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同时测量 92 种血清蛋白生物标志物,以开发用于卵巢癌检测的多蛋白分类器。

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection.

机构信息

Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota.

Ovarian Cancer Early Detection Program, University of Minnesota, Minneapolis, Minnesota.

出版信息

Cancer Prev Res (Phila). 2019 Mar;12(3):171-184. doi: 10.1158/1940-6207.CAPR-18-0221. Epub 2019 Feb 1.

Abstract

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly ( < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

摘要

最著名的卵巢癌生物标志物 CA125 既不够敏感也不够特异,无法用于一般人群的筛查。通过使用多种蛋白质进行筛查,有可能在单独使用 CA125 的基础上提高灵敏度和特异性。在这项研究中,我们使用 Proseek 多重肿瘤学 II 板通过临近延伸分析(proximity extension assay),同时测量血清中 92 种癌症相关蛋白的表达。该技术结合了 PCR 的灵敏度和基于抗体的检测方法的特异性,可实现多重生物标志物检测和高通量定量。我们分析了 61 名卵巢癌女性的每个患者 1μL 血清,并将获得的值与 88 名年龄匹配的健康女性进行比较。主成分分析和无监督层次聚类将卵巢癌患者与健康者区分开来,几乎没有错误分类。Proseek 板上 CA125 水平的数据与 CA125 的临床值表现出很强的相关性。我们鉴定了 52 种在卵巢癌和健康样本之间差异显著(<0.006)的蛋白质,其中一些是卵巢癌的新型血清生物标志物。总共 40 种蛋白质的 ROC 曲线下面积估计值为 0.70 或更高,表明它们有潜力成为卵巢癌的生物标志物。单独的 CA125 在特异性为 98%时的灵敏度为 93.4%。通过将 Onc Ⅱ五种蛋白的值添加到 CA125 中进行多蛋白分类器分析,我们将检测灵敏度提高到特异性为 98%时的 98.4%,从而提高了 CA125 的灵敏度和特异性。

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