Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.
Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.
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DOI：
10.1038/srep11689
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发表时间：
2015-07-03
影响因子：
4.6
通讯作者：
Yu JS
中科院分区：
文献类型：
--
作者：
Chang KP;Lin SJ;Liu SC;Yi JS;Chien KY;Chi LM;Kao HK;Liang Y;Lin YT;Chang YS;Yu JS
癌细胞分泌组的分析被认为是鉴定癌症相关生物标志物的良好策略，但很少有研究集中于鉴定癌细胞分泌组中的低分子量（LMr）蛋白（<15 kDa）。在这里，我们使用tricine-SDS-gel-assisted fractionation和LC-MS/MS系统地确定LMR蛋白在5个口腔鳞状细胞癌（OSCC）细胞系的分泌。这些结果与9个OSCC组织转录组数据集的交叉匹配使我们能够鉴定出33个在OSCC组织中高度上调并从OSCC细胞分泌/释放的LMr基因/蛋白。采用免疫组化和实时荧光定量PCR技术检测HMGA 2和MIF在口腔鳞癌组织中的表达。两种蛋白的过度表达与宫颈转移、神经浸润、肿瘤浸润深度、总体分期较高以及治疗后生存预后较差相关。功能分析进一步表明，这两种蛋白在体外促进OSCC细胞系的迁移和侵袭。总的来说，我们的数据表明，tricine-SDS-gel/LC-MS/MS方法可以用来有效地识别LMR蛋白从口腔鳞癌细胞分泌，并建议HMGA 2和MIF可能是潜在的组织生物标志物的口腔鳞癌。
The profiling of cancer cell secretomes is considered to be a good strategy for identifying cancer-related biomarkers, but few studies have focused on identifying low-molecular-mass (LMr) proteins (<15 kDa) in cancer cell secretomes. Here, we used tricine–SDS-gel-assisted fractionation and LC–MS/MS to systemically identify LMr proteins in the secretomes of five oral cavity squamous cell carcinoma (OSCC) cell lines. Cross-matching of these results with nine OSCC tissue transcriptome datasets allowed us to identify 33 LMr genes/proteins that were highly upregulated in OSCC tissues and secreted/released from OSCC cells. Immunohistochemistry and quantitative real-time PCR were used to verify the overexpression of two candidates, HMGA2 and MIF, in OSCC tissues. The overexpressions of both proteins were associated with cervical metastasis, perineural invasion, deeper tumor invasion, higher overall stage, and a poorer prognosis for post-treatment survival. Functional assays further revealed that both proteins promoted the migration and invasion of OSCC cell lines in vitro. Collectively, our data indicate that the tricine–SDS-gel/LC–MS/MS approach can be used to efficiently identify LMr proteins from OSCC cell secretomes, and suggest that HMGA2 and MIF could be potential tissue biomarkers for OSCC.