性，而蛋白质与蛋白质相互作用网络（protein-protein interaction network, PPIN）分析能够在一定程度上弥补上述不足，使各种组学研究结果具有一致性和可比性。本研究应用同位素标记相对和绝对定量（iTRAQ）联用串联质谱技术鉴定了与食管鳞状细胞癌（esophageal squamous cell carcinoma,ESCC）相关的差异表达蛋白质244个（ESCC中,升高和降低的蛋白质分别为119个和125个），基因本体论（gene ontology, GO）富集与肿瘤十大特征相关的17个GO条目|以该17个条目包含的117个蛋白质为种子蛋白搜索STRING（http: //www.string-db.org）数据库，构建包含96个存在相互作用的PPIN和21个离散蛋白质。用CytoHubba算法确定34个中心节点蛋白质和36个瓶颈蛋白质，非重复49个中心节点和/或瓶颈蛋白质中含7个目前已报道的癌基因表达蛋白（PPP2R1A、CTNNB1、ENO1、EZR、TPM4、COL1A1、TPM3），确定与该7个癌蛋白直接相互作用的4个蛋白质（FN1、ITGB1、TAGLN和YWHAZ）可能为参与食管癌变的关键蛋白质，并应用Western印迹实验验证了 FN1、ITGB1、TAGLN和YWHAZ等4个关键蛋白质在ESCC中具有显著的表达差异，表明PPIN分析是确定具有重要生物学意义分子的有效途经之一。

Analysis of Protein-protein Interaction Network using Fingerprinting Proteins Identified by iTRAQ and MS/MS

Mass-spectrometry-based proteomic profiling is troubled by limits in coverage and reproducibility. Protein-protein interaction network (PPIN) analysis compensates for such problems with improved consistency for comparisons in omic investigations. From the present study, a total of 244 differential proteins of 119 up-regulated and 125 down-regulated were identified from esophageal squamous cell carcinoma (ESCC) using isobaric tags relative and absolute quantitation (iTRAQ) combined with MS/MS. GO enrichment analysis determined 117 seed proteins in 17 GO terms with 10 tumor features. These seed proteins were send to STRING（http://www.string-db.org）for the building of PPIN, which results 96 interacting proteins and 21 scattered proteins. Using the CytoHubba algorithm, 34 hub and 36 bottleneck proteins were identified, including 49 non-redundant proteins overlapping with 7 known cancer proteins of PPP2R1A, CTNNB1, ENO1, EZR, TPM4, COL1A1 and TPM3. Four additional proteins interacting with the 7 cancer proteins were determined to be key proteins probably involved in esophageal carcinogenesis. Western blot was used to validate the 4 proteins of FN1, ITGB1,TAGLN and YWHAZ. Our results suggested that PPIN could be an effective approach to identify key proteins with biological functions.