TMT定量蛋白组学方法筛选乳腺癌腋窝淋巴结转移患者血清差异蛋白

目的:分析有腋窝淋巴结转移和无腋窝淋巴结转移的乳腺浸润性导管癌患者血清中的差异蛋白,筛选与乳腺癌转移相关的生物标志物和治疗靶点.方法:本研究采用定量蛋白质组学串联质谱标签(tandem mass tag,TMT)标记技术分别对14例有腋窝淋巴结转移及14例无腋窝淋巴结转移的乳腺癌患者血清蛋白进行检测,并对蛋白质进行定量分析,筛选出发生显著变化的差异蛋白,再搜索Uniprot数据库和用Proteome Discoverer软件分析,进一步进行生物信息学分析.结果:有腋窝淋巴结转移组中共筛选出差异蛋白119个,其中6个表达上调,113个表达下调.基因本体(gene ontology,GO)注释分析和功能聚类分析表明,这些差异蛋白质主要定位于细胞外区,与肿瘤的生物合成、细胞增殖、血管生成相关.Western boltting和qRT-PCR验证了K1C19(下调0.11倍)和PSME2(上调2.02倍)的表达.结论:TMT定量蛋白组学方法能有效筛选有腋窝淋巴结转移的和无腋窝淋巴结转移的乳腺癌患者血清中的差异蛋白.其中,K1C19和PSME2是值得进一步研究的乳腺癌淋巴结转移的候选血清标志物.

Application of TMT quantitative proteomics in identification of differentially expressed serum proteins of breast cancer patients with axillary lymph node metastasis

Objective:To indentify the differentially expressed proteins in serum among patients of breast cancer with and without axillary lymph node metastasis,and to screen the diagnostic biomarkers and therapeutic targets that related to breast cancer metastasis.Methods:Quantitative proteomics TMT (tandem mass tag) technology was used to detect and quantitatively analyze serum proteins of breast cancer patients with and without axillary lymph node metastasis (14 cases in each group),and to further screen significant differentially expressed proteins.Uniprot database and proteome discoverer software were applied to analyze the bioinformatics.Results:One hundred and nineteen differentially expressed proteins were identified,and 6 proteins were significantly up-regulated,113 proteins were significantly down-regulated.Gene ontology (GO) annotation and functional cluster analyses showed that these differentially expressed proteins are locate at extracellular domain,and correlate with biosynthesis,cell proliferation and angiogenesis of tumor.Western boltting and qRT-PCR verified that the expressions of K1C19 (down-regulated by 0.11 times) and PSME2 (up-regulated by 2.02 times).Conclusion:TMT quantitative proteomics is a compelling way to discover differentially expressed proteins of breast cancer patients with and without axillary lymph node metastasis,and K1C19 and PSME2 are the potential serum biomarkers that deserve further exploration.