WCX2蛋白芯片筛选食管鳞癌血清标志蛋白的研究

Screening of serum proteome biomarker of esophageal squamous cell carcinoma by WCX2 protein chip

背景与目的:蛋白质组学研究有助于筛选食管上皮癌变相关的分子变化。本研究通过比较食管鳞癌(esophageal squamous cell carcinoma,ESCC)患者和正常对照血清蛋白表达谱的差异,来筛选食管鳞癌相关血清蛋白标志物,为筛选和建立食管鳞癌早期诊断的血清学指标提供依据。方法:应用表面增强激光解吸离子化飞行时间质谱(SELDI-TOF-MS)技术,采用弱阳离子交换芯片(WCX2)首先对训练组44对食管鳞癌患者和性别年龄匹配的正常对照血清蛋白表达谱的差异进行了分析,建立决策树分类模型后,对测试组进行盲法验证。结果:在质荷比(M/Z)2000～20000范围内,共检测到84个有效蛋白峰,其中28个峰差异有显著性(P<0.05)。自动选用M/Z为2545、3371、3746、5009、5021和15886的6个差异蛋白峰,建立食管鳞癌决策树分类模型,其灵敏度为93.18%(41/44),特异度为97.73%(43/44)。对测试组进行双盲检测,结果显示灵敏度和特异度分别为77.27%(34/44)和75.00%(33/44)。结论:应用SELDI-TOF-MS技术可以筛选出食管鳞癌相关的血清蛋白标志,建立的决策树模型可能对食管鳞癌的诊断具有重要的临床价值。

Background and purpose：Proteomics are useful in helping to identify the molecular changes closely related to esophageal carcinogenesis. In order to provide some theoretical evidence for screening and establishing serum indications of early diagnosis of esophageal squamous cell carcinoma（ESCC） patients, the serum proteomics profiling difference of subjects with ESCC and healthy controls were analyzed to screen serum proteomic biomarker related to ESCC. Methods：Serum samples were collected from training set that included 44 ESCC before surgery and 44 age- and sex-matched healthy controls. With WCX2 protein chip, surface-enhanced laser desorption ionization time of flight mass spectrometry （SELDI-TOF-MS） was used to analyze the difference of serum protein profiling and a classification model for diagnosis of ESCC was established. The blind testing set containing another 44 ESCC patients and age- and sex-matched healthy controls was used to determine the sensitivity and specificity of the classification model.Results：84 effective protein peaks were detected at the molecular range of 2000 to 20000Da, among which 28 were significantly different between ESCC and controls（P〈0.05）.Among them 6 candidate protein peaks with the M/Z values of 2 545、3 371、3 746、5 009、 5 021 and 15 886 were selected to establish a predictive model with 93.18%（41/44）sensitivity and 97.73%（43/44）specificity. After double blind examination of the testing set with that rule,the corresponding sensitivity was 77.27%（34/44）and the corresponding specificity was 75.00%（33/44）.Conclusions：SELDI-TOF-MS Protein Chip combined with artificial intelligence classification algorithm helps find serum proteome biomarkers and the predictive model combining 6 protein peaks can discriminate ESCC patients from healthy controls, which may have some potential value for diagnosis of ESCC.