食管癌血清差异表达蛋白的研究

目的 探讨食管癌患者和健康人群蛋白表达的差异,筛选用于早期诊断的肿瘤标志物并建立诊断模型.方法 回顾性分析2008年1月至8月新疆医科大学第一附属医院收治的127例原发性食管癌患者(食管癌组)和63例健康体检者(健康对照组)的临床资料.采用表面增强激光解吸离子化飞行时间质谱(SELDI-TOF-MS)技术,应用弱阳离子交换蛋白芯片检测和分析两组受试者的血清蛋白表达谱,筛选可以用于临床食管癌早期诊断新的肿瘤标志物,建立蛋白质指纹图诊断模型.采用秩和检验分析数据.结果 食管癌组与健康对照组血清蛋白质荷比(M/Z)峰值图谱明显不同.得到差异性较大的10个蛋白中,有6个在食管癌组呈高表达,M/Z为4488、5495、15964、3948、8154、8166;4个呈低表达,M/Z为8789、6682、8714、6650.建立由6个蛋白组成的蛋白质指纹图诊断模型,食管癌组患者中124例判定正确,3例误判;健康对照组患者中60例判定正确,3例误判,其准确度为96.8%(184/190),敏感度为97.6%(124/127),特异度为95.2%(60/63).结论 应用SELDI-TOF-MS技术筛选食管癌肿瘤标志物建立的蛋白质指纹图诊断模型灵敏度高、特异性强.

Serum proteomic patterns for detection of esophageal cancer

Objective To explore differential expression of protiens between patients with esophageal cancer and healthy individuals, and to screen out the tumor biomarkers to construct a dignostic model. Methods From January to August, 2008, the clinical data of 127 patients with esophageal cancer (esophageal cancer group) who had been admitted to the First Affiliated Hospital of Xinjiang Medical University and 63 healthy individuals (control group) were retrospectively analyzed. The serum proteomic profiles of the esophageal cancer pateints and healthy individuals were deteced by weak cation exchange and hydrophobic surface ProteinChip using the surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDT-TOF-MS) technique.Serum differentially expressed markers of esophageal cancer were screened out to establish the diagnostic model for esophageal cancer. All data were analyzed using rank sum test. Results Six proteins were high-expressed in the esophageal cancer group, and the mass-to-charge ratios were 4488, 5495, 15964, 3948, 8154, 8166. Four were low-expressed in esophageal cancer group, and the mass-to-charge ratios were 8789, 6682, 8714, 6650. A diagnostic model consisting six proteins was established. A total of 124 patients were correctly diagnosed and three were misdiagnosed in the esophageal cancer group, and 60 were correctly diagnosed and three were misdiagnosed in the control group. The accuracy, sensitivity and specificity of the diagnostic model were 96.8% ( 184/190),97.6% ( 124/127 ) and 95.2% (60/63). Conclusions The diagnostic model established based on the tumor markers screened out by the SELDT-TOF-MS is highly sensitive and specific.