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首页> 外文期刊>Molecular & cellular proteomics: MCP >Discovery of Lung Cancer Biomarkers by Profiling the Plasma Proteome with Monoclonal Antibody Libraries
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Discovery of Lung Cancer Biomarkers by Profiling the Plasma Proteome with Monoclonal Antibody Libraries

机译:通过用单克隆抗体文库分析血浆蛋白质组来发现肺癌生物标志物

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摘要

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrome-try. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.
机译:肺癌的治疗中的挑战是缺乏早期诊断。在这里,我们描述了单克隆抗体蛋白质组学在发现非小细胞肺癌(NSCLC)早期检测(I期)生物标志物方面的应用。我们产生了针对NSCLC患者血浆中天然形式的蛋白质抗原的大型单克隆抗体库。通过高通量ELISA检测与肺癌存在相关的血浆生物标志物。共有301名肺癌患者和235名健康对照的四个临床队列的血浆蛋白质组差异分析,确定了13种与肺癌相关的(p <0.05)单克隆抗体。单克隆抗体识别通过免疫沉淀和质谱鉴定的五种不同的同源蛋白质。五个抗原中的四个存在于非小细胞肺癌原位细胞中。该方法能够产生针对相同蛋白质不同表位的独立抗体,从而可以快速翻译成多重夹心测定法。基于这些结果,我们已经在两个独立的临床馆藏中验证了五个生物标记物组,用于对患者疾病状态进行分类,其诊断性能为77%的敏感性和87%的特异性。将CYFRA(一种已建立的癌症标志物)与该检测组相结合,可对I期NSCLC表现出83%的敏感性和95%的特异性。

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