摘要
AIM： To detect the new serum biomarkers for colorectal cancer （CRC） by serum protein profiling with surfaceenhanced 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） 3.1×10^3, 3.3× 10^3, 4.5×10^3, 6.6×10^3 and 28×10^3 were used as classitiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%.Host of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3× 10^3, main classifier in most trees, was a doubly charged form of the 6.6× 10^3-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1×10^3 was identified as an N-terminal fragment of albumin, and m/z 28× 10^3 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.
瞄准：为颜色检测新浆液简历标记由浆液蛋白质与提高表面的激光解吸附作用 ionisation 介绍的表面的癌症(CRC )-- 飞行团分光术(SELDI-TOF MS ) 的时间。方法：二个独立浆液样品集合与 ProteinChip 技术独立被分析(集合 A：40 CRC+49 健康控制；集合 B：37 CRC+31 健康控制) ，有一个弱阳离子的使用的芯片交换一半和缓冲区 pH 5。差别的歧视的力量表示了蛋白质与一个分类树算法被估计。产生分类树的敏感和特性被盲目地从集合 B 并且反过来也如此从集合 A 把数据用于产生的树获得。CRC 浆液蛋白质侧面也与从胸的那些相比，卵巢，前列腺，和非小的房间肺癌症。结果：Mass-to-charge 比率(m/z ) 3.1x10 (3 ) ， 3.3x10 (3 ) ， 4.5x10 (3 ) ， 6.6x10 (3 ) 和 28x10 (3 ) 在最好执行的分类树上被用作分类器。树敏感和特性在 65% 和 90% 之间。大多数这些歧视的 m/z 价值在调查的另外的瘤类型也是不同的。M/z 3.3x10 (3 ) ，在大多数树上的主要分类器，是 6.6x10 (3 ) 的一种二倍地控告的形式 -Da 蛋白质。后者作为 apolipoprotein C-I 被识别。M/z 3.1x10 (3 ) 作为 apolipoprotein A-I 作为白朊，和 m/z 28x10 (3 ) 的 N 终端碎片被识别。结论：分类树模式分析跟随的 SELDI-TOF MS 是为为 CRC 发现新浆液标记的一种合适的技术。Biomarkers 能与高敏感和特性在独立样品集合被识别并且 reproducibly 检测了。尽管为 CRC 不特定，这些简历标记在监视的疾病和治疗有一个潜在的角色。
