Importin subunit alpha-2 is identified as a potential biomarker for non-small cell lung cancer by integration of the cancer cell secretome and tissue transcriptome
Importin subunit alpha-2 is identified as a potential biomarker for non-small cell lung cancer by integration of the cancer cell secretome and tissue transcriptome
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DOI：
10.1002/ijc.25568
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发表时间：
2011-05-01
影响因子：
6.4
通讯作者：
Yu, Chia-Jung
中科院分区：
文献类型：
--
作者：
Wang, Chun-I.;Wang, Chih-Liang;Yu, Chia-Jung
癌细胞分泌组可能含有潜在有用的生物标志物。在本研究中，我们将肺癌细胞系中的分泌蛋白谱与肺腺癌组织的mRNA表达水平相结合，以期鉴定非小细胞肺癌（NSCLC）的有效生物标志物。在分离的新候选物中，选择输入蛋白亚基 α-2（也称为核转运蛋白亚基 α [KPNA]-2）进行进一步验证。免疫组织化学染色显示，与邻近的正常细胞相比，肿瘤细胞的细胞核中 KPNA2 过度表达。为检测血清样本中 KPNA2 水平而开发的夹心 ELISA 检测显示，NSCLC 患者的血清 KPNA2 显着高于健康对照。血清 KPNA2 和癌胚抗原的组合显示出比单独使用任一标记物更高的诊断能力。重要的是，NSCLC 患者胸腔积液中 KPNA2 的蛋白水平也显着高于非肺癌患者的胸腔积液。此外，KPNA2的敲低抑制了肺癌细胞的迁移能力和活力。我们的结果总体表明，癌细胞分泌组和转录组数据集的整合提供了识别 NSCLC 新型生物标志物（例如 KPNA2）的有效方法。
The cancer cell secretome may contain potentially useful biomarkers. In this study, we integrated the profiles of secreted proteins in lung cancer cell lines with mRNA expression levels from pulmonary adenocarcinoma tissue, with a view to identify effective biomarkers for non-small cell lung cancer (NSCLC). Among the novel candidates isolated, importin subunit alpha-2 (also known as karyopherin subunit alpha [KPNA]-2), was selected for further validation. Immunohistochemical staining revealed overexpression of KPNA2 in the nuclei of tumor cells, compared with adjacent normal cells. A sandwich ELISA assay developed to detect KPNA2 levels in serum samples showed significantly higher serum KPNA2 in NSCLC patients than in healthy controls. A combination of serum KPNA2 and carcinoembryonic antigen displayed higher diagnostic capacity than either marker alone. Importantly, protein levels of KPNA2 in pleural effusion from NSCLC patients were also significantly higher than those from non-lung cancer. Moreover, knockdown of KPNA2 inhibited the migration ability and viability of lung cancer cells. Our results collectively suggest that integration of the cancer cell secretome and transcriptome datasets provides an efficient means of identifying novel biomarkers for NSCLC, such as KPNA2.