【摘要】 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(i TRAQ)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Cyto Hubba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。更多还原

【Abstract】 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( i TRAQ)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 Cyto Hubba algorithm,34 hub and 36 bottleneck proteins were identified,including 49 non-redundant proteins overlapping with7 known cancer proteins of PPP2R1 A,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.更多还原