Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry
Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry
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DOI：
10.3748/wjg.v12.i10.1536
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发表时间：
2006-03-14
影响因子：
4.3
通讯作者：
Beijnen, Jos H.
中科院分区：
文献类型：
--
作者：
Engwegen, Judith Y. M. N.;Helgason, Helgi H.;Beijnen, Jos H.
目的：应用表面增强激光解吸电离-飞行时间质谱技术检测结直肠癌（CRC）新的血清标志物方法：采用蛋白质芯片技术对两组独立的血清样品进行分析（A组：40个CRC +49个健康对照; B组：37个CRC +31个健康对照），使用具有弱阳离子交换部分和缓冲液pH 5的芯片。用分类树算法评估差异表达蛋白的区分能力。通过将来自集合A的数据盲应用于来自集合B的生成的树来获得生成的分类树的灵敏度和特异性，反之亦然。CRC的血清蛋白质谱也与乳腺癌、卵巢癌、前列腺癌和非小细胞肺癌的血清蛋白质谱进行了比较。结果：质荷比（m/z）3.1x10（3）、3.3x10（3）、4.5x10（3）、6.6x10（3）和28x10（3）被用作性能最好的分类树中的分类器。树的敏感性和特异性在65%和90%之间。大多数这些区别性m/z值在研究的其他肿瘤类型中也不同。M/z 3.3x10（3）是大多数树中的主要分类器，是6.6x10（3）-Da蛋白的双电荷形式。后者被鉴定为载脂蛋白C-I。m/z3.1x10（3）为白蛋白N端片段，m/z28x10（3）为载脂蛋白A-I。结论：SELDI-TOF MS结合分类树模式分析是寻找大肠癌新血清标志物的合适技术。生物标志物可以在独立的样品组中以高灵敏度和特异性被鉴定和可重复地检测。尽管这些生物标志物对CRC没有特异性，但在疾病和治疗监测中具有潜在作用。(C)2006年，WJG出版社。All rights reserved.
AIM: To detect the new serum biomarkers for colorectal cancer (CRC) by serum protein profiling with surface-enhanced laser desorption ionisation - time of flight mass spectrometry (SELDI-TOF MS).METHODS: Two independent serum sample sets were analysed separately with the ProteinChip technology (set A: 40 CRC + 49 healthy controls; set B: 37 CRC + 31 healthy controls), using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer.RESULTS: Mass-to-charge ratios (m/z) 3.1x10(3), 3.3x 10(3), 4.5x10(3), 6.6x10(3) and 28x10(3) were used as classifiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%. Most of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3x 10(3), main classifier in most trees, was a doubly charged form of the 6.6x10(3)-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1x10(3) was identified as an N-terminal fragment of albumin, and m/z 28x10(3) as apolipoprotein A-I.CONCLUSION: SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring. (C) 2006 The WJG Press. All rights reserved.