Hardouin Julie, Lasserre Jean-Paul, Sylvius Loïk, Joubert-Caron Raymonde, Caron Michel
Protein Biochemistry and Proteomics Laboratory, CNRS UMR 7033 (BioMoCeti), UFR SMBH Leonard de Vinci, University Paris13, 74, rue Marcel Cachin, 93017 Bobigny cedex, France.
Ann N Y Acad Sci. 2007 Jun;1107:223-30. doi: 10.1196/annals.1381.024.
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.
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。