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Identification of Five Candidate Lung Cancer Biomarkers by Proteomics Analysis of Conditioned Media of Four Lung Cancer Cell Lines*

机译:通过蛋白质组学技术分析四种肺癌细胞系的条件培养基,从而鉴定出五种候选肺癌生物标志物*

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摘要

Detection of lung cancer at an early stage is necessary for successful therapy and improved survival rates. We performed a bottom-up proteomics analysis using a two-dimensional LC-MS/MS strategy on the conditioned media of four lung cancer cell lines of different histological backgrounds (non-small cell lung cancer: H23 (adenocarcinoma), H520 (squamous cell carcinoma), and H460 (large cell carcinoma); small cell lung cancer: H1688) to identify secreted or membrane-bound proteins that could be useful as novel lung cancer biomarkers. Proteomics analysis of the four conditioned media allowed identification of 1,830 different proteins (965, 871, 726, and 847 from H1688, H23, H460, and H520, respectively). All proteins were assigned a subcellular localization, and 38% were classified as extracellular or membrane-bound. We successfully identified the internal control proteins (also detected by ELISA), kallikrein-related peptidases 14 and 11, and IGFBP2. We also identified known or putative lung cancer tumor markers such as squamous cell carcinoma antigen, carcinoembryonic antigen, chromogranin A, creatine kinase BB, progastrin-releasing peptide, neural cell adhesion molecule, and tumor M2-PK. To select the most promising candidates for validation, we performed tissue specificity assays, functional classifications, literature searches for association to cancer, and a comparison of our proteome with the proteome of lung-related diseases and serum. Five novel lung cancer candidates, ADAM-17, osteoprotegerin, pentraxin 3, follistatin, and tumor necrosis factor receptor superfamily member 1A were preliminarily validated in the serum of patients with lung cancer and healthy controls. Our results demonstrate the utility of this cell culture proteomics approach to identify secreted and shed proteins that are potentially useful as serological markers for lung cancer.
机译:早期发现肺癌对于成功治疗和提高生存率是必不可少的。我们使用二维LC-MS / MS策略对四种不同组织学背景的肺癌细胞系(非小细胞肺癌:H23(腺癌),H520(鳞状细胞癌)的条件培养基)进行了自下而上的蛋白质组学分析。和H460(大细胞癌);小细胞肺癌:H1688),以鉴定分泌的或膜结合蛋白,这些蛋白可用作新型的肺癌生物标志物。通过对四种条件培养基的蛋白质组学分析,可以鉴定1,830种不同的蛋白质(分别来自H1688,H23,H460和H520的965、871、726和847)。所有蛋白质均被分配到亚细胞定位,并且38%被归类为细胞外或膜结合。我们成功鉴定出内部对照蛋白(也可通过ELISA检测),激肽释放酶相关的肽酶14和11以及IGFBP2。我们还确定了已知或推测的肺癌肿瘤标志物,如鳞状细胞癌抗原,癌胚抗原,嗜铬粒蛋白A,肌酸激酶BB,前胃泌素释放肽,神经细胞粘附分子和肿瘤M2-PK。为了选择最有希望的候选者进行验证,我们进行了组织特异性测定,功能分类,与癌症相关性的文献检索,以及我们的蛋白质组与肺部相关疾病和血清蛋白质组的比较。初步在肺癌患者和健康对照者的血清中验证了五种新颖的候选肺癌药物ADAM-17,骨保护素,五合蛋白3,卵泡抑素和肿瘤坏死因子受体超家族成员1A。我们的结果证明了这种细胞培养蛋白质组学方法可用于鉴定分泌和脱落的蛋白质,这些蛋白质可能用作肺癌的血清学标志物。

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