Identification of gastric cancer patients by serum protein profiling
Identification of gastric cancer patients by serum protein profiling
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DOI：
10.1021/pr049865s
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发表时间：
2004-11-01
影响因子：
4.4
通讯作者：
Röcken, C
中科院分区：
文献类型：
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作者：
Ebert, MPA;Meuer, J;Röcken, C
使用表面增强激光解吸电离质谱（SELDI/TOF-MS）和蛋白质芯片技术，结合模式匹配算法和血清样本，我们筛选蛋白质模式，以区分胃癌患者和非癌症患者。由50个决策树组成的分类器集成正确地分类了训练集的所有胃癌和所有对照（100%灵敏度和100%特异性）。9例1期胃癌中有8例（1期敏感性为88.9%）被正确分类。此外，28例来自不同医院的胃癌患者的血清被正确分类（100%灵敏度）。此外，从非胃癌患者中获得的所有11份对照血清（100%特异性）均被正确分类，30名健康献血者中有29名被分类为非癌。蛋白质芯片技术与生物信息学相结合，可以对胃癌患者进行高灵敏度和特异性的识别。
Using surface-enhanced laser desorption ionization mass spectrometry (SELDI/TOF-MS) and ProteinChip technology, coupled with a pattern-matching algorithm and serum samples, we screened for protein patterns to differentiate gastric cancer patients from noncancer patients. A classifier ensemble, consisting of 50 decision trees, correctly classified all gastric cancers and all controls of a training set (100% sensitivity and 100% specificity). Eight of 9 stage 1 gastric cancers (88.9% sensitivity for stage 1) were correctly classified. In addition, 28 sera from gastric cancer patients taken in different hospitals were correctly classified (100% sensitivity). Furthermore, all 11 control sera obtained from patients without gastric cancer (100% specificity) were classified correctly and 29 of 30 healthy blood-donors were classified as noncancerous. ProteinChip technology in conjunction with bioinformatics allows the highly sensitive and specific recognition of gastric cancer patients.