Molecular Diagnostics Program, Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
Mol Cell Proteomics. 2010 Jul;9(7):1449-60. doi: 10.1074/mcp.M900496-MCP200. Epub 2010 May 13.
The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.
发现疾病的新型早期检测生物标志物可能是降低卵巢癌和其他癌症发病率和死亡率的最佳方法之一。我们报告了使用单链可变片段抗体文库筛选卵巢血清,以寻找用于癌症检测的新型生物标志物。我们用卵巢癌和无疾病对照血清交替淘选文库,以制作在癌症中差异表达的蛋白质结合抗体的亚文库。该亚文库被打印在抗体微阵列上,并用来自多组癌症患者和对照者的标记血清孵育。选择在区分疾病状态方面表现最佳的抗体,并使用功能蛋白质微阵列鉴定其相应抗原。通过斑点印迹和免疫组织化学染色,在癌症血清、肿瘤近端液和癌症组织中观察到一些抗原的过表达。因此,我们使用重组抗体微阵列进行无偏见的发现,在多个样本集中找到了用于卵巢癌检测的靶标,支持进一步研究其用于疾病诊断。