SELDI-TOF-MS技术在HD患儿血清蛋白质标记物检测中的应用

Using of SELDI-TOF-MS for serum protein markers in patients with Hirschsprung′s Disease

目的从先天性巨结肠(HD)患儿血清蛋白质中筛选特异的蛋白质标记物,构建诊断HD的血清蛋白质指纹图谱模型。方法采用表面增强激光解吸电离—飞行时间质谱(SELDI-TOF-MS)技术检测132例份血清标本(来自HD术前患儿64例份,术后40例份,术后复发5例份,对照组23例份)的蛋白质质谱,用支持向量机分析数据。结果筛选出质荷比(m/z)为3221.7、5639.2、6884.2的三个蛋白质标记物,其在HD术前组低表达(分别为2.96±1.17、15.57±8.87、4.09±1.78),在对照组高表达(分别为4.95±0.99、30.31±6.18、8.31±3.07),两组相比,P均<0.01;在HD术后组高表达(分别为3.76±2.15、27.98±7.22、9.06±2.14),与术前组相比,P均<0.01,与对照组相比,P均>0.05;5例术后复发者三种蛋白质标记物表达强度(分别为3.18±0.951、3.86±10.69、3.95±1.83),与术前组相比,P均>0.05。结论采用SELDI-TOF-MS结合支持向量机构建的血清蛋白质指纹图谱模型可用于HD的诊断及判断其是否完全根治。

Objective To set up a model for the detection of the serum protein by using the protein chip technology for exploration of serum protein finger print pattern models in Hirschsprung＇s Disease （liD）.Method The protein mass spectrograms was detected by the surface-enhanced laser desorption ionization time of flight mass spectrometry （SELDI-TOF-MS） technology combined with support vector machine （SVM） in 132 serum samples（64 preoperative HI）, 40 postoperative IID, 5 recurrent, 23 normal control）. Results Three protein markers whose m/z positioned at 3 221.7,5 639.2 and 6 884.2 were detected. The intensity of three biomarks were 2.96± 1.17,15.57± 8.87,4.09± 1.78 in preoperative HI） group,4.95±0.99,30.31± 6.18,8.31± 3.07 in normal children＇s group. There was statistic significance between two groups, P 〈 0.01. The intensity of three biomarks were 3.76 ± 2.15,27.98 ± 7.22,9.06 ± 2.14 in postoperative HD group, there was statistic significance compared with preoperative HD group, P 〈 0. 01, whereas the diference did not reach statistic significance compared with normal children＇s group, P 〉 0.05. The intensity of three biomarks were 3.18 ± 0.95,13.86 ± 10.69,3.95 ± 1.83 in 5 patients with colostomy procedure in neonate reeurrented, the diference did not reach statistic significance compared with preoperative HD group, P 〉 0.05. Conclusion The fingerprint chromatogram model of serum protein using SELDI-TOF-MS combining SVM contributes to diagnosis of HD and monitoring the prognosis of HD.