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癌症免疫组学:从血清蛋白质组分析到多重亲和蛋白质分析

Cancer immunomics: from serological proteome analysis to multiple affinity protein profiling.

作者信息

Hardouin Julie, Lasserre Jean-Paul, Sylvius Loïk, Joubert-Caron Raymonde, Caron Michel

机构信息

Protein Biochemistry and Proteomics Laboratory, CNRS UMR 7033 (BioMoCeti), UFR SMBH Leonard de Vinci, University Paris13, 74, rue Marcel Cachin, 93017 Bobigny cedex, France.

出版信息

Ann N Y Acad Sci. 2007 Jun;1107:223-30. doi: 10.1196/annals.1381.024.

Abstract

Cancer remains one of the leading causes of death worldwide. Thus, to identify any useful biomarkers is still a need. We performed "cancer immunomics" to identify autoantibody signatures produced in response to the presence of either breast or colorectal cancer. SERological proteome analysis (SERPA) was performed by two-dimensional (2-D) electrophoresis separation, immunoblotting, image analysis, and mass spectrometry. Alternatively, to identify the antigens recognized by the autoantibodies of cancer patients, we developed an approach combining 2-D immunoaffinity chromatography, enzymatic digestion of the isolated antigens, nano flow separation of the resulting peptides, and identification: MAPPing (multiple affinity protein profiling). By these approaches we identified both proteins recognized by autoantibodies independently of a cancer status, and a limited number of proteins reacting preferentially with cancer sera.

摘要

癌症仍然是全球主要死因之一。因此,识别任何有用的生物标志物仍然很有必要。我们开展了“癌症免疫组学”研究,以识别因乳腺癌或结直肠癌的存在而产生的自身抗体特征。血清蛋白质组分析(SERPA)通过二维(2-D)电泳分离、免疫印迹、图像分析和质谱法进行。另外,为了识别癌症患者自身抗体所识别的抗原,我们开发了一种将二维免疫亲和色谱、分离抗原的酶消化、所得肽段的纳流分离和鉴定相结合的方法:多重亲和蛋白质谱分析(MAPPing)。通过这些方法,我们既鉴定了与癌症状态无关的自身抗体所识别的蛋白质,也鉴定了有限数量的优先与癌症血清反应的蛋白质。

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